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add some basic benchmarks
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arashbm committed Nov 3, 2024
1 parent 38745dd commit f672c34
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1 change: 1 addition & 0 deletions .gitignore
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.cache
compile_commands.json
.asv
184 changes: 184 additions & 0 deletions asv.conf.json
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{
// The version of the config file format. Do not change, unless
// you know what you are doing.
"version": 1,

// The name of the project being benchmarked
"project": "reticula",

// The project's homepage
"project_url": "https://reticula.network/",

// The URL or local path of the source code repository for the
// project being benchmarked
"repo": ".",

// The Python project's subdirectory in your repo. If missing or
// the empty string, the project is assumed to be located at the root
// of the repository.
// "repo_subdir": "",

// Customizable commands for building the project.
// See asv.conf.json documentation.
// To build the package using pyproject.toml (PEP518), uncomment the following lines
"build_command": [
"python -m pip wheel -v -w {build_cache_dir} {build_dir}"
],

// Customizable commands for installing and uninstalling the project.
// See asv.conf.json documentation.
// "install_command": ["in-dir={env_dir} python -mpip install {wheel_file}"],
// "uninstall_command": ["return-code=any python -mpip uninstall -y {project}"],

"branches": ["main"], // for git

// The DVCS being used. If not set, it will be automatically
// determined from "repo" by looking at the protocol in the URL
// (if remote), or by looking for special directories, such as
// ".git" (if local).
// "dvcs": "git",

// The tool to use to create environments. May be "conda",
// "virtualenv", "mamba" (above 3.8)
// or other value depending on the plugins in use.
// If missing or the empty string, the tool will be automatically
// determined by looking for tools on the PATH environment
// variable.
"environment_type": "virtualenv",

// timeout in seconds for installing any dependencies in environment
// defaults to 10 min
//"install_timeout": 600,

// the base URL to show a commit for the project.
"show_commit_url": "http://github.com/reticula-network/reticula-python/commit/",

// The Pythons you'd like to test against. If not provided, defaults
// to the current version of Python used to run `asv`.
// "pythons": ["3.8", "3.12"],

// The list of conda channel names to be searched for benchmark
// dependency packages in the specified order
// "conda_channels": ["conda-forge", "defaults"],

// A conda environment file that is used for environment creation.
// "conda_environment_file": "environment.yml",

// The matrix of dependencies to test. Each key of the "req"
// requirements dictionary is the name of a package (in PyPI) and
// the values are version numbers. An empty list or empty string
// indicates to just test against the default (latest)
// version. null indicates that the package is to not be
// installed. If the package to be tested is only available from
// PyPi, and the 'environment_type' is conda, then you can preface
// the package name by 'pip+', and the package will be installed
// via pip (with all the conda available packages installed first,
// followed by the pip installed packages).
//
// The ``@env`` and ``@env_nobuild`` keys contain the matrix of
// environment variables to pass to build and benchmark commands.
// An environment will be created for every combination of the
// cartesian product of the "@env" variables in this matrix.
// Variables in "@env_nobuild" will be passed to every environment
// during the benchmark phase, but will not trigger creation of
// new environments. A value of ``null`` means that the variable
// will not be set for the current combination.
//
// "matrix": {
// "req": {
// "numpy": ["1.6", "1.7"],
// "six": ["", null], // test with and without six installed
// "pip+emcee": [""] // emcee is only available for install with pip.
// },
// "env": {"ENV_VAR_1": ["val1", "val2"]},
// "env_nobuild": {"ENV_VAR_2": ["val3", null]},
// },

// Combinations of libraries/python versions can be excluded/included
// from the set to test. Each entry is a dictionary containing additional
// key-value pairs to include/exclude.
//
// An exclude entry excludes entries where all values match. The
// values are regexps that should match the whole string.
//
// An include entry adds an environment. Only the packages listed
// are installed. The 'python' key is required. The exclude rules
// do not apply to includes.
//
// In addition to package names, the following keys are available:
//
// - python
// Python version, as in the *pythons* variable above.
// - environment_type
// Environment type, as above.
// - sys_platform
// Platform, as in sys.platform. Possible values for the common
// cases: 'linux2', 'win32', 'cygwin', 'darwin'.
// - req
// Required packages
// - env
// Environment variables
// - env_nobuild
// Non-build environment variables
//
// "exclude": [
// {"python": "3.2", "sys_platform": "win32"}, // skip py3.2 on windows
// {"environment_type": "conda", "req": {"six": null}}, // don't run without six on conda
// {"env": {"ENV_VAR_1": "val2"}}, // skip val2 for ENV_VAR_1
// ],
//
// "include": [
// // additional env for python3.12
// {"python": "3.12", "req": {"numpy": "1.26"}, "env_nobuild": {"FOO": "123"}},
// // additional env if run on windows+conda
// {"platform": "win32", "environment_type": "conda", "python": "3.12", "req": {"libpython": ""}},
// ],

// The directory (relative to the current directory) that benchmarks are
// stored in. If not provided, defaults to "benchmarks"
// "benchmark_dir": "benchmarks",

// The directory (relative to the current directory) to cache the Python
// environments in. If not provided, defaults to "env"
"env_dir": ".asv/env",

// The directory (relative to the current directory) that raw benchmark
// results are stored in. If not provided, defaults to "results".
"results_dir": ".asv/results",

// The directory (relative to the current directory) that the html tree
// should be written to. If not provided, defaults to "html".
"html_dir": ".asv/html",

// The number of characters to retain in the commit hashes.
// "hash_length": 8,

// `asv` will cache results of the recent builds in each
// environment, making them faster to install next time. This is
// the number of builds to keep, per environment.
// "build_cache_size": 2,

// The commits after which the regression search in `asv publish`
// should start looking for regressions. Dictionary whose keys are
// regexps matching to benchmark names, and values corresponding to
// the commit (exclusive) after which to start looking for
// regressions. The default is to start from the first commit
// with results. If the commit is `null`, regression detection is
// skipped for the matching benchmark.
//
// "regressions_first_commits": {
// "some_benchmark": "352cdf", // Consider regressions only after this commit
// "another_benchmark": null, // Skip regression detection altogether
// },

// The thresholds for relative change in results, after which `asv
// publish` starts reporting regressions. Dictionary of the same
// form as in ``regressions_first_commits``, with values
// indicating the thresholds. If multiple entries match, the
// maximum is taken. If no entry matches, the default is 5%.
//
// "regressions_thresholds": {
// "some_benchmark": 0.01, // Threshold of 1%
// "another_benchmark": 0.5, // Threshold of 50%
// },
}
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1 change: 1 addition & 0 deletions benchmarks/ba_sequence.json

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9 changes: 9 additions & 0 deletions benchmarks/module.py
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class ModuleImport:
"""
Benchmark total import time.
"""

def timeraw_import_reticula(self):
return """
import reticula
"""
123 changes: 123 additions & 0 deletions benchmarks/static.py
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import reticula as ret

import random
import json
import pathlib


class Construction:
"""
Benchmarking the construction and basic operation of static graphs.
"""

def setup(self):
self.n = 2**16
k = 32
self.g = ret.regular_ring_lattice[ret.int64](size=self.n, degree=k)
self.verts = list(self.g.vertices())

self.edges = list(self.g.edges())
self.tuples = []
for e in self.edges:
verts = e.incident_verts()
self.tuples.append((verts[0], verts[-1]))

rand = random.Random(42)

self.shuffled_edges = rand.sample(self.edges, k=len(self.edges))
self.shuffled_tuples = []
for e in self.shuffled_edges:
verts = e.incident_verts()
if rand.random() > 0.5:
self.shuffled_tuples.append((verts[0], verts[-1]))
else:
self.shuffled_tuples.append((verts[-1], verts[0]))

def time_copy_construction(self):
ret.undirected_network[ret.int64](self.g)

def time_tuple_construction(self):
ret.undirected_network[ret.int64](
verts=self.verts, edges=self.tuples)

def time_shuffled_tuple_construction(self):
ret.undirected_network[ret.int64](
verts=self.verts, edges=self.shuffled_tuples)

def time_edge_obj_construction(self):
ret.undirected_network[ret.int64](
verts=self.verts, edges=self.edges)

def time_shuffled_edge_obj_construction(self):
ret.undirected_network[ret.int64](
verts=self.verts, edges=self.shuffled_edges)


class Graphicallity:
def setup(self):
base_path = pathlib.Path(__file__).parent
with open(base_path / "ba_sequence.json") as f:
self.ba_sequence = json.load(f)

def time_is_graphic(self):
ret.is_graphic(self.ba_sequence)


class Algorithms:
def setup(self):
self.n = 2**16
k = 32
self.g = ret.regular_ring_lattice[ret.int64](size=self.n, degree=k)
self.g_isolated = ret.undirected_network[ret.int64](
edges=[], verts=range(self.n))

def time_degree(self):
ret.degree(self.g, 12)

def time_degree_sequence(self):
ret.degree_sequence(self.g)

def time_density(self):
ret.density(self.g)

def time_assortativity(self):
ret.degree_assortativity(self.g)

def time_attribute_assortativity_lambda(self):
ret.attribute_assortativity(self.g, lambda x: x)

def time_connected_component(self):
ret.connected_component(self.g, 12)

def time_connected_component_isolated(self):
ret.connected_component(self.g_isolated, 12)

def time_connected_components(self):
ret.connected_components(self.g)

def time_connected_components_isolated(self):
ret.connected_components(self.g_isolated)

def time_is_connected(self):
ret.is_connected(self.g)

def time_is_connected_isolated(self):
ret.is_connected(self.g_isolated)

def time_largest_connected_component(self):
ret.largest_connected_component(self.g)

def time_largest_connected_component_isolated(self):
ret.largest_connected_component(self.g_isolated)

def time_is_reachable(self):
ret.is_reachable(self.g, 0, self.n//2)

def time_is_reachable_isolated(self):
ret.is_reachable(self.g_isolated, 0, self.n//2)

def time_shortest_path_lengths_from(self):
ret.shortest_path_lengths_from(self.g, 0)

def time_shortest_path_lengths_to(self):
ret.shortest_path_lengths_to(self.g, 0)
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