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42 changes: 42 additions & 0 deletions asv_bench/README.md
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Benchmarks
==========

pvlib includes a small number of performance benchmarking tests. These
tests are run using
[airspeed velocity](https://asv.readthedocs.io/en/stable/) (ASV).

The basic structure of the tests and how to run them is described below.
We refer readers to the ASV documentation for more details.

The test configuration is described in
[``asv.conf.json``](asv.conf.json).

The performance tests are located in the [benchmarks](benchmarks) directory.

First, from this directory, run the tests:

```
asv run
```

Note that, unlike pytest, the asv tests require changes to be committed
to git before they can be tested. The ``run`` command takes a positional
argument to describe the range of git commits or branches to be tested.
For example, if your feature branch is named ``feature``, a useful asv
run may be:

```
asv run master..feature
```

Next, publish the test results to the archive:

```
asv publish
```

Finally, start a http server to view the test results:

```
asv preview
```
147 changes: 147 additions & 0 deletions asv_bench/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": "pvlib python",

// The project's homepage
"project_url": "https://github.com/pvlib/pvlib-python",

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

// List of branches to benchmark. If not provided, defaults to "master"
// (for git) or "default" (for mercurial).
// "branches": ["master"], // for git
// "branches": ["default"], // for mercurial

// 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" 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": "conda",

// 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/pvlib/pvlib-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": ["2.7", "3.7"],

// The matrix of dependencies to test. Each key 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).
//
// "matrix": {
// "numpy": ["1.6", "1.7"],
// "six": ["", null], // test with and without six installed
// "pip+emcee": [""], // emcee is only available for install with pip.
// },
"matrix": {
"numpy": [""],
"pandas": [""],
"bottleneck": [""],
"numexpr": [""]
},

// 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'.
//
// "exclude": [
// {"python": "3.2", "sys_platform": "win32"}, // skip py3.2 on windows
// {"environment_type": "conda", "six": null}, // don't run without six on conda
// ],
//
// "include": [
// // additional env for python2.7
// {"python": "2.7", "numpy": "1.8"},
// // additional env if run on windows+conda
// {"platform": "win32", "environment_type": "conda", "python": "2.7", "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 wheels of the recent builds in each
// environment, making them faster to install next time. This is
// number of builds to keep, per environment.
// "wheel_cache_size": 0

// 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%
// }
}
1 change: 1 addition & 0 deletions asv_bench/benchmarks/__init__.py
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20 changes: 20 additions & 0 deletions asv_bench/benchmarks/location.py
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# Write the benchmarking functions here.
# See "Writing benchmarks" in the asv docs for more information.

import pandas as pd
import pvlib

class TimeSuite:
"""
An example benchmark that times the performance of various kinds
of iterating over dictionaries in Python.
"""
def setup(self):
self.location = pvlib.location.Location(32, -110, altitude=700)
self.times = pd.DatetimeIndex(start='20180601', freq='3min',
periods=1440)
self.solar_position = self.location.get_solarposition(self.times)

# GH 502
def time_location_get_airmass(self):
self.location.get_airmass(solar_position=self.solar_position)
23 changes: 23 additions & 0 deletions asv_bench/benchmarks/solarposition.py
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# Write the benchmarking functions here.
# See "Writing benchmarks" in the asv docs for more information.

import pandas as pd
import pvlib

class TimeSuite:
"""
An example benchmark that times the performance of various kinds
of iterating over dictionaries in Python.
"""
def setup(self):
self.times = pd.DatetimeIndex(start='20180601', freq='1min',
periods=14400)
self.times_localized = self.times.tz_localize('Etc/GMT+7')

# GH 512
def time_ephemeris(self):
pvlib.solarposition.ephemeris(self.times, 35.1, -106.6)

# GH 512
def time_ephemeris_localized(self):
pvlib.solarposition.ephemeris(self.times_localized, 35.1, -106.6)
11 changes: 11 additions & 0 deletions docs/sphinx/source/contributing.rst
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Expand Up @@ -404,6 +404,17 @@ PVSystem method is called through ``ModelChain.run_model``.
assert isinstance(mc.dc, (pd.Series, pd.DataFrame))


Benchmarking
~~~~~~~~~~~~

pvlib includes a small number of performance benchmarking tests. These
tests are run using the `airspeed velocity
<https://asv.readthedocs.io/en/stable/>`_ tool. We do not require new
performance tests for most contributions at this time. Pull request
reviewers will provide further information if a performance test is
necessary.


This documentation
~~~~~~~~~~~~~~~~~~

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2 changes: 2 additions & 0 deletions docs/sphinx/source/whatsnew/v0.6.0.rst
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Expand Up @@ -100,6 +100,8 @@ Testing
* Use pytest-mock to ensure that ModelChain DC model is set up correctly.
* Add Python 3.7 to build matrix
* Make test_forecast.py more robust. (:issue:`293`)
* Add airspeed velocity performance testing configuration and a few tests.
(:issue:`419`)


Contributors
Expand Down