Add the 'bm_btree' benchmark.

Author: nascheme

doc/benchmarks.rst

@@ -76,6 +76,22 @@ These benchmarks also have an "eager" flavor that uses asyncio eager task factor
 if available.
 
 
+btree
+-----
+
+Benchmark a pure-Python implementation of a B-tree data structure.  The tree
+is created with a relatively large number of nodes (default is 200,000).  This
+attempts to simulate an application that operates on a large number of objects
+in memory (at least, large compared to other benchmarks currently in this
+suite). There are two variations of this benchmark: `btree` records the time to
+create the B-tree, run `gc.collect()` and then do some operations on it; the
+`btree_gc_only` variant records only the time to run `gc.collect()` and it
+skips the operations after creation.
+
+Note that this benchmark does not create any reference cycles that the garbage
+collector will need to break to free memory.
+
+
 chameleon
 ---------
 

pyperformance/data-files/benchmarks/MANIFEST

@@ -25,6 +25,8 @@ asyncio_tcp	<local>
 asyncio_tcp_ssl	<local:asyncio_tcp>
 asyncio_websockets	<local>
 bpe_tokeniser	<local>
+btree	<local>
+btree_gc_only	<local:btree>
 concurrent_imap	<local>
 coroutines	<local>
 coverage	<local>

pyperformance/data-files/benchmarks/bm_btree/bm_btree.toml

@@ -0,0 +1,3 @@
+[tool.pyperformance]
+name = "btree_gc"
+extra_opts = ["all"]

pyperformance/data-files/benchmarks/bm_btree/bm_btree_gc_only.toml

@@ -0,0 +1,3 @@
+[tool.pyperformance]
+name = "btree_gc"
+extra_opts = ["--gc-only"]

pyperformance/data-files/benchmarks/bm_btree/pyproject.toml

@@ -0,0 +1,9 @@
+[project]
+name = "pyperformance_bm_btree"
+requires-python = ">=3.8"
+dependencies = ["pyperf"]
+urls = {repository = "https://github.com/python/pyperformance"}
+dynamic = ["version"]
+
+[tool.pyperformance]
+name = "btree"