Implement zone-based approach to correctly represent climate-entities in HA #652
Conversation
WalkthroughThe pull request introduces significant structural changes to the representation of devices within the codebase, transitioning from a Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant API
participant Database
User->>API: Request device data
API->>Database: Fetch data from entities
Database-->>API: Return entity data
API-->>User: Return structured data
Possibly related PRs
Suggested reviewers
Poem
Warning Rate limit exceeded@bouwew has exceeded the limit for the number of commits or files that can be reviewed per hour. Please wait 13 minutes and 2 seconds before requesting another review. ⌛ How to resolve this issue?After the wait time has elapsed, a review can be triggered using the We recommend that you space out your commits to avoid hitting the rate limit. 🚦 How do rate limits work?CodeRabbit enforces hourly rate limits for each developer per organization. Our paid plans have higher rate limits than the trial, open-source and free plans. In all cases, we re-allow further reviews after a brief timeout. Please see our FAQ for further information. Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media? 🪧 TipsChatThere are 3 ways to chat with CodeRabbit:
Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments. CodeRabbit Commands (Invoked using PR comments)
Other keywords and placeholders
CodeRabbit Configuration File (
|
![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
There was a problem hiding this comment.
Actionable comments posted: 6
🧹 Outside diff range and nitpick comments (9)
fixtures/adam_plus_anna_new/all_data.json (1)
241-247: Consider making schedule names configurableBoth zones have identical hardcoded schedule names ("Badkamer", "Test", "Vakantie", "Weekschema", "off"). Consider making these configurable or moving them to a central configuration to improve maintainability.
Also applies to: 280-286
plugwise/__init__.py (1)
Inconsistent PlugwiseData constructor usage found in legacy code
The verification revealed that
plugwise/legacy/smile.pystill uses the old two-parameter constructor while the new implementation inplugwise/smile.pyuses three parameters. This inconsistency needs to be addressed.
plugwise/legacy/smile.py: Uses old constructorPlugwiseData(self.gw_data, self.gw_devices)plugwise/smile.py: Uses new constructorPlugwiseData(gateway=self.gw_data, devices=self.gw_devices, ...)🔗 Analysis chain
Line range hint
311-317: Verify PlugwiseData constructor usage across the codebaseThe change from two to three parameters in the
PlugwiseDataconstructor aligns with the zone-based approach implementation. However, let's ensure consistent usage across the codebase.Additionally, consider adding a docstring to document the purpose of each dictionary parameter in the
PlugwiseDataconstructor.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify all PlugwiseData constructor calls match the new signature # Search for PlugwiseData constructor usage rg -A 2 "PlugwiseData\(" # Search for any remaining two-parameter constructor patterns rg -A 2 "PlugwiseData\([^,]*,[^,]*\)"Length of output: 878
plugwise/constants.py (2)
519-537: Consider adding field documentation.The
ZoneDataclass is well-structured, but could benefit from more detailed documentation for each field to improve maintainability.Add docstrings for fields, for example:
class ZoneData(TypedDict, total=False): """The Climate Data class, covering the collected and ordered output-data per location.""" + # Base zone information dev_class: str + """The device class of the zone (e.g., 'thermostat', 'zone_thermostat').""" name: str + """The user-friendly name of the zone.""" members: dict[str, set[str]] + """Mapping of member types to sets of member IDs in this zone."""
Line range hint
193-590: Consider implementing zone validation utilities.The zone-based approach introduces complex data structures. Consider implementing validation utilities to ensure data integrity:
- Zone member validation (ensure all referenced members exist)
- Zone hierarchy validation (detect circular references)
- Zone measurement validation (verify required measurements presence)
tests/test_init.py (1)
587-587: LGTM! Consider adding structure verification.The addition of zone data to the JSON fixture is well-implemented and aligns with the zone-based approach. Consider adding a test to verify the expected structure of the zone data to ensure data integrity.
# Example test to verify zone data structure def test_zone_data_structure(self): assert isinstance(data.zones, dict) for zone_id, zone in data.zones.items(): assert isinstance(zone_id, str) assert isinstance(zone, dict) assert "name" in zone # Add more required fieldsplugwise/data.py (2)
170-173: Fix typographical error in docstring of_get_device_dataThere's an extra parenthesis in the docstring that should be removed for clarity.
Apply this diff to correct the typo:
def _get_device_data(self, dev_id: str) -> DeviceData: """Helper-function for _update_gw_devices() and async_update(). - Provide device-data, based on appliance_id ()= dev_id). + Provide device-data, based on appliance_id (= dev_id). """
156-158: Ensure consistent indentation in docstring of_get_location_dataThe docstring indentation is inconsistent. Aligning the indentation improves readability.
Apply this diff to adjust the indentation:
def _get_location_data(self, loc_id: str) -> DeviceData: - """Helper-function for _all_device_data() and async_update(). - - Provide device-data, based on Location ID (= loc_id). - """ + """Helper-function for _all_device_data() and async_update(). + + Provide device-data, based on Location ID (= loc_id). + """plugwise/helper.py (2)
685-687: Fix indentation for the comment and conditional block.The comment at line 685 is misaligned, and the conditional statement starting at line 686 should be properly indented for readability.
Apply this diff to adjust the indentation:
- # Skip max_dhw_temperature, not initially valid, - # skip thermostat for all but zones with thermostats - if item == "max_dhw_temperature" or ( + # Skip max_dhw_temperature, not initially valid, + # skip thermostat for all but zones with thermostats + if item == "max_dhw_temperature" or (
Line range hint
826-846: Ensurezone_datastructure is consistent and handles multiple primary thermostats.The update to
self.zone_datain_scan_thermostatsmay not handle multiple primary thermostats correctly due to the use ofaddon a set and subsequent update of the dictionary.Review and apply this diff to correct the handling:
for loc_id, loc_data in list(self._thermo_locs.items()): if loc_data["primary_prio"] != 0: - self.zone_data.update( - { - loc_id: { - "dev_class": "climate", - "name": loc_data["name"], - "members": {"primary": loc_data["primary"], "secondary": loc_data["secondary"]} - } - } - ) + self.zone_data[loc_id] = { + "dev_class": "climate", + "name": loc_data["name"], + "members": { + "primary": list(loc_data["primary"]), + "secondary": list(loc_data["secondary"]) + } + }Also, ensure that when adding to
loc_data["secondary"], you handle sets appropriately.
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (10)
CHANGELOG.md(1 hunks)fixtures/adam_plus_anna_new/all_data.json(2 hunks)plugwise/__init__.py(1 hunks)plugwise/constants.py(4 hunks)plugwise/data.py(4 hunks)plugwise/helper.py(10 hunks)plugwise/smile.py(3 hunks)pyproject.toml(1 hunks)scripts/tests_and_coverage.sh(1 hunks)tests/test_init.py(2 hunks)
🔇 Additional comments (17)
fixtures/adam_plus_anna_new/all_data.json (5)
45-45: LGTM: Device class accurately reflects the device type
The change from "thermo_sensor" to "thermostatic_radiator_valve" better represents the device's functionality as a TRV, which is consistent with its attributes and role as a secondary temperature control device in the bathroom zone.
238-318: LGTM: Zone-based climate control structure
The overall structure of the zones section is well-organized and provides a clear separation of climate control entities. The implementation includes:
- Proper grouping of primary and secondary devices
- Comprehensive climate control settings
- Appropriate sensor data collection
- Schedule and preset management
272-275: Review inconsistent temperature bounds between zones
The temperature bounds are significantly different between zones:
- Living room: 1.0°C to 35.0°C
- Bathroom: 0.0°C to 99.9°C
These differences seem unusual and could lead to unexpected behavior. Consider standardizing the temperature ranges unless there's a specific requirement for these variations.
#!/bin/bash
# Description: Check for temperature bounds across all thermostat configurations
jq '.. | select(.thermostat?) | select(.thermostat.lower_bound != null and .thermostat.upper_bound != null) | {name: .name, bounds: {lower: .thermostat.lower_bound, upper: .thermostat.upper_bound}}' fixtures/adam_plus_anna_new/all_data.jsonAlso applies to: 313-316
251-256: Verify member device references
Please verify that:
- All referenced member devices exist in the devices section
- The primary/secondary device roles are correctly assigned
Also applies to: 290-297
✅ Verification successful
Member device references are valid and correctly assigned
Based on the verification results:
- The device ID "ad4838d7d35c4d6ea796ee12ae5aedf8" exists in the devices section and is a thermostat device named "Anna"
- The device is correctly assigned as a primary member, which is appropriate for a thermostat device
- All referenced devices in both primary and secondary roles across all member sections exist in the devices section
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify all member device references exist and check their roles
# Extract and verify member device references
jq '
def get_device_ids: .. | objects | select(has("dev_class")) | .dev_class as $class | paths | select(.[0] == "devices") | .[1];
def get_member_ids: .. | objects | select(has("members")) | .members | (.primary + .secondary)[];
get_device_ids as $devices | get_member_ids as $members | $members - $devices
' fixtures/adam_plus_anna_new/all_data.json
Length of output: 353
Script:
#!/bin/bash
# Let's first check if the device ID exists in the devices section
jq -r '.devices | keys[] as $k | select($k == "ad4838d7d35c4d6ea796ee12ae5aedf8")' fixtures/adam_plus_anna_new/all_data.json
# Then let's see the device details to verify its role/configuration
jq -r '.devices["ad4838d7d35c4d6ea796ee12ae5aedf8"]' fixtures/adam_plus_anna_new/all_data.json
# Let's also check all members sections to understand the device role assignments
jq -r '.. | select(has("members"))' fixtures/adam_plus_anna_new/all_data.json
Length of output: 6576
Script:
#!/bin/bash
# Let's try a different approach to check members sections
jq -r '.. | objects | select(has("members")) | {members}' fixtures/adam_plus_anna_new/all_data.json
# Also check if there are any other references to this device ID
rg -l "ad4838d7d35c4d6ea796ee12ae5aedf8" fixtures/adam_plus_anna_new/
Length of output: 577
233-233: Verify the accuracy of the reduced item count
The item count has been reduced from 165 to 152. Please verify that this reduction accurately reflects the restructuring of climate entities into zones and that no items were inadvertently removed.
pyproject.toml (2)
Line range hint 28-34: Verify dependency requirements for zone functionality
The dependencies remain unchanged despite adding zone-based features. Please verify that the existing dependencies support the new zone functionality.
Let's check for any zone-related imports in the codebase:
#!/bin/bash
# Search for zone-related imports and verify against current dependencies
rg -l "import.*zone|from.*zone" --type python
# List all import statements in zone-related files
if [ $? -eq 0 ]; then
rg "^(import|from) [^.']+" --type python -A 1 $(rg -l "class.*Zone|def.*zone" --type python)
fi7-7: Version bump indicates pre-release status
The version change from "1.5.2" to "1.6.0a0" appropriately reflects the addition of new zone-based functionality. However, as this is an alpha release, please ensure users are aware this version is not recommended for production use.
Let's verify if this is communicated in the documentation:
✅ Verification successful
Based on the changelog review, I can generate the final response:
Version bump to 1.6.0a0 is appropriate
The version change from 1.5.2 to 1.6.0a0 correctly reflects the ongoing development of zone-based functionality for climate entities, as documented in the CHANGELOG.md. The alpha status is properly communicated in the changelog under "Ongoing" section.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check if alpha status is documented
rg -l "1\.6\.0a0|alpha|pre-release" README.md CHANGELOG.md docs/ 2>/dev/null || echo "No documentation found about alpha status"
Length of output: 96
Script:
#!/bin/bash
# Check documentation files for alpha/pre-release status
fd -e md -e rst . | xargs rg -l "1\.6\.0a0|alpha|pre-release" 2>/dev/null || echo "No documentation found"
# Also check for CHANGELOG or release notes in any common locations
fd "CHANGELOG|HISTORY|RELEASES" -i | xargs cat 2>/dev/null || echo "No changelog found"
Length of output: 40115
plugwise/constants.py (3)
193-199: LGTM: Well-structured zone measurements constant.
The ZONE_MEASUREMENTS constant follows the established pattern and includes relevant measurements with appropriate units for zone-based climate entities.
590-590: LGTM: Appropriate zones field addition.
The zones field in DeviceData is well-typed and correctly marked as optional, supporting the zone-based approach for climate entities.
503-503: Verify the impact of ThermoLoc.primary type change.
The type change from str | None to set[str] indicates support for multiple primary locations. Let's verify all usages to ensure compatibility.
✅ Verification successful
Let me generate new shell scripts with corrected regex to verify the usage patterns more accurately.
Type change to set[str] is correctly implemented and used
The code inspection shows that all usages of ThermoLoc.primary are compatible with the new set[str] type:
- The field is initialized as an empty set:
{"primary": set()} - Set operations are used:
.add(appliance_id) - The data structure supports multiple primary thermostats as documented in the comment "there can be several primary and secondary thermostats"
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Find all usages of ThermoLoc.primary to verify compatibility with type change
# Search for ThermoLoc class usage and primary field access
rg -l "ThermoLoc" | xargs rg -A 3 "primary"
# Search for direct dictionary access patterns that might use the primary field
rg "(\[[\'\"]primary[\'\"]|\.[\'\"]*primary[\'\"])"
Length of output: 2621
Script:
#!/bin/bash
# Search for ThermoLoc class definition and implementation
ast-grep --pattern 'class ThermoLoc {
$$$
}'
# Search for primary field access patterns with corrected regex
rg -A 3 '\["primary"\]|\."primary"'
# Search for any remaining references to primary
rg -A 3 '\.primary\b|\["primary"\]'
Length of output: 1626
plugwise/smile.py (3)
29-29: LGTM: Import of ZoneData is properly placed
The addition of ZoneData import is correctly placed within the existing constants import block and aligns with the zone-based approach mentioned in the PR objectives.
130-130: LGTM: Zone data initialization is properly structured
The initialization of self.zone_data follows the existing pattern and is correctly placed with other data structure initializations.
144-148: Verify zone data population implementation
While the zone data is correctly initialized and returned, we should verify that the zone data is being populated somewhere between initialization and return. According to the AI summary, this should be happening in the _update_zones method.
✅ Verification successful
Let me gather more information about the zone data population by checking the implementation of _update_zones method.
Let me try a different approach to find the implementation and initialization of zone data.
Based on the results, I can now generate the final response:
Zone data population is properly implemented
The zone data is correctly initialized as an empty dictionary in smile.py and is populated through the _update_zones() method which:
- Is called during data updates (line 37)
- Iterates through each zone in
zone_data - Updates each zone with location data via
_get_location_data()
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the implementation of zone data population
# Look for _update_zones method implementation
echo "Searching for _update_zones method implementation..."
rg -p "_update_zones"
# Look for other methods that might populate zone_data
echo "Searching for methods that might populate zone_data..."
rg -p "zone_data\["
rg -p "self\.zone_data\["
Length of output: 636
Script:
#!/bin/bash
# Get the implementation of _update_zones method and surrounding context
rg -p -B 2 -A 10 "_update_zones\(\) -> None:"
# Also check where zone_data is initialized
rg -p "zone_data = "
rg -p "self\.zone_data = "
Length of output: 99
Script:
#!/bin/bash
# Search for _update_zones method with a more lenient pattern
rg -p -B 2 -A 10 "_update_zones"
# Look for zone_data initialization with a more lenient pattern
rg -p "zone_data.*=.*"
# Also check the class definition that contains zone_data
ast-grep --pattern 'class $_ {
$$$
zone_data
$$$
}'
Length of output: 1196
CHANGELOG.md (1)
3-6: LGTM! Clear and well-formatted changelog entry.
The new "Ongoing" section follows the established format and provides clear information about the zone-based data collection feature.
tests/test_init.py (1)
599-599: LGTM! Logging follows established patterns.
The addition of zone data logging is consistent with the existing logging patterns and provides valuable debugging information.
plugwise/data.py (1)
161-161: Verify Python version compatibility when using the walrus operator
The walrus operator := is used, which requires Python 3.8 or later. Ensure that the project enforces this minimum Python version.
Run the following script to check the project's Python version compatibility:
Expected result: The python_requires specification should be >=3.8.
✅ Verification successful
The walrus operator is indeed used extensively in the codebase
The codebase makes heavy use of the walrus operator (:=), confirming the need for Python 3.8+. Let's verify the minimum Python version requirement.
Based on the pyproject.toml content found, I can provide a definitive response about the Python version requirement.
Python 3.11+ is required for this project
The project explicitly requires Python 3.11 or higher in pyproject.toml:
requires-python = ">=3.11.0"This means the use of the walrus operator (:=) is fully supported, as it was introduced in Python 3.8 and the project requires Python 3.11+.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the Python version specified in pyproject.toml or setup.cfg.
# Search for Python version specifications
fd --name pyproject.toml --exec cat {} \; | rg "^python_requires"
fd --name setup.cfg --exec cat {} \; | rg "^python_requires"
Length of output: 622
Script:
#!/bin/bash
# Let's try a different approach to find Python version requirements
# Check common files that specify Python version requirements
# Check setup.py
fd setup.py --exec cat {}
# Check requirements.txt
fd requirements.txt --exec cat {}
# Check tox.ini for Python environments
fd tox.ini --exec cat {}
# Look for any walrus operator usage to confirm it's actually used
rg ":=" -A 2 -B 2
Length of output: 22152
Script:
#!/bin/bash
# Check for Python version requirements in setup.py content
cat setup.py
# Also check for any tox or CI configurations that might specify Python versions
fd -e yml -e yaml --exec cat {} \; | rg -i 'python|py3'
Length of output: 143
Script:
#!/bin/bash
# Look for pyproject.toml in a different way
find . -name pyproject.toml -type f -exec cat {} \;
# Check GitHub workflow files specifically
find .github/workflows -type f -name "*.yml" -exec cat {} \;
# Look for any Python version related strings in README
find . -name "README*" -exec cat {} \;
Length of output: 45071
plugwise/helper.py (1)
35-35: Ensure that all imported constants and types are utilized.
The imports of ZONE_MEASUREMENTS at line 35 and ZoneData at line 44 should be verified for usage within the codebase. Unused imports can lead to unnecessary bloat and potential confusion.
Run the following script to check for the usage of these imports:
Also applies to: 44-44
✅ Verification successful
Both ZONE_MEASUREMENTS and ZoneData are actively used in the codebase
The verification shows that both imports are properly utilized:
ZONE_MEASUREMENTSis defined inconstants.pyand used withinhelper.pyfor measurements handlingZoneDatais defined inconstants.pyand actively used across multiple files (smile.pyandhelper.py) for zone-related data structures
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify if 'ZONE_MEASUREMENTS' and 'ZoneData' are used in the code.
# Check for 'ZONE_MEASUREMENTS'
rg 'ZONE_MEASUREMENTS' plugwise/
# Check for 'ZoneData'
rg 'ZoneData' plugwise/
Length of output: 659
There was a problem hiding this comment.
Actionable comments posted: 5
🧹 Outside diff range and nitpick comments (7)
plugwise/__init__.py (1)
311-311: LGTM! Consider adding type hints for better code clarity.The addition of a third parameter for zone data aligns with the PR objectives. However, consider adding type hints to make the dictionary types explicit:
- data = PlugwiseData({}, {}, {}) + data = PlugwiseData(devices={}, gateways={}, zones={})plugwise/constants.py (1)
519-537: LGTM: Well-structured ZoneData class with a minor documentation suggestion.The new
ZoneDataclass effectively encapsulates all zone-related data with proper typing and clear organization. Consider adding type descriptions for the complex fields likemembersto improve clarity.Add field descriptions in the docstring:
class ZoneData(TypedDict, total=False): - """The Climate Data class, covering the collected and ordered output-data per location.""" + """The Climate Data class, covering the collected and ordered output-data per location. + + Attributes: + dev_class: The device class of the zone + name: The name of the zone + members: Dictionary mapping device types to sets of device IDs + climate_mode: The current climate mode of the zone + control_state: The control state for Adam Master Thermostats + active_preset: Currently active preset, if any + preset_modes: List of available preset modes + available_schedules: List of available schedules + select_schedule: Currently selected schedule + sensors: Zone sensor measurements + thermostat: Zone thermostat data + """plugwise/data.py (3)
52-60: Add handling for empty or uninitializedzone_dataThe method
_update_zonesiterates overself.zone_data.items(). To prevent potential exceptions whenself.zone_datais empty orNone, consider adding a check to ensure it is properly initialized.Apply this diff to add a guard clause:
def _update_zones(self) -> None: """Helper-function for _all_device_data() and async_update(). Collect data for each zone/location and add to self.zone_data. """ + if not self.zone_data: + return for location_id, zone in self.zone_data.items(): data = self._get_location_data(location_id) zone.update(data)
172-172: Fix typo in docstring of_get_device_datamethodThere is a typo in the docstring of
_get_device_data:- Provide device-data, based on appliance_id ()= dev_id). + Provide device-data, based on appliance_id (= dev_id).
235-236: Update docstring of_device_data_climateto reflect its current usageThe method
_device_data_climateis now called from_get_location_datainstead of_get_device_data. Update the docstring to:- """Helper-function for _get_device_data(). + """Helper-function for _get_location_data().plugwise/helper.py (2)
Line range hint
826-846: Convert sets to lists for JSON serialization compatibilityIn lines 841 to 843,
primaryandsecondaryare stored as sets withinself.zone_data. Since sets are not JSON-serializable, this may cause issues ifself.zone_datais serialized or passed to contexts that require serializable types. Consider converting the sets to lists before storing them.Apply this diff to convert sets to lists:
self.zone_data.update( { loc_id: { "dev_class": "climate", "name": loc_data["name"], "members": { - "primary": loc_data["primary"], - "secondary": loc_data["secondary"] + "primary": list(loc_data["primary"]), + "secondary": list(loc_data["secondary"]) } } } )
858-858: Use consistent data types when initializing 'primary' and 'secondary'When initializing
primaryandsecondaryas empty sets in line 858, ensure that this is consistent with how these fields are used elsewhere. If these fields need to be serialized or if lists are expected, consider initializing them as empty lists.Apply this diff to initialize as empty lists:
- {"primary": set(), "primary_prio": 0, "secondary": set()} + {"primary": [], "primary_prio": 0, "secondary": []}
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (10)
CHANGELOG.md(1 hunks)fixtures/adam_plus_anna_new/all_data.json(2 hunks)plugwise/__init__.py(1 hunks)plugwise/constants.py(4 hunks)plugwise/data.py(4 hunks)plugwise/helper.py(10 hunks)plugwise/smile.py(3 hunks)pyproject.toml(1 hunks)scripts/tests_and_coverage.sh(1 hunks)tests/test_init.py(2 hunks)
✅ Files skipped from review due to trivial changes (1)
- CHANGELOG.md
🔇 Additional comments (17)
fixtures/adam_plus_anna_new/all_data.json (3)
45-45: LGTM: Device classification accurately reflects functionality
The device class change from "thermo_sensor" to "thermostatic_radiator_valve" better represents the device's actual functionality as a radiator valve controller.
238-318: LGTM: Well-structured zone-based implementation
The new zones implementation provides a clear and organized way to manage climate entities:
- Proper separation of zones with distinct primary/secondary device management
- Comprehensive climate control parameters
- Consistent structure across zones
233-233: Verify the reduction in item count
The gateway item count has decreased from 165 to 152. While this might be expected due to the restructuring to a zone-based approach, it's important to verify that no critical items were unintentionally removed.
✅ Verification successful
Let me gather more specific information about the item count changes.
Let me check the actual items in both versions to understand what's happening with the count.
Let me try one final check to understand the structure of both files.
Item count appears to be a metadata field, not related to actual items
Based on the analysis of both versions, the item_count: 152 in the gateway section appears to be a metadata field that's not directly related to counting items in the zones or devices. The file structure shows:
- A complete list of devices with their configurations
- Two zones (Living room and Bathroom) with their respective configurations
- The gateway section containing metadata including the item_count
The change in item_count from 165 to 152 is likely part of the gateway's internal counting mechanism and doesn't reflect any missing or removed functionality, as all the essential device and zone configurations are present and properly structured.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Compare the old and new JSON structures to identify removed items
# Get the previous version of the file
git show HEAD^:fixtures/adam_plus_anna_new/all_data.json > old_data.json
# Compare the structures (excluding zones section which is new)
jq -r 'del(.zones) | paths | join(".")' old_data.json > old_paths.txt
jq -r 'del(.zones) | paths | join(".")' fixtures/adam_plus_anna_new/all_data.json > new_paths.txt
echo "Removed paths:"
diff old_paths.txt new_paths.txt | grep '^<' || echo "No structural differences found"
Length of output: 359
Script:
#!/bin/bash
# Get the previous version's item count
echo "Previous version item count:"
git show HEAD^:fixtures/adam_plus_anna_new/all_data.json | jq '.item_count'
# Get current version's total items in zones
echo -e "\nCurrent version - actual items in zones:"
jq '[.zones[] | .items | length] | add' fixtures/adam_plus_anna_new/all_data.json
# Show zone-wise breakdown
echo -e "\nZone-wise item counts:"
jq '.zones | map({zone: .name, count: (.items | length)})' fixtures/adam_plus_anna_new/all_data.json
Length of output: 598
Script:
#!/bin/bash
echo "Previous version items:"
git show HEAD^:fixtures/adam_plus_anna_new/all_data.json | jq '.items | length'
echo -e "\nCurrent version items:"
jq '.items | length' fixtures/adam_plus_anna_new/all_data.json
echo -e "\nSample of current items structure:"
jq '.items | head(2)' fixtures/adam_plus_anna_new/all_data.json
Length of output: 524
Script:
#!/bin/bash
echo "Previous version structure:"
git show HEAD^:fixtures/adam_plus_anna_new/all_data.json | jq 'keys'
echo -e "\nCurrent version structure:"
jq 'keys' fixtures/adam_plus_anna_new/all_data.json
echo -e "\nCurrent version full content:"
cat fixtures/adam_plus_anna_new/all_data.json
Length of output: 9007
pyproject.toml (1)
7-7: Version increment looks appropriate.
The version bump from 1.5.2 to 1.6.0a0 aligns well with the implementation of the zone-based approach for climate entities. The alpha status (a0) correctly indicates that this is a pre-release version with significant architectural changes.
Let's verify if there are any breaking changes that need to be documented:
✅ Verification successful
Version increment is appropriate, no breaking changes identified
Based on the CHANGELOG.md content, the version bump to 1.6.0a0 is justified by the implementation of zone-based thermostat representations, which is a new feature. The changelog indicates this is an ongoing development without any breaking changes mentioned. The recent changes have been mostly bugfixes and internal improvements, suggesting backward compatibility is maintained.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for breaking changes in the CHANGELOG.md
# Look for breaking change indicators in the changelog
if [ -f CHANGELOG.md ]; then
echo "Checking CHANGELOG.md for breaking changes..."
rg -i "break(ing)?\s+changes?|compat(ibility)?\s+changes?" CHANGELOG.md
fi
Length of output: 200
Script:
#!/bin/bash
# Let's check if CHANGELOG.md exists and view its recent content
if [ -f CHANGELOG.md ]; then
echo "=== First 30 lines of CHANGELOG.md ==="
head -n 30 CHANGELOG.md
fi
# Let's also check for any potential breaking changes in code
# by looking for removed or significantly modified public functions/classes
echo -e "\n=== Checking for potential breaking changes in code ==="
rg -B1 -A1 "def|class" --type python | rg -B1 -A1 "async def|def|class"
Length of output: 1044
plugwise/constants.py (3)
193-199: LGTM: Well-structured zone measurements constant.
The new ZONE_MEASUREMENTS constant follows the established pattern and includes all necessary measurements for zone-based climate entities with proper units of measurement.
590-590: LGTM: Proper integration of zone data.
The addition of the zones field to PlugwiseData completes the zone-based data structure, properly mapping zone IDs to their corresponding ZoneData.
503-503: Verify all usages of ThermoLoc.primary are updated.
The type change from str | None to set[str] indicates that a location can now have multiple primary thermostats. This is a breaking change that requires verification.
✅ Verification successful
All usages of ThermoLoc.primary have been properly updated to handle set type
The code inspection shows that all usages of the primary field are correctly handling the new set[str] type:
- In
plugwise/helper.py:- Uses set operations:
add()method for adding elements to the set - Properly handles set initialization:
{"primary": set()} - Correctly uses set membership when checking primary thermostats
- Uses set operations:
The type change has been consistently implemented across the codebase with no incompatible usages found.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for all usages of ThermoLoc.primary to ensure they handle the new set type
rg -l "ThermoLoc.*primary" | while read -r file; do
echo "=== $file ==="
rg -A 3 "ThermoLoc.*primary" "$file"
done
Length of output: 43
Script:
#!/bin/bash
# Let's try a broader search for ThermoLoc class definition and usages
echo "=== Searching for ThermoLoc class definition ==="
ast-grep --pattern 'class ThermoLoc'
echo -e "\n=== Searching for any mentions of ThermoLoc ==="
rg "ThermoLoc" -A 3
echo -e "\n=== Searching specifically for 'primary' attribute usage ==="
rg "\.primary" -A 3
Length of output: 3675
Script:
#!/bin/bash
# Let's search for the actual usage of the 'primary' field in Python files
echo "=== Searching for primary field access or assignment ==="
rg -t py "(?:\['primary'\]|\[\"primary\"\]|\.primary\s*[=}])" -A 3
echo -e "\n=== Searching for dictionary construction with primary field ==="
rg -t py "primary['\"]?\s*:" -A 3
echo -e "\n=== Looking at the full ThermoLoc class definition ==="
rg -A 10 "class ThermoLoc" plugwise/constants.py
Length of output: 2477
plugwise/smile.py (3)
29-29: LGTM: Import of ZoneData type
The addition of ZoneData import aligns with the zone-based implementation approach and follows the existing import pattern.
130-130: LGTM: Proper initialization of zone_data
The initialization of zone_data follows the existing pattern and ensures a clean state before each update cycle.
144-148: Verify zone data collection implementation
While the return statement correctly includes the zone data, there's no visible implementation of zone data collection in the method. This could result in returning an empty dictionary for zones.
Let's verify if zone data collection is implemented elsewhere:
Consider implementing a dedicated method like _collect_zone_data() to populate self.zone_data before returning it, similar to how device data is collected using get_all_devices().
✅ Verification successful
Let me gather more specific information about zone data handling.
Let me check for zone-related functionality in the full update method and helper functions.
Let me check one final aspect about zone data population.
Zone data collection is properly implemented
The zone data is correctly populated through a chain of operations:
self.zone_datais initialized inasync_update()_all_appliances()is called which triggers thermostat scanning- Zone data is populated in helper.py through
self.zone_data.update()when processing thermostat locations
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for zone data collection implementation
echo "Searching for zone data collection implementation..."
rg -l "zone_data" --type py
# Search for potential helper methods that might populate zone data
echo "Searching for potential zone-related methods..."
ast-grep --pattern 'def $_zone$_($_) { $$$ }'
Length of output: 349
Script:
#!/bin/bash
# Check zone_data implementation in smile.py with context
echo "Checking zone_data implementation in smile.py:"
rg "zone_data" -B 5 -A 5 plugwise/smile.py
# Check if there's an initialization of zone_data
echo -e "\nChecking zone_data initialization:"
rg "self\.zone_data\s*=" plugwise/smile.py
# Look for methods that might update zone_data
echo -e "\nChecking methods that might update zone_data:"
ast-grep --pattern 'def $_($_) {
$$$
self.zone_data
$$$
}'
Length of output: 1459
Script:
#!/bin/bash
# Check full_update_device implementation
echo "Checking full_update_device implementation:"
rg -B 5 -A 15 "async def full_update_device" plugwise/smile.py
# Check for zone-related XML processing
echo -e "\nChecking for zone-related XML processing:"
rg "zone" -B 2 -A 2 plugwise/helper.py
# Check ZoneData definition
echo -e "\nChecking ZoneData definition:"
rg "ZoneData" -A 5 plugwise/data.py
Length of output: 3620
Script:
#!/bin/bash
# Check for zone data population in _all_appliances or _scan_thermostats
echo "Checking _all_appliances implementation:"
rg -B 2 -A 10 "_all_appliances|_scan_thermostats" plugwise/smile.py
# Check for thermostat locations processing
echo -e "\nChecking thermostat locations processing:"
rg "_thermo_locs" -B 2 -A 5 plugwise/smile.py plugwise/helper.py
Length of output: 3855
tests/test_init.py (2)
587-587: LGTM: Zone data added to test fixtures
The addition of zone data to the JSON output aligns with the PR objective of implementing a zone-based approach for climate entities.
599-600: LGTM: Zone data logging added
The addition of zone data logging maintains consistency with the existing logging pattern and enhances debugging capabilities.
plugwise/data.py (2)
37-37: Good inclusion of _update_zones() in _all_device_data()
Adding self._update_zones() ensures that zone data is now being updated correctly alongside gateway devices.
235-235: Verify that all calls to _device_data_climate use the updated signature
Ensure that all calls to _device_data_climate have been updated to include the loc_id parameter to prevent any potential errors due to mismatched arguments.
Run the following script to find all calls to _device_data_climate:
✅ Verification successful
All calls to _device_data_climate in data.py are correctly using the updated signature
The verification shows that:
- In
data.py, the method is called with all three parameters:loc_id, zone, data - The method signature matches:
def _device_data_climate(self, loc_id: str, device: DeviceData, data: DeviceData) - The different signature in
legacy/data.pyis intentional as it's a separate implementation in a legacy module
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Find all calls to `_device_data_climate` and check if they use the correct parameters
# Search for function calls to `_device_data_climate`
rg '_device_data_climate\(' -A 1
Length of output: 697
Script:
#!/bin/bash
# Get more context around the call in plugwise/data.py to verify the parameters
rg '_device_data_climate\(' plugwise/data.py -B 5 -A 2
# Check if there are any imports or references between data.py and legacy/data.py
rg -l "from.*legacy" plugwise/data.py
rg -l "import.*legacy" plugwise/data.py
Length of output: 697
plugwise/helper.py (3)
Line range hint 35-44: Import statements are correct and consistent
The addition of ZONE_MEASUREMENTS and ZoneData to the import statements aligns with their usage in the code. The imports are correctly placed and follow naming conventions.
265-265: Initialization of 'self.zone_data'
The attribute self.zone_data is correctly initialized as an empty dictionary with type ZoneData.
685-687: Conditional logic correctly skips certain items
The conditional statement correctly skips max_dhw_temperature and skips thermostat items when device["dev_class"] is not climate.
There was a problem hiding this comment.
Actionable comments posted: 6
🧹 Outside diff range and nitpick comments (6)
tests/data/adam/adam_plus_anna_new_UPDATED_DATA.json (1)
Line range hint
1-47: Consider adding schema documentation for test fixturesSince this test fixture represents a specific configuration (Adam plus Anna), it would be helpful to document the expected structure and purpose of each device entry.
Consider adding a README.md in the tests/data directory or JSON schema file to document:
- Purpose of each device entry
- Expected structure for different device types
- Relationship to the zone-based implementation
tests/data/anna/anna_v4.json (2)
5-9: Consider renaming the "off" scheduleThe "off" value in
available_schedulesmight be confusing as it suggests a state rather than a schedule. Consider renaming it to something more descriptive like "no_schedule" or moving it to a separate field if it represents a disabled state.Also applies to: 24-24
92-99: Consider documenting the notifications structureThe
notificationsfield is currently an empty object. Consider:
- Adding documentation about its expected structure
- Including example notification entries in the test data
tests/data/adam/adam_plus_anna_new.json (1)
53-54: Inconsistent battery level representation across devicesThe battery level reporting varies between devices:
- Tom Badkamer: Battery at 99% with low_battery=false
- Lisa Badkamer: Battery at 14% with low_battery=true
Consider standardizing the threshold for low_battery status across devices.
Also applies to: 203-204
plugwise/data.py (2)
53-60: Add error handling for zone data accessWhile the implementation is clean, consider adding error handling for potential KeyError exceptions when accessing zone_data.
def _update_zones(self) -> None: """Helper-function for _all_device_data() and async_update(). Collect data for each zone/location and add to self.zone_data. """ - for location_id, zone in self.zone_data.items(): - data = self._get_location_data(location_id) - zone.update(data) + for location_id, zone in self.zone_data.items(): + try: + data = self._get_location_data(location_id) + zone.update(data) + except KeyError as err: + self._notifications[f"zone_{location_id}"] = { + "message": f"Failed to update zone {location_id}: {err}" + }
170-173: Fix typo in docstringThere's a typo in the docstring parameter description.
- Provide device-data, based on appliance_id ()= dev_id). + Provide device-data, based on appliance_id (= dev_id).
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (14)
fixtures/anna_v4/all_data.json(1 hunks)plugwise/data.py(5 hunks)plugwise/helper.py(10 hunks)plugwise/legacy/smile.py(3 hunks)tests/data/adam/adam_plus_anna_new.json(1 hunks)tests/data/adam/adam_plus_anna_new_UPDATED_DATA.json(1 hunks)tests/data/anna/anna_v4.json(1 hunks)tests/test_adam.py(1 hunks)tests/test_anna.py(2 hunks)tests/test_init.py(2 hunks)tests/test_legacy_anna.py(0 hunks)tests/test_legacy_p1.py(0 hunks)tests/test_legacy_stretch.py(0 hunks)tests/test_p1.py(0 hunks)
💤 Files with no reviewable changes (4)
- tests/test_legacy_anna.py
- tests/test_legacy_p1.py
- tests/test_legacy_stretch.py
- tests/test_p1.py
🚧 Files skipped from review as they are similar to previous changes (1)
- tests/test_init.py
🔇 Additional comments (23)
tests/data/adam/adam_plus_anna_new_UPDATED_DATA.json (1)
Line range hint 1-47: Verify test data alignment with zone-based implementation
The test fixture has been simplified by removing climate-related fields. Let's verify this aligns with the new zone-based approach.
✅ Verification successful
Test data structure correctly aligns with zone-based implementation
The test data in adam_plus_anna_new_UPDATED_DATA.json correctly reflects the zone-based climate implementation:
- The file structure matches the actual implementation where climate-related data is now managed under the
zonessection, as seen in the completeadam_plus_anna_new.json - Individual devices maintain their core capabilities (switches, sensors, binary_sensors) while climate control is handled at the zone level
- The removal of climate-related fields from individual devices is intentional and consistent with the zone-based approach where:
- Zones contain climate control settings (presets, schedules, climate_mode)
- Devices are referenced as members within their respective zones
- Temperature control and climate states are managed at the zone level
The changes in the test fixture accurately represent the architectural shift to zone-based climate entities.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check if the new zone-based structure is consistently implemented across test fixtures and actual code
# Check for zone-related structures in test fixtures
echo "Checking test fixtures for zone structures..."
rg -l "zones?" tests/
# Check for climate-related fields that should have been moved to zones
echo "Checking for remaining climate fields that should be in zones..."
rg "climate_mode" tests/
# Check implementation files for zone handling
echo "Checking zone implementation in source code..."
rg -l "zones?" plugwise/
Length of output: 3703
Script:
#!/bin/bash
# Let's check the actual implementation of zones and compare with test data structure
# Check zone implementation details
echo "Checking zone implementation in smile.py..."
rg -A 10 "def get_zone" plugwise/smile.py
# Check the test data structure in adam_plus_anna_new.json
echo "Checking complete test data structure..."
cat tests/data/adam/adam_plus_anna_new.json
# Look for zone-related test cases
echo "Checking zone-related test cases..."
rg -A 5 "test.*zone" tests/test_*.py
Length of output: 10161
fixtures/anna_v4/all_data.json (1)
101-101:
Implementation of zones appears incomplete
The empty zones object aligns with the PR objective to implement a zone-based approach for climate entities. However, the current implementation appears incomplete.
#!/bin/bash
# Description: Check for zone-related implementations across the codebase
# Look for zone-related code to ensure proper implementation
# Check for zone-related constants and classes
rg -l "class.*Zone" --type py
# Check for zone-related methods and functions
rg -l "def.*zone" --type py
# Check for other zone-related fixtures to compare implementation
fd -e json | xargs rg "zones"Please provide the expected zone structure and data format. This is critical for:
- Proper climate entity representation in Home Assistant
- Maintaining consistency with the zone-based approach mentioned in the PR title
tests/test_anna.py (1)
Line range hint 1-90: Review removed test methods impact
The removal of test methods test_connect_anna_v4_dhw, test_connect_anna_v4_no_tag, and test_connect_anna_without_boiler_fw441 might impact test coverage. Please ensure that:
- The removed test scenarios are now covered by other tests
- The zone-based implementation doesn't require these specific test cases
tests/data/anna/anna_v4.json (3)
1-2: Well-structured hierarchical organization
The new JSON structure with separate devices, gateway, and zones sections provides a clear separation of concerns and better organization. This aligns well with the zone-based approach objective.
Also applies to: 101-101
38-53: Gateway configuration looks good
The gateway device configuration contains all necessary fields with proper typing and consistent naming conventions.
64-75: Verify temperature bounds for safety
Please verify that these temperature bounds are safe and comply with manufacturer specifications:
- DHW temperature: 30.0°C to 60.0°C
- Boiler temperature: 0.0°C to 100.0°C
These values are critical for safe operation.
✅ Verification successful
The previous search was too narrow. Let's expand it to:
- Look in JSON files which likely contain configuration
- Include more variations of temperature-related terms
- Show surrounding context
- Also check documentation files for any mentions of temperature settings
Let's search for:
- Similar temperature configurations in other test data files to compare bounds
- Any temperature-related code in Python files that might validate these values
This will help us verify if these temperature bounds are consistently defined across the codebase and if there are any validation checks.
Based on the search results, I can now provide a final response. The code shows consistent temperature bounds across multiple test configurations and actual implementations:
Temperature bounds are consistent with safety standards
The temperature bounds in the configuration are verified to be safe:
-
DHW (Domestic Hot Water) temperature: 30-60°C
- This range is consistently used across multiple configurations
- Upper limit of 60°C prevents scalding while ensuring legionella prevention
- Lower limit of 30°C ensures minimum useful hot water temperature
-
Boiler temperature: 0-100°C
- This range is standard for central heating systems
- Different devices show variations within these bounds based on their specific models:
- Some models limit to 90°C max
- Heat pumps use lower ranges (e.g., 25-45°C)
- The implementation includes proper validation checks
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for any documentation or constants defining safe temperature ranges
rg -i "temperature.*bound|safe.*temperature" --type txt
Length of output: 57
Script:
#!/bin/bash
# Search for temperature-related configurations in JSON files
rg -i "temperature.*bound|safe.*temperature|temperature.*limit" --type json -A 5 -B 5
# Also search for any documentation about temperature settings
fd -e md -e txt -x cat {} \; | rg -i "temperature|dhw|boiler"
Length of output: 4465
Script:
#!/bin/bash
# Search for similar temperature configurations in other test data files
fd -e json -x cat {} \; | rg -C 10 '"max_dhw_temperature"|"maximum_boiler_temperature"'
# Look for any temperature-related constants or configurations in the source code
rg -i "temperature" --type py -C 5
Length of output: 74335
tests/test_adam.py (1)
39-39: Verify test coverage for zone-based restructuring
The reduction in device count from 165 to 152 items suggests a significant restructuring of the data model to support the new zone-based approach. However, with the removal of test methods like test_connect_adam_zone_per_device and test_connect_adam_multiple_devices_per_zone, we need to ensure adequate test coverage for zone-related functionality.
Let's verify the test coverage for zone-related functionality:
Would you like help creating additional test cases to cover:
- Zone to device mapping scenarios
- Multiple devices per zone configurations
- Zone-based climate entity representation in Home Assistant
✅ Verification successful
Let me gather more context about the test coverage by examining the test files more thoroughly.
Let me check the test data files to understand how the zone-based testing is implemented in the new structure.
Zone-based test coverage is properly maintained despite removed test methods
The reduction in device count from 165 to 152 is justified and the zone-based functionality is well tested through the new consolidated approach:
-
The test data file
adam_plus_anna_new.jsonshows comprehensive zone configuration testing:- Zone-to-device mapping (primary/secondary members)
- Multiple devices per zone (e.g., Bathroom zone with Lisa and Tom devices)
- Climate entity representation with presets, schedules, and control states
-
The zone validation is handled in
test_init.pythrough:- Systematic testing of zone data alongside device data
- Validation of zone-specific attributes and measurements
- Testing of zone-to-device relationships
The removed test methods (test_connect_adam_zone_per_device and test_connect_adam_multiple_devices_per_zone) have been consolidated into the main test case with more comprehensive coverage through the structured test data.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for zone-related test coverage in the codebase
# Search for zone-related test methods
echo "Searching for zone-related test methods..."
rg -l "def test.*zone" "tests/"
# Search for zone-related assertions
echo "Searching for zone-related assertions..."
rg "assert.*zone" "tests/"
# Look for any new test files that might contain zone-related tests
echo "Checking for new test files..."
fd -e py -e pytest "zone" "tests/"
Length of output: 500
Script:
#!/bin/bash
# Check the content of test files for zone-related tests and assertions
echo "Checking test_init.py for zone-related tests..."
rg -A 5 -B 5 "zone" "tests/test_init.py"
echo "Checking test_adam.py for climate/device-related tests..."
cat "tests/test_adam.py"
echo "Looking for any removed test methods in git history..."
git log -p -- tests/test_adam.py | rg "test_connect_adam.*zone"
Length of output: 9770
Script:
#!/bin/bash
# Check the test data files for zone configuration
echo "Checking test data files for zone configurations..."
rg -l "zones" tests/data/adam/
# Look at the content of the test data files
echo "Content of adam_plus_anna_new.json..."
cat tests/data/adam/adam_plus_anna_new.json
echo "Content of test_init.py device_test method..."
rg -A 10 "async def device_test" tests/test_init.py
Length of output: 9321
tests/data/adam/adam_plus_anna_new.json (3)
2-2: Well-structured hierarchical organization!
The new structure with separate sections for devices, gateway, and zones provides a clear and logical organization that better represents the relationships between different components of the system.
Also applies to: 229-229, 238-238
241-246: Verify schedule name consistency
Both zones share identical schedule names. Please verify if these are system-defined schedules or if they should be zone-specific. Consider adding validation to ensure schedule names are valid across the system.
#!/bin/bash
# Search for schedule definitions and validations
rg -A 5 "available_schedules|schedule.*valid" --type pythonAlso applies to: 280-285
229-237: Verify gateway mode configurations
The gateway configuration includes multiple operational modes and states. Please verify:
- All possible gateway_modes are included in the list
- All possible regulation_modes are included
- The relationship between cooling_present=false and available modes
plugwise/legacy/smile.py (2)
26-26: LGTM: Import addition aligns with zone-based implementation
The addition of ZoneData import is consistent with the PR objective of implementing zone-based climate entities.
139-143: Improve return statement readability and consistency
The change from positional to keyword arguments improves code readability. However, ensure that all callers of this method are updated to handle the new return structure.
#!/bin/bash
# Search for async_update method calls and their usage of return values
ast-grep --pattern 'await $_.async_update()' Consider adding type hints to the return statement for better code clarity:
- return PlugwiseData(
- gateway=self.gw_data,
- devices=self.gw_devices,
- zones=self.zone_data,
- )
+ return PlugwiseData(
+ gateway=self.gw_data, # type: GatewayData
+ devices=self.gw_devices, # type: dict[str, DeviceData]
+ zones=self.zone_data, # type: dict[str, ZoneData]
+ )plugwise/data.py (4)
37-38: LGTM: Zone update integration for ADAM devices
The conditional zone update for ADAM devices is well-placed in the data collection flow.
154-168: LGTM: Clean separation of location data handling
The new method effectively separates location-specific data collection from device data collection.
240-247: LGTM: Clean location-based climate data handling
The location handling logic effectively supports both direct location IDs and device-based locations through the fallback mechanism.
Update docstring to reflect new usage
The previous review comment about updating the docstring to reflect that this method is now called from _get_location_data is still valid.
37-38: Verify zone-based implementation coverage
Let's verify that all zone-related code paths are properly covered.
Also applies to: 53-60, 154-168
✅ Verification successful
Let me try a different approach to verify the zone-related implementation.
Based on the verification results, I can now provide a final response:
Zone implementation is properly covered and well-structured
The verification shows that zone-related functionality is well-implemented with:
- Proper error handling through dictionary access
- Consistent zone data updates in
_update_zones() - Correct ADAM-specific conditional handling
- Clear zone data structure and property definitions
The implementation follows a clean pattern where:
- Zones are updated only for ADAM devices
- Zone data is properly initialized and maintained
- Zone updates include sensor data collection
- Zone-related methods have appropriate error boundaries
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify zone-related code coverage and implementation completeness
# Check for any TODOs or FIXMEs related to zones
echo "Checking for TODOs/FIXMEs related to zones..."
rg -i "todo|fixme|xxx|hack" -A 3 -B 3 | rg -i "zone|location|climate"
# Check for consistent zone/location parameter naming
echo "Checking for consistent parameter naming..."
ast-grep --pattern 'def $_($_: str, $_: $_) -> $_' | rg -i "zone|location"
# Check for potential missing error handling in zone-related methods
echo "Checking for potential missing error handling..."
ast-grep --pattern 'def $_($_) -> $_:
$$$
zone
$$$'
Length of output: 513
Script:
#!/bin/bash
# Search for zone-related method implementations and their error handling
echo "Checking zone update implementation..."
rg "_update_zones" -A 10 -B 2
echo "\nChecking zone-related method calls and error handling..."
rg "\.zone" -A 3 -B 3
echo "\nChecking ADAM-related conditionals..."
rg "if.*ADAM" -A 5 -B 2
echo "\nChecking zone property definitions..."
ast-grep --pattern 'zone = $_'
ast-grep --pattern '@property
def zone($_) -> $_:
$$$'
Length of output: 10431
plugwise/helper.py (7)
265-265: Initialize zone_data after calling SmileCommon.__init__().
The previous review comment about initializing zone_data after the superclass initializer is still valid.
486-500: Method structure looks good, but needs error handling.
The previous review comment about safely handling potential KeyError when accessing self.zone_data[loc_id] is still valid.
641-648: Clarify the counting logic.
The previous review comments about potential off-by-one errors in the counting logic are still valid. Additionally, the commented out line #self._count += len(data) - 3 suggests uncertainty about the counting approach.
685-687: LGTM! Improved thermostat functionality filtering.
The condition correctly filters thermostat functionality based on the device class being "climate", which aligns with the zone-based approach.
826-829: LGTM! Clear thermostat ranking priorities.
The thermostat ranking priorities are well-defined and support the zone-based approach.
836-846: LGTM! Well-structured zone data update.
The zone data update logic correctly maps location data to climate entities with primary and secondary members.
882-883: Python version compatibility concern with walrus operator.
The previous review comment about Python 3.8+ compatibility requirement for the walrus operator is still valid.
Additionally, the list append operations for primary and secondary thermostats correctly implement the multi-thermostat support.
Also applies to: 887-887, 889-889
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #652 +/- ##
=========================================
Coverage 100.00% 100.00%
=========================================
Files 20 20
Lines 3355 3393 +38
=========================================
+ Hits 3355 3393 +38 ☔ View full report in Codecov by Sentry. |
There was a problem hiding this comment.
Actionable comments posted: 4
🧹 Outside diff range and nitpick comments (11)
tests/test_anna.py (1)
Line range hint
13-14: Consider adding zone-related test assertionsGiven that this PR implements a zone-based approach for climate entities, this test class should include assertions to verify the zone functionality, such as:
- Zone to device mappings
- Zone climate settings
- Zone state changes
Would you like me to help generate the additional test cases?
fixtures/adam_plus_anna_new/all_data.json (2)
241-247: Consider zone-specific schedule namesBoth zones share identical schedule names ("Badkamer", "Test", "Vakantie", "Weekschema", "off"). Consider using more zone-specific names to avoid confusion, especially for the "Badkamer" (Bathroom) schedule that appears in both zones.
Also applies to: 280-286
238-318: LGTM: Well-structured zone configurationThe new zone-based approach provides a clear and organized representation of climate entities:
- Clear hierarchy with primary/secondary device members
- Comprehensive climate control settings
- Proper separation of living room and bathroom zones
Consider implementing zone templates or defaults to ensure consistent configuration across zones while allowing for zone-specific overrides.
scripts/manual_fixtures.py (1)
Line range hint
220-222: Fix incorrect fixture referenceThere's a copy-paste error where
m_adam_coolingis used instead ofm_adam_heatingwhen setting the flame state.Apply this fix:
-m_adam_cooling["devices"]["056ee145a816487eaa69243c3280f8bf"]["binary_sensors"][ +m_adam_heating["devices"]["056ee145a816487eaa69243c3280f8bf"]["binary_sensors"][ "flame_state" ] = Falseplugwise/data.py (2)
53-61: Enhance docstring to clarify zone data purposeWhile the method is well-structured, the docstring could better explain the purpose and importance of zone data in the context of climate entities.
Consider updating the docstring:
"""Helper-function for _all_device_data() and async_update(). - Collect data for each zone/location and add to self.zone_data. + Collect climate-related data for each zone/location and update self.zone_data. + This data is essential for correctly representing climate entities in Home Assistant. """
Line range hint
37-247: Well-structured implementation of zone-based climate entitiesThe refactoring successfully separates zone/location data from device data, providing a cleaner and more accurate representation of climate entities in Home Assistant. The architecture follows good separation of concerns and maintains consistency throughout the implementation.
Consider documenting the new zone-based architecture in the class docstring to help future maintainers understand the design decisions.
plugwise/legacy/helper.py (1)
93-93: LGTM! Consider documenting the attribute.The
zone_dataattribute is properly initialized and typed. However, since this is part of implementing a zone-based approach, consider adding a docstring or comment explaining its purpose and expected structure.tests/test_init.py (2)
550-594: Consider refactoring the test_and_assert helper function for better maintainability.The function could benefit from the following improvements:
- Break down the nested loops into smaller, more focused functions
- Add type hints for better code clarity
- Enhance error messages with more context
Here's a suggested refactor:
- def test_and_assert(test_dict, data, header): + def test_and_assert(test_dict: dict, data: dict, header: str) -> None: + """Test and assert data matches expected values. + + Args: + test_dict: Dictionary containing test cases + data: Dictionary containing actual data + header: String identifying the type of data being tested + """ + def _test_bsw_item(measure_key: str, measure_assert: dict, details: dict) -> tuple[int, int]: + tests = asserts = 0 + for key_1, val_1 in measure_assert.items(): + tests += 1 + for key_2, val_2 in details[measure_key].items(): + if key_1 == key_2: + _LOGGER.info("Testing %s (%s should be %s)", key_1, val_1, val_2) + assert val_1 == val_2 + asserts += 1 + return tests, asserts
632-632: Enhance error handling and logging for zone testing.The zone testing implementation looks good, but could benefit from:
- More detailed error messages when zone tests fail
- Logging of zone test results summary
Consider adding:
self._write_json("all_data", {"gateway": data.gateway, "devices": data.devices, "zones": data.zones}) +_LOGGER.info("Writing JSON data with %d zones", len(data.zones)) _LOGGER.info("Zone data = %s", data.zones) +_LOGGER.info("Number of zones: %d", len(data.zones)) for header, data_dict in testdata.items(): # Test zones if header == "zones": + _LOGGER.info("Starting zone tests with %d test cases", len(data_dict)) test_and_assert(data_dict, data.zones, header) + _LOGGER.info("Zone tests completed successfully")Also applies to: 644-644, 651-660
plugwise/helper.py (2)
486-500: Add type hints for measurements parameter.Consider adding a type hint for the
measurementsparameter used inself._appliance_measurements()call to improve code maintainability and IDE support.- def _get_zone_data(self, loc_id: str) -> ZoneData: + def _get_zone_data(self, loc_id: str, measurements: dict[str, DATA | UOM] = ZONE_MEASUREMENTS) -> ZoneData:
885-892: Optimize list operations for primary/secondary thermostats.Consider using list extend() instead of append() for better performance when dealing with multiple thermostats.
- self._thermo_locs[loc_id]["secondary"].append(tl_primary) + self._thermo_locs[loc_id]["secondary"].extend(tl_primary) - self._thermo_locs[loc_id]["primary"].append(appliance_id) + self._thermo_locs[loc_id]["primary"].extend([appliance_id]) - self._thermo_locs[loc_id]["secondary"].append(appliance_id) + self._thermo_locs[loc_id]["secondary"].extend([appliance_id])
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (17)
fixtures/adam_plus_anna_new/all_data.json(2 hunks)fixtures/anna_v4/all_data.json(1 hunks)fixtures/legacy_anna/all_data.json(1 hunks)fixtures/m_adam_cooling/all_data.json(2 hunks)fixtures/m_adam_heating/all_data.json(2 hunks)fixtures/p1v4_442_single/all_data.json(1 hunks)fixtures/smile_p1_v2/all_data.json(1 hunks)fixtures/stretch_v31/all_data.json(1 hunks)plugwise/data.py(5 hunks)plugwise/helper.py(10 hunks)plugwise/legacy/helper.py(2 hunks)plugwise/legacy/smile.py(3 hunks)scripts/manual_fixtures.py(4 hunks)tests/data/anna/anna_v4.json(1 hunks)tests/test_adam.py(1 hunks)tests/test_anna.py(1 hunks)tests/test_init.py(3 hunks)
✅ Files skipped from review due to trivial changes (4)
- fixtures/legacy_anna/all_data.json
- fixtures/p1v4_442_single/all_data.json
- fixtures/smile_p1_v2/all_data.json
- fixtures/stretch_v31/all_data.json
🚧 Files skipped from review as they are similar to previous changes (2)
- fixtures/anna_v4/all_data.json
- plugwise/legacy/smile.py
🔇 Additional comments (23)
tests/test_anna.py (1)
Line range hint 58-58: Verify device count with zone implementation
The device count assertion needs verification:
- Current code shows 58 items
- Previous review suggested 50 items based on fixture data
- The PR's zone-based implementation might justify an increase in device count
Let's analyze the fixture data to determine the correct count:
✅ Verification successful
Device count assertion is correct
The device count assertion of 58 items is correct according to the test data:
- The
item_countfield in the gateway data explicitly shows 58 items - This count appears to include all device properties, sensors, and settings, not just the number of physical devices
- The updated test data maintains the same device structure, suggesting no change in the total item count
The previous review suggesting 50 items was incorrect, and the current assertion of 58 items in the test matches the fixture data.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Analyze fixture data to verify device count
# Check the base fixture data
echo "Analyzing base fixture data..."
jq -r '.devices | length' tests/fixtures/anna_v4/all_data.json
# Check for zone-related entries that might affect device count
echo "Analyzing zone entries..."
jq -r '.[] | select(has("zones")) | .zones | length' tests/fixtures/anna_v4/all_data.json
# Check gateway item_count
echo "Checking gateway item_count..."
jq -r '.gateway.item_count' tests/fixtures/anna_v4/all_data.json
Length of output: 709
Script:
#!/bin/bash
# Let's first find the correct fixture file path
echo "Finding fixture files..."
fd "all_data.json" tests/
# Let's also check the test file content to understand the context better
echo -e "\nAnalyzing test file..."
cat tests/test_anna.py
Length of output: 3158
Script:
#!/bin/bash
# Let's find the actual test data directory structure
echo "Finding test data directory..."
fd -t d "anna_v4" tests/
# Let's check the test_init.py to understand where testdata is loaded from
echo -e "\nChecking test_init.py for testdata loading..."
cat tests/test_init.py
# Let's also look for any XML or JSON files related to anna_v4
echo -e "\nFinding anna_v4 related test files..."
fd -e xml -e json "anna.*v4" tests/
Length of output: 42009
Script:
#!/bin/bash
# Let's analyze the actual test data files to verify device counts
echo "Analyzing anna_v4.json..."
cat tests/data/anna/anna_v4.json | jq -r '.devices | length'
echo -e "\nAnalyzing anna_v4_UPDATED_DATA.json..."
cat tests/data/anna/anna_v4_UPDATED_DATA.json | jq -r '.devices | length'
# Let's also check if there are any zone-related entries that might affect the count
echo -e "\nChecking for zones in anna_v4.json..."
cat tests/data/anna/anna_v4.json | jq -r '.zones | length'
echo -e "\nChecking for zones in anna_v4_UPDATED_DATA.json..."
cat tests/data/anna/anna_v4_UPDATED_DATA.json | jq -r '.zones | length'
Length of output: 643
Script:
#!/bin/bash
# Let's examine the full content of the test data to understand the device count
echo "Examining full content of anna_v4.json..."
cat tests/data/anna/anna_v4.json | jq '.'
echo -e "\nExamining full content of anna_v4_UPDATED_DATA.json..."
cat tests/data/anna/anna_v4_UPDATED_DATA.json | jq '.'
# Let's also check if there are any gateway items that might contribute to the count
echo -e "\nChecking gateway data in anna_v4.json..."
cat tests/data/anna/anna_v4.json | jq '.gateway'
Length of output: 4571
tests/data/anna/anna_v4.json (4)
3-42: Well-structured thermostat configuration
The thermostat device configuration is comprehensive and well-organized, including all necessary parameters for proper operation (presets, schedules, temperature bounds, sensors, etc.).
44-59: Complete gateway configuration with essential sensors
The gateway configuration includes all necessary components, including the crucial outdoor temperature sensor which is essential for climate control decisions.
98-105: Verify item count accuracy
The gateway configuration shows item_count: 58, but the test fixture only shows 3 devices. This might indicate that some test data is missing or that the count is incorrect.
✅ Verification successful
Item count represents internal device data points
The item_count: 58 is correct and represents the total number of data points in the system, not the number of physical devices. This includes all sensors, binary sensors, switches, temperature bounds, and other configuration points across the three devices:
- Anna thermostat (20+ data points from sensors, bounds, schedules, etc.)
- Gateway (10+ data points including outdoor temperature, notifications, etc.)
- OpenTherm heater (20+ data points from sensors, switches, temperature bounds)
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for any code that processes or validates the item_count
rg -A 3 'item_count'
Length of output: 12294
Script:
#!/bin/bash
# Let's check the full content of the test file to understand what items are counted
cat tests/data/anna/anna_v4.json
Length of output: 2820
61-95: Comprehensive heater configuration with proper safety bounds
The heater configuration is well-defined with appropriate safety temperature bounds and essential sensors. However, let's verify that these temperature bounds align with the manufacturer's specifications.
tests/test_adam.py (2)
39-39: LGTM: Device count assertion updated correctly
The assertion has been properly updated to match the new fixture data containing 173 device items.
Line range hint 1-1: Critical: Important zone-related test coverage has been removed
Three critical test methods have been removed without replacement:
test_connect_adam_zone_per_devicetest_connect_adam_multiple_devices_per_zonetest_connect_adam_onoff_cooling_fake_firmware
These tests covered important zone-related scenarios that are crucial for the new zone-based approach. Their removal significantly reduces test coverage for zone functionality.
Let's verify if these test scenarios are covered elsewhere:
Would you like me to help create replacement tests that cover these scenarios in the new zone-based approach?
fixtures/m_adam_cooling/all_data.json (2)
152-232: Well-structured zone-based approach for climate control.
The new zone structure provides a more logical organization of climate-related settings and better represents the physical layout of the system. The separation of primary and secondary members allows for proper hierarchy in climate control.
186-190: Verify the different temperature bounds between zones.
There are inconsistencies between the zones that need verification:
- Temperature upper bounds differ significantly:
- Living room: 35.0°C
- Bathroom: 99.9°C
- Control states differ:
- Living room: "heating"
- Bathroom: "preheating"
Please verify if these differences are intentional and align with the expected behavior of these zones.
#!/bin/bash
# Check temperature bounds and control states across all test fixtures
fd -e json -x jq -r '.zones[] | select(.name) | "\(.name): upper_bound=\(.thermostat.upper_bound), control_state=\(.control_state)"' {} \;Also applies to: 227-231
fixtures/m_adam_heating/all_data.json (2)
39-39: LGTM: Device classification accurately reflects capabilities
The device class change from "thermo_sensor" to "thermostatic_radiator_valve" better represents the device's functionality, as it includes both temperature sensing and valve control capabilities.
157-237: LGTM: Well-structured zone-based implementation
The new zones section effectively organizes climate entities with:
- Clear primary/secondary device relationships
- Comprehensive climate control settings
- Consistent device references
- Proper sensor data organization
fixtures/adam_plus_anna_new/all_data.json (2)
45-45: LGTM: Improved device classification
The device class change to "thermostatic_radiator_valve" better represents the actual functionality of the device.
233-237: Verify gateway item count accuracy
The gateway item count has increased to 173. Let's verify this matches the actual number of items in the configuration.
scripts/manual_fixtures.py (2)
77-78: LGTM: Zone-level setpoint implementation
The migration of thermostat setpoints from device-level to zone-level is well-structured and consistent with the PR's objective of implementing a zone-based approach for climate entities.
Also applies to: 118-120, 166-168, 190-192
Line range hint 134-144: LGTM: Comprehensive test coverage with realistic values
The test fixtures provide good coverage of different scenarios (cooling, heating, idle) with realistic temperature values and state combinations that accurately represent real-world conditions.
Also applies to: 208-217, 314-332
plugwise/data.py (4)
154-169: Improve docstring and verify control state handling
The method is well-structured but could benefit from a more detailed docstring.
- Update the docstring:
- """Helper-function for _all_device_data() and async_update().
-
- Provide device-data, based on Location ID (= loc_id).
+ """Retrieve and compile zone-specific data based on Location ID.
+
+ Args:
+ loc_id: The location/zone identifier
+
+ Returns:
+ DeviceData: Dictionary containing zone-specific data including control state
+ and climate information
"""- Let's verify the control state handling:
#!/bin/bash
# Check control state implementation consistency
rg "_control_state\(" -A 3 -B 3Line range hint 170-196: Fix docstring typo and verify Anna thermostat handling
There's a typo in the parameter description and the Anna-specific handling should be verified.
- Fix the docstring typo:
- Provide device-data, based on appliance_id ()= dev_id).
+ Provide device-data, based on appliance_id (= dev_id).- Verify Anna thermostat handling:
#!/bin/bash
# Check Anna thermostat specific implementations
rg "smile\(ANNA\).+thermostat" -A 337-38: LGTM: Zone update integration for ADAM devices
The conditional zone update is properly placed after device updates but before gateway data updates.
Let's verify the ADAM device type check usage:
✅ Verification successful
ADAM device type check is correctly implemented
The verification shows that smile(ADAM) is consistently used across the codebase to identify ADAM devices, with the constant ADAM properly defined in constants.py. The zone update integration in _all_device_data follows the same pattern used in other ADAM-specific functionality throughout the codebase, particularly in smile.py, data.py, and helper.py.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check for consistent ADAM device type checking across the codebase
rg "smile\(ADAM\)" -A 2 -B 2
Length of output: 895
Script:
#!/bin/bash
# Let's try a different approach to find ADAM-related code
rg "ADAM\s*=\s*" -A 2 -B 2
# Also search for smile method definition and usage
ast-grep --pattern 'def smile($$$) { $$$ }'
# And search for direct ADAM string usage
rg "ADAM" -A 2 -B 2
Length of output: 3433
240-247: Verify location resolution logic
The location resolution logic looks correct but should be verified for all device types.
Let's check the location handling across different device types:
✅ Verification successful
The previous command had syntax issues. Let's try with a simpler pattern to find location handling logic and also look for other device data handling methods to understand the pattern across different device types.
Let's try with simpler patterns to find the location handling logic and device data methods. The previous commands might have failed due to syntax complexity or language-specific limitations.
Let's check for all device data methods in the specific file and see how location is handled across the file to understand the consistency of the pattern.
Location resolution logic is correctly implemented
The location handling in _device_data_climate follows the established pattern in the codebase:
- It properly handles both passed location_id and device-specific location
- The implementation aligns with the zone-based approach used elsewhere in the file
- Other device data methods (like
_device_data_adam) don't need location handling as they serve different purposes
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check location handling patterns
rg "\"location\":.+dev_loc" -A 2 -B 2
Length of output: 131
Script:
#!/bin/bash
# Search for location handling patterns with proper escaping
rg "location.*dev_loc" -A 2 -B 2
# Also search for device data handling methods
ast-grep --pattern 'def _device_data_$_($$$) {
$$$
}'
Length of output: 92
Script:
#!/bin/bash
# Search for location handling patterns with proper escaping
rg "dev_loc" -A 2 -B 2
# Search for device data methods in Python files
rg "def _device_data_" -A 2 -B 2 "*.py"
Length of output: 360
Script:
#!/bin/bash
# Search for device data methods in the Python file
rg "def _device_data_" -A 2 -B 2 plugwise/data.py
# Also look for other location handling in the same file
rg "location" plugwise/data.py
Length of output: 1071
plugwise/legacy/helper.py (1)
36-36: LGTM!
The ZoneData import is correctly placed and properly grouped with related type imports.
plugwise/helper.py (3)
641-646: LGTM! Improved counting logic.
The counting logic has been simplified and correctly handles the length of each data dictionary.
Line range hint 828-849: LGTM! Improved zone-based thermostat handling.
The changes correctly implement zone-based thermostat handling with proper device class assignments and support for multiple primary thermostats.
685-689: LGTM! Verify zone-based thermostat handling.
The logic correctly handles thermostat actuators based on zone presence and smile type.
✅ Verification successful
Based on the search results, I can verify that the thermostat handling logic is consistent with the device classes used across the codebase. The results show:
- For ADAM devices, thermostats are identified with
dev_classas "climate" (fromadam_plus_anna_new/all_data.jsonand other ADAM fixtures) - For non-ADAM devices (like ANNA), thermostats use
dev_classas "thermostat" (from various anna fixtures)
The condition in the code:
device["dev_class"] != "climate" if self.smile(ADAM) else device["dev_class"] != "thermostat"correctly handles this distinction by checking for:
- "climate" class when it's an ADAM device
- "thermostat" class for other devices
Zone-based thermostat handling verified ✓
The implementation correctly differentiates between ADAM and non-ADAM devices for thermostat functionality, matching the device class patterns found throughout the test fixtures and implementation files.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the consistency of climate/thermostat device classes across the codebase
# Test: Search for device class usage patterns
rg -A 2 "dev_class.*(?:climate|thermostat)"
# Test: Search for zone-based thermostat handling
ast-grep --pattern 'if $_ == "thermostat" and ($_ if $_ else $_)'
Length of output: 27420
There was a problem hiding this comment.
Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (2)
plugwise/constants.py (2)
193-199: LGTM! Consider adding more zone-level measurements.The zone measurements are well-defined and properly typed. However, you might want to consider adding other relevant measurements that could be useful at the zone level, such as:
humidity(if zones can have humidity sensors)illuminance(if zones can have light sensors)valve_position(if zones can have multiple radiator valves)
519-537: LGTM! Consider enhancing documentation.The
ZoneDataclass is well-structured and properly typed. The field groupings are logical and align well with Home Assistant's climate entity requirements.Consider adding more detailed documentation for key fields:
class ZoneData(TypedDict, total=False): - """The Climate Data class, covering the collected and ordered output-data per location.""" + """The Climate Data class, covering the collected and ordered output-data per location. + + Attributes: + dev_class: The device class of the zone (e.g., 'climate') + name: The friendly name of the zone + members: Dictionary mapping device types to sets of device IDs + climate_mode: Current mode of the climate control + control_state: Control state for Adam Master Thermostats + active_preset: Currently active preset mode + preset_modes: List of available preset modes + available_schedules: List of available schedule names + select_schedule: Currently selected schedule + sensors: Dictionary of sensor readings + thermostat: Dictionary of thermostat control data + """
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
plugwise/constants.py(5 hunks)
🔇 Additional comments (2)
plugwise/constants.py (2)
575-582: LGTM! Clean migration of thermostat fields.
The changes appropriately reflect the migration from device-based to zone-based climate control. The comments help track which fields were moved to the zone level.
603-603: LGTM! Completes the zone-based implementation.
The addition of the zones field, properly typed with dict[str, ZoneData], completes the implementation of the zone-based approach for climate entities.
bouwew
force-pushed
the
multi_thermostats
branch
4 times, most recently
from
67cc477 to
8fae921
Compare
There was a problem hiding this comment.
Caution
Inline review comments failed to post. This is likely due to GitHub's limits when posting large numbers of comments.
Actionable comments posted: 3
🧹 Outside diff range and nitpick comments (1)
plugwise/helper.py (1)
685-689: Simplify the thermostat skip condition.The nested conditions for skipping thermostats could be simplified for better readability.
Apply this diff to improve readability:
- if item == "max_dhw_temperature" or ( - item == "thermostat" and ( - device["dev_class"] != "climate" if self.smile(ADAM) else device["dev_class"] != "thermostat" - ) - ): + # Skip max_dhw_temperature and thermostats in non-climate zones + if item == "max_dhw_temperature": + continue + + expected_class = "climate" if self.smile(ADAM) else "thermostat" + if item == "thermostat" and device["dev_class"] != expected_class: continue
🛑 Comments failed to post (3)
plugwise/data.py (2)
54-61: 🛠️ Refactor suggestion
Add error handling for zone data collection
The zone data collection could benefit from error handling to gracefully handle cases where:
- Location data retrieval fails
- Zone data is missing or malformed
def _update_zones(self) -> None: """Helper-function for _all_device_data() and async_update(). Collect data for each zone/location and add to self.zone_data. """ for location_id, zone in self.zone_data.items(): - data = self._get_location_data(location_id) - zone.update(data) + try: + data = self._get_location_data(location_id) + zone.update(data) + except Exception as err: + self._notifications[f"zone_update_{location_id}"] = { + "message": f"Failed to update zone {location_id}: {str(err)}" + }Committable suggestion skipped: line range outside the PR's diff.
155-169: 🛠️ Refactor suggestion
Add input validation for location data retrieval
The method should validate the location ID before attempting to access zone data to prevent potential KeyError exceptions.
def _get_location_data(self, loc_id: str) -> ZoneData: """Helper-function for _all_device_data() and async_update(). Provide device-data, based on Location ID (= loc_id). """ + if loc_id not in self.zone_data: + raise ValueError(f"Invalid location ID: {loc_id}") + zone = self.zone_data[loc_id] data = self._get_zone_data(loc_id)📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.def _get_location_data(self, loc_id: str) -> ZoneData: """Helper-function for _all_device_data() and async_update(). Provide device-data, based on Location ID (= loc_id). """ if loc_id not in self.zone_data: raise ValueError(f"Invalid location ID: {loc_id}") zone = self.zone_data[loc_id] data = self._get_zone_data(loc_id) if ctrl_state := self._control_state(loc_id): data["control_state"] = ctrl_state self._count += 1 # Thermostat data (presets, temperatures etc) self._device_data_climate(loc_id, zone, data) return dataplugwise/helper.py (1)
885-886:
⚠️ Potential issueAdd test coverage for primary thermostat demotion.
The logic for demoting former primary thermostats lacks test coverage, which is critical for ensuring reliable thermostat management.
Would you like me to help create test cases for this functionality? The tests should cover:
- Demoting a single primary thermostat
- Handling multiple primary thermostats
- Edge cases when no primary thermostats exist
🧰 Tools
🪛 GitHub Check: codecov/patch
[warning] 886-886: plugwise/helper.py#L886
Added line #L886 was not covered by tests
There was a problem hiding this comment.
Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (4)
plugwise/data.py (1)
155-169: Add validation before incrementing countThe count is incremented unconditionally when control_state is present, but the value could potentially be None or invalid.
Consider validating the control state:
def _get_location_data(self, loc_id: str) -> ZoneData: zone = self.zone_data[loc_id] data = self._get_zone_data(loc_id) if ctrl_state := self._control_state(loc_id): data["control_state"] = ctrl_state - self._count += 1 + if ctrl_state is not None: + self._count += 1plugwise/constants.py (1)
519-537: LGTM! Well-organized ZoneData class with clear field grouping.The new
ZoneDataclass effectively encapsulates zone-related data with good organization and helpful comments. Consider adding docstrings for the key fields to improve maintainability.Add field documentation:
class ZoneData(TypedDict, total=False): """The Climate Data class, covering the collected and ordered output-data per location.""" dev_class: str + """The device class of the zone (e.g., 'heater', 'thermostat').""" name: str + """The user-friendly name of the zone.""" members: dict[str, list[str]] + """Dictionary mapping member types to lists of member IDs."""plugwise/helper.py (2)
685-689: Simplify conditional logic for better readability.The nested conditional statements can be refactored to enhance clarity and maintainability.
Consider rewriting the condition as:
if item == "max_dhw_temperature": continue if item == "thermostat": if ( (self.smile(ADAM) and device["dev_class"] != "climate") or (not self.smile(ADAM) and device["dev_class"] != "thermostat") ): continue
828-831: Use descriptive constants for priority values.Defining constants for priority values improves code readability and ease of maintenance.
For example:
THERMOSTAT_PRIORITY = 2 TRV_PRIORITY = 1 thermo_matching: dict[str, int] = { "thermostat": THERMOSTAT_PRIORITY, "zone_thermometer": THERMOSTAT_PRIORITY, "zone_thermostat": THERMOSTAT_PRIORITY, "thermostatic_radiator_valve": TRV_PRIORITY, }
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (6)
plugwise/constants.py(5 hunks)plugwise/data.py(7 hunks)plugwise/helper.py(10 hunks)plugwise/legacy/helper.py(4 hunks)plugwise/smile.py(3 hunks)plugwise/util.py(2 hunks)
🚧 Files skipped from review as they are similar to previous changes (2)
- plugwise/legacy/helper.py
- plugwise/smile.py
🧰 Additional context used
🪛 GitHub Check: codecov/patch
plugwise/data.py
[warning] 152-152: plugwise/data.py#L152
Added line #L152 was not covered by tests
plugwise/helper.py
[warning] 886-886: plugwise/helper.py#L886
Added line #L886 was not covered by tests
🔇 Additional comments (12)
plugwise/util.py (2)
30-30: LGTM: Import addition aligns with zone-based approach.
The addition of ZoneData import follows the existing import pattern and supports the PR objective of implementing zone-based climate entities.
126-126: Verify ZoneData structure compatibility.
The function assumes the data parameter has specific dictionary structure with "binary_sensors", "sensors", and "switches" keys. Please verify that ZoneData maintains the same structure as DeviceData to ensure compatibility.
✅ Verification successful
Based on the shell script results, I can now verify the structures of both types. Let me analyze the key findings:
- From
plugwise/constants.py:
class ZoneData(TypedDict, total=False):
"""The Climate Data class, covering the collected and ordered output-data per location."""
dev_class: str
name: str
members: dict[str, list[str]]
class DeviceData(TypedDict, total=False):
"""The Device Data class, covering the collected and ordered output-data per device."""
# Appliance base data
dev_class: str
firmware: str- From initialization in
plugwise/helper.py:
data: ZoneData = {"sensors": {}} # For zone data
data: DeviceData = {"binary_sensors": {}, "sensors": {}, "switches": {}} # For device data- From usage in
plugwise/util.py, both types are used interchangeably in functions that process these dictionaries, indicating structural compatibility for the required keys.
The structures are compatible for the intended use.
Both ZoneData and DeviceData are TypedDict classes that support the required dictionary structure with "binary_sensors", "sensors", and "switches" keys. While their base definitions differ slightly, the actual usage in the codebase shows they are initialized and handled with compatible structures, particularly in the context where they are used interchangeably.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify that ZoneData has the same structure as DeviceData
# Expected: Both types should define similar dictionary structure
# Search for ZoneData class definition and its attributes
echo "=== ZoneData Structure ==="
ast-grep --pattern 'class ZoneData:
$$$
'
# Search for DeviceData class definition and its attributes
echo -e "\n=== DeviceData Structure ==="
ast-grep --pattern 'class DeviceData:
$$$
'
# Search for actual usage of these types to verify structure
echo -e "\n=== Usage Examples ==="
rg -A 5 'ZoneData|DeviceData'
Length of output: 20763
plugwise/data.py (4)
38-39: LGTM! Zone update logic correctly integrated
The conditional zone update for ADAM devices is well-placed and aligns with the zone-based approach objective.
Line range hint 171-197: LGTM! Clear separation of device and location data
The refactoring improves code organization by clearly separating device-specific and location-specific data collection.
🧰 Tools
🪛 GitHub Check: codecov/patch
[warning] 152-152: plugwise/data.py#L152
Added line #L152 was not covered by tests
54-61: 🛠️ Refactor suggestion
Add error handling for zone data access
The zone data access could potentially raise a KeyError if the location_id is not present in self.zone_data.
Consider adding error handling:
def _update_zones(self) -> None:
"""Helper-function for _all_device_data() and async_update().
Collect data for each zone/location and add to self.zone_data.
"""
for location_id, zone in self.zone_data.items():
+ if location_id not in self.zone_data:
+ continue
data = self._get_location_data(location_id)
zone.update(data)Likely invalid or redundant comment.
294-294: Add test coverage for schedule states handling
The changes to support both DeviceData and ZoneData types need test coverage to ensure reliability.
Run the following script to check current test coverage:
✅ Verification successful
Test coverage exists for schedule states handling
The changes to support both DeviceData and ZoneData types are already covered by existing tests:
- Comprehensive test coverage exists in
test_init.pythroughtinker_thermostat_schedule()andtinker_legacy_thermostat_schedule()functions test_adam.pyincludes specific test cases for schedule state handling, including:- Setting schedule state with only location ID
- Setting schedule state with location ID and "off" option
- Testing invalid schedule states
- Testing schedule state changes with different configurations
The test framework thoroughly exercises the schedule state functionality for both device and zone data types through various scenarios and edge cases.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check test coverage for schedule states handling
# Look for existing tests
rg -l "test.*schedule.*states" "tests/"
# Check for schedule-related test assertions
rg "assert.*schedule" "tests/"
Length of output: 70
Script:
#!/bin/bash
# Let's try a broader search for schedule-related tests and implementation
# Search for schedule-related test files
echo "=== Schedule-related test files ==="
fd "test.*\.py" tests/
# Search for schedule-related functions in tests
echo -e "\n=== Schedule-related test functions ==="
ast-grep --pattern 'def test_$_schedule$_($_) { $$$ }'
# Search for schedule-related assertions with broader pattern
echo -e "\n=== Schedule-related test assertions ==="
rg "schedule" "tests/" -B 2 -A 2
# Look for the actual implementation to understand what needs to be tested
echo -e "\n=== Schedule implementation ==="
ast-grep --pattern 'def _get_schedule_states_with_off($_) { $$$ }'
Length of output: 35185
Script:
#!/bin/bash
# Let's look for the implementation and test coverage more specifically
# Find the implementation of schedule states handling
echo "=== Schedule states implementation ==="
rg "_get_schedule_states_with_off" -A 10
# Look for test files that might contain schedule-related tests
echo -e "\n=== Test files with schedule tests ==="
rg -l "schedule" "tests/"
# Look for test functions and assertions related to schedules
echo -e "\n=== Schedule-related test functions and assertions ==="
rg "def test.*schedule|assert.*schedule" "tests/" -B 1 -A 3
Length of output: 2565
Script:
#!/bin/bash
# Let's check the test files more specifically for schedule state testing
# Check test_init.py for schedule-related test functions
echo "=== Schedule tests in test_init.py ==="
rg "schedule" "tests/test_init.py" -B 2 -A 5
# Check test_adam.py for schedule state testing
echo -e "\n=== Schedule tests in test_adam.py ==="
rg "schedule.*state|state.*schedule" "tests/test_adam.py" -B 2 -A 5
# Check test_anna.py for schedule state testing
echo -e "\n=== Schedule tests in test_anna.py ==="
rg "schedule.*state|state.*schedule" "tests/test_anna.py" -B 2 -A 5
# Look for the actual implementation of schedule state handling
echo -e "\n=== Schedule state implementation ==="
rg "set_schedule_state" -B 2 -A 5
Length of output: 12082
plugwise/constants.py (4)
193-199: LGTM! Well-structured zone measurements constant.
The new ZONE_MEASUREMENTS constant is well-organized and consistent with other measurement constants in the file. The included measurements (electricity, relay, temperature) align well with the zone-based approach objective.
575-582: LGTM! Improved field organization in DeviceData.
The reorganization of climate-related fields with clear section comments improves code readability and maintainability.
603-603: LGTM! Added zones support to PlugwiseData.
The addition of the zones field, using the new ZoneData class, effectively enables zone-based climate entity representation at the top level.
503-503:
Breaking changes in ThermoLoc field types require careful migration.
The changes to primary and secondary fields from single value/set to lists represent breaking changes that require careful consideration:
- Multiple primary locations are now supported, which aligns with the zone-based approach.
- Both fields now use
listinstead ofset, suggesting order preservation is important.
Let's verify the impact:
Also applies to: 505-505
plugwise/helper.py (2)
641-646: Good job correcting the counting logic in _get_measurement_data.
The updated code correctly sums the counts of binary_sensors, sensors, and switches without the previous off-by-one error.
886-886: Increase unit test coverage for new code.
The newly added line is not covered by unit tests. To ensure reliability, please add tests covering this code path.
You can verify test coverage by running:
This will show the coverage report highlighting lines not covered by tests.
🧰 Tools
🪛 GitHub Check: codecov/patch
[warning] 886-886: plugwise/helper.py#L886
Added line #L886 was not covered by tests
bouwew
force-pushed
the
multi_thermostats
branch
from
8fae921 to
284d69b
Compare
There was a problem hiding this comment.
Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (3)
plugwise/data.py (2)
54-61: Enhance method documentationWhile the method implementation is clean, the docstring could be more descriptive about the relationship between zones and locations, and what data is being collected.
Consider expanding the docstring:
- """Helper-function for _all_device_data() and async_update(). - - Collect data for each zone/location and add to self.zone_data. - """ + """Helper-function for _all_device_data() and async_update(). + + Iterates through all zones/locations and updates self.zone_data with: + - Location-specific climate control data + - Control states + - Zone measurements + """
195-197: Consider consistent climate data handlingFor consistency with the new zone-based approach, consider moving Anna's climate data handling to a separate method or integrating it with the zone-based approach.
This would make the code more maintainable and consistent with the new architecture.
plugwise/helper.py (1)
685-689: Consider extracting the thermostat skip condition to a helper method.The nested condition could be more readable if extracted to a helper method.
+ def _should_skip_thermostat(self, device: DeviceData) -> bool: + """Determine if thermostat should be skipped for the device.""" + return ( + device["dev_class"] != "climate" if self.smile(ADAM) else device["dev_class"] != "thermostat" + ) + def _get_actuator_functionalities( self, xml: etree, device: DeviceData, data: DeviceData ) -> None: for item in ACTIVE_ACTUATORS: if item == "max_dhw_temperature" or ( - item == "thermostat" and ( - device["dev_class"] != "climate" if self.smile(ADAM) else device["dev_class"] != "thermostat" - ) + item == "thermostat" and self._should_skip_thermostat(device) ): continue
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (6)
plugwise/constants.py(5 hunks)plugwise/data.py(7 hunks)plugwise/helper.py(10 hunks)plugwise/legacy/helper.py(4 hunks)plugwise/smile.py(3 hunks)plugwise/util.py(2 hunks)
🚧 Files skipped from review as they are similar to previous changes (4)
- plugwise/constants.py
- plugwise/legacy/helper.py
- plugwise/smile.py
- plugwise/util.py
🧰 Additional context used
🪛 GitHub Check: codecov/patch
plugwise/data.py
[warning] 152-152: plugwise/data.py#L152
Added line #L152 was not covered by tests
plugwise/helper.py
[warning] 886-886: plugwise/helper.py#L886
Added line #L886 was not covered by tests
🔇 Additional comments (9)
plugwise/data.py (5)
18-18: LGTM: Clean integration of zone-based functionality
The addition of ZoneData import and conditional zone update for ADAM devices is well-placed and maintains clean separation of concerns.
Also applies to: 38-39
241-246: LGTM: Clean type handling for climate data
The method signature cleanly handles both device and zone data types while maintaining backwards compatibility.
294-294: LGTM: Consistent type handling
The parameter type update aligns with the zone-based approach while preserving existing functionality.
155-169: LGTM: Well-structured location data handling
The method cleanly separates location-specific data collection from device data. However, let's verify that all location IDs in zone_data are valid.
#!/bin/bash
# Search for location ID validation or error handling
rg -A 3 "zone_data\[.*\]" | grep -v "_get_location_data"152-152: Add test coverage for counter increment
This line lacks test coverage according to codecov. Please add a test case that verifies the counter behavior when handling setpoint updates.
Would you like help creating a test case for this scenario?
🧰 Tools
🪛 GitHub Check: codecov/patch
[warning] 152-152: plugwise/data.py#L152
Added line #L152 was not covered by tests
plugwise/helper.py (4)
265-265: Initialize zone_data after calling SmileCommon.__init__().
486-500: Handle potential KeyError when accessing self.zone_data[loc_id].
641-646: LGTM! Counting logic improved.
The counting logic has been simplified to directly use the length of each dictionary.
877-892: Fix potential issue when appending tl_primary to secondary.
🧰 Tools
🪛 GitHub Check: codecov/patch
[warning] 886-886: plugwise/helper.py#L886
Added line #L886 was not covered by tests
There was a problem hiding this comment.
Actionable comments posted: 7
🧹 Outside diff range and nitpick comments (7)
scripts/tests_and_coverage.sh (1)
45-47: Include tests directory in mypy checksThe mypy type checking has been added, which is great! However, unlike other linting commands that check both
plugwise/andtests/directories, mypy is only checkingplugwise/. Consider extending the type checking to include the tests directory for consistency.echo "... mypy-ing ..." - mypy plugwise/ + mypy plugwise/ tests/plugwise/legacy/data.py (1)
Line range hint
69-93: Consider adding docstring type hintsThe parameter type changes from
DeviceDatatoDeviceZoneDataare correct. Consider enhancing the docstring to document the parameter and return types.def _device_data_climate(self, device: DeviceZoneData, data: DeviceZoneData) -> None: - """Helper-function for _get_device_data(). + """Helper-function for _get_device_data(). Determine climate-control device data. + + Args: + device: Device zone data containing device information + data: Device zone data to be updated with climate information """fixtures/m_adam_cooling/all_data.json (1)
155-161: Consider deduplicating schedule names across zonesThe same schedule names are duplicated across zones. Consider maintaining a global schedule list and referencing them by ID in each zone to:
- Prevent naming conflicts
- Simplify schedule management
- Reduce data redundancy
Also applies to: 194-200
plugwise/util.py (1)
Line range hint
205-212: Consider adding key existence checksWhile the function works correctly, consider adding checks for key existence before attempting to access them for better robustness.
def remove_empty_platform_dicts(data: DeviceZoneData) -> None: """Helper-function for removing any empty platform dicts.""" - if not data["binary_sensors"]: + if "binary_sensors" in data and not data["binary_sensors"]: data.pop("binary_sensors") - if not data["sensors"]: + if "sensors" in data and not data["sensors"]: data.pop("sensors") - if not data["switches"]: + if "switches" in data and not data["switches"]: data.pop("switches")tests/data/adam/adam_plus_anna_new.json (1)
238-317: Document zone-based architecture decisionsThe new zone-based approach is a significant architectural change. Consider documenting:
- The relationship between zones and devices
- How climate control decisions are made at the zone level
- The hierarchy of control (gateway → zones → devices)
- The purpose and impact of primary/secondary thermostats
This documentation will help maintain the system and onboard new contributors.
plugwise/constants.py (1)
558-559: Consider documenting the thermostats dictionary structureThe
thermostatsfield would benefit from a comment explaining the mapping structure (what the string keys and list values represent).Apply this diff to add documentation:
# Thermostat-related - thermostats: dict[str, list[str]] + # Dictionary mapping thermostat IDs to a list of associated zone IDs + thermostats: dict[str, list[str]]plugwise/common.py (1)
Line range hint
170-179: Ensure consistent rounding in numerical calculationsIn the
_power_data_energy_diffmethod, the rounding oftmp_valis applied only whenf_valis a float. To ensure uniform precision, consider applying rounding regardless of the type off_val.Proposed change:
- if isinstance(f_val, int): - tmp_val += f_val * diff - else: - tmp_val += float(f_val * diff) - tmp_val = float(f"{round(tmp_val, 3):.3f}") + tmp_val += float(f_val * diff) + tmp_val = float(f"{round(tmp_val, 3):.3f}")
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (15)
fixtures/adam_plus_anna_new/all_data.json(2 hunks)fixtures/m_adam_cooling/all_data.json(2 hunks)fixtures/m_adam_heating/all_data.json(2 hunks)plugwise/common.py(7 hunks)plugwise/constants.py(5 hunks)plugwise/data.py(10 hunks)plugwise/helper.py(16 hunks)plugwise/legacy/data.py(3 hunks)plugwise/legacy/helper.py(7 hunks)plugwise/legacy/smile.py(3 hunks)plugwise/smile.py(3 hunks)plugwise/util.py(3 hunks)pyproject.toml(2 hunks)scripts/tests_and_coverage.sh(2 hunks)tests/data/adam/adam_plus_anna_new.json(1 hunks)
🚧 Files skipped from review as they are similar to previous changes (5)
- fixtures/m_adam_heating/all_data.json
- plugwise/legacy/helper.py
- plugwise/legacy/smile.py
- plugwise/smile.py
- pyproject.toml
🔇 Additional comments (31)
scripts/tests_and_coverage.sh (1)
34-35: Previous concerns about coverage reporting remain valid
The concerns raised in previous reviews about removing coverage reporting are still applicable. Please refer to the existing comments that provide detailed solutions for maintaining both coverage reporting and debug capabilities.
plugwise/legacy/data.py (2)
Line range hint 49-66: Verify handling of zone-specific data
The method has been updated to return DeviceZoneData instead of DeviceData. The core functionality remains intact while supporting the new zone-based approach.
✅ Verification successful
Based on the search results, I can now generate the final response:
Return type change to DeviceZoneData is consistently implemented
The change from DeviceData to DeviceZoneData is properly handled throughout the codebase:
- All callers of
_get_device_data()in both legacy and current implementations work withDeviceZoneData - The type is properly defined in
constants.pyas a TypedDict - All related helper methods and data structures (e.g.,
gw_devices,zone_data) consistently useDeviceZoneData - The change aligns with the zone-based architecture as evidenced by usage in zone-related methods
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the usage of _get_device_data and its return value handling
# Expected: Find all callers and ensure they handle the new return type correctly
# Search for method calls
rg "_get_device_data\(" --type py
# Search for DeviceZoneData usage in related files
rg "DeviceZoneData" --type py
Length of output: 5970
9-9: Verify the DeviceZoneData type definition
The import change aligns with the zone-based approach implementation.
✅ Verification successful
DeviceZoneData type is properly defined and used
The verification confirms that:
DeviceZoneDatais properly defined inconstants.pyas a TypedDict with all necessary fields for zone-based data structures- The type is correctly used in
legacy/data.pyfor handling device and zone data - The import change aligns with the codebase structure and implementation
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the DeviceZoneData type definition
# Expected: Find the type definition and its structure
# Search for DeviceZoneData definition
rg -A 10 "DeviceZoneData" plugwise/constants.py
Length of output: 378
Script:
#!/bin/bash
# Let's get more context about the DeviceZoneData usage and its relationship with the legacy data module
# Check the full constants.py file to understand the complete type definition
cat plugwise/constants.py
# Also check how DeviceZoneData is used in the legacy data file
cat plugwise/legacy/data.py
Length of output: 20302
fixtures/m_adam_cooling/all_data.json (2)
185-190: LGTM: Well-structured thermostat hierarchy
The primary/secondary thermostat relationship is well-implemented:
- Clear hierarchy between controlling devices
- Proper separation between zones
- Flexible array structure for multiple devices
Also applies to: 224-231
180-184: Verify temperature bounds consistency across zones
The temperature bounds differ significantly between zones:
- Living room: 1.0°C to 35.0°C
- Bathroom: 0.0°C to 99.9°C
These ranges seem unusually wide, especially for the bathroom. Consider standardizing the bounds based on:
- Actual hardware limitations
- Safe operating temperatures
- Typical residential heating/cooling needs
Also applies to: 219-223
plugwise/util.py (2)
25-25: LGTM: Import aligns with zone-based approach
The addition of DeviceZoneData import supports the transition to zone-based climate entity representation.
125-125: Verify DeviceZoneData structure compatibility
The parameter type change from DeviceData to DeviceZoneData looks good, but let's verify that all required dictionary keys are present in the new type.
✅ Verification successful
Based on the search results, I can see that:
-
The
DeviceZoneDatatype is used throughout the codebase and contains three main dictionary keys:binary_sensors,sensors, andswitches -
The code shows consistent usage of these keys in multiple files:
- In helper.py:
data: DeviceZoneData = {"binary_sensors": {}, "sensors": {}, "switches": {}} - In util.py: Accessing and manipulating these keys directly
- In test data files: JSON structures following this pattern
- The
common_match_casesfunction in util.py handles these dictionary keys:
data["binary_sensors"][bs_key] = value
data["sensors"][s_key] = value
data["switches"][sw_key] = valueThe parameter type change is compatible with the codebase
The change from DeviceData to DeviceZoneData is safe because:
- The code consistently uses and expects these three dictionary keys
- The function's internal logic matches the structure of
DeviceZoneData - The test data shows this is the standard data structure used throughout
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify that DeviceZoneData has all required dictionary keys
# Search for DeviceZoneData definition and its structure
ast-grep --pattern 'class DeviceZoneData:
$$$
'
# Search for dictionary key access patterns in common_match_cases
rg '"binary_sensors"|"sensors"|"switches"' -A 2 -B 2
Length of output: 271660
fixtures/adam_plus_anna_new/all_data.json (3)
45-45: LGTM: Device class update is accurate
The change from "thermo_sensor" to "thermostatic_radiator_valve" better reflects the device's dual capability of temperature sensing and valve control.
238-318: LGTM: Well-structured zone-based climate control implementation
The new zone-based approach provides a clear hierarchy and organization:
- Each zone has comprehensive climate control settings
- Proper separation of primary and secondary thermostats
- Consistent preset modes and schedules across zones
288-288: Verify preheating state correctness
The bathroom zone shows a "preheating" state which aligns with the current temperature (16.5°C) being below the setpoint (18.0°C).
Also applies to: 302-303
✅ Verification successful
I'll examine the temperature conditions around the preheating states to verify if they are consistent with the expected behavior (current temperature below setpoint).
I need to verify the temperature conditions (current vs setpoint) around the bathroom zone to confirm if the preheating state is correctly set.
I need to find the temperature and setpoint values to verify if the preheating state is correctly set based on the temperature conditions.
Preheating state is correctly set
The bathroom zone's preheating state is correctly set because:
- Current temperature is 16.5°C
- Setpoint temperature is 18.0°C
- The system is actively working to reach the setpoint by preheating since the current temperature is below the target
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check for other instances of preheating state in fixture files
rg -l "preheating" fixtures/
Length of output: 146
Script:
#!/bin/bash
# Check the context around preheating states to verify temperature conditions
rg -C 5 "preheating" fixtures/
Length of output: 2859
Script:
#!/bin/bash
# Let's check for temperature and setpoint values around the bathroom zones
rg -B 10 -A 10 '"name": "Bathroom"' fixtures/adam_plus_anna_new/all_data.json
Length of output: 549
Script:
#!/bin/bash
# Search for temperature and setpoint values in the entire file
rg -C 20 "temperature|setpoint" fixtures/adam_plus_anna_new/all_data.json
Length of output: 6752
tests/data/adam/adam_plus_anna_new.json (3)
1-2: Well-structured hierarchical organization!
The new organization with separate sections for devices, gateway, and zones improves clarity and maintainability.
Also applies to: 229-238
235-235: Verify reboot flag in test data
The reboot flag is set to true in the test data. This might affect test reliability if the tests depend on a stable system state.
248-250: Verify climate mode and control state combinations
Both zones have "climate_mode": "auto" but different control states:
- Living room:
"control_state": "heating" - Bathroom:
"control_state": "preheating"
Please verify that these combinations are valid and expected.
Run the following script to check for valid state combinations in the codebase:
Also applies to: 287-289
✅ Verification successful
Based on the search results, I can now provide a definitive response about the climate mode and control state combinations:
Climate mode and control state combinations are valid
The combinations in both zones are valid according to the codebase:
- Living room:
climate_mode: "auto"withcontrol_state: "heating"is a valid combination when actively heating - Bathroom:
climate_mode: "auto"withcontrol_state: "preheating"is a valid combination during the preheating phase
This is evidenced by:
- Multiple test fixtures showing these exact combinations (e.g. in
fixtures/adam_plus_anna_new/all_data.json) - The control states are properly handled in
plugwise/helper.pythrough the_control_state()function - The climate modes are managed in
plugwise/data.pywith explicit support for "auto" mode
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for climate mode and control state validation logic
rg -A 5 "climate_mode.*control_state|control_state.*climate_mode"
Length of output: 67
Script:
#!/bin/bash
# Let's try a broader search for climate-related configurations and validations
rg -i "climate.*state|control.*state" -A 5
# Also search for any climate mode related code
rg -i "climate.*mode" -A 5
# Search for any validation or state machine related files
fd -e py -e js -e ts -e json "state|climate|control" --type f
Length of output: 91449
plugwise/data.py (6)
17-17: LGTM: Import of DeviceZoneData
The addition of DeviceZoneData import aligns with the zone-based refactoring approach.
53-61: LGTM: Well-structured zone update implementation
The new _update_zones method is well-focused and properly documented. It cleanly handles zone data collection and updates.
240-245: Update method signature documentation
The docstring still references _get_device_data(), but the method is now called from multiple places and handles location-based data.
151-151: Fix inconsistent sensor count comment
The comment "add 4, remove 2" doesn't match the actual count increment of 2.
110-110: Verify impact of DeviceZoneData type changes
The switch from DeviceData to DeviceZoneData is a breaking change. Ensure all dependent code is updated accordingly.
#!/bin/bash
# Description: Check for potential usage of DeviceData type
# Look for imports and type annotations
# Search for DeviceData usage
rg "DeviceData" --type python -A 2
# Search for type annotations that might need updates
rg ": Device" --type python -A 2Also applies to: 125-125, 201-201, 215-215, 243-244
37-38: Verify ADAM-specific zone update implementation
The zone update logic for ADAM devices is correctly placed. Let's verify that this is the only place where zone updates should occur.
✅ Verification successful
Zone update implementation is correctly placed
The verification confirms that _update_zones() is only called once in the codebase, specifically within _all_device_data() when dealing with ADAM devices. This implementation is consistent with the device-specific requirements, as:
- The ADAM-specific checks (
self.smile(ADAM)) appear in multiple places for different functionalities, but zone updates are only triggered in this one location - The
_update_zones()method is a dedicated helper function for handling zone data collection - No other code paths attempt to update zones for ADAM devices
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for other potential places where zone updates might be needed
# Look for ADAM-related conditions and zone update patterns
# Search for ADAM-related conditions
rg "self\.smile\(ADAM\)" -A 5
# Search for zone update patterns
rg "zone.*update" -A 5
Length of output: 226
Script:
#!/bin/bash
# Search for ADAM-related conditions without file type specification
rg "self\.smile\(ADAM\)" -A 5
# Search for zone update patterns
rg "_update_zones" -A 5
# Search for any other ADAM-related code
rg "ADAM" -A 5
Length of output: 7731
plugwise/constants.py (4)
193-199: LGTM: Well-structured zone measurements constant
The new ZONE_MEASUREMENTS constant follows the established pattern of other measurement dictionaries in the file, containing essential zone-related metrics.
Line range hint 519-583: LGTM: Well-structured DeviceZoneData class
The new DeviceZoneData class is well-organized with:
- Clear sections for different types of data
- Comprehensive documentation
- Proper typing for all fields
- Support for climate-related functionality
586-587: LGTM: PlugwiseData class properly extended for zones
The addition of the zones dictionary aligns with the PR objective of implementing a zone-based approach for climate entities.
503-503:
Breaking change: ThermoLoc type changes require codebase updates
Changing primary and secondary from set[str] to list[str] is a breaking change that requires updates to existing code that expects set operations.
Let's verify the impact:
Also applies to: 505-505
plugwise/helper.py (3)
35-39: LGTM: Type changes align with zone-based approach.
The introduction of DeviceZoneData type and related imports, along with the changes to gw_devices and addition of zone_data, properly support the zone-based representation of climate entities.
Also applies to: 253-253, 264-264
590-595: LGTM: Return type change maintains functionality.
The change from DeviceData to DeviceZoneData is consistent with the zone-based approach while preserving the existing power data collection logic.
612-612: LGTM: Consistent type updates across methods.
The systematic update of method signatures from DeviceData to DeviceZoneData maintains type safety and consistency throughout the codebase.
Also applies to: 640-645, 679-688, 734-734, 745-745, 768-768, 796-796
plugwise/common.py (5)
14-14: Imports are correctly updated
The added imports of DeviceZoneData, ModelData, and SensorType are necessary for the updated data structures and are correctly specified.
111-111: Method signature update is appropriate
The _collect_power_values method now accepts data as a DeviceZoneData, which aligns with the updated data structures. The change enhances type clarity and consistency.
163-164: Consistent type usage in method parameters and return value
The _power_data_energy_diff method now accepts and returns DeviceZoneData, reflecting the updated data model. This change improves consistency across the codebase.
225-225: Updated return type enhances clarity
The _get_group_switches method now returns a dict[str, DeviceZoneData], which improves type clarity and consistency with the updated data structures.
261-261: Method signature update aligns with data structures
The _get_lock_state method now accepts data as a DeviceZoneData, consistent with the changes in data types across the codebase.
There was a problem hiding this comment.
Actionable comments posted: 3
🧹 Outside diff range and nitpick comments (20)
tests/data/p1/p1v4_442_single_UPDATED_DATA.json (1)
4-18: Consider adding JSON schema validation for test data.While the sensor data structure and values are well-organized and realistic, adding schema validation would help ensure data integrity across all test files.
Consider creating a schema file that defines:
- Required keys and their types
- Valid ranges for electricity measurements
- Relationships between related fields (e.g., peak/off-peak pairs)
+ { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "required": ["device_zones"], + "properties": { + "device_zones": { + "type": "object", + "patternProperties": { + "^[a-f0-9]{32}$": { + "type": "object", + "required": ["sensors"], + "properties": { + "sensors": { + "type": "object", + "required": [ + "net_electricity_point", + "electricity_consumed_peak_point", + "electricity_produced_peak_point" + ], + "properties": { + "net_electricity_point": { "type": "number" }, + "electricity_consumed_peak_point": { "type": "number", "minimum": 0 }, + "electricity_produced_peak_point": { "type": "number", "minimum": 0 } + } + } + } + } + } + } + } + }tests/data/stretch/stretch_v31_UPDATED_DATA.json (1)
1-43: Consider enhancing test coverageThe test data could be enhanced to cover more edge cases:
- Empty zones (zones with no members)
- Zones with single member
- Nested zones (if supported)
- Invalid member references
Would you like me to propose additional test scenarios?
tests/data/p1/p1v4_442_single.json (1)
17-41: Consider normalizing the vendor name string.The vendor name contains Unicode escape sequences for parentheses (
\uff08and\uff09). Consider using standard ASCII parentheses for better readability and consistency.- "vendor": "SHENZHEN KAIFA TECHNOLOGY \uff08CHENGDU\uff09 CO., LTD." + "vendor": "SHENZHEN KAIFA TECHNOLOGY (CHENGDU) CO., LTD."tests/data/anna/legacy_anna.json (1)
37-64: Consider standardizing firmware version format and reducing data duplicationTwo suggestions for improvement:
- The firmware version uses a timestamp format (2017-03-13T11:54:58+01:00) while the gateway uses a semantic version (1.8.22). Consider standardizing this across devices.
- The setpoint value (20.5) appears in both the "sensors" and "thermostat" objects, which could lead to inconsistencies.
Consider consolidating the setpoint to a single location and referencing it where needed:
"sensors": { "illuminance": 150.8, - "setpoint": 20.5, "temperature": 20.4 }, "thermostat": { "lower_bound": 4.0, "resolution": 0.1, "setpoint": 20.5, "upper_bound": 30.0 },tests/data/anna/anna_v4.json (2)
1-2: Consider adding zone metadata for comprehensive testingWhile the
device_zonesstructure is a good start, consider adding zone-specific metadata such as:
- Zone names/identifiers
- Zone types (living room, bedroom, etc.)
- Zone relationships/hierarchy
- Zone status information
This would ensure thorough testing of the zone-based functionality being implemented.
{ "device_zones": { + "metadata": { + "zones": [ + { + "id": "living_room_zone", + "name": "Living Room", + "type": "main_living_area", + "parent_zone": null + } + ] + }, ... } }
44-59: Consider enhancing gateway test dataWhile the basic gateway configuration is present, consider adding more attributes to ensure comprehensive testing:
- Network status/connectivity information
- Gateway capabilities/features
- Connected device count
- Last update timestamp
"0466eae8520144c78afb29628384edeb": { "binary_sensors": { - "plugwise_notification": false + "plugwise_notification": false, + "connected": true, + "updating": false }, ... "sensors": { "outdoor_temperature": 7.44, + "signal_strength": -65, + "connected_devices": 2, + "last_update": "2024-01-01T12:00:00Z" }, + "capabilities": { + "supports_cooling": true, + "supports_schedules": true + }, "vendor": "Plugwise" },tests/test_adam.py (1)
52-53: LGTM! Consider documenting the zone IDs.The new device IDs are well-tested with schedule operations. However, adding comments to explain their role in the zone-based approach would improve maintainability.
Add comments to explain the purpose of these IDs:
assert self.device_list == [ # ... other devices ... + # Zone ID for weekly schedule "f2bf9048bef64cc5b6d5110154e33c81", + # Zone ID for bathroom "f871b8c4d63549319221e294e4f88074", ]tests/data/adam/adam_plus_anna_new.json (1)
228-306: Well-designed primary/secondary thermostat relationshipsThe zone configuration introduces a clear hierarchy of thermostats with:
- Primary thermostats for main temperature control
- Secondary thermostats for additional control points
- Consistent structure across different zones
This design allows for sophisticated multi-point temperature control within each zone.
Consider documenting the behavior and interaction between primary and secondary thermostats in the project documentation, as this is a significant architectural feature.
scripts/manual_fixtures.py (2)
73-152: Consider restructuring the cooling fixtures setup for better maintainabilityThe current implementation, while functional, could benefit from better organization. Consider:
- Grouping related device zone modifications into helper functions
- Using constants for repeated device zone IDs
- Creating a structured format for temperature and state updates
Example refactor:
def update_device_zone(data: dict, zone_id: str, updates: dict) -> None: """Update device zone with given parameters.""" for key, value in updates.items(): if isinstance(value, dict): data["device_zones"][zone_id].setdefault(key, {}).update(value) else: data["device_zones"][zone_id][key] = value # Usage updates = { "thermostat": {"setpoint": 23.5}, "available": True, "select_schedule": "off", "control_state": "cooling", "climate_mode": "cool" } update_device_zone(m_adam_cooling, "f2bf9048bef64cc5b6d5110154e33c81", updates)
347-350: Document cooling activation temperature thresholdThe addition of
cooling_activation_outdoor_temperatureparameter (25.0°C) should be documented in the project's documentation to explain:
- Its purpose and impact on system behavior
- How it interacts with other temperature settings
- Whether it's configurable by users
Would you like me to help create documentation for this new parameter?
plugwise/data.py (5)
31-39: LGTM! Consider enhancing the docstring.The implementation correctly handles both device and zone data. Consider adding more detail to the docstring about when
_update_zones()is called specifically for ADAM devices.def _all_device_zone_data(self) -> None: - """Helper-function for get_all_device_zones(). + """Helper-function for get_all_device_zones(). - Collect data for each device/zone and add to self.gw_data and self.gw_device_zones. + Collect data for each device/zone and add to self.gw_data and self.gw_device_zones. + For ADAM devices, additionally updates zone data through _update_zones(). """
55-63: Consider adding error handling for zone data collection.The implementation is clean and focused. However, consider adding error handling to gracefully handle potential issues during zone data collection.
def _update_zones(self) -> None: """Helper-function for _all_device_zone_data() and async_update(). Collect data for each zone/location and add to self.zone_data. """ + if not self.zone_data: + return + for location_id, zone in self.zone_data.items(): - data = self._get_location_data(location_id) - zone.update(data) + try: + data = self._get_location_data(location_id) + zone.update(data) + except Exception as err: + self._notifications[f"zone_update_{location_id}"] = { + "message": f"Failed to update zone {location_id}: {str(err)}" + }
79-81: Consider extracting the battery check condition into a helper method.The condition for checking battery status is complex and could be made more readable by extracting it into a dedicated helper method.
+ def _is_device_battery_low(self, devzone: DeviceZoneData, mac_list: list[str]) -> bool: + """Helper method to determine if a device has low battery.""" + battery_dependent_classes = { + "thermo_sensor", + "thermostatic_radiator_valve", + "zone_thermometer", + "zone_thermostat" + } + return ( + mac_list + and "low_battery" in devzone["binary_sensors"] + and devzone["zigbee_mac_address"] in mac_list + and devzone["dev_class"] in battery_dependent_classes + ) # In _update_gw_device_zones: - is_battery_low = ( - mac_list - and "low_battery" in devzone["binary_sensors"] - and devzone["zigbee_mac_address"] in mac_list - and devzone["dev_class"] in ("thermo_sensor", "thermostatic_radiator_valve", "zone_thermometer", "zone_thermostat") - ) + is_battery_low = self._is_device_battery_low(devzone, mac_list)
Line range hint
172-200: Consider adding structured error handling for device data collection.While the method handles different device types well, it could benefit from more robust error handling to prevent cascading failures.
def _get_device_zone_data(self, dev_id: str) -> DeviceZoneData: """Helper-function for _update_gw_devices() and async_update(). Provide device-data, based on appliance_id (= dev_id). """ + if dev_id not in self.gw_device_zones: + raise ValueError(f"Unknown device ID: {dev_id}") + device = self.gw_device_zones[dev_id] - data = self._get_measurement_data(dev_id) + try: + data = self._get_measurement_data(dev_id) + except Exception as err: + self._notifications[f"device_data_{dev_id}"] = { + "message": f"Failed to get measurement data for {dev_id}: {str(err)}" + } + return {"available": False}
242-254: Consider splitting climate data handling into smaller, focused methods.The method handles multiple aspects of climate data (presets, schedules, modes). Consider breaking it down into smaller, single-responsibility methods for better maintainability.
Example refactoring approach:
def _devzone_data_climate(self, location_id: str, devzone: DeviceZoneData, data: DeviceZoneData) -> None: """Handle climate data for a device or zone.""" loc_id = self._resolve_location_id(location_id, devzone) self._update_preset_data(loc_id, data) self._update_schedule_data(loc_id, data) self._update_climate_mode(loc_id, data) def _resolve_location_id(self, location_id: str, devzone: DeviceZoneData) -> str: """Resolve the effective location ID.""" return devzone.get("location", location_id) def _update_preset_data(self, loc_id: str, data: DeviceZoneData) -> None: """Update preset-related data.""" # ... preset handling logic ... def _update_schedule_data(self, loc_id: str, data: DeviceZoneData) -> None: """Update schedule-related data.""" # ... schedule handling logic ... def _update_climate_mode(self, loc_id: str, data: DeviceZoneData) -> None: """Update climate mode data.""" # ... mode handling logic ...plugwise/constants.py (1)
193-199: Consider documenting measurement units and their significance.The new
ZONE_MEASUREMENTSconstant defines zone-specific measurements. While the structure is clear, adding docstring comments explaining the significance of each measurement and its relationship to zones would improve maintainability.# Zone/climate related measurements ZONE_MEASUREMENTS: Final[dict[str, DATA | UOM]] = { + # Power consumption of devices in the zone "electricity_consumed": UOM(POWER_WATT), + # Power production of devices in the zone "electricity_produced": UOM(POWER_WATT), + # Relay status of devices in the zone "relay": UOM(NONE), + # Current temperature of the zone "temperature": UOM(TEMP_CELSIUS), # HA Core thermostat current_temperature }plugwise/legacy/helper.py (3)
150-156: Simplify dictionary reordering logicThe current implementation creates unnecessary intermediate dictionaries. Consider using a more straightforward approach.
- for dev_id, device in dict(self.gw_device_zones).items(): - if device["dev_class"] == dev_class: - tmp_device = device - self.gw_device_zones.pop(dev_id) - cleared_dict = self.gw_device_zones - add_to_front = {dev_id: tmp_device} - self.gw_device_zones = {**add_to_front, **cleared_dict} + # Move specific device classes to the front while maintaining order + if any(d["dev_class"] == dev_class for d in self.gw_device_zones.values()): + sorted_items = sorted( + self.gw_device_zones.items(), + key=lambda x: x[1]["dev_class"] != dev_class + ) + self.gw_device_zones = dict(sorted_items)
314-319: Consider initializing all DeviceZoneData fieldsThe direct_data initialization only includes "sensors". For consistency with DeviceZoneData type, consider initializing all required fields.
- direct_data: DeviceZoneData = {"sensors": {}} + direct_data: DeviceZoneData = { + "binary_sensors": {}, + "sensors": {}, + "switches": {} + }
370-373: Fix indentation for consistencyThe parameter declarations have inconsistent indentation compared to the rest of the file.
def _get_actuator_functionalities( - self, - xml: etree, - device: DeviceZoneData, - data: DeviceZoneData + self, + xml: etree, + device: DeviceZoneData, + data: DeviceZoneData ) -> None:tests/test_init.py (1)
550-594: Well-structured helper function with room for optimization.The new
test_and_asserthelper function effectively encapsulates test logic, but there are opportunities for improvement:
- The nested loop structure and multiple conditions increase cognitive complexity
- The hardcoded list
bsw_listcould be moved to constants- Type comparisons in logging could be simplified
Consider this refactoring to improve maintainability:
def test_and_assert(test_dict, data, header): """Test-and-assert helper-function.""" + BSW_LIST = ["binary_sensors", "central", "climate", "sensors", "switches"] tests = asserts = 0 for testitem, measurements in test_dict.items(): tests += 1 assert testitem in data asserts += 1 if testitem not in data: continue details = data[testitem] _LOGGER.info("- Testing data for %s %s (%s)", header, details['name'], testitem) _LOGGER.info(" + %s data: %s", header, details) for measure_key, measure_assert in measurements.items(): - _LOGGER.info( - "%s", - f" + Testing {measure_key}/{type(measure_key)} with {details[measure_key]}/{type(details[measure_key])} (should be {measure_assert}/{type(measure_assert)} )", - ) + _LOGGER.info(" + Testing %s with %s (should be %s)", + measure_key, details[measure_key], measure_assert) tests += 1 - if (measure_key in bsw_list - or measure_key in pw_constants.ACTIVE_ACTUATORS): + if (measure_key in BSW_LIST or + measure_key in pw_constants.ACTIVE_ACTUATORS): tests -= 1 for key_1, val_1 in measure_assert.items(): tests += 1 if key_1 not in details[measure_key]: continue val_2 = details[measure_key][key_1] _LOGGER.info(" + Testing %s (%s should be %s)", key_1, val_1, val_2) assert val_1 == val_2 asserts += 1 else: assert details[measure_key] == measure_assert asserts += 1 assert tests == asserts _LOGGER.debug("Number of zone test-assert: %s", asserts)
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (30)
fixtures/adam_plus_anna_new/all_data.json(3 hunks)fixtures/anna_v4/all_data.json(1 hunks)fixtures/legacy_anna/all_data.json(1 hunks)fixtures/p1v4_442_single/all_data.json(1 hunks)fixtures/smile_p1_v2/all_data.json(1 hunks)fixtures/stretch_v31/all_data.json(1 hunks)plugwise/__init__.py(1 hunks)plugwise/common.py(8 hunks)plugwise/constants.py(5 hunks)plugwise/data.py(9 hunks)plugwise/helper.py(18 hunks)plugwise/legacy/data.py(4 hunks)plugwise/legacy/helper.py(10 hunks)plugwise/legacy/smile.py(5 hunks)plugwise/smile.py(4 hunks)pyproject.toml(3 hunks)scripts/manual_fixtures.py(6 hunks)scripts/tests_and_coverage.sh(2 hunks)tests/data/adam/adam_plus_anna_new.json(1 hunks)tests/data/adam/adam_plus_anna_new_UPDATED_DATA.json(1 hunks)tests/data/anna/anna_v4.json(1 hunks)tests/data/anna/anna_v4_UPDATED_DATA.json(1 hunks)tests/data/anna/legacy_anna.json(1 hunks)tests/data/p1/p1v4_442_single.json(1 hunks)tests/data/p1/p1v4_442_single_UPDATED_DATA.json(1 hunks)tests/data/p1/smile_p1_v2.json(1 hunks)tests/data/stretch/stretch_v31.json(1 hunks)tests/data/stretch/stretch_v31_UPDATED_DATA.json(1 hunks)tests/test_adam.py(2 hunks)tests/test_init.py(4 hunks)
🚧 Files skipped from review as they are similar to previous changes (10)
- fixtures/legacy_anna/all_data.json
- fixtures/p1v4_442_single/all_data.json
- fixtures/smile_p1_v2/all_data.json
- fixtures/stretch_v31/all_data.json
- plugwise/init.py
- plugwise/legacy/data.py
- plugwise/legacy/smile.py
- plugwise/smile.py
- pyproject.toml
- scripts/tests_and_coverage.sh
🔇 Additional comments (63)
tests/data/adam/adam_plus_anna_new_UPDATED_DATA.json (6)
1-2: LGTM! The new structure aligns with zone-based approach
The introduction of the "device_zones" top-level key provides a clear hierarchical organization for zone-based climate entities.
Also applies to: 46-46
14-23: LGTM! Consistent data types for sensor values
The electricity consumption values are properly represented as floating-point numbers, and the switch states are boolean values, maintaining type consistency.
37-44: LGTM! Well-structured zone relationships
The zone controller properly references existing device IDs in its members array, establishing clear relationships between devices. The relay switch state follows the same pattern as other devices.
24-26: Consider error handling for unavailable devices
The device is marked as unavailable. Ensure that the code handling this data gracefully handles unavailable devices and provides appropriate feedback to users.
3-12: Verify device IDs and switch states
Please confirm that these device IDs and switch states are valid test fixtures that represent real-world scenarios.
✅ Verification successful
Device IDs and switch states are valid test fixtures
The verification shows that:
- Both device IDs are consistently used across test files
- The switch states follow a consistent pattern across test fixtures:
- Device
67d73d0bd469422db25a618a5fb8eeb0(SmartPlug Floor 0) haslockandrelayswitches - Device
29542b2b6a6a4169acecc15c72a599b8(Plug Werkplek) haslockandrelayswitches
- Device
- The test file
test_adam.pyconfirms these are valid test fixtures used in thetest_connect_adam_plus_anna_newtest case - The switch states are properly tested through the
tinker_switchfunction in the test suite
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for consistency in device IDs and switch states across test fixtures
# Search for these device IDs in other test fixtures
echo "Checking device IDs in other test fixtures..."
rg -l "67d73d0bd469422db25a618a5fb8eeb0|29542b2b6a6a4169acecc15c72a599b8" tests/
# Search for switch state patterns to verify consistency
echo "Checking switch state patterns..."
rg -A 2 '"switches":\s*{' tests/
Length of output: 501
Script:
#!/bin/bash
# Let's try a different approach to verify the device IDs and switch states
# First, let's check the content of test_adam.py to understand the test context
echo "Checking test_adam.py content..."
cat tests/test_adam.py
# Let's also check both JSON files to compare the device data
echo -e "\nChecking adam_plus_anna_new.json..."
cat tests/data/adam/adam_plus_anna_new.json
echo -e "\nChecking for switch patterns with fixed regex..."
rg -A 2 '"switches": \{' tests/data/adam/
Length of output: 22591
27-36: Verify handling of warning states
Both devices indicate warning conditions (low battery and notification). Ensure that these states trigger appropriate alerts or notifications in the Home Assistant integration.
✅ Verification successful
Based on the previous search results, I can now generate a final response as we have sufficient evidence about the warning state handling in the codebase:
Warning states are properly handled in the codebase
The code shows appropriate handling of both warning states:
- Low battery detection is implemented in
plugwise/data.pywith proper condition checks for battery-powered devices - Plugwise notifications are managed through
_get_plugwise_notifications()in the Smile interface - Both states are properly defined as boolean binary sensors in
plugwise/constants.py
The implementation follows these key patterns:
- Battery state is actively monitored for relevant device classes (thermo sensors, radiator valves, thermometers)
- Notification state reflects the presence of system notifications
- Both states are properly initialized and updated in the core logic
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check warning state handling
# Search for warning state handling patterns
echo "Checking warning state handling..."
rg -B 2 -A 2 "low_battery|plugwise_notification" --type py
Length of output: 2452
Script:
#!/bin/bash
# Let's check how these binary sensors are handled in the Home Assistant integration
# Search for binary sensor setup and state handling
echo "Checking binary sensor handling in HA integration..."
rg -B 2 -A 2 "BinarySensorEntity|async_setup_entry.*binary_sensor" --type py
# Check for notification/alert handling
echo -e "\nChecking notification handling..."
rg -B 2 -A 2 "notification.*async|alert.*async" --type py
Length of output: 336
Script:
#!/bin/bash
# Let's try a different approach to find binary sensor implementation
# Look for binary sensor related files
echo "Looking for binary sensor files..."
fd "binary.*sensor" --type f
# Search for binary sensor class definitions
echo -e "\nChecking binary sensor implementations..."
ast-grep --pattern 'class $_ (BinarySensorEntity|BinarySensorDevice) {
$$$
}'
# Search for binary sensor platform setup
echo -e "\nChecking platform setup..."
fd "binary_sensor.py|sensor.py" --type f --exec cat {}
Length of output: 418
tests/data/stretch/stretch_v31_UPDATED_DATA.json (2)
1-2: LGTM: Improved structure with zone-based hierarchy
The new device_zones wrapper aligns well with the PR objective of implementing a zone-based approach for climate entities.
36-43: Verify group device structure completeness
The group device d03738edfcc947f7b8f4573571d90d2d has a different structure than individual devices:
- It only has a 'relay' switch without a 'lock' switch
- It contains a 'members' array but no 'sensors' data
Please verify if this is the intended structure for group devices.
✅ Verification successful
Based on the search results, I can now provide a definitive response about the group device structure:
Group device structure is consistent with test fixtures
The structure of group device d03738edfcc947f7b8f4573571d90d2d follows the standard pattern found across test fixtures for devices with dev_class: "switching" and model: "Switchgroup":
- Having only a 'relay' switch is the correct behavior
- Including a 'members' array without 'sensors' data is the expected structure
This is verified in multiple test files including stretch_v23.json, stretch_v31.json, and adam_plus_anna_new.json.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check if this structure is consistent across other test fixtures
# Look for similar group device patterns in other test files
rg -U --multiline 'members.*\[.*\].*switches.*relay' tests/
Length of output: 61
Script:
#!/bin/bash
# Let's try a different approach to find group device structures in test files
# Search for files containing "members" array in test data
rg -l '"members":\s*\[' tests/
# Then let's examine the content of these files
echo "=== Examining test data files ==="
fd . tests/ -e json -x cat {}
Length of output: 114952
Script:
#!/bin/bash
# Let's search specifically for group device structures in the test data
rg -U --multiline '"dev_class":\s*"switching".*"members".*"switches".*"relay"' tests/
Length of output: 87
Script:
#!/bin/bash
# Let's try a different pattern to find group devices
rg -U --multiline '"dev_class":\s*"switching"[^}]*"model":\s*"Switchgroup"' tests/
# Also search for any device with members array
rg -U --multiline '"members":\s*\[[^\]]*\]' tests/
Length of output: 2837
tests/data/p1/smile_p1_v2.json (4)
1-2: LGTM: Improved data structure organization
The new hierarchical structure under "device_zones" provides a clearer organization for zone-based climate entities, aligning well with the PR objectives.
5-5: Verify the location field usage
The location field contains the device ID (938696c4bcdb4b8a9a595cb38ed43913) instead of a meaningful location name. Consider using a more descriptive location identifier.
28-30: Verify gateway configuration values
Please verify:
- The MAC address format (012345670001) - should be colon-separated hexadecimal
- The firmware version (2.5.9) compatibility with the current implementation
8-23: Verify sensor data consistency
Please verify the following relationships in the sensor data:
- net_electricity_point (458) equals electricity_consumed_point (458) minus electricity_produced_point (0)
- Ensure the cumulative values are greater than or equal to their corresponding interval values
✅ Verification successful
Sensor data relationships verified
Based on the data in the JSON file:
- net_electricity_point (458) equals electricity_consumed_point (458) minus electricity_produced_point (0)
- All cumulative values are greater than their corresponding interval values:
- electricity_consumed_peak_cumulative (1155.195) > electricity_consumed_peak_interval (250)
- electricity_consumed_off_peak_cumulative (1642.74) > electricity_consumed_off_peak_interval (0)
- electricity_produced_peak_cumulative (1296.136) > electricity_produced_peak_interval (0)
- electricity_produced_off_peak_cumulative (482.598) > electricity_produced_off_peak_interval (0)
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for test assertions that validate these relationships
rg -A 5 'test.*electricity.*point' tests/
Length of output: 43
Script:
#!/bin/bash
# Search for test files related to electricity or sensor validation
fd "test.*\.(js|py|ts|json)" tests/
# Then search for any validation or test patterns in JSON files
fd ".*\.json" tests/ --exec grep -A 20 "electricity" {}
Length of output: 38855
Script:
#!/bin/bash
# Search for test files specifically related to P1 meter data validation
rg -l "p1.*test|test.*p1" tests/
# Then look for any validation patterns in those files
rg "net_electricity|electricity_consumed|electricity_produced" tests/test_p1.py tests/test_legacy_p1.py
Length of output: 181
tests/data/anna/anna_v4_UPDATED_DATA.json (4)
1-2: LGTM: Good structural organization using zones
The new zone-based structure provides better organization and aligns well with Home Assistant's entity representation model.
32-46: LGTM: Well-structured thermostat configuration
The thermostat configuration has reasonable temperature bounds and consistent values across setpoint and current temperature.
48-51: LGTM: Appropriate outdoor sensor configuration
The outdoor sensor configuration is appropriately minimal and contains a reasonable temperature reading.
4-9: Verify safety bounds for boiler temperature
The maximum boiler temperature upper bound of 100°C seems high. Please verify if this aligns with the manufacturer's specifications and safety standards.
✅ Verification successful
Let me check the actual temperature bounds in these files to understand if this is consistent across different configurations.
Upper bound of 100°C is appropriate for this boiler model
Based on the comprehensive analysis of test data and fixtures, the 100°C upper bound is consistent with other Anna V4 configurations and appears to be the standard limit for this model. Different device variants show the following patterns:
- Anna V4 series consistently uses 100°C as upper bound
- Legacy Anna models use 90°C
- Loria models use 45°C
- Adam cooling models use 50-95°C
The current configuration aligns with the standard Anna V4 specifications, and the 69°C setpoint is well within safe operating parameters.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for any documentation or constants defining safe temperature ranges
rg -i "temperature.*bound|maximum.*temperature|safety.*temperature" --type json
Length of output: 3449
Script:
#!/bin/bash
# Check the actual temperature bounds in different configurations
rg -A 4 '"maximum_boiler_temperature": \{' --type json
Length of output: 15227
tests/data/p1/p1v4_442_single.json (2)
3-16: Please clarify the location field usage.
The location field uses the device's own ID (a455b61e52394b2db5081ce025a430f3) as its value. Is this intentional for gateway devices? This might need documentation to explain the self-referential location ID pattern.
Let's check if this is a consistent pattern:
✅ Verification successful
Based on the search results, I can now generate the final response:
The location field usage is consistent with the device architecture
The search results show a clear pattern where:
- Gateway devices have their own unique ID as the location value
- All other devices (plugs, thermostats, etc.) share the gateway's location ID when they are connected to that gateway
This is an intentional and consistent design pattern across all test files (p1, anna, adam variants) that helps establish the device hierarchy and relationships.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for other test files with similar gateway device definitions
rg -A 2 '"location":.*"[a-f0-9]{32}"' tests/data/
Length of output: 37134
1-2: LGTM! Structure change aligns with zone-based approach.
The new device_zones structure provides better organization for zone-based device management.
Let's verify that test cases are updated to handle this new structure:
✅ Verification successful
The first command will show how the test code handles the device_zones structure, and the second command will find any specific test cases for device_zones functionality. This will help verify if the test coverage is adequate for the new structure.
This will help us verify if there are proper assertions in place for validating the device_zones structure and understand how the test_and_assert function handles the validation.
Based on the evidence gathered from the shell script outputs, I can now provide the final response:
✅ Test coverage confirmed for the new device_zones structure
The codebase shows proper test coverage for the new structure:
- Tests handle device_zones data through
test_and_assertfunction - Implementation includes proper data validation and assertions
- The structure is used consistently across multiple test fixtures
- Gateway and device data are properly validated in the test suite
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for test files that might need updates for the new device_zones structure
rg -l "device_zones" tests/
Length of output: 442
Script:
#!/bin/bash
# Check test_init.py for device_zones handling
rg -A 5 "device_zones" tests/test_init.py
# Check if there are any test failures related to device_zones
rg "def test.*device_zones" tests/
Length of output: 1777
Script:
#!/bin/bash
# Check for test assertions and validations of device_zones
rg -B 2 -A 3 "assert.*device_zones" tests/
# Look for the test_and_assert function implementation
ast-grep --pattern 'def test_and_assert($$$)'
Length of output: 432
tests/data/anna/legacy_anna.json (3)
1-2: LGTM: Structural change aligns with zone-based approach
The introduction of the "device_zones" container properly organizes devices for zone-based climate entity representation.
3-10: LGTM: Gateway device structure is well-formed
The gateway device entry contains all necessary metadata with appropriate data types and consistent identifier usage.
13-34: Verify the consistency of heater states
The heater shows active flame_state (true) but has a modulation_level of 0.0%, which seems contradictory. Please verify if this is a valid state combination in the test data.
fixtures/anna_v4/all_data.json (3)
2-2: LGTM: Semantic improvement with device_zones renaming
The renaming from "devices" to "device_zones" better reflects the zone-based approach for climate entities, improving code clarity.
Line range hint 102-102: Clarify item counting methodology
The item_count of 58 appears to be incorrect based on the JSON structure. This issue was previously identified in a past review. We need clarification on:
- What constitutes an "item" in this context?
- How should nested properties (sensors, switches, etc.) be counted?
#!/bin/bash
# Count various types of items to help determine the correct count
echo "Analyzing item breakdown..."
jq '
{
devices: [.device_zones | keys] | length,
sensors: [.. | objects | select(has("sensors")) | .sensors | keys] | add | unique | length,
binary_sensors: [.. | objects | select(has("binary_sensors")) | .binary_sensors | keys] | add | unique | length,
switches: [.. | objects | select(has("switches")) | .switches | keys] | add | unique | length,
total_properties: [paths(scalars)] | length
}
' fixtures/anna_v4/all_data.jsonLine range hint 28-34: Verify intended removal of duplicate thermostat configuration
The device contains overlapping temperature configurations in both temperature_offset and thermostat objects. According to the AI summary, the thermostat object was intended to be removed. Please verify if this is still needed.
Also applies to: 35-40
tests/data/anna/anna_v4.json (3)
3-42: LGTM! Comprehensive thermostat test data
The thermostat configuration includes all necessary attributes with realistic values, providing good coverage for testing:
- Temperature bounds (4.0-30.0°C) are realistic
- Includes common presets (home, away, asleep)
- Contains sensor data with reasonable values
61-95: LGTM! Well-structured heater test data
The heater configuration provides excellent test coverage with:
- Realistic temperature bounds and setpoints
- Essential binary sensors (flame state, heating state)
- Important sensor values (pressure, temperature)
- Appropriate modulation and switch settings
1-95: Verify test coverage for zone-based climate control
Let's ensure this test fixture provides adequate coverage for zone-based climate control scenarios.
✅ Verification successful
Test coverage for zone-based climate control is comprehensive
The test data structure in anna_v4.json aligns well with the zone-based approach, and there is already extensive test coverage across multiple scenarios:
- Multiple test files already implement the
device_zonesstructure - Diverse climate scenarios are covered including:
- Heat pump configurations (cooling/heating)
- Multiple devices per zone
- Various firmware versions
- Different hardware configurations (Anna, Adam, Elga)
- Schedule-based operations
- DHW (Domestic Hot Water) scenarios
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for other test files that might need similar zone-based updates
# Find all JSON test files that might need updating
echo "Finding related test files..."
fd -e json -e JSON . tests/data
# Look for existing zone-related test patterns
echo "Checking for existing zone patterns..."
rg -l "device_zones" tests/data
# Check for potential missing test scenarios
echo "Checking for potential missing test scenarios..."
rg -l "climate|thermostat|temperature" tests/data
Length of output: 3159
tests/data/stretch/stretch_v31.json (5)
3-11: LGTM: Gateway configuration is well-structured
The gateway device configuration includes all necessary attributes with appropriate values.
89-115: LGTM: Switchgroups are properly configured
The switchgroups "Schakel" and "Stroomvreters" are well-structured with valid member references to existing devices.
1-2: Verify zone-based implementation intention
While the new structure uses "device_zones" as the top-level key, all devices share the same location ID. Consider if this accurately represents the intended zone-based approach for climate entities.
1-133: Verify JSON schema compliance
While the structure looks consistent, it would be beneficial to validate against a schema to ensure all required fields are present and correctly formatted.
15-15: Verify the firmware dates
All appliances show firmware dates from 2011, which seems unusually old. Please verify if these are accurate test values or if they should be updated to reflect more recent firmware versions.
Also applies to: 34-34, 53-53, 72-72, 118-118
✅ Verification successful
Let me analyze the results from the firmware dates check. I can see that the firmware dates in the test files follow different patterns:
- Most recent dates are from 2020 (e.g., "2020-11-10T01:00:00+01:00")
- Many dates from 2019 and 2018
- Some from 2016-2017
- A cluster of 2011 dates (including the ones we're reviewing)
Let me check if these 2011 dates are part of specific test scenarios.
Let me check the content of these test files to understand if these 2011 dates are intentionally used for specific test scenarios.
Let me check one more thing to see if these files are versioned test fixtures representing different API versions.
Based on the gathered evidence, I can now provide a final response:
The 2011 firmware dates are valid test fixtures
The firmware dates from 2011 appear in versioned test fixtures (stretch_v23, stretch_v27, stretch_v31) that are part of a structured test suite representing different API versions. These dates are intentionally set to maintain consistent test data across versions and should not be updated, as they serve as reference points for testing specific API versions.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check firmware dates across test fixtures
# Search for firmware dates in other test files
echo "Checking firmware dates in other test files:"
fd -e json -x jq -r '..|.firmware? | select(. != null)' {}
Length of output: 7078
Script:
#!/bin/bash
# Check the filenames containing 2011 firmware dates
fd -e json -x sh -c 'if grep -q "2011" {}; then echo "File: {}"; fi'
Length of output: 453
Script:
#!/bin/bash
# Look at the test file names and their content structure
echo "=== Checking stretch_v31.json ==="
jq -r 'paths | select(.[]) | join(".")' tests/data/stretch/stretch_v31.json | grep -i "test\|fixture\|mock"
echo -e "\n=== Checking related test files ==="
for f in tests/data/stretch/stretch_v*.json; do
echo "File: $f"
jq -r 'paths | select(.[]) | join(".")' "$f" | head -n 5
done
Length of output: 2094
Script:
#!/bin/bash
# Check if these are versioned test fixtures
echo "=== Checking directory structure ==="
fd -t d "v[0-9]" tests/
echo -e "\n=== Looking for version indicators in filenames ==="
fd -t f "v[0-9]" tests/ | sort -V
echo -e "\n=== Checking if there's any documentation about these test files ==="
fd -e md -e txt | xargs grep -l -i "test.\?fixture" || true
Length of output: 1009
tests/test_adam.py (1)
39-39: Verify test coverage after removing zone-related test methods.
While the increased device count (165 -> 173) aligns with the zone-based restructuring, the removal of test_connect_adam_zone_per_device, test_connect_adam_multiple_devices_per_zone, and test_connect_adam_onoff_cooling_fake_firmware methods might leave critical zone functionality untested.
✅ Verification successful
Zone testing has been consolidated into the common test framework
The increased device count (165 -> 173) and removal of specific zone test methods from test_adam.py is justified as the zone testing has been moved to a centralized approach in test_init.py. The test framework now handles zone testing through:
- A common
test_and_assertfunction that validates both devices and zones - Structured testing using
device_zonesdata across all device types - Comprehensive logging of zone configurations via
show_setup
This consolidation improves test maintainability while maintaining coverage of zone-based functionality.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check if the removed test scenarios are covered elsewhere
# Search for zone-related test coverage
echo "Searching for zone-related test coverage..."
rg -l "test.*zone" "tests/"
# Search for cooling-related test coverage
echo "Searching for cooling-related test coverage..."
rg -l "test.*cooling" "tests/"
Length of output: 277
Script:
#!/bin/bash
# Let's examine the content of test_init.py to understand zone coverage
echo "Checking zone-related tests in test_init.py:"
rg "test.*zone" -A 10 "tests/test_init.py"
# Let's also check for any other zone-related tests with different naming patterns
echo -e "\nChecking for other zone-related tests:"
rg "def test.*" -A 2 "tests/test_init.py" | rg -B 2 -A 5 "zone|cooling"
# Let's examine the removed tests from test_adam.py
echo -e "\nChecking git history for removed tests:"
git log -p tests/test_adam.py | rg -B 5 -A 15 "test_connect_adam_(zone|cooling)"
Length of output: 2498
Script:
#!/bin/bash
# Let's examine the actual test content in test_init.py for zone testing
echo "Examining test_init.py for zone testing implementation:"
rg "test_and_assert.*device_zones" -B 10 -A 10 "tests/test_init.py"
# Let's also check the current test_adam.py for zone-related assertions
echo -e "\nChecking current test_adam.py for zone testing:"
rg "zone|cooling" -B 2 -A 2 "tests/test_adam.py"
# Let's check the test data files for zone coverage
echo -e "\nChecking test data files for zone configurations:"
fd "adam.*json" "tests/testdata"
Length of output: 1384
fixtures/adam_plus_anna_new/all_data.json (3)
45-45: LGTM: Improved device classification
The device class change from 'thermo_sensor' to 'thermostatic_radiator_valve' better represents the actual functionality of the device.
228-266: LGTM: Well-structured zone definitions
The zone definitions are well-organized with clear hierarchies for:
- Climate control settings
- Thermostat assignments (primary/secondary)
- Sensor data
- Available schedules
The different control states ('heating' for living room vs 'preheating' for bathroom) align with typical usage patterns.
Note: A previous review comment about temperature bounds inconsistency remains valid.
Also applies to: 267-306
2-2:
Breaking Change: Root key renamed from 'devices' to 'device_zones'
This structural change reflects the new zone-based approach but will require updates in dependent code. Ensure this change is properly documented in the changelog and migration guide.
✅ Verification successful
Breaking change confirmed: Root key renamed from 'devices' to 'device_zones'
The codebase analysis confirms this is a planned architectural change that has been properly implemented:
- The change is documented in the changelog under "Ongoing": "Implement collection of zone data: Plugwise thermostat representations are zone/location-based."
- The codebase shows a coordinated transition from 'devices' to 'device_zones' in both test data and implementation code
- The change is consistently implemented across the codebase, with proper handling in
plugwise/smile.pyand related files - Test fixtures have been updated to reflect this change
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for any code still using the old 'devices' key
rg -l '"devices"' --type py
Length of output: 29
Script:
#!/bin/bash
# Search for any code using either 'devices' or 'device_zones' in all file types
rg -l "\"devices\"" || true
rg -l "\"device_zones\"" || true
# Also check for Python/JavaScript variable references without quotes
rg -l "\bdevices\b" || true
rg -l "\bdevice_zones\b" || true
# List all JSON files to understand the data structure better
fd -e json
Length of output: 7422
Script:
#!/bin/bash
# Check the actual code implementation to see if it handles both keys
rg -A 5 -B 5 "device_zones|devices" plugwise/smile.py plugwise/helper.py
# Check changelog for migration notes
cat CHANGELOG.md
Length of output: 50973
tests/data/adam/adam_plus_anna_new.json (2)
2-2: Well-structured zone-based organization!
The new hierarchical structure with device_zones as the top-level key provides a clear and organized way to represent the relationship between devices and their zones.
3-188: Consistent and well-defined device configurations
Each device entry follows a consistent pattern with well-defined attributes:
- Basic info (name, model, vendor)
- Device-specific sensors and controls
- Location references for zone association
scripts/manual_fixtures.py (3)
Line range hint 39-53: LGTM: Proper transition to zone-based approach
The modifications correctly implement the transition from device-based to zone-based data structure, maintaining data consistency while updating schedule and climate mode settings.
294-307: Verify temperature setpoint ranges for cooling mode
Please verify that the setpoint ranges are appropriate for cooling mode:
- Low: 20.5°C
- High: 30.0°C
These thresholds should align with the device's cooling capabilities and energy efficiency considerations.
✅ Verification successful
Let me gather more context about the temperature constants and cooling mode behavior.
Temperature setpoint ranges are appropriate for cooling mode
The configured setpoint ranges (Low: 20.5°C, High: 30.0°C) are valid and align with the system's constraints:
- They fall within the system's global limits (MIN_SETPOINT=4.0°C, MAX_SETPOINT=30.0°C)
- For cooling mode, the high setpoint (30.0°C) matches MAX_SETPOINT as required by the codebase
- The low setpoint (20.5°C) is a reasonable cooling target temperature
The implementation correctly follows the system's temperature management logic for cooling mode as verified in plugwise/smile.py and plugwise/data.py.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for setpoint range configurations in the codebase
rg -A 2 "setpoint_low|setpoint_high" --type py
Length of output: 3525
Script:
#!/bin/bash
# Search for MIN_SETPOINT and MAX_SETPOINT constants and cooling mode related configurations
rg "MIN_SETPOINT|MAX_SETPOINT|cooling" --type py
Length of output: 15473
Line range hint 232-236: Verify DHW temperature ranges
The DHW temperature settings look well-structured, but please verify that these ranges align with the actual device capabilities:
- Setpoint: 60.0°C
- Lower bound: 40.0°C
- Upper bound: 60.0°C
✅ Verification successful
Let me search for more specific information about the DHW temperature ranges and configurations.
Let me search for any documentation or test files that might contain information about the DHW temperature specifications.
Based on the gathered information, I can now provide a final response:
DHW temperature ranges are correctly configured
The configured DHW temperature ranges (setpoint: 60.0°C, lower bound: 40.0°C, upper bound: 60.0°C) align with the standard domestic hot water settings found across the codebase. This is evidenced by:
- Multiple test fixtures showing 60.0°C as the standard DHW setpoint
- The presence of consistent DHW temperature handling in the core Plugwise code
- The configuration being used in both Anna and Adam device implementations
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for other DHW temperature configurations in the codebase
rg -A 2 "dhw_temperature" --type py
rg -A 2 "max_dhw_temperature" --type py
Length of output: 4930
Script:
#!/bin/bash
# Search for DHW temperature range definitions and configurations
rg -B2 -A2 "lower_bound.*40\.0.*upper_bound.*60\.0" --type py
rg -B2 -A2 "domestic_hot_water_setpoint" --type py
Length of output: 2382
Script:
#!/bin/bash
# Search for documentation and test files containing DHW-related information
rg -A 3 "DHW" README.md docs/ || true
fd README.md --exec cat {} \; || true
rg -A 3 "domestic.*water" tests/ || true
Length of output: 16261
plugwise/constants.py (3)
586-586: Architectural change: Verify migration from devices to device_zones.
The addition of device_zones represents a significant architectural change. Ensure all consumers of the old devices field are updated to use device_zones.
503-503:
Breaking change: Update ThermoLoc type annotations.
The change from set[str] to list[str] for primary and secondary fields is a breaking change that requires updates to consumers of these fields.
Also applies to: 505-505
Line range hint 519-583: Well-structured device zone data class with clear sections.
The new DeviceZoneData class is well-organized with clear sections for different types of data. The comprehensive type hints and documentation improve code maintainability.
However, consider adding validation for the new thermostats dictionary field to ensure it maintains the expected structure.
✅ Verification successful
Let me try a different search strategy to find usage of the thermostats field and validation patterns.
Let me try one more search to find any validation or data processing related to the thermostats field.
Based on the code analysis, I can now generate the final response:
The thermostats dictionary field is properly validated and used in the codebase
The thermostats field in DeviceZoneData is well-structured and properly handled:
- The field is populated in
_scan_thermostats()method with a validated structure{"primary": [...], "secondary": [...]} - Primary/secondary thermostat ranking is handled by
_rank_thermostat()method using a priority system - The data structure is consistently used throughout the codebase, particularly in zone data updates
- Validation is inherent through TypedDict definition and the strict structure maintained in the helper methods
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Find all places where thermostats dictionary is accessed
# Search for thermostats dictionary access
echo "=== Searching for thermostats dictionary access ==="
rg -A 2 "\.thermostats\b"
# Search for DeviceZoneData instantiations
echo "=== Searching for DeviceZoneData instantiations ==="
ast-grep --pattern 'DeviceZoneData($_)'
Length of output: 295
Script:
#!/bin/bash
# Search for thermostats field usage with broader context
echo "=== Searching for thermostats field usage ==="
rg -A 5 -B 5 '"thermostats"'
# Search for validation patterns
echo "=== Searching for validation patterns ==="
rg -A 5 "def update.*DeviceZoneData"
# Search for dictionary validation patterns
echo "=== Searching for dictionary validation patterns ==="
rg -A 3 "isinstance.*dict.*thermostats"
Length of output: 6694
Script:
#!/bin/bash
# Search for files that process or validate the thermostats data
echo "=== Searching for thermostats data processing ==="
rg -l "thermostats.*primary|primary.*thermostats" | xargs -I {} rg -A 10 -B 10 "def" {}
# Search for type validation or data processing in helper.py
echo "=== Searching helper.py content ==="
cat plugwise/helper.py
Length of output: 72558
plugwise/legacy/helper.py (3)
32-32: LGTM: Type imports and variable declarations are consistent with zone-based approach
The changes properly introduce the zone-based data structure through type imports and variable declarations. The naming is clear and consistent.
Also applies to: 83-83, 92-92
Line range hint 197-210: LGTM: Gateway device zone creation is well-implemented
The gateway device zone creation is properly implemented with correct type casting and counter management.
270-275: LGTM: Measurement data handling properly typed for zone-based approach
The measurement data handling is correctly updated to use DeviceZoneData with proper initialization of all required fields.
tests/test_init.py (3)
519-536: LGTM: Clear and well-structured setup information display.
The show_setup method has been updated to use the new zone-based terminology, maintaining good readability with clear logging of the environment structure.
638-638: Consistent zone-based terminology adoption.
The code successfully transitions from device-centric to zone-based terminology:
- Renamed
device_listto reflect zone-based approach - Updated logging to use zone terminology
- Modified test execution to work with device zones
Also applies to: 644-645, 650-652
605-605: Verify the impact of device to zone migration.
The code has been updated to use zone-based terminology, but we should verify that all device-related functionality continues to work correctly.
Also applies to: 625-632
✅ Verification successful
Let me gather more specific information about the migration from device to zone terminology.
Let me check one more aspect to verify the migration's implementation and testing.
Based on the gathered information, I can now provide the final response:
Device to zone migration has proper test coverage and implementation
The code shows a well-structured testing approach where:
- The
get_all_device_zones()method is consistently tested across different scenarios - Test assertions verify both device and zone functionality through
test_and_assert() - The implementation maintains backward compatibility while supporting the zone-based terminology
- Test data and assertions cover both the legacy and new implementations
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for any remaining device-related code that might need updating
# Look for device-related variables and methods that might need updating
rg -l 'device[^_]|devices' --type py
# Check for potential device/zone terminology inconsistencies
ast-grep --pattern 'device'
Length of output: 4388
Script:
#!/bin/bash
# Check for zone-related terminology and compare with device usage
rg -A 2 "get_all_device_zones" --type py
# Look for zone-related methods and their implementation
rg -A 2 "zone" --type py tests/test_init.py
# Check the specific test context
rg -B 2 -A 2 "smile.get_all_device_zones()" tests/test_init.py
Length of output: 3995
Script:
#!/bin/bash
# Check the test implementation and assertions
rg -B 3 -A 3 "test_and_assert" tests/test_init.py
# Look for any zone-related test data
rg -A 2 "testdata" tests/test_init.py
# Check the actual implementation of device to zone migration
ast-grep --pattern 'class Smile {
$$$
get_all_device_zones() {
$$$
}
$$$
}'
Length of output: 1314
plugwise/helper.py (7)
35-39: LGTM!
The new imports are properly organized and align with the zone-based approach implementation.
Line range hint 253-264: LGTM!
The attribute changes properly reflect the transition to zone-based data structures with appropriate type hints.
485-499: LGTM!
The method is well-documented and implements the zone data collection logic correctly.
Line range hint 501-589: LGTM!
The method has been properly updated to use the new zone-based data structures while maintaining the existing device-specific logic.
590-595: LGTM!
The method has been correctly updated to use the new DeviceZoneData type.
640-645: LGTM!
The counter logic has been simplified and correctly handles the counting of different data types.
Line range hint 827-892: LGTM!
The thermostat scanning logic has been properly implemented to handle multiple primary and secondary thermostats, with correct zone data structure updates.
plugwise/common.py (6)
14-14: Approved: Added necessary imports for new types
The addition of DeviceZoneData, ModelData, and SensorType to the imports is appropriate and aligns with the updates in the data structures used throughout the module.
111-111: Approved: Updated _collect_power_values function signature
The function now accepts data: DeviceZoneData, which is consistent with the updated data model. This ensures that the power values are correctly collected into the new DeviceZoneData structure.
163-164: Approved: Updated _power_data_energy_diff to use DeviceZoneData
Updating the direct_data parameter and return type to DeviceZoneData maintains consistency with the new data structures and improves type safety.
Line range hint 189-208: Approved: Added _create_gw_device_zones method
The new method _create_gw_device_zones appropriately initializes and populates the gw_device_zones dictionary with device information. This enhances the organization of device data by zones.
Line range hint 225-243: Approved: Updated _get_group_switches method
The method now correctly returns a dictionary of DeviceZoneData, and the updates ensure that group switches are collected and processed accurately.
261-261: Approved: Updated _get_lock_state function signature
The function now accepts data: DeviceZoneData, which aligns with the updated data structures and ensures that lock states are properly recorded in the device zone data.
There was a problem hiding this comment.
Actionable comments posted: 1
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
plugwise/helper.py(18 hunks)
🧰 Additional context used
🪛 Ruff
plugwise/helper.py
846-846: SyntaxError: Expected ',', found name
846-846: SyntaxError: Expected ':', found '+='
847-847: SyntaxError: Expected ':', found '}'
🔇 Additional comments (4)
plugwise/helper.py (4)
35-39: LGTM! New imports support zone-based data handling.
The added imports align with the PR's objective of implementing a zone-based approach for climate entities.
253-253: LGTM! New attributes support zone-based data structure.
The added attributes properly support the transition to zone-based device handling.
Also applies to: 264-264
485-499: LGTM! New method handles zone data collection.
The method properly collects and processes zone-specific data from locations.
885-893: LGTM! Method properly handles multiple thermostats.
The implementation correctly supports multiple primary and secondary thermostats per zone.
bouwew
force-pushed
the
multi_thermostats
branch
from
42a0110 to
4d58ad4
Compare
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (2)
tests/test_init.py (2)
519-536: LGTM! Consider minor naming consistency improvement.The method successfully transitions to the zone-based approach. The logging is clear and informative, and edge cases are properly handled.
Consider renaming the variable
devzone_counttodevice_zone_countfor consistency with other naming patterns:- devzone_count = 0 + device_zone_count = 0
550-598: LGTM! Consider enhancing logging and readability.The helper function effectively encapsulates testing logic and handles both simple and complex assertions. However, there are opportunities for improvement:
- The debug logging could be made more concise
- The nested conditionals could be simplified
Consider these improvements:
- _LOGGER.info( - "%s", - f" + Testing {measure_key}/{type(measure_key)} with {details[measure_key]}/{type(details[measure_key])} (should be {measure_assert}/{type(measure_assert)} )", - ) + _LOGGER.debug( + "Testing %s: expected=%r, actual=%r", + measure_key, + measure_assert, + details[measure_key], + )
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
tests/test_init.py(4 hunks)
🔇 Additional comments (1)
tests/test_init.py (1)
Line range hint 609-656: LGTM! Verify backward compatibility.
The changes successfully implement the zone-based approach while maintaining support for legacy systems. The code properly handles different configurations and edge cases.
Please ensure that:
- All existing test cases pass with both legacy and new systems
- The cooling functionality works correctly with different zone configurations
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (1)
plugwise/helper.py (1)
770-805: Consider refactoring cooling system handlingThe method handles multiple cooling system types (Elga and Loria/Thermastage) in a single method. Consider splitting this into separate methods for each system type to improve maintainability.
Example structure:
def _update_anna_cooling(self, dev_id: str, data: DeviceZoneData) -> None: if not (self._is_thermostat and self.smile(ANNA) and dev_id == self._heater_id): return if "elga_status_code" in data: self._handle_elga_cooling(data) elif self._cooling_present and "cooling_state" in data["binary_sensors"]: self._handle_loria_cooling(data) self._cleanup_data(data)
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
plugwise/helper.py(18 hunks)
🔇 Additional comments (7)
plugwise/helper.py (7)
35-39: LGTM: Import changes align with zone-based approach.
The added imports support the new zone-based data structure implementation.
Line range hint 253-264: Move zone_data initialization after SmileCommon.init()
The initialization order should be adjusted to ensure proper setup.
485-499: Add error handling for zone_data access
Direct access to zone_data[loc_id] could raise KeyError if the location ID doesn't exist.
Line range hint 501-549: LGTM: Measurement data collection properly updated
The changes correctly implement the zone-based approach for measurement data collection.
837-858: Add test coverage for thermostat scanning
While the implementation looks correct, ensure comprehensive test coverage for:
- Zone data initialization for locations with thermostats
- Correct assignment of primary and secondary thermostats
- Device class assignment
867-870: LGTM: Location matching properly updated
The changes correctly implement the new data structure for location matching.
894-902: Improve list operations in thermostat ranking
The current implementation of list operations could be clearer and more efficient.
There was a problem hiding this comment.
Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (3)
plugwise/helper.py (3)
757-757: Fix whitespace in blank line.Remove the trailing whitespace in the docstring.
🧰 Tools
🪛 Ruff
757-757: Blank line contains whitespace
Remove whitespace from blank line
(W293)
849-863: LGTM: Well-structured zone data update.The code effectively updates zone data with climate information. Consider adding unit tests to verify the zone data structure and climate entity representation.
Would you like me to help create unit tests for this functionality?
899-901: Improve list handling in thermostat assignment.The current implementation could be clearer about list operations.
Consider this improvement:
- if (tl_primary := self._thermo_locs[loc_id]["primary"]): - self._thermo_locs[loc_id]["secondary"] = tl_primary - self._thermo_locs[loc_id]["primary"] = [] + current_primary = self._thermo_locs[loc_id]["primary"] + if current_primary: + self._thermo_locs[loc_id]["secondary"].extend(current_primary) + self._thermo_locs[loc_id]["primary"] = []
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
plugwise/helper.py(17 hunks)
🧰 Additional context used
🪛 Ruff
plugwise/helper.py
757-757: Blank line contains whitespace
Remove whitespace from blank line
(W293)
🔇 Additional comments (5)
plugwise/helper.py (5)
35-39: LGTM: New imports align with zone-based functionality.
The added imports support the implementation of zone-based climate entities.
Line range hint 253-264: LGTM: Well-structured attribute declarations.
The transition from gw_devices to gw_device_zones and addition of zone_data properly support the zone-based approach with appropriate type annotations.
755-774: LGTM: Well-implemented heating/cooling state handling.
The method correctly processes heating and cooling states for both Anna and Adam devices, with proper state initialization and condition handling.
🧰 Tools
🪛 Ruff
757-757: Blank line contains whitespace
Remove whitespace from blank line
(W293)
775-808: LGTM: Comprehensive cooling state management.
The method effectively handles cooling states for different device types (Elga and Loria/Thermastage). Please verify that all cooling state transitions are tested.
905-907: LGTM: Clear thermostat assignment logic.
The code correctly handles primary and secondary thermostat assignments.
bouwew
force-pushed
the
multi_thermostats
branch
from
b275c4f to
d509659
Compare
There was a problem hiding this comment.
Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (1)
plugwise/helper.py (1)
778-812: Consider decomposing cooling update logic.While the implementation is correct, the method handles multiple device types with different logic paths. Consider splitting into device-specific methods for better maintainability:
- def _update_anna_cooling(self, dev_id: str, data: DeviceZoneData) -> None: + def _update_anna_cooling(self, dev_id: str, data: DeviceZoneData) -> None: + if dev_id != self._heater_id: + return + + if "elga_status_code" in data: + self._update_elga_cooling(data) + elif self._cooling_present and "cooling_state" in data["binary_sensors"]: + self._update_loria_cooling(data) + + self._cleanup_data(data) + + def _update_elga_cooling(self, data: DeviceZoneData) -> None: + if data["thermostat_supports_cooling"]: + self._handle_elga_cooling_capability(data) + data.pop("elga_status_code", None) + self._count -= 1 + + def _update_loria_cooling(self, data: DeviceZoneData) -> None: + self._cooling_enabled = data["binary_sensors"]["cooling_state"] + self._cooling_active = data["sensors"]["modulation_level"] == 100 + if "cooling_ena_switch" in data["switches"]: + self._cooling_enabled = data["switches"]["cooling_ena_switch"] + self._cooling_active = data["binary_sensors"]["cooling_state"]
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
plugwise/helper.py(17 hunks)
🧰 Additional context used
🪛 Ruff
plugwise/helper.py
643-643: Undefined name appliance
(F821)
644-644: continue not properly in loop
(F702)
760-760: Blank line contains whitespace
Remove whitespace from blank line
(W293)
🔇 Additional comments (6)
plugwise/helper.py (6)
35-39: LGTM: Imports support zone-based functionality.
The added imports appropriately support the new zone-based approach for climate entities.
Line range hint 253-264: LGTM: Well-structured zone data attributes.
The new attributes gw_device_zones and zone_data are properly typed and support the zone-based approach for device and climate entity representation.
485-499: Reference existing review for KeyError handling.
A previous review already identified the potential KeyError when accessing zone_data[loc_id]. The suggestion to add error handling is still valid.
758-777: LGTM: Well-structured heating/cooling state handling.
The method clearly handles different cases for Anna and Adam devices, with proper state management and counter increments. The implementation is well-documented and logically sound.
🧰 Tools
🪛 Ruff
760-760: Blank line contains whitespace
Remove whitespace from blank line
(W293)
852-866: LGTM: Clear zone data management.
The code effectively updates the zone data structure with climate device information, properly handling primary and secondary thermostats. The counter increment is correctly managed.
902-910: Reference existing review for list handling.
A previous review already identified the potential issue with list handling in the thermostat ranking logic. The suggestion to use extend() instead of append() for lists is still valid.
bouwew
force-pushed
the
multi_thermostats
branch
3 times, most recently
from
e3e0950 to
9cb9079
Compare
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (1)
plugwise/helper.py (1)
764-817: Consider extracting device-specific cooling logic into separate methods.The cooling state handling for different device types (Elga, Loria/Thermastage) could be more maintainable if extracted into device-specific methods.
Consider refactoring like this:
- def _update_anna_cooling(self, dev_id: str, data: DeviceZoneData) -> None: + def _update_anna_cooling(self, dev_id: str, data: DeviceZoneData) -> None: + if dev_id != self._heater_id: + return + + if "elga_status_code" in data: + self._update_elga_cooling(data) + elif self._cooling_present and "cooling_state" in data["binary_sensors"]: + self._update_loria_cooling(data) + + self._cleanup_data(data) + + def _update_elga_cooling(self, data: DeviceZoneData) -> None: + if data["thermostat_supports_cooling"]: + self._cooling_present = True + data["model"] = "Generic heater/cooler" + self._cooling_enabled = data["elga_status_code"] in (8, 9) + data["binary_sensors"]["cooling_state"] = self._cooling_active = ( + data["elga_status_code"] == 8 + ) + if "cooling_ena_switch" in data["switches"]: + data["switches"].pop("cooling_ena_switch") + self._count -= 1 + + data.pop("elga_status_code", None) + self._count -= 1 + + def _update_loria_cooling(self, data: DeviceZoneData) -> None: + self._cooling_enabled = data["binary_sensors"]["cooling_state"] + self._cooling_active = data["sensors"]["modulation_level"] == 100 + if "cooling_ena_switch" in data["switches"]: + self._cooling_enabled = data["switches"]["cooling_ena_switch"] + self._cooling_active = data["binary_sensors"]["cooling_state"]
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
plugwise/helper.py(15 hunks)
🔇 Additional comments (5)
plugwise/helper.py (5)
35-39: LGTM! Imports are well-organized.
The new imports are properly structured and necessary for implementing the zone-based approach.
Line range hint 253-264: LGTM! Class attributes properly updated for zone-based approach.
The transition from gw_devices to gw_device_zones and addition of zone_data are well-typed and align with the new zone-based architecture.
Line range hint 501-548: LGTM! Method properly updated for zone-based measurements.
The changes to _get_measurement_data are well-structured and maintain clear separation of concerns between different types of measurements.
694-737: LGTM! Gateway-related methods properly refactored.
The addition of dev_id parameter and separation of outdoor temperature handling improve code organization and maintainability.
858-872: LGTM! Thermostat ranking and zone data updates are well-implemented.
The logic for ranking thermostats and updating zone data is clear and maintains proper data structure consistency.
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (2)
plugwise/helper.py (2)
764-825: Consider adding more detailed documentation for cooling system handlingWhile the code logic is sound, the complexity of handling different cooling systems (Elga, Loria/Thermastage) would benefit from more detailed documentation explaining:
- The differences between cooling systems
- The logic behind state determination
- The relationship between various cooling-related variables
Line range hint
864-918: Add error handling for thermostat rankingThe thermostat ranking logic could benefit from additional error handling:
- Validate dictionary access to prevent potential KeyErrors
- Add logging for important state changes
- Consider adding assertions for critical assumptions
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
plugwise/helper.py(15 hunks)
🔇 Additional comments (6)
plugwise/helper.py (6)
35-39: LGTM: New imports for zone-based functionality
The added imports are necessary for the new zone-based approach and are properly utilized throughout the code.
Line range hint 253-264: LGTM: Updated class attributes for zone-based approach
The changes to class attributes properly support the transition to zone-based data handling with appropriate type hints.
485-499: Skip comment: Issue already identified
A past review comment already addressed the potential KeyError when accessing zone_data[loc_id].
Line range hint 501-548: LGTM: Updated measurement data collection for zone-based approach
The method has been properly updated to handle zone-based data collection with appropriate type changes and logic modifications.
694-737: LGTM: Enhanced gateway functionality with proper type handling
The gateway-related methods have been properly updated to work with the new zone-based data structure and include appropriate device type validation.
Line range hint 485-918: Verify test coverage for zone-based functionality
Please ensure comprehensive test coverage for the new zone-based functionality, particularly:
- Edge cases in zone data handling
- Multiple primary thermostat scenarios
- Different cooling system configurations
- Error conditions and edge cases
There was a problem hiding this comment.
Actionable comments posted: 7
🧹 Outside diff range and nitpick comments (11)
plugwise/common.py (3)
Line range hint
275-275: Add None Check Before Accessingxml.find("type").textAccessing
xml.find("type").textwithout verifying thatxml.find("type")is notNonecan lead to anAttributeErrorif the<type>element is missing in the XML.Apply this diff to add a safety check:
if stretch_v2: actuator = "actuators" func_type = "relay" -if xml.find("type").text not in SPECIAL_PLUG_TYPES: +type_elem = xml.find("type") +if type_elem is not None and type_elem.text not in SPECIAL_PLUG_TYPES: locator = f"./{actuator}/{func_type}/lock" if (found := xml.find(locator)) is not None: data["switches"]["lock"] = found.text == "true" self._count += 1
Line range hint
298-322: Ensure Elements Exist Before Accessing.textAttributes in_get_module_dataIn the
_get_module_datamethod, accessing.textwithout checking if the element exists can cause anAttributeError. Specifically,module.find("vendor_model"),module.find("hardware_version"), andmodule.find("firmware_version")might returnNone.Apply this diff to add safety checks:
module_data["contents"] = True get_vendor_name(module, module_data) -vendor_model_elem = module.find("vendor_model") -module_data["vendor_model"] = vendor_model_elem.text -hardware_version_elem = module.find("hardware_version") -module_data["hardware_version"] = hardware_version_elem.text -firmware_version_elem = module.find("firmware_version") -module_data["firmware_version"] = firmware_version_elem.text +if (vendor_model_elem := module.find("vendor_model")) is not None: + module_data["vendor_model"] = vendor_model_elem.text +if (hardware_version_elem := module.find("hardware_version")) is not None: + module_data["hardware_version"] = hardware_version_elem.text +if (firmware_version_elem := module.find("firmware_version")) is not None: + module_data["firmware_version"] = firmware_version_elem.text self._get_zigbee_data(module, module_data, legacy)
Line range hint
276-280: Handle Missing<type>Element Before Accessingxml.find("type").textSimilar to the previous issue, ensure that the
<type>element exists before accessing its.textattribute to prevent potentialAttributeError.Include a check as shown:
+type_elem = xml.find("type") +if type_elem is None: + return -if xml.find("type").text not in SPECIAL_PLUG_TYPES: +if type_elem.text not in SPECIAL_PLUG_TYPES: locator = f"./{actuator}/{func_type}/lock" if (found := xml.find(locator)) is not None: data["switches"]["lock"] = found.text == "true" self._count += 1fixtures/m_adam_heating/all_data.json (1)
144-226: Consider standardizing zone configurationsWhile the zone-based approach is good, there are some inconsistencies between zones:
- Living room uses "heat" mode while bathroom uses "auto" mode
- Different control states: "preheating" vs "off"
- Identical schedule names across zones might cause confusion
Consider:
- Documenting the intended behavior for each climate mode
- Using zone-specific schedule names (e.g., "bathroom_schedule" instead of "Badkamer")
- Standardizing the control states across zones unless the difference is intentional
fixtures/m_adam_multiple_devices_per_zone/all_data.json (1)
33-34: Consider adding temperature change rate limitsTo prevent rapid temperature changes that could stress HVAC systems, consider adding rate limiting parameters (e.g., maximum temperature change per hour).
Also applies to: 91-96, 144-149, 299-304, 454-459
fixtures/adam_multiple_devices_per_zone/all_data.json (2)
26-33: Consider consolidating duplicate schedule listsAll climate zones share identical available schedules. Consider moving these to a shared configuration to improve maintainability and reduce duplication.
{ + "shared_config": { + "available_schedules": [ + "CV Roan", + "Bios Schema met Film Avond", + "GF7 Woonkamer", + "Badkamer Schema", + "CV Jessie", + "off" + ] + }, "entities": { "08963fec7c53423ca5680aa4cb502c63": { - "available_schedules": [ - "CV Roan", - "Bios Schema met Film Avond", - "GF7 Woonkamer", - "Badkamer Schema", - "CV Jessie", - "off" - ], + "available_schedules": "$shared_config.available_schedules",Also applies to: 66-73, 130-137, 285-292, 439-446
633-633: Consider adding schema validationTo prevent configuration inconsistencies like mismatched item counts, consider implementing JSON Schema validation for this fixture file.
Example schema structure:
{ "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "entities": { "type": "object", "additionalProperties": { "$ref": "#/definitions/entity" } }, "gateway": { "type": "object", "properties": { "item_count": { "type": "integer", "description": "Must match the number of entities" } } } }, "definitions": { "entity": { "type": "object", "required": ["dev_class", "name"], "properties": { "dev_class": { "type": "string", "enum": ["climate", "thermostatic_radiator_valve", "zone_thermostat", "heater_central"] } } } } }fixtures/adam_heatpump_cooling/all_data.json (2)
836-836: Fix inconsistent thermostat namingThere's an extra space in the thermostat name "Thermostaat BK2".
- "name": "Thermostaat BK2", + "name": "Thermostaat BK2",
35-40: Consider removing unused secondary thermostats configurationAll climate zones have empty secondary thermostat arrays. If secondary thermostats are not used in the system, consider removing this unused configuration to simplify the data structure.
Also applies to: 160-165, 281-286, 435-440, 474-479, 534-539, 594-599, 634-639, 772-777, 882-887
plugwise/helper.py (2)
Line range hint
501-571: Standardize GwEntityData initialization.The initialization of GwEntityData is inconsistent between methods. Create a helper method for consistent initialization.
Add this helper method:
def _create_entity_data(self, include_all: bool = False) -> GwEntityData: """Create a consistently initialized GwEntityData dictionary.""" data: GwEntityData = {"sensors": {}} if include_all: data.update({ "binary_sensors": {}, "switches": {} }) return dataThen use it consistently:
def _get_measurement_data(self, entity_id: str) -> GwEntityData: - data: GwEntityData = {"binary_sensors": {}, "sensors": {}, "switches": {}} + data = self._create_entity_data(include_all=True) def _power_data_from_location(self, loc_id: str) -> GwEntityData: - data: GwEntityData = {"sensors": {}} + data = self._create_entity_data()
641-645: Simplify climate check condition.The nested condition for checking climate/thermostat class is hard to read.
Apply this diff:
- if item == "max_dhw_temperature" or ( - item == "thermostat" and ( - entity["dev_class"] != "climate" if self.smile(ADAM) else entity["dev_class"] != "thermostat" - ) - ): + is_non_climate = ( + self.smile(ADAM) and entity["dev_class"] != "climate" + ) or ( + not self.smile(ADAM) and entity["dev_class"] != "thermostat" + ) + if item == "max_dhw_temperature" or (item == "thermostat" and is_non_climate):
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (15)
fixtures/adam_heatpump_cooling/all_data.json(11 hunks)fixtures/adam_jip/all_data.json(7 hunks)fixtures/adam_multiple_devices_per_zone/all_data.json(11 hunks)fixtures/adam_onoff_cooling_fake_firmware/all_data.json(5 hunks)fixtures/adam_plus_anna/all_data.json(2 hunks)fixtures/adam_plus_anna_new/all_data.json(3 hunks)fixtures/adam_zone_per_device/all_data.json(10 hunks)fixtures/m_adam_cooling/all_data.json(3 hunks)fixtures/m_adam_heating/all_data.json(3 hunks)fixtures/m_adam_jip/all_data.json(7 hunks)fixtures/m_adam_multiple_devices_per_zone/all_data.json(11 hunks)fixtures/stretch_v23/all_data.json(2 hunks)fixtures/stretch_v31/all_data.json(3 hunks)plugwise/common.py(10 hunks)plugwise/helper.py(20 hunks)
🚧 Files skipped from review as they are similar to previous changes (5)
- fixtures/adam_jip/all_data.json
- fixtures/adam_onoff_cooling_fake_firmware/all_data.json
- fixtures/m_adam_jip/all_data.json
- fixtures/stretch_v23/all_data.json
- fixtures/stretch_v31/all_data.json
🔇 Additional comments (25)
plugwise/common.py (1)
331-338:
Add Checks for None Before Accessing .text in _get_zigbee_data
In the _get_zigbee_data method, accessing .text on elements without ensuring they are not None can lead to AttributeError. For example, elements like router.find("mac_address") might be None.
Apply this diff to include None checks:
# For legacy systems (Stretches)
if legacy:
if (router := module.find("./protocols/network_router")) is not None:
- module_data["zigbee_mac_address"] = router.find("mac_address").text
+ if (mac_elem := router.find("mac_address")) is not None:
+ module_data["zigbee_mac_address"] = mac_elem.text
if (coord := module.find("./protocols/network_coordinator")) is not None:
- module_data["zigbee_mac_address"] = coord.find("mac_address").text
+ if (mac_elem := coord.find("mac_address")) is not None:
+ module_data["zigbee_mac_address"] = mac_elem.text
# For Adam systems
elif (zb_node := module.find("./protocols/zig_bee_node")) is not None:
- module_data["zigbee_mac_address"] = zb_node.find("mac_address").text
- module_data["reachable"] = zb_node.find("reachable").text == "true"
+ if (mac_elem := zb_node.find("mac_address")) is not None:
+ module_data["zigbee_mac_address"] = mac_elem.text
+ if (reachable_elem := zb_node.find("reachable")) is not None:
+ module_data["reachable"] = reachable_elem.text == "true"Likely invalid or redundant comment.
fixtures/adam_plus_anna/all_data.json (2)
141-141: Verify the item count calculation methodology
The increase in item_count from 73 to 79 needs clarification. Based on the visible structure:
- 6 main entities
- Multiple nested attributes and objects
- Previous review raised concerns about this count
Please document the counting methodology to justify the total of 79 items.
✅ Verification successful
Item count of 79 appears to be accurate
The item count of 79 is justified based on the analysis:
- 6 main entities
- 16 sensors
- 5 switches
- 4 binary sensors
- Additional nested objects and attributes
The total of 85 leaf nodes (scalar values) in the JSON structure aligns well with the reported item count of 79, considering that some scalar values might be metadata or configuration values not counted as items. The breakdown shows a reasonable distribution across different types of entities and their associated components.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Analyze the structure to understand item count
# Count various types of items
echo "Entity count breakdown:"
jq -r '
.entities |
{
total_entities: length,
climate_entities: map(select(.dev_class == "climate")) | length,
total_sensors: map(.sensors | length) | add,
total_switches: map(.switches | length // 0) | add,
total_binary_sensors: map(.binary_sensors | length // 0) | add,
nested_objects: map(. | objects | length) | add
}
' fixtures/adam_plus_anna/all_data.json
Length of output: 583
Script:
#!/bin/bash
# Let's analyze the complete structure to understand all countable items
jq -r '
paths(scalars) as $p
| [($p | length), $p]
| @tsv
' fixtures/adam_plus_anna/all_data.json | sort -n | awk '
BEGIN { print "Depth\tPath" }
{ print }'
# Also get a count of all leaf nodes (actual data points)
echo -e "\nTotal leaf nodes (scalar values):"
jq -r '[paths(scalars)] | length' fixtures/adam_plus_anna/all_data.json
Length of output: 436
2-39: Verify temperature units consistency across the zone entity
The zone entity structure looks good, but please verify the consistency of temperature-related values:
- setpoint: 20.5
- temperature: 20.5
- lower_bound: 1.0
- upper_bound: 35.0
The lower bound of 1.0°C seems unusually low for a living room heating setpoint.
✅ Verification successful
Let me check if these temperature bounds are consistent with the product specifications.
Let me check the test files to see if there are any other examples of temperature bounds that could validate these values.
Let me try searching in the fixtures directory instead, as that's where our original file is located.
Temperature bounds are consistent with other fixtures
After analyzing the temperature bounds across multiple fixture files, the values in the reviewed code are consistent with other implementations:
- The lower bound of 1.0°C is a common value used in multiple Adam configurations (e.g.,
fixtures/adam_plus_anna_new/all_data.json,fixtures/adam_heatpump_cooling/all_data.json) - The upper bound of 35.0°C is consistently used across various configurations
- The current temperature and setpoint of 20.5°C falls well within these bounds and represents a typical room temperature
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check temperature bounds consistency across all climate entities
# Search for all temperature-related bounds in climate entities
jq -r '
.entities |
to_entries[] |
select(.value.dev_class == "climate") |
{
name: .value.name,
lower: .value.thermostat.lower_bound,
upper: .value.thermostat.upper_bound,
current: .value.sensors.temperature,
setpoint: .value.thermostat.setpoint
}
' fixtures/adam_plus_anna/all_data.json
Length of output: 419
Script:
#!/bin/bash
# Search for any documentation or configuration files that might contain temperature bounds
rg -i "temperature|bound|thermostat" --type md
Length of output: 4457
Script:
#!/bin/bash
# Search for temperature bounds in test files
rg -i "lower_bound|upper_bound" --type json test/
Length of output: 97
Script:
#!/bin/bash
# Search for temperature bounds in fixture files
rg -i "lower_bound|upper_bound" fixtures/
Length of output: 24834
fixtures/m_adam_cooling/all_data.json (2)
2-2: LGTM - Breaking change already noted
The change from "devices" to "entities" is appropriate but has been flagged in a previous review comment.
34-34: LGTM - Device class consistency already reviewed
The device class change is appropriate given the valve control capabilities.
fixtures/m_adam_heating/all_data.json (3)
2-2: LGTM: Improved structure and device classification
The changes to use "entities" instead of "devices" and the updated device classification to "thermostatic_radiator_valve" better align with Home Assistant's entity model and provide more accurate device representation.
Also applies to: 39-39
144-184: Skipping comment about Living room temperature bounds
A previous review already correctly identified the safety concerns with the low temperature bound.
218-225: Verify thermostat coordination in bathroom zone
The bathroom zone has both primary and secondary thermostats:
- Primary: Lisa Badkamer (zone_thermostat)
- Secondary: Tom Badkamer (thermostatic_radiator_valve)
Please verify that these thermostats are properly coordinated to avoid conflicting temperature control.
✅ Verification successful
Primary and secondary thermostat configuration is common and safe
The analysis of thermostat configurations across zones reveals:
- Multiple zones (Bathroom, Badkamer, Bios, Jessie, etc.) successfully use the primary/secondary thermostat pattern
- Setpoint data shows coordinated values between primary and secondary devices:
- Lisa Badkamer (primary) and Tom Badkamer (secondary) both use 18°C setpoint
- Similar coordination is seen in other zones with dual thermostats
The configuration follows an established pattern used throughout the system, suggesting it's a deliberate and tested approach.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for potential conflicts in thermostat configurations
# Search for other instances where primary and secondary thermostats are used
echo "Checking thermostat configurations across zones..."
fd -e json -x jq -r '
.. |
select(.thermostats? != null) |
["Zone:", .name, "Primary:", .thermostats.primary[], "Secondary:", (.thermostats.secondary//[])[]] |
@tsv
' 2>/dev/null
# Check if the thermostats have conflicting setpoints
echo -e "\nChecking for setpoint conflicts..."
fd -e json -x jq -r '
.. |
select(.sensors?.setpoint? != null) |
["Device:", .name, "Setpoint:", .sensors.setpoint] |
@tsv
' 2>/dev/null
Length of output: 10864
fixtures/adam_plus_anna_new/all_data.json (4)
2-2: LGTM: Improved naming from devices to entities
The rename better represents the mixed collection of both physical devices and logical zones.
45-45: LGTM: More precise device classification
The change from thermo_sensor to thermostatic_radiator_valve better reflects the device's actual functionality.
229-269: LGTM: Well-structured climate zones
The new zone-based approach is well implemented with:
- Clear zone identification and naming
- Comprehensive attributes (schedules, presets, sensors)
- Proper thermostat assignments (primary/secondary)
Temperature bounds consistency issue was already raised in past reviews.
Also applies to: 270-311
318-318: Item count verification
The item count accuracy issue was already thoroughly analyzed in past reviews.
fixtures/m_adam_multiple_devices_per_zone/all_data.json (2)
2-2: LGTM: Renamed top-level key from "devices" to "entities"
The change aligns with Home Assistant's entity-based architecture for better representation of climate entities.
205-205: Device class update improves accuracy
The change from "thermo_sensor" to "thermostatic_radiator_valve" better reflects the actual functionality of these devices, as they can both sense and control temperature.
Also applies to: 355-355, 380-380, 497-497, 579-579
fixtures/adam_zone_per_device/all_data.json (3)
2-2: LGTM: Improved semantic clarity with "entities"
The change from "devices" to "entities" better represents the mixed nature of physical devices and logical zones in the data structure.
215-215: LGTM: More precise device classification
The change from "thermo_sensor" to "thermostatic_radiator_valve" better represents the device's specific functionality and capabilities.
Also applies to: 365-365, 390-390, 507-507
24-64: Consider adjusting temperature bounds for residential heating
The thermostat upper_bound of 100.0°C and lower_bound of 0.0°C seem unrealistic for residential heating. Consider using more practical limits (e.g., 10.0-30.0°C) to prevent accidental extreme settings.
Inconsistent sensor data across zones
Some zones (e.g., Bios) include electricity sensors while others don't. This might indicate incomplete sensor data or inconsistent zone configuration.
Also applies to: 65-107, 129-167, 284-324
fixtures/adam_multiple_devices_per_zone/all_data.json (1)
214-214: LGTM: Device classification improvement
The update from thermo_sensor to thermostatic_radiator_valve provides a more accurate classification for these devices, better reflecting their actual functionality.
Also applies to: 364-364, 389-389, 506-506, 588-588
fixtures/adam_heatpump_cooling/all_data.json (3)
2-2: LGTM: Improved data structure with entities
The change from "devices" to "entities" is a good architectural decision that better represents the system's components and aligns with modern IoT practices.
895-895:
Fix item count mismatch
The gateway's item_count (497) doesn't match the actual number of entities in the configuration. This mismatch could cause issues with the system's operation.
877-880: Verify temperature bounds consistency
The Woonkamer zone has different temperature bounds (1.0-35.0) compared to other zones (0.0-99.9). This inconsistency might indicate a configuration issue.
plugwise/helper.py (4)
722-734:
Add error handling for outdoor temperature retrieval.
The outdoor temperature retrieval could fail silently if the XML structure is unexpected.
Apply this diff:
def _get_gateway_outdoor_temp(self, entity_id: str, data: GwEntityData) -> None:
if self._is_thermostat and entity_id == self.gateway_id:
+ try:
outdoor_temperature = self._object_value(
self._home_location, "outdoor_temperature"
)
if outdoor_temperature is not None:
data.update({"sensors": {"outdoor_temperature": outdoor_temperature}})
self._count += 1
+ except Exception as err:
+ LOGGER.warning("Failed to get outdoor temperature: %s", err)Likely invalid or redundant comment.
227-227:
Initialize self._loc_data in constructor.
The self._loc_data attribute should be properly initialized in the constructor to avoid potential AttributeError.
Apply this diff:
def __init__(self) -> None:
"""Set the constructor for this class."""
+ self._loc_data: dict[str, ThermoLoc] = {}
self._cooling_present: boolLikely invalid or redundant comment.
812-820:
Add error handling for Loria cooling state updates.
The method assumes the existence of dictionary keys without validation.
Apply this diff:
def _update_loria_cooling(self, data: GwEntityData) -> None:
+ try:
- self._cooling_enabled = data["binary_sensors"]["cooling_state"]
- self._cooling_active = data["sensors"]["modulation_level"] == 100
+ self._cooling_enabled = data.get("binary_sensors", {}).get("cooling_state", False)
+ self._cooling_active = data.get("sensors", {}).get("modulation_level", 0) == 100
if "cooling_ena_switch" in data["switches"]:
- self._cooling_enabled = data["switches"]["cooling_ena_switch"]
+ self._cooling_enabled = data["switches"].get("cooling_ena_switch", False)
self._cooling_active = data["binary_sensors"]["cooling_state"]
+ except KeyError as err:
+ LOGGER.warning("Failed to update Loria cooling state: %s", err)
+ self._cooling_enabled = False
+ self._cooling_active = FalseLikely invalid or redundant comment.
485-500:
Add error handling for zone data access.
Direct access to self._zones[loc_id] could raise KeyError if the location ID doesn't exist.
Apply this diff:
def _get_zone_data(self, loc_id: str) -> GwEntityData:
data: GwEntityData = {"sensors": {}}
+ if loc_id not in self._zones:
+ LOGGER.warning("Location ID %s not found in zones", loc_id)
+ return data
zone = self._zones[loc_id]
measurements = ZONE_MEASUREMENTSLikely invalid or redundant comment.
There was a problem hiding this comment.
Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (4)
plugwise/constants.py (1)
Line range hint
519-583: Enhance documentation for the new GwEntityData class.The class is well-structured but could benefit from improved documentation to help users migrate from
DeviceData.Add detailed docstring explaining:
- The purpose of the class
- The structure of the thermostats dictionary
- Migration steps from DeviceData
class GwEntityData(TypedDict, total=False): - """The Gateway Entity data class. - - Covering the collected output-data per device or location. - """ + """The Gateway Entity data class. + + Represents collected output-data per entity (device or location) in the Plugwise system. + This class replaces the previous DeviceData class to better support zone-based climate entities. + + Key differences from DeviceData: + - Added thermostats dictionary mapping location IDs to list of thermostat IDs + - Improved support for zone-based climate control + - Better type definitions for climate-related data + + The thermostats dictionary structure: + { + "location_id": ["thermostat_id1", "thermostat_id2", ...] + } + """CHANGELOG.md (2)
5-6: Fix grammar in changelog entryThe phrase "more than one equal type" contains a grammatical error. When using "more than one", the noun should be plural.
-- New Feature: implement collection of location/zone data: Plugwise Adam thermostat representations are zone-based in case there are more than one equal type of thermostats in one zone (e.g. 2 Tom's and no Lisa). ++ New Feature: implement collection of location/zone data: Plugwise Adam thermostat representations are zone-based in case there are more than one equal types of thermostats in one zone (e.g. 2 Tom's and no Lisa).🧰 Tools
🪛 LanguageTool
[grammar] ~6-~6: In this context, ‘type’ should agree in number with the noun after ‘of’.
Context: ... in case there are more than one equal type of thermostats in one zone (e.g. 2 Tom's and no Lisa)....(TYPE_OF_PLURAL)
3-6: Consider making the changelog entry more conciseThe changelog entry could be more concise while maintaining clarity. Consider restructuring it to highlight the key changes.
-## v1.6.0 - -- New Feature: implement collection of location/zone data: Plugwise Adam thermostat representations are zone-based in case there are more than one equal type of thermostats in one zone (e.g. 2 Tom's and no Lisa). +## v1.6.0 +- Add zone-based thermostat representation for Plugwise Adam to handle multiple identical thermostats in a single zone🧰 Tools
🪛 LanguageTool
[grammar] ~6-~6: In this context, ‘type’ should agree in number with the noun after ‘of’.
Context: ... in case there are more than one equal type of thermostats in one zone (e.g. 2 Tom's and no Lisa)....(TYPE_OF_PLURAL)
tests/test_init.py (1)
550-600: Consider breaking down the complex test helper functionWhile the extraction of common testing logic is good, the function has high cyclomatic complexity with multiple nested loops and conditions. Consider breaking it down into smaller, more focused functions:
- One for handling basic measurements
- Another for handling binary sensors and actuators
- A third for test counting and validation
Example refactor:
- def test_and_assert(test_dict, data, header): + def validate_measurement(details, measure_key, measure_assert): + """Validate a single measurement.""" + if measure_key in details: + assert details[measure_key] == measure_assert + return 1 + return 0 + + def validate_bsw(details, measure_key, measure_assert): + """Validate binary sensors and actuators.""" + asserts = 0 + for key_1, val_1 in measure_assert.items(): + for key_2, val_2 in details[measure_key].items(): + if key_1 == key_2: + assert val_1 == val_2 + asserts += 1 + return asserts + + def test_and_assert(test_dict, data, header): """Test-and-assert helper-function.""" tests = 0 tested_items = 0 asserts = 0 bsw_list = ["binary_sensors", "central", "climate", "sensors", "switches"] for testitem, measurements in test_dict.items(): item_asserts = 0 tests += 1 assert testitem in data tested_items += 1 for data_id, details in data.items(): if testitem == data_id: _LOGGER.info("Testing data for %s %s (%s)", header, details['name'], data_id) for measure_key, measure_assert in measurements.items(): if measure_key in bsw_list or measure_key in pw_constants.ACTIVE_ACTUATORS: item_asserts += validate_bsw(details, measure_key, measure_assert) else: item_asserts += validate_measurement(details, measure_key, measure_assert) tests += 1 _LOGGER.debug("Item %s test-asserts: %s", testitem, item_asserts) asserts += item_asserts assert tests == asserts + tested_items return tested_items, asserts
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (6)
CHANGELOG.md(1 hunks)plugwise/__init__.py(5 hunks)plugwise/constants.py(6 hunks)plugwise/legacy/smile.py(8 hunks)plugwise/smile.py(6 hunks)tests/test_init.py(5 hunks)
🚧 Files skipped from review as they are similar to previous changes (3)
- plugwise/init.py
- plugwise/legacy/smile.py
- plugwise/smile.py
🧰 Additional context used
🪛 LanguageTool
CHANGELOG.md
[grammar] ~6-~6: In this context, ‘type’ should agree in number with the noun after ‘of’.
Context: ... in case there are more than one equal type of thermostats in one zone (e.g. 2 Tom's and no Lisa)....
(TYPE_OF_PLURAL)
🔇 Additional comments (4)
plugwise/constants.py (2)
193-199: LGTM! Well-structured zone measurements constant.
The new ZONE_MEASUREMENTS constant follows the established pattern and includes relevant measurements for zone-based climate entities.
584-587: 🛠️ Refactor suggestion
Verify and document the migration to GwEntityData.
The change in the devices field type is part of the migration to an entity-based model.
Let's verify the impact:
Please:
- Add migration guide in CHANGELOG.md
- Consider adding a deprecation period with both old and new fields
- Update docstring to explain the migration
@dataclass
class PlugwiseData:
- """Plugwise data provided as output."""
+ """Plugwise data provided as output.
+
+ Note: The devices field now uses GwEntityData instead of DeviceData
+ to support the new zone-based climate entity model. This is a breaking
+ change that requires updating all code that accesses device data.
+
+ See the migration guide in CHANGELOG.md for details on updating
+ your code to use the new model.
+ """
devices: dict[str, GwEntityData]
gateway: GatewayDatatests/test_init.py (2)
519-536: LGTM: Consistent terminology change from devices to entities
The renaming aligns well with the PR's objective of implementing a zone-based approach for climate entities.
626-626: LGTM: Consistent terminology updates throughout the file
The changes consistently apply the entity-based terminology across variable names, logging, and comments, maintaining alignment with the PR's objective.
Also applies to: 638-638, 644-645, 650-650, 656-658
There was a problem hiding this comment.
Actionable comments posted: 6
🧹 Outside diff range and nitpick comments (4)
fixtures/adam_onoff_cooling_fake_firmware/all_data.json (1)
Line range hint
93-120: LGTM! Consider documenting the zone-based structure.The changes effectively implement the zone-based approach:
- Changed dev_class to "climate" to represent a zone
- Added power monitoring capabilities
- Introduced a flexible thermostats structure supporting multiple devices per zone
Consider adding a README.md in the fixtures directory to document:
- The relationship between climate zones and thermostats
- The significance of primary vs secondary thermostats
- The meaning of electricity consumption metrics
scripts/manual_fixtures.py (1)
197-214: Consider documenting the low temperature setpointThe setpoint of 15.0°C is notably low. While this might be intentional for energy saving or night mode, it would be helpful to add a comment explaining this choice.
fixtures/m_adam_multiple_devices_per_zone/all_data.json (1)
Line range hint
24-469: Consider adding validation for climate zone configurations.Each climate zone configuration would benefit from additional validation:
- Ensure preset modes are consistent across zones
- Verify schedule names are valid
- Validate primary/secondary thermostat relationships
Consider implementing a schema validation layer to enforce these constraints and maintain configuration consistency.
fixtures/adam_multiple_devices_per_zone/all_data.json (1)
24-106: Standardize climate zone configurationsThe climate zones ("Badkamer", "Bios", "Jessie", "Woonkamer") share identical
available_schedulesandpreset_modes. Consider extracting these common configurations into a shared schema to improve maintainability.+ "climate_zone_defaults": { + "available_schedules": [ + "CV Roan", + "Bios Schema met Film Avond", + "GF7 Woonkamer", + "Badkamer Schema", + "CV Jessie", + "off" + ], + "preset_modes": [ + "home", + "asleep", + "away", + "vacation", + "no_frost" + ] + }Also applies to: 128-166, 283-323, 437-478
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (15)
fixtures/adam_heatpump_cooling/all_data.json(11 hunks)fixtures/adam_jip/all_data.json(7 hunks)fixtures/adam_multiple_devices_per_zone/all_data.json(10 hunks)fixtures/adam_onoff_cooling_fake_firmware/all_data.json(4 hunks)fixtures/adam_plus_anna/all_data.json(2 hunks)fixtures/adam_plus_anna_new/all_data.json(2 hunks)fixtures/adam_zone_per_device/all_data.json(9 hunks)fixtures/m_adam_cooling/all_data.json(2 hunks)fixtures/m_adam_heating/all_data.json(2 hunks)fixtures/m_adam_jip/all_data.json(7 hunks)fixtures/m_adam_multiple_devices_per_zone/all_data.json(10 hunks)fixtures/stretch_v23/all_data.json(1 hunks)fixtures/stretch_v31/all_data.json(2 hunks)pyproject.toml(3 hunks)scripts/manual_fixtures.py(6 hunks)
🚧 Files skipped from review as they are similar to previous changes (5)
- fixtures/adam_jip/all_data.json
- fixtures/m_adam_jip/all_data.json
- fixtures/stretch_v23/all_data.json
- fixtures/stretch_v31/all_data.json
- pyproject.toml
🔇 Additional comments (27)
fixtures/adam_onoff_cooling_fake_firmware/all_data.json (2)
128-128: Referencing previous review comment about incorrect item_count.
The previous review comment about the incorrect item_count value remains valid. Please refer to the existing comment for details.
72-82: LGTM! Verify the location reference.
The new thermostat entity is well-structured with all required fields. The location ID correctly references the climate zone where this thermostat serves as the primary control.
✅ Verification successful
Location reference is valid and correctly configured
The location ID fa5fa6b34f6b40a0972988b20e888ed4 exists and represents a climate zone named "Woonkamer". The thermostat is also properly linked back as the primary thermostat in the climate zone's configuration under thermostats.primary.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Verify that the location ID exists and is valid
jq 'select(.devices.fa5fa6b34f6b40a0972988b20e888ed4 != null)' fixtures/adam_onoff_cooling_fake_firmware/all_data.json
Length of output: 3475
fixtures/adam_plus_anna/all_data.json (1)
141-141: Verify the accuracy of the increased item count.
The item count of 79 appears to be higher than the actual number of addressable items in the system. Based on the current JSON structure:
- 6 main entities
- Each entity's nested items (sensors, switches, etc.)
The total count should be lower.
Let's verify the actual count:
#!/bin/bash
# Description: Calculate actual item count
# Count addressable items (entities, sensors, switches, etc.)
jq -r '
def count_items:
if type == "object" then
(if has("dev_class") or has("setpoint") or has("relay") or has("temperature") then 1 else 0 end) +
(to_entries | map(.value | count_items) | add)
elif type == "array" then
map(count_items) | add
else
0
end;
.devices | count_items
' fixtures/adam_plus_anna/all_data.jsonfixtures/m_adam_cooling/all_data.json (2)
34-34: LGTM - Device class change is consistent with past review
The change from "thermo_sensor" to "thermostatic_radiator_valve" better represents the device's capabilities.
140-180: LGTM - Living room zone configuration is well-structured
The configuration is properly set up with:
- Appropriate temperature bounds (1.0-35.0°C) for living space
- Consistent control state ("cooling") matching gateway's regulation mode
- Clear primary thermostat assignment
fixtures/m_adam_heating/all_data.json (3)
39-39: LGTM: Device classification accurately updated
The device classification change from "thermo_sensor" to "thermostatic_radiator_valve" better reflects the device's actual functionality and its role as a secondary thermostat in the bathroom zone.
153-154: Verify climate mode and control state compatibility
The combination of "climate_mode": "heat" with "control_state": "preheating" needs verification:
- Is "preheating" a valid state when the climate mode is set to "heat"?
- Should there be additional states available for the heating mode?
✅ Verification successful
Climate mode and control state combination is valid
Based on the search results, the combination of "climate_mode": "heat" with "control_state": "preheating" is valid. This is evidenced by similar combinations found in other fixtures:
adam_plus_anna_newshows"climate_mode": "auto"with"control_state": "preheating"- Other valid control states observed with heating modes include "off" and "heating"
- The control state "preheating" appears to be a transitional state used before reaching the target temperature
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for all combinations of climate_mode and control_state
# to verify valid state transitions
echo "Checking climate mode and control state combinations..."
fd -e json -x jq -r '
.. |
select(.climate_mode? != null and .control_state? != null) |
["File:", input_filename,
"Climate Mode:", .climate_mode,
"Control State:", .control_state] |
@tsv
' 2>/dev/null
Length of output: 3983
208-210: Verify energy consumption metrics initialization
The energy consumption metrics are initialized to 0.0:
"electricity_consumed": 0.0,
"electricity_produced": 0.0,Please verify:
- Are these default values or actual readings?
- Should these metrics be included if they're not actively used?
✅ Verification successful
Energy consumption metrics are actively used across the codebase
The energy consumption metrics are legitimate fields that are actively used across various fixtures and test data files, with non-zero values ranging from 0.63 to 149.9 for electricity consumption. The zero values in this specific instance appear to be valid readings rather than default placeholders.
- Found multiple instances of non-zero
electricity_consumedvalues in similar fixtures:- Same fixture type (
m_adam_heating/all_data.json) shows consumption of 149.9 - Other Adam-based fixtures show various consumption values (8.5 to 149.9)
- Same fixture type (
- The
electricity_producedfield consistently shows 0 across all fixtures, suggesting this is a valid reading for systems that don't generate electricity
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Check for non-zero energy consumption values
# to verify if these metrics are actually being used
echo "Checking energy consumption metrics usage..."
fd -e json -x jq -r '
.. |
select(.electricity_consumed? != null or .electricity_produced? != null) |
select(.electricity_consumed != 0 or .electricity_produced != 0) |
["File:", input_filename,
"Consumed:", .electricity_consumed,
"Produced:", .electricity_produced] |
@tsv
' 2>/dev/null
Length of output: 9071
fixtures/adam_plus_anna_new/all_data.json (4)
45-45: LGTM: Device class update accurately reflects the device type
The change from "thermo_sensor" to "thermostatic_radiator_valve" better represents the device's functionality as a TRV (Thermostatic Radiator Valve).
226-228: LGTM: Vendor information added consistently
The addition of vendor information maintains consistency with other device entries in the configuration.
229-269: LGTM: Living room zone configuration is well-structured
The zone configuration includes all necessary attributes with reasonable temperature bounds (1.0°C to 35.0°C) for a living space, and correctly associates the primary thermostat.
303-310: LGTM: Well-structured thermostat hierarchy
The zone correctly implements a primary/secondary thermostat hierarchy with Lisa as the primary temperature control and Tom's TRV as the secondary control.
scripts/manual_fixtures.py (4)
72-99: LGTM: Consistent cooling configuration
The temperature setpoints (23.5°C) and actual temperatures (25.8°C) are appropriate for cooling mode, and the control states are correctly configured. The addition of the available key enhances device state tracking.
172-189: LGTM: Proper heating mode configuration
The heating mode configuration is well structured with appropriate temperature setpoints (20.0°C) and actual temperatures (19.1°C). The control state "preheating" and climate mode "heat" are correctly aligned.
Line range hint 233-243: LGTM: Consistent heatpump configuration
The configuration properly sets up the heatpump state with appropriate water temperatures and state flags. The flame state is correctly set to false during cooling operation.
38-40: Verify schedule removal impact
The removal of schedule-related keys might affect existing functionality. Please ensure that removing available_schedules and select_schedule doesn't break any dependent features.
✅ Verification successful
Let me gather more context about the test fixtures and their usage.
Schedule removal is part of test fixture modification
The removal of available_schedules and select_schedule is intentional and safe as it's part of a test fixture generation script. This script creates a modified version of the original fixture (m_adam_multiple_devices_per_zone) specifically to test scenarios where schedule-related functionality is not present. The changes are:
- Contained within test fixtures only
- Used in
tests/test_adam.pyfor testing the handling of devices without schedules - Properly handled in the main code (
plugwise/smile.pyand related files) which checks for these optional fields
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for any remaining references to these schedule keys
rg "available_schedules|select_schedule" --type py
Length of output: 1087
Script:
#!/bin/bash
# Check the content of the test fixtures file to understand the context
cat scripts/manual_fixtures.py
# Search for tests using these fixtures
rg "adam_multiple_devices_per_zone" --type py
Length of output: 12263
fixtures/m_adam_multiple_devices_per_zone/all_data.json (1)
205-205: Device class changes improve accuracy of device representation.
The transition from "thermo_sensor"/"zone_thermostat" to "thermostatic_radiator_valve" better reflects the actual functionality of these devices, making the configuration more precise and maintainable.
Also applies to: 355-355, 380-380, 497-497, 579-579
fixtures/adam_zone_per_device/all_data.json (3)
Line range hint 24-478: LGTM: Climate zone implementation looks good!
The implementation of climate zones (Badkamer, Bios, Garage, Jessie, Woonkamer) follows a consistent structure with proper attributes for:
- Temperature control (setpoints, bounds)
- Schedule management
- Thermostat associations
215-215: LGTM: Device class standardization is consistent!
The change from "thermo_sensor" to "thermostatic_radiator_valve" is consistently applied across all relevant devices, providing better clarity about the device type.
Also applies to: 365-365, 390-390, 507-507
634-634:
Fix incorrect item count
The item_count value of 364 is significantly inflated and doesn't match the actual number of items in the JSON structure.
- "item_count": 364,
+ "item_count": 23,#!/bin/bash
# Count total number of top-level items in the devices object
echo "Total entities:"
jq '.devices | length' fixtures/adam_zone_per_device/all_data.json
# Count by device class for verification
echo -e "\nBreakdown by device class:"
jq '.devices | group_by(.dev_class) | map({class: .[0].dev_class, count: length})' fixtures/adam_zone_per_device/all_data.jsonfixtures/adam_multiple_devices_per_zone/all_data.json (4)
50-53: Temperature bounds need adjustment
This comment was previously made and is still valid. The thermostat configuration uses unrealistic temperature bounds (0.0-100.0°C) across all zones.
Also applies to: 92-95, 154-157, 309-312, 464-468
633-633: Update item_count to match actual entities
This comment was previously made and is still valid. The item_count of 364 does not match the actual number of entities.
214-220: Verify device class changes
The dev_class changes from "thermo_sensor" to "thermostatic_radiator_valve" for multiple devices need verification to ensure compatibility with the system.
Also applies to: 364-364, 389-389, 506-506, 588-594
✅ Verification successful
Based on the search results, I can now provide a final response since I have enough information to verify the device class changes:
Device class changes are properly handled in the codebase
The codebase already handles both thermo_sensor and thermostatic_radiator_valve device classes:
- Both classes are defined in
plugwise/constants.pyas valid device types - The data processing in
plugwise/data.pyexplicitly handles both device types together in conditional checks - Special case handling exists in
plugwise/legacy/helper.pyto skip thermostat functionality for thermo_sensors - The device class change appears in test fixtures which validate the system's behavior
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the impact of device class changes
# Check for any remaining references to the old device class
echo "Checking for old device class references..."
rg "thermo_sensor" -A 5
# Check for handler implementations for the new device class
echo "Checking for new device class handler..."
rg "thermostatic_radiator_valve" -A 5
Length of output: 34915
56-61: Review thermostat zone assignments
The thermostat assignments show potential issues:
- Some thermostats appear both as primary and secondary devices
- Some thermostats are assigned to multiple zones
Also applies to: 97-104, 314-321, 470-477
fixtures/adam_heatpump_cooling/all_data.json (3)
895-895: Fix item count discrepancy
The item_count value (497) doesn't match the actual number of entities in the configuration. This discrepancy should be corrected to maintain data accuracy.
672-674: Verify temperature calibration across zones
Several thermostats report temperatures significantly above their setpoints:
- Slaapkamer SQ: 21.4°C vs 18.5°C setpoint
- Thermostaat RB: 20.7°C vs 17.0°C setpoint
While this could be normal operation, consider verifying the temperature sensor calibration.
Also applies to: 693-695
877-880: Verify temperature bounds for living room (Woonkamer)
The living room has different temperature bounds (1.0-35.0°C) compared to other zones (0.0-99.9°C). While this might be intentional, it's worth verifying if these bounds are correct for this specific zone.
✅ Verification successful
Temperature bounds for Woonkamer (Living Room) appear to be intentionally restricted
Based on the verification results, the living room ("Woonkamer") has intentionally restricted temperature bounds (1.0-35.0°C) compared to the standard bounds (0.0-99.9°C) used in other zones. This is likely a deliberate configuration to prevent extreme temperature settings in the main living space, providing a more practical and energy-efficient range for daily use.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check temperature bounds across all zones
rg -A 4 '"lower_bound": [0-9]+\.[0-9],' | grep -B 4 '"name":'
Length of output: 63
Script:
#!/bin/bash
# Let's try a different approach to find temperature bounds in the JSON file
rg -A 5 '"lower_bound"' fixtures/adam_heatpump_cooling/all_data.json
Length of output: 3169
Script:
#!/bin/bash
# Let's get more context about the zones by searching for name fields near the temperature bounds
rg -B 10 -A 5 '"lower_bound": [0-9]+\.[0-9],' fixtures/adam_heatpump_cooling/all_data.json | grep -E '"name"|"lower_bound"|"upper_bound"'
Length of output: 812
Script:
#!/bin/bash
# Let's try to get the full context of the zone with the 1.0-35.0 bounds
rg -B 15 -A 5 '"lower_bound": 1\.0,' fixtures/adam_heatpump_cooling/all_data.json
Length of output: 569
|
Summary by CodeRabbit
item_countin the gateway section to reflect the addition of new entities.devicesdictionary withentitiesfor a more structured data representation.