diff --git a/Makefile b/Makefile index f277f04..6a24dab 100644 --- a/Makefile +++ b/Makefile @@ -1,18 +1,14 @@ RUN = poetry run -biosample_sqlite_file = ~/biosample_basex_data_good_subset.db - .PHONY: test clean all -all: clean test examples/outputs/report.tsv assets/bibo_DocumentStatus.tsv rel_to_oxygen_example \ -examples/outputs/non_attribute_metadata_sel_envs_partial.tsv +all: clean test examples/outputs/report.tsv # --------------------------------------- # Test runner # ---------------------------------------- test: $(RUN) pytest 2>&1 | tee logs/tests.log - $(RUN) pytest -sv tests/test_capitalization.py clean: @@ -32,28 +28,3 @@ clean: examples/outputs/report.tsv: examples/gold.json $(RUN) annotate-sample -R $@ $< -downloads/mixs6_core.tsv: - curl -L -s 'https://docs.google.com/spreadsheets/d/1QDeeUcDqXes69Y2RjU2aWgOpCVWo5OVsBX9MKmMqi_o/export?format=tsv&gid=178015749' > $@ - -examples/outputs/non_attribute_metadata_sel_envs_partial.tsv: - $(RUN) sqlite_client_cli \ - --sqlite_path $(biosample_sqlite_file) \ - --query "select * from non_attribute_metadata_sel_envs limit 9" \ - --tsv_out $@ - -rel_to_oxygen_example: downloads/mixs6_core.tsv - $(RUN) rel_to_oxygen_example \ - --sqlite_path $(biosample_sqlite_file) \ - --mixs_core_path $< - - -bin/robot.jar: - curl -s https://api.github.com/repos/ontodev/robot/releases/latest | grep 'browser_download_url.*\.jar"' | cut -d : -f 2,3 | tr -d \" | wget -O $@ -i - - -downloads/bibo.owl: - # --location (-L) pursues redirects - curl --location https://raw.githubusercontent.com/structureddynamics/Bibliographic-Ontology-BIBO/master/bibo.owl -o $@ - -assets/bibo_DocumentStatus.tsv: downloads/bibo.owl bin/robot.jar - java -jar bin/robot.jar query --input $< --query sparql/bibo_DocumentStatus.sparql $@ - sed --in-place=.bak 's/^\?//' $@ \ No newline at end of file diff --git a/make-gold-cache.Makefile b/make-gold-cache.Makefile index f72d051..7291a96 100644 --- a/make-gold-cache.Makefile +++ b/make-gold-cache.Makefile @@ -1,30 +1,56 @@ # review and fix readmes and poetry dependencies -MAX_STUDIES=70000 # 2025-01 +# see also https://github.com/microbiomedata/external-metadata-awareness/blob/751ddb6360f95f164a6605ca056e81fced59e195/Makefiles/gold.Makefile + +RUN=poetry run .PHONY: load-gold-biosamples-into-mongo +gold-to-mongo-all: gold-to-mongo-clean load-gold-biosamples-into-mongo + +gold-to-mongo-clean: + rm -rf downloads/goldData.xlsx local/gold-study-ids-with-biosamples.txt + downloads/goldData.xlsx: - wget -O $@ "https://gold.jgi.doe.gov/download?mode=site_excel" + curl -o $@ "https://gold.jgi.doe.gov/download?mode=site_excel" local/gold-studies.tsv: downloads/goldData.xlsx - poetry run python sample_annotator/file_utils/xlsx_to_tsv.py \ + $(RUN) xlsx-to-tsv \ --excel-file $< \ --sheet-name Study \ --output-file $@ -local/gold-study-ids.txt: local/gold-studies.tsv - # without the grep filter, this introduces some noise (non-id rows) - tail -n +2 $< | cut -f 1 | sort | grep 'Gs' > $@ - -local/gold-study-ids-subset.txt: local/gold-study-ids.txt - head -n $(MAX_STUDIES) $< > $@ +# Extract Study GOLD IDs that have associated Biosample GOLD IDs +local/gold-study-ids-with-biosamples.txt: downloads/goldData.xlsx + date && time $(RUN) extract-study-ids-with-biosamples \ + --excel-file $< \ + --sheet-name 'Sequencing Project' \ + --output-file $@.tmp && date # 8 minutes + sort $@.tmp | uniq > $@ + rm -rf $@.tmp + +# gold-to-mongo no supports both local and remote MongoDB servers with or without authentication. +# +# Environment variables (from .env file) +# MONGODB_USER: MongoDB username +# MONGODB_PASSWORD: MongoDB password + +# # --purge-mongodb +# # --purge-diskcache +# # --env-file + +load-gold-biosamples-into-mongo: local/gold-study-ids-with-biosamples.txt + $(RUN) gold-to-mongo \ + --authentication-file config/gold-key.txt \ + --log-failures-to-file local/gold-to-mongo-failures.json \ + --mongo-uri "mongodb://localhost:27017/gold_metadata" \ + --study-ids-file $< -local/gold-cache.json: local/gold-study-ids-subset.txt +local/gold-cache.json: local/gold-studies.tsv # ~ 3 seconds/uncached study # GOLD has ~ 63k studies - # < 2 days to fetch all studies ? - poetry run python sample_annotator/clients/gold_client.py \ + # ~ 2.5 days to fetch all studies with no hiccups + $(RUN) python sample_annotator/clients/gold_client.py \ --verbose \ fetch-studies \ --output-format json \ @@ -33,20 +59,3 @@ local/gold-cache.json: local/gold-study-ids-subset.txt --authentication-file config/gold-key.txt \ $< -load-gold-biosamples-into-mongo: local/gold-study-ids-subset.txt - # --purge-mongodb - # --purge-diskcache - poetry run python sample_annotator/gold_to_mongo.py \ - --authentication-file config/gold-key.txt \ - --mongo-db-name gold_metadata \ - --study-ids-file $< - -#.PHONY: split-out-gold-biosamples -#split-out-gold-biosamples: local/gold-cache.json -# poetry run python sample_annotator/file_utils/split_out_gold_biosamples.py \ -# --input-file $< \ -# --study-output-file local/gold-studies-only.json \ -# --biosample-output-file local/gold-biosamples-only.json \ -# --project-output-file local/gold-projects-only.json \ -# --remove-contacts \ -# --remove-nulls \ No newline at end of file diff --git a/poetry.lock b/poetry.lock index 2acf9a0..8fb0dc3 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand. [[package]] name = "alabaster" @@ -6,6 +6,7 @@ version = "1.0.0" description = "A light, configurable Sphinx theme" optional = false python-versions = ">=3.10" +groups = ["main"] files = [ {file = "alabaster-1.0.0-py3-none-any.whl", hash = "sha256:fc6786402dc3fcb2de3cabd5fe455a2db534b371124f1f21de8731783dec828b"}, {file = "alabaster-1.0.0.tar.gz", hash = "sha256:c00dca57bca26fa62a6d7d0a9fcce65f3e026e9bfe33e9c538fd3fbb2144fd9e"}, @@ -17,6 +18,7 @@ version = "0.7.0" description = "Reusable constraint types to use with typing.Annotated" optional = false python-versions = ">=3.8" +groups = ["main", "dev"] files = [ {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, @@ -28,6 +30,7 @@ version = "4.9.3" description = "ANTLR 4.9.3 runtime for Python 3.7" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "antlr4-python3-runtime-4.9.3.tar.gz", hash = "sha256:f224469b4168294902bb1efa80a8bf7855f24c99aef99cbefc1bcd3cce77881b"}, ] @@ -38,6 +41,7 @@ version = "1.3.0" description = "Better dates & times for Python" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "arrow-1.3.0-py3-none-any.whl", hash = "sha256:c728b120ebc00eb84e01882a6f5e7927a53960aa990ce7dd2b10f39005a67f80"}, {file = "arrow-1.3.0.tar.gz", hash = "sha256:d4540617648cb5f895730f1ad8c82a65f2dad0166f57b75f3ca54759c4d67a85"}, @@ -53,32 +57,34 @@ test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock [[package]] name = "attrs" -version = "24.3.0" +version = "25.3.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.8" +groups = ["main", "dev"] files = [ - {file = "attrs-24.3.0-py3-none-any.whl", hash = "sha256:ac96cd038792094f438ad1f6ff80837353805ac950cd2aa0e0625ef19850c308"}, - {file = "attrs-24.3.0.tar.gz", hash = "sha256:8f5c07333d543103541ba7be0e2ce16eeee8130cb0b3f9238ab904ce1e85baff"}, + {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"}, + {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"}, ] [package.extras] -benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"] -tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"] +benchmark = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +cov = ["cloudpickle ; platform_python_implementation == \"CPython\"", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +dev = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier"] +tests = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +tests-mypy = ["mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\""] [[package]] name = "autopep8" -version = "2.3.1" +version = "2.3.2" description = "A tool that automatically formats Python code to conform to the PEP 8 style guide" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" +groups = ["dev"] files = [ - {file = "autopep8-2.3.1-py2.py3-none-any.whl", hash = "sha256:a203fe0fcad7939987422140ab17a930f684763bf7335bdb6709991dd7ef6c2d"}, - {file = "autopep8-2.3.1.tar.gz", hash = "sha256:8d6c87eba648fdcfc83e29b788910b8643171c395d9c4bcf115ece035b9c9dda"}, + {file = "autopep8-2.3.2-py2.py3-none-any.whl", hash = "sha256:ce8ad498672c845a0c3de2629c15b635ec2b05ef8177a6e7c91c74f3e9b51128"}, + {file = "autopep8-2.3.2.tar.gz", hash = "sha256:89440a4f969197b69a995e4ce0661b031f455a9f776d2c5ba3dbd83466931758"}, ] [package.dependencies] @@ -87,31 +93,34 @@ tomli = {version = "*", markers = "python_version < \"3.11\""} [[package]] name = "babel" -version = "2.16.0" +version = "2.17.0" description = "Internationalization utilities" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ - {file = "babel-2.16.0-py3-none-any.whl", hash = "sha256:368b5b98b37c06b7daf6696391c3240c938b37767d4584413e8438c5c435fa8b"}, - {file = "babel-2.16.0.tar.gz", hash = "sha256:d1f3554ca26605fe173f3de0c65f750f5a42f924499bf134de6423582298e316"}, + {file = "babel-2.17.0-py3-none-any.whl", hash = "sha256:4d0b53093fdfb4b21c92b5213dba5a1b23885afa8383709427046b21c366e5f2"}, + {file = "babel-2.17.0.tar.gz", hash = "sha256:0c54cffb19f690cdcc52a3b50bcbf71e07a808d1c80d549f2459b9d2cf0afb9d"}, ] [package.extras] -dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"] +dev = ["backports.zoneinfo ; python_version < \"3.9\"", "freezegun (>=1.0,<2.0)", "jinja2 (>=3.0)", "pytest (>=6.0)", "pytest-cov", "pytz", "setuptools", "tzdata ; sys_platform == \"win32\""] [[package]] name = "beautifulsoup4" -version = "4.12.3" +version = "4.13.3" description = "Screen-scraping library" optional = false -python-versions = ">=3.6.0" +python-versions = ">=3.7.0" +groups = ["main"] files = [ - {file = "beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed"}, - {file = "beautifulsoup4-4.12.3.tar.gz", hash = "sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051"}, + {file = "beautifulsoup4-4.13.3-py3-none-any.whl", hash = "sha256:99045d7d3f08f91f0d656bc9b7efbae189426cd913d830294a15eefa0ea4df16"}, + {file = "beautifulsoup4-4.13.3.tar.gz", hash = "sha256:1bd32405dacc920b42b83ba01644747ed77456a65760e285fbc47633ceddaf8b"}, ] [package.dependencies] soupsieve = ">1.2" +typing-extensions = ">=4.0.0" [package.extras] cchardet = ["cchardet"] @@ -122,13 +131,14 @@ lxml = ["lxml"] [[package]] name = "bioregistry" -version = "0.11.29" +version = "0.11.35" description = "Integrated registry of biological databases and nomenclatures" optional = false python-versions = ">=3.9" +groups = ["main"] files = [ - {file = "bioregistry-0.11.29-py3-none-any.whl", hash = "sha256:f4d8b9130297b505c186a51aa5451a355f29e9fef25fd358441b6c95bb5606e4"}, - {file = "bioregistry-0.11.29.tar.gz", hash = "sha256:6d6b1c9943bb80eea4fee699d1f9f86b13a260151468db53e70c557b9a0538ef"}, + {file = "bioregistry-0.11.35-py3-none-any.whl", hash = "sha256:64713a6595190175d506f2053b1599707a8cf266a2ba44cff3c2e29b71063f90"}, + {file = "bioregistry-0.11.35.tar.gz", hash = "sha256:f3c57638c193161674f3569312dd6c3a3f99ace862a5c8e0c7986c06e30815d0"}, ] [package.dependencies] @@ -147,6 +157,7 @@ docs = ["autodoc_pydantic", "sphinx (>=8)", "sphinx-click", "sphinx-rtd-theme (> export = ["ndex2", "pyyaml", "rdflib", "rdflib-jsonld"] gha = ["more_itertools"] health = ["click_default_group", "jinja2", "pandas", "pyyaml", "tabulate"] +paper-ranking = ["indra", "more_itertools", "pandas", "scikit-learn", "tabulate"] tests = ["coverage", "httpx", "indra", "more_itertools", "pytest", "scikit-learn"] web = ["a2wsgi", "bootstrap-flask (<=2.0.0)", "curies[fastapi]", "fastapi", "flask (<2.2.4)", "markdown", "pyyaml", "rdflib", "rdflib-endpoint", "rdflib-jsonld", "uvicorn", "werkzeug (<2.3.0)"] @@ -156,6 +167,7 @@ version = "24.10.0" description = "The uncompromising code formatter." optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "black-24.10.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e6668650ea4b685440857138e5fe40cde4d652633b1bdffc62933d0db4ed9812"}, {file = "black-24.10.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1c536fcf674217e87b8cc3657b81809d3c085d7bf3ef262ead700da345bfa6ea"}, @@ -198,24 +210,26 @@ uvloop = ["uvloop (>=0.15.2)"] [[package]] name = "cachetools" -version = "5.5.0" +version = "5.5.2" description = "Extensible memoizing collections and decorators" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ - {file = "cachetools-5.5.0-py3-none-any.whl", hash = "sha256:02134e8439cdc2ffb62023ce1debca2944c3f289d66bb17ead3ab3dede74b292"}, - {file = "cachetools-5.5.0.tar.gz", hash = "sha256:2cc24fb4cbe39633fb7badd9db9ca6295d766d9c2995f245725a46715d050f2a"}, + {file = "cachetools-5.5.2-py3-none-any.whl", hash = "sha256:d26a22bcc62eb95c3beabd9f1ee5e820d3d2704fe2967cbe350e20c8ffcd3f0a"}, + {file = "cachetools-5.5.2.tar.gz", hash = "sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4"}, ] [[package]] name = "certifi" -version = "2024.12.14" +version = "2025.1.31" description = "Python package for providing Mozilla's CA Bundle." optional = false python-versions = ">=3.6" +groups = ["main", "dev"] files = [ - {file = "certifi-2024.12.14-py3-none-any.whl", hash = "sha256:1275f7a45be9464efc1173084eaa30f866fe2e47d389406136d332ed4967ec56"}, - {file = "certifi-2024.12.14.tar.gz", hash = "sha256:b650d30f370c2b724812bee08008be0c4163b163ddaec3f2546c1caf65f191db"}, + {file = "certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe"}, + {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"}, ] [[package]] @@ -224,6 +238,7 @@ version = "0.2.1" description = "rdflib collections flattening graph" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "CFGraph-0.2.1.tar.gz", hash = "sha256:b57fe7044a10b8ff65aa3a8a8ddc7d4cd77bf511b42e57289cd52cbc29f8fe74"}, ] @@ -237,6 +252,7 @@ version = "5.2.0" description = "Universal encoding detector for Python 3" optional = false python-versions = ">=3.7" +groups = ["main", "dev"] files = [ {file = "chardet-5.2.0-py3-none-any.whl", hash = "sha256:e1cf59446890a00105fe7b7912492ea04b6e6f06d4b742b2c788469e34c82970"}, {file = "chardet-5.2.0.tar.gz", hash = "sha256:1b3b6ff479a8c414bc3fa2c0852995695c4a026dcd6d0633b2dd092ca39c1cf7"}, @@ -248,6 +264,7 @@ version = "3.4.1" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." optional = false python-versions = ">=3.7" +groups = ["main", "dev"] files = [ {file = "charset_normalizer-3.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de"}, {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7461baadb4dc00fd9e0acbe254e3d7d2112e7f92ced2adc96e54ef6501c5f176"}, @@ -349,6 +366,7 @@ version = "8.1.8" description = "Composable command line interface toolkit" optional = false python-versions = ">=3.7" +groups = ["main", "dev"] files = [ {file = "click-8.1.8-py3-none-any.whl", hash = "sha256:63c132bbbed01578a06712a2d1f497bb62d9c1c0d329b7903a866228027263b2"}, {file = "click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a"}, @@ -363,6 +381,7 @@ version = "0.4.0" description = "Logging integration for Click" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "click-log-0.4.0.tar.gz", hash = "sha256:3970f8570ac54491237bcdb3d8ab5e3eef6c057df29f8c3d1151a51a9c23b975"}, {file = "click_log-0.4.0-py2.py3-none-any.whl", hash = "sha256:a43e394b528d52112af599f2fc9e4b7cf3c15f94e53581f74fa6867e68c91756"}, @@ -377,10 +396,12 @@ version = "0.4.6" description = "Cross-platform colored terminal text." optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" +groups = ["main", "dev"] files = [ {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"}, {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"}, ] +markers = {main = "sys_platform == \"win32\" or platform_system == \"Windows\""} [[package]] name = "commonmark" @@ -388,6 +409,7 @@ version = "0.9.1" description = "Python parser for the CommonMark Markdown spec" optional 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b/pyproject.toml @@ -42,6 +42,7 @@ linkml = "^1.7" nmdc-schema = "^11.0" numpy = "^2.2" pandas = "^2.2" +pymongo = "^4.11" python = "^3.10" python-dotenv = "^1.0" pyyaml = "^6.0" # to humor deptry @@ -50,21 +51,21 @@ recommonmark = "^0.7.1" sphinx-rtd-theme = "3.0" -[tool.poetry.dev-dependencies] +[tool.poetry.group.dev.dependencies] autopep8 = "^2.0" black = "^24.0" -deptry = "^0.21.2" -pytest = "^8.0" -tox = "4.20" -matplotlib = "^3.9.2" # for notebooks/DataGood-NMDC-Code.ipynb -nltk = "^3.8" # for notebooks/DataGood-NMDC-Code.ipynb -seaborn = "^0.13" # for notebooks/DataGood-NMDC-Code.ipynb -sqlalchemy = "^2.0" # for notebooks/DataGood-NMDC-Code.ipynb click = "^8.1" # recommended by deptry +deptry = "^0.21.2" jsonschema = "^4.21" # recommended by deptry linkml-runtime = "^1.8" # recommended by deptry +matplotlib = "^3.9.2" # for notebooks/DataGood-NMDC-Code.ipynb +nltk = "^3.8" # for notebooks/DataGood-NMDC-Code.ipynb pydantic = "^2.10" # recommended by deptry +pytest = "^8.0" requests = "^2.32.2" # recommended by deptry +seaborn = "^0.13" # for notebooks/DataGood-NMDC-Code.ipynb +sqlalchemy = "^2.0" # for notebooks/DataGood-NMDC-Code.ipynb +tox = "4.20" [build-system] requires = ["poetry-core>=1.0.0"] @@ -72,6 +73,8 @@ build-backend = "poetry.core.masonry.api" [tool.poetry.scripts] annotate-sample = "sample_annotator.sample_annotator:cli" -sqlite_client_cli = "sample_annotator.clients.biosample_sqlite_client:cli" +cache-gold = "sample_annotator.clients.gold_client:main" +extract-study-ids-with-biosamples = "sample_annotator.file_utils.extract_study_ids_with_biosamples:main" +gold-to-mongo = "sample_annotator.gold_to_mongo:main" rel_to_oxygen_example = "sample_annotator.rel_to_oxygen_example:cli" - +xlsx-to-tsv = "sample_annotator.file_utils.xlsx_to_tsv:xlsx_to_tsv" \ No newline at end of file diff --git a/sparql/.gitkeep b/sample_annotator/cache/.gitkeep similarity index 100% rename from sparql/.gitkeep rename to sample_annotator/cache/.gitkeep diff --git a/sample_annotator/capitalizer.py b/sample_annotator/capitalizer.py deleted file mode 100644 index 3ec587e..0000000 --- a/sample_annotator/capitalizer.py +++ /dev/null @@ -1,2 +0,0 @@ -def capitalizer(sometext): - return sometext.title() diff --git a/sample_annotator/clients/biosample_sqlite_client.py b/sample_annotator/clients/biosample_sqlite_client.py deleted file mode 100644 index fab7de3..0000000 --- a/sample_annotator/clients/biosample_sqlite_client.py +++ /dev/null @@ -1,56 +0,0 @@ -import logging -import sqlite3 - -import click -import click_log -import pandas as pd - -logger = logging.getLogger(__name__) -click_log.basic_config(logger) - - -@click.command() -@click_log.simple_verbosity_option(logger) -@click.option("--sqlite_path", type=click.Path(exists=True), required=True) -@click.option("--tsv_out", type=click.Path(), required=True) -@click.option("--query", required=True) -def cli(sqlite_path: str, query: str, tsv_out: str): - """ - :param sqlite_path: - :return: - """ - - conn = create_connection(sqlite_path) - - res = q_to_frame(conn, query) - - logger.info(res) - - res.to_csv(tsv_out, sep="\t", index=False) - - -if __name__ == '__main__': - cli() - - -def create_connection(db_file): - """ create a database connection to the SQLite database - specified by the db_file - :param db_file: database file - :return: Connection object or None - """ - conn = None - try: - conn = sqlite3.connect(db_file) - except Exception as e: - print(e) - - return conn - - -def q_to_frame(conn, query): - result_frame = pd.read_sql(query, conn, index_col=None, coerce_float=True, params=None, parse_dates=None, - columns=None, - chunksize=None) - - return result_frame diff --git a/sample_annotator/file_utils/extract_study_ids_with_biosamples.py b/sample_annotator/file_utils/extract_study_ids_with_biosamples.py new file mode 100644 index 0000000..b45f769 --- /dev/null +++ b/sample_annotator/file_utils/extract_study_ids_with_biosamples.py @@ -0,0 +1,96 @@ +#!/usr/bin/env python3 +import sys +import warnings +from typing import Optional, Set + +import click +import pandas as pd + +warnings.filterwarnings("ignore", category=UserWarning, module="openpyxl.styles.stylesheet") + + +def extract_study_ids_with_biosamples(excel_file: str, sheet_name: str = "Sequencing Project") -> Set[str]: + """ + Extract Study GOLD IDs from the Sequencing Project sheet, filtering for rows that have Biosample GOLD IDs. + + Args: + excel_file: Path to the GOLD data Excel file + sheet_name: Name of the sheet to extract from (default: "Sequencing Project") + + Returns: + Set of unique Study GOLD IDs that have associated Biosample GOLD IDs + """ + try: + # Read the Sequencing Project sheet + df = pd.read_excel(excel_file, sheet_name=sheet_name) + + # Identify column names + column_map = {} + for col in df.columns: + col_upper = col.upper().replace(" ", "_") + if "STUDY_GOLD_ID" in col_upper: + column_map["study_id"] = col + elif "BIOSAMPLE_GOLD_ID" in col_upper: + column_map["biosample_id"] = col + elif "PROJECT_GOLD_ID" in col_upper: + column_map["project_id"] = col + + if "study_id" not in column_map or "biosample_id" not in column_map: + raise ValueError(f"Required columns not found in {sheet_name} sheet") + + # Print summary statistics + print(f"# Rows in sheet: {len(df)}", file=sys.stderr) + if "project_id" in column_map: + print(f"# Unique Project IDs: {df[column_map['project_id']].nunique(dropna=True)}", file=sys.stderr) + print(f"# Unique Study IDs: {df[column_map['study_id']].nunique(dropna=True)}", file=sys.stderr) + print(f"# Unique Biosample IDs: {df[column_map['biosample_id']].nunique(dropna=True)}", file=sys.stderr) + + # Filter for rows with Biosample IDs + mask = df[column_map["biosample_id"]].notna() & df[column_map["biosample_id"]].astype(str).str.len() > 0 + filtered_df = df[mask] + + # Extract valid Study IDs (must start with 'Gs') + study_ids = set(filtered_df[column_map["study_id"]].unique()) + valid_study_ids = {str(study_id) for study_id in study_ids if str(study_id).startswith('Gs')} + + print(f"# Unique Study IDs linked to Biosamples: {len(valid_study_ids)}", file=sys.stderr) + + return valid_study_ids + + except Exception as e: + print(f"Error processing Excel file: {e}", file=sys.stderr) + return set() + + +@click.command() +@click.option("--excel-file", "-e", required=True, type=click.Path(exists=True), + help="Path to the GOLD data Excel file (.xlsx)") +@click.option("--sheet-name", "-s", default="Sequencing Project", + help="Name of the sheet containing sequencing project data") +@click.option("--output-file", "-o", default=None, type=click.Path(), + help="Output file for study IDs (defaults to stdout)") +def main(excel_file: str, sheet_name: str, output_file: Optional[str]): + """ + Extract Study GOLD IDs from rows in the Sequencing Project sheet that have Biosample GOLD IDs. + """ + study_ids = extract_study_ids_with_biosamples(excel_file, sheet_name) + + if not study_ids: + click.echo(f"No Study GOLD IDs with Biosample IDs found in {sheet_name} sheet", err=True) + sys.exit(1) + + sorted_ids = sorted(study_ids) + + if output_file: + with open(output_file, 'w') as f: + for study_id in sorted_ids: + f.write(f"{study_id}\n") + click.echo(f"Extracted {len(sorted_ids)} Study GOLD IDs to '{output_file}'") + else: + for study_id in sorted_ids: + click.echo(study_id) + click.echo(f"Extracted {len(sorted_ids)} Study GOLD IDs", err=True) + + +if __name__ == "__main__": + main() diff --git a/sample_annotator/file_utils/split_out_gold_biosamples.py b/sample_annotator/file_utils/split_out_gold_biosamples.py deleted file mode 100644 index fcabd15..0000000 --- a/sample_annotator/file_utils/split_out_gold_biosamples.py +++ /dev/null @@ -1,121 +0,0 @@ -import json -from typing import Any, Dict, List, Union -import click - - -def remove_null_keys(obj: Union[Dict, List]) -> Union[Dict, List]: - """ - Recursively remove keys with null (None) values or empty lists from a JSON-like object. - - Args: - obj (Union[Dict, List]): The JSON-like object (dictionary or list) to process. - - Returns: - Union[Dict, List]: The cleaned JSON-like object with null keys and empty lists removed. - """ - if isinstance(obj, dict): - return {k: remove_null_keys(v) for k, v in obj.items() if v is not None and v != []} - elif isinstance(obj, list): - return [remove_null_keys(v) for v in obj] - return obj - - -def split_study_biosample_project( - input_file: str, - study_output_file: str, - biosample_output_file: str, - project_output_file: str, - remove_contacts: bool, - remove_nulls: bool -) -> None: - """ - Splits a JSON file containing study metadata into three JSON files: - one for studies, one for biosamples, and one for projects. - - Args: - input_file (str): Path to the input JSON file containing study metadata. - study_output_file (str): Path to the output JSON file for studies. - biosample_output_file (str): Path to the output JSON file for biosamples. - project_output_file (str): Path to the output JSON file for projects. - remove_contacts (bool): Whether to remove the 'contacts' key from all objects. - remove_nulls (bool): Whether to remove keys with null values and empty lists from all objects. - """ - - def remove_key(obj: Dict, key: str) -> None: - """Remove a key from a dictionary if it exists.""" - if key in obj: - del obj[key] - - with open(input_file, 'r') as infile: - study_data: List[Dict] = json.load(infile) - - studies: List[Dict] = [] - biosamples: List[Dict] = [] - projects: List[Dict] = [] - - for study in study_data: - if remove_contacts: - remove_key(study, 'contacts') - if remove_nulls: - study = remove_null_keys(study) - if 'biosamples' in study: - biosample_ids = [] - for biosample in study['biosamples']: - if remove_contacts: - remove_key(biosample, 'contacts') - if remove_nulls: - biosample = remove_null_keys(biosample) - if 'projects' in biosample: - project_ids = [project['projectGoldId'] for project in biosample['projects']] - for project in biosample['projects']: - if remove_contacts: - remove_key(project, 'contacts') - if remove_nulls: - project = remove_null_keys(project) - projects.append(project) - biosample['projects'] = project_ids # Replace with only IDs - biosamples.append(biosample) - biosample_ids.append(biosample['biosampleGoldId']) - study['biosamples'] = biosample_ids # Replace with only IDs - studies.append(study) - - # Write studies to output file - with open(study_output_file, 'w') as study_outfile: - json.dump(studies, study_outfile, indent=4) - - # Write biosamples to output file - with open(biosample_output_file, 'w') as biosample_outfile: - json.dump(biosamples, biosample_outfile, indent=4) - - # Write projects to output file - with open(project_output_file, 'w') as project_outfile: - json.dump(projects, project_outfile, indent=4) - - -@click.command() -@click.option('--input-file', '-i', type=click.Path(exists=True, dir_okay=False, readable=True), required=True, - help='Path to the input JSON file containing study metadata.') -@click.option('--study-output-file', '-s', type=click.Path(writable=True), required=True, - help='Path to the output JSON file for studies.') -@click.option('--biosample-output-file', '-b', type=click.Path(writable=True), required=True, - help='Path to the output JSON file for biosamples.') -@click.option('--project-output-file', '-p', type=click.Path(writable=True), required=True, - help='Path to the output JSON file for projects.') -@click.option('--remove-contacts', '-r', is_flag=True, default=False, - help="If set, removes the 'contacts' key from all objects.") -@click.option('--remove-nulls', '-n', is_flag=True, default=False, - help="If set, removes keys with null values or empty lists from all objects.") -def main(input_file: str, study_output_file: str, biosample_output_file: str, project_output_file: str, - remove_contacts: bool, remove_nulls: bool) -> None: - """ - CLI tool to split a JSON file of study metadata into three JSON files: - one for studies, one for biosamples, and one for projects. - - Optionally removes the 'contacts' key and/or keys with null values and empty lists from all objects. - """ - split_study_biosample_project(input_file, study_output_file, biosample_output_file, project_output_file, - remove_contacts, remove_nulls) - - -if __name__ == "__main__": - main() diff --git a/sample_annotator/gold_to_mongo.py b/sample_annotator/gold_to_mongo.py index 0a129b7..5448209 100644 --- a/sample_annotator/gold_to_mongo.py +++ b/sample_annotator/gold_to_mongo.py @@ -1,32 +1,82 @@ +import json import logging -from typing import List, Set +import os +from datetime import datetime +from time import sleep +from typing import List, Optional, Set +from urllib.parse import quote_plus import click +import dotenv from pymongo import MongoClient, ASCENDING from pymongo.errors import DuplicateKeyError +from pymongo.uri_parser import parse_uri -from clients.gold_client import GoldClient +# Fix import path for both direct script execution and CLI entry point +try: + # When running as a script + from clients.gold_client import GoldClient +except ModuleNotFoundError: + # When running as an installed package + from sample_annotator.clients.gold_client import GoldClient # todo might need better API error handling # should be more consistent about bundling (projects in biosamples) vs getting biosamples separate from studies # todo document the fact that a biosamples key is added to studies -# biosamples kave no foreign keys +# biosamples have no foreign keys # (sequencing) projects include native study and biosample foreign keys # Configure logging logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') -def create_unique_index(collection, field_name: str, index_name: str) -> None: - """ - Creates a unique index on the specified field for a MongoDB collection. +def load_mongodb_credentials(env_file: Optional[str] = None) -> dict: + if env_file: + dotenv.load_dotenv(env_file) + else: + default_env_path = os.path.join('local', '.env') + if os.path.exists(default_env_path): + dotenv.load_dotenv(default_env_path) + return { + 'user': os.environ.get('MONGODB_USER'), + 'password': os.environ.get('MONGODB_PASSWORD') + } + - Args: - collection: The MongoDB collection object. - field_name: The field to index. - index_name: The name of the index. +def build_mongodb_connection_string( + mongo_uri: Optional[str] = None, + user: Optional[str] = None, + password: Optional[str] = None) -> str: """ + Injects user and password into an existing MongoDB URI if missing. + If no URI is provided, falls back to localhost unauthenticated. + """ + if mongo_uri: + parsed = parse_uri(mongo_uri) + if parsed.get('username') or parsed.get('password'): + return mongo_uri # already has credentials + if not user or not password: + return mongo_uri # let it connect anonymously + # Inject user/pass + escaped_user = quote_plus(user) + escaped_password = quote_plus(password) + # Find where to insert credentials + protocol_split = mongo_uri.split("://", 1) + if len(protocol_split) != 2: + raise ValueError("Invalid MongoDB URI") + scheme, rest = protocol_split + return f"{scheme}://{escaped_user}:{escaped_password}@{rest}" + + # If no URI provided, build a basic local one + if not user or not password: + return "mongodb://localhost:27017/" + escaped_user = quote_plus(user) + escaped_password = quote_plus(password) + return f"mongodb://{escaped_user}:{escaped_password}@localhost:27017/" + + +def create_unique_index(collection, field_name: str, index_name: str) -> None: try: collection.create_index([(field_name, ASCENDING)], name=index_name, unique=True) except Exception as e: @@ -34,31 +84,13 @@ def create_unique_index(collection, field_name: str, index_name: str) -> None: def insert_document(collection, document: dict, key_name: str) -> None: - """ - Inserts a document into a MongoDB collection, handling duplicate key errors. - - Args: - collection: The MongoDB collection object. - document: The document to insert. - key_name: The key used for the unique index, for logging purposes. - """ try: collection.insert_one(document) - except DuplicateKeyError as e: - # logging.warning(f"Duplicate key error for {key_name}: {e}") + except DuplicateKeyError: logging.warning(f"Duplicate key error for {key_name}") def process_study_ids(file_path: str) -> List[str]: - """ - Reads and processes study IDs from a file. - - Args: - file_path: Path to the file containing study IDs. - - Returns: - A sorted list of unique study IDs. - """ ids = set() with open(file_path) as file: for line in file: @@ -69,88 +101,165 @@ def process_study_ids(file_path: str) -> List[str]: return sorted(ids) +def get_processed_study_ids(db) -> Set[str]: + study_collection = db['studies'] + processed_ids = set() + for study in study_collection.find({}, {'studyGoldId': 1}): + if 'studyGoldId' in study: + processed_ids.add(study['studyGoldId']) + return processed_ids + + @click.command() -@click.option('--mongo-db-name', '-d', required=True, - help='Name of the local, unauthenticated MongoDB database to use.') -@click.option('--study-ids-file', '-i', - type=click.Path(exists=True, dir_okay=False, readable=True), - required=True, - help='Path to the input text file containing one GOLD study ID per line.') -@click.option('--authentication-file', '-a', default="config/gold-key.txt", - help='Path to the authentication file. Contents should be user:pass.') -@click.option('--purge-mongodb', '-p', is_flag=True, default=False, - help='Purge the destination MongoDB database before running.') -@click.option('--purge-diskcache', '-P', is_flag=True, default=False, - help='Purge the input disk cache before running.') -def main(mongo_db_name: str, study_ids_file: str, authentication_file: str, - purge_mongodb: bool, purge_diskcache: bool, **args): - """ - Fetch, process, and store biosamples, studies, and projects into MongoDB in real-time. - """ - # MongoDB setup - client = MongoClient('mongodb://localhost:27017/') - db = client[mongo_db_name] +@click.option('--authentication-file', '-a', default="config/gold-key.txt") +@click.option('--env-file', '-e') +@click.option('--log-failures-to-file', type=click.Path(writable=True), default=None) +@click.option('--max-retries', '-m', type=int, default=3) +@click.option('--mongo-uri', '-u', required=True) +@click.option('--purge-diskcache', '-P', is_flag=True, default=False) +@click.option('--purge-mongodb', '-p', is_flag=True, default=False) +@click.option('--resume', '-r', is_flag=True, default=True) +@click.option('--study-ids-file', '-i', type=click.Path(exists=True), required=True) +def main(study_ids_file: str, authentication_file: str, mongo_uri: Optional[str], + env_file: Optional[str], purge_mongodb: bool, purge_diskcache: bool, + resume: bool, max_retries: int, log_failures_to_file: Optional[str]): + mongo_creds = load_mongodb_credentials(env_file) + conn_str = build_mongodb_connection_string( + mongo_uri=mongo_uri, + user=mongo_creds.get('user'), + password=mongo_creds.get('password'), + ) + + logging.info("Connecting to MongoDB") + client = MongoClient(conn_str) + + try: + db_name = MongoClient(conn_str).get_default_database().name + db = client[db_name] + except Exception as e: + logging.error(f"Could not determine database name from URI: {e}") + return + + try: + client.admin.command('ping') + logging.info("MongoDB connection successful") + except Exception as e: + logging.error(f"MongoDB connection failed: {e}") + return if purge_mongodb: logging.info("Purging MongoDB collections...") db.drop_collection('biosamples') db.drop_collection('studies') db.drop_collection('projects') + db.drop_collection('seq_projects') + db.drop_collection('study_import_failures') + resume = False - # Setup collections and indexes biosample_collection = db['biosamples'] study_collection = db['studies'] - project_collection = db['projects'] + project_collection = db['seq_projects'] + failure_collection = db['study_import_failures'] create_unique_index(biosample_collection, "biosampleGoldId", "biosampleGoldId_index") create_unique_index(study_collection, "studyGoldId", "studyGoldId_index") create_unique_index(project_collection, "projectGoldId", "projectGoldId_index") + create_unique_index(failure_collection, "studyGoldId", "failedStudy_index") - # Initialize GoldClient gc = GoldClient() - if purge_diskcache: logging.info("Purging disk cache...") gc.clear_cache() - gc.load_key(authentication_file) - # Process study IDs study_ids = process_study_ids(study_ids_file) + total_studies = len(study_ids) - for study_id in study_ids: - logging.info(f"Processing study {study_id}...") - - # Fetch the study record - study = gc.fetch_study(study_id, **args) - - # Fetch biosamples associated with the study - biosamples = gc.fetch_biosamples_by_study(study_id, **args) - logging.info(f"Retrieved {len(biosamples)} biosamples for study {study_id}") - - # Collect biosampleGoldIds for the study - biosample_ids = [] + processed_study_ids = set() + if resume: + processed_study_ids = get_processed_study_ids(db) + if processed_study_ids: + logging.info(f"Found {len(processed_study_ids)} studies already in MongoDB that will be skipped") - for biosample in biosamples: - biosample_id = biosample.get('biosampleGoldId', None) - if biosample_id: - biosample_ids.append(biosample_id) + completed = 0 + failed = 0 + skipped = 0 + failed_study_logs = [] - # Handle associated projects - for project in biosample.pop('projects', []): - insert_document(project_collection, project, project.get('projectGoldId', 'Unknown')) - - # Insert biosample into MongoDB - insert_document(biosample_collection, biosample, biosample_id) - - # Add the biosamples list to the study record - study['biosamples'] = biosample_ids - - # Insert the study record into MongoDB - insert_document(study_collection, study, study_id) + for study_id in study_ids: + if resume and study_id in processed_study_ids: + logging.info(f"Skipping study {study_id} (already in MongoDB)") + skipped += 1 + continue + + logging.info(f"Processing study {study_id} ({completed + skipped + 1}/{total_studies})...") + + retry_count = 0 + success = False + + while retry_count <= max_retries and not success: + try: + study = gc.fetch_study(study_id) + if not study: + logging.warning(f"No data returned for study {study_id}, skipping") + failed += 1 + failure_doc = { + 'studyGoldId': study_id, + 'error': "No data returned (null response)", + 'timestamp': datetime.utcnow(), + 'failed': True + } + insert_document(failure_collection, failure_doc, study_id) + failed_study_logs.append(failure_doc) + break + + biosamples = gc.fetch_biosamples_by_study(study_id) + logging.info(f"Retrieved {len(biosamples)} biosamples for study {study_id}") + + biosample_ids = [] + for biosample in biosamples: + biosample_id = biosample.get('biosampleGoldId') + if biosample_id: + biosample_ids.append(biosample_id) + + for project in biosample.pop('projects', []): + insert_document(project_collection, project, project.get('projectGoldId', 'Unknown')) + insert_document(biosample_collection, biosample, biosample_id) + + study['biosamples'] = biosample_ids + insert_document(study_collection, study, study_id) + + completed += 1 + success = True + + except Exception as e: + retry_count += 1 + if retry_count <= max_retries: + wait_time = 5 * retry_count + logging.warning( + f"Error processing study {study_id}: {e}. Retrying in {wait_time} seconds (attempt {retry_count}/{max_retries})") + sleep(wait_time) + else: + logging.error(f"Failed to process study {study_id} after {max_retries} attempts: {e}") + failed += 1 + failure_doc = { + 'studyGoldId': study_id, + 'error': str(e), + 'timestamp': datetime.utcnow(), + 'failed': True + } + insert_document(failure_collection, failure_doc, study_id) + failed_study_logs.append(failure_doc) + + logging.info(f"Import completed: {completed} studies processed, {skipped} skipped, {failed} failed") + + if log_failures_to_file and failed_study_logs: + with open(log_failures_to_file, 'w') as f: + json.dump(failed_study_logs, f, indent=2, default=str) + logging.info(f"Wrote failed study logs to {log_failures_to_file}") - # Close the connection client.close() + logging.info("MongoDB connection closed") if __name__ == "__main__": diff --git a/sample_annotator/r2o_from_nb.py b/sample_annotator/r2o_from_nb.py deleted file mode 100644 index 539f8bc..0000000 --- a/sample_annotator/r2o_from_nb.py +++ /dev/null @@ -1,155 +0,0 @@ -from pathlib import Path - -# MAM: numpy is only being used once, for its where method. -# I bet we can replace that with .loc indexing -import numpy as np -import pandas as pd -# MAM: Using sqlalchemy probably IS a best practice, since it's flexible wrt database backends -# and encourages object orientated/relational integration, but that's not being used here yet. -# It might be a little heavyweight here. Could use native sqlite3 library instead -import sqlalchemy - -# # MAM: I don't think these are necessary -# import matplotlib.pyplot as plt -# import nltk -# import re -# import seaborn as sns -# import string - -# plt.style.use("fivethirtyeight") -# sns.set() -# sns.set_context("talk") - -# Setup - Load the SQL extension and connect to the Mini IMDB dataset we've prepared -# MAM what does IMDB stand for here? -# MAM: we should either ask the user where their database file is -# or the Makefile should contain code to download the file into and expected directory -db_path = Path("/home/mark/biosample_basex_data_good_subset.db") - -engine = sqlalchemy.create_engine(f"sqlite:///{db_path}") -connection = engine.connect() - -# MAM: what's this for? -inspector = sqlalchemy.inspect(engine) - -query_name = """ -SELECT * -FROM harmonized_wide_sel_envs -""" -harmonized_wide_sel_envs_df = pd.read_sql(query_name, engine) - -# Hardcoded rules below -# MAM: this is now the precedent: repaired columns get a _rep suffix -# and their status metadata gets a _status suffix -# We should consider putting them in a different table lin the database -# the repair rules should come form an external, shared document. they shouldn't be embedded in the code -# see biosamples-annotation-dg sample sheet -# https://docs.google.com/spreadsheets/d/1c3l487XdqFSZZ8PmptE3t3NHI4uPYoziSn3DX4A8_kA/edit#gid=0 -# and https://github.com/turbomam/pygsheets-examples -# the proper_values should come from either the MIxS Google Sheet -# https://docs.google.com/spreadsheets/d/1QDeeUcDqXes69Y2RjU2aWgOpCVWo5OVsBX9MKmMqi_o/edit?pli=1#gid=178015749&range=33:33 -# or the MIxS LinkML model (which is more up to date, nut which we haven't discussed before) -# https://github.com/GenomicsStandardsConsortium/mixs/blob/74744eea9b149b0587b58f48e3dd8d1f879820d2/model/schema/terms.yaml#L13559-L13567 - -aerobe_pattern = "^[Aa]erob(ic)*(-){0}" -anaerobe_pattern = "^(anaero)" -facultative_pattern = "^(facultative)" -microaerophilic_pattern = "microaerophilic" # microaerophilic already looks clean -microanaerobe_pattern = "microanaerobe" # None microanaerobe ? -obligate_aerobe_pattern = "obligate aerobe" # None obligate aerobe ? -obligate_anaerobe_pattern = "^obligate anaerobe" # already looks clean - -proper_values = [ - "aerobe", - "anaerobe", - "facultative", - "microaerophilic", - "microanaerobe", - "obligate aerobe", - "obligate anaerobe", -] - -harmonized_wide_sel_envs_df["rel_to_oxygen_rep"] = harmonized_wide_sel_envs_df[ - "rel_to_oxygen" -].astype(str) - -# MAM: don't test with == False -# use "if not" instead -harmonized_wide_sel_envs_df["rel_to_oxygen_rep_status"] = ( - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].isin( - proper_values) == False - ) & (harmonized_wide_sel_envs_df[ - "rel_to_oxygen_rep"] != "None") - -harmonized_wide_sel_envs_df["rel_to_oxygen_rep_status"] = harmonized_wide_sel_envs_df[ - "rel_to_oxygen_rep_status" -].replace(to_replace=False, value="Unchanged") -harmonized_wide_sel_envs_df["rel_to_oxygen_rep_status"] = harmonized_wide_sel_envs_df[ - "rel_to_oxygen_rep_status" -].replace(to_replace=True, value="Repaired") - -harmonized_wide_sel_envs_df.loc[ - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].str.contains( - aerobe_pattern, regex=True - ), - "rel_to_oxygen_rep", -] = "aerobe" - -harmonized_wide_sel_envs_df.loc[ - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].str.contains( - anaerobe_pattern, regex=True - ), - "rel_to_oxygen_rep", -] = "anaerobe" -harmonized_wide_sel_envs_df.loc[ - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].str.contains( - facultative_pattern, regex=True - ), - "rel_to_oxygen_rep", -] = "facultative" -harmonized_wide_sel_envs_df.loc[ - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].str.contains( - microaerophilic_pattern, regex=True - ), - "rel_to_oxygen_rep", -] = "microaerophilic" -harmonized_wide_sel_envs_df.loc[ - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].str.contains( - microanaerobe_pattern, regex=True - ), - "rel_to_oxygen_rep", -] = "microanaerobe" -harmonized_wide_sel_envs_df.loc[ - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].str.contains( - obligate_aerobe_pattern, regex=True - ), - "rel_to_oxygen_rep", -] = "obligate aerobe" -harmonized_wide_sel_envs_df.loc[ - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].str.contains( - obligate_anaerobe_pattern, regex=True - ), - "rel_to_oxygen_rep", -] = "obligate anaerobe" - -# note this UserWarning: -# UserWarning: This pattern is interpreted as a regular expression, and has match groups. To actually get the groups, use str.extract. -# harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].str.contains( - -# harmonized_wide_sel_envs_df.loc[~df["rel_to_oxygen_rep"].isin(proper_values), "rel_to_oxygen_rep"] = None -harmonized_wide_sel_envs_df["rel_to_oxygen_rep"] = np.where( - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"].isin(proper_values), - harmonized_wide_sel_envs_df["rel_to_oxygen_rep"], - None, -) - -harmonized_wide_sel_envs_df["air_temp"] = harmonized_wide_sel_envs_df[ - "air_temp" -].str.replace(" degree Celsius", "") -harmonized_wide_sel_envs_df["air_temp"] = ( - harmonized_wide_sel_envs_df["air_temp"] + " degree Celsius" -) - -# MAM just printing for now -# need to inject back into the SQLite database -print(harmonized_wide_sel_envs_df) diff --git a/sparql/bibo_DocumentStatus.sparql b/sparql/bibo_DocumentStatus.sparql deleted file mode 100644 index ba72bea..0000000 --- a/sparql/bibo_DocumentStatus.sparql +++ /dev/null @@ -1,8 +0,0 @@ -prefix rdfs: -prefix rdf: -prefix owl: -prefix bibo: -select distinct (str(?status_label_raw) as ?status_label) -where { ?s a bibo:DocumentStatus ; -rdfs:label ?status_label_raw } -order by ?status_label diff --git a/tests/test_capitalization.py b/tests/test_capitalization.py deleted file mode 100644 index 78f1fb7..0000000 --- a/tests/test_capitalization.py +++ /dev/null @@ -1,35 +0,0 @@ -# -*- coding: utf-8 -*- -import os -import unittest - -import yaml - -from sample_annotator import capitalizer -# MODEL_DIR, INPUT_DIR, OUTPUT_DIR -from tests import INPUT_DIR - -"""Test the ability to capitalize a text slot.""" - -"""Run as follows to get see test-time printouts:""" - -"""python -m pytest -sv tests/test_capitalization.py""" - -# INPUT_DIR comes from __init__.py -PWD = os.path.dirname(os.path.realpath(__file__)) -TEST_DATA = os.path.join(INPUT_DIR, 'test_sample_info.yaml') - - -class TestCapitalization(unittest.TestCase): - """capitalization test.""" - - def test_capitalization(self): - with open(TEST_DATA) as stream: - test_obj = yaml.load(stream, Loader=yaml.FullLoader) - for t in test_obj.get('tests'): - desc = t.get('description', None) - # pdb.set_trace() - if desc == 'capitalization test': - current_input = t['sample']['text'] - processed_input = capitalizer.capitalizer(current_input) - expected_output = t['output']['text'] - assert processed_input == expected_output