围绕开发人员生产力、公司生产力和项目生产力的机器学习、统计和实用程序
devml的Python项目详细描述
devml
围绕开发人员生产力的机器学习、统计和实用程序
一些方便的功能:
- 可以签出github中的所有存储库
- 将磁盘上已签出存储库的树转换为熊猫 数据帧
- 组合数据帧的统计信息
安装
pip install devml
这个pip安装安装了一个命令行工具:dml(它被引用 在下面的文档中)。以及引用的库devml 下面也是。
获取环境设置
编写代码是为了支持Python3.6或更高版本。你可以在这里得到: https://www.python.org/downloads/release/python-360/。
在本地运行项目的一个简单方法是签出repo并在repo的根目录中运行:
make setup
这将在~/.devml中创建一个virtualenv
下一步,获取virtualenv:
source ~/.devml/bin/activate
运行make all(安装、绒布和测试)
make all # #Example output #(.devml) ➜ devml git:(master) make all #pip install -r requirements.txt #Requirement already satisfied: pytest in /Users/noahgift/.devml/lib/python3.6/site-packages (from -r requirements.txt (line #1) ---------- coverage: platform darwin, python 3.6.2-final-0 ----------- Name Stmts Miss Cover ---------------------------------------------- devml/__init__.py 1 0 100% devml/author_stats.py 6 6 0% devml/fetch_repo.py 54 42 22% devml/mkdata.py 84 21 75% devml/org_stats.py 76 55 28% devml/post_processing.py 50 35 30% devml/state.py 29 9 69% devml/stats.py 55 43 22% devml/ts.py 29 14 52% devml/util.py 12 4 67% dml.py 111 66 41% ---------------------------------------------- TOTAL 507 295 42% ....
你不使用virtualenv或者不想使用它。没问题,快跑 make all如果安装了python 3.6,它可能会工作。
make all
在GitHub组织中浏览Jupyter笔记本
在这里,您可以使用这个示例作为开始来探索组合数据集:
https://github.com/noahgift/devml/blob/master/notebooks/github_data_exploration.ipynb
托盘项目
探索存储库流失上的jupyter笔记本
您可以在此处探索文件元数据探索示例:
https://github.com/noahgift/devml/blob/master/notebooks/repo_file_exploration.ipynb
按类型搅动的所有文件:
按文件类型排列的托盘项目相对变动
按类型列出的流失统计摘要:
按文件类型列出的托盘项目客户流失统计信息
预期配置
命令行工具希望您创建项目目录 使用config.json文件。在config.json文件中,您需要 提供誓词。你可以找到如何做到这一点的信息 在这里: https://help.github.com/articles/creating-a-personal-access-token-for-the-command-line/。
或者,可以通过python api或 命令行作为选项。它们代表以下内容:
- org:github组织(克隆整个回购树)
- 签出目录:签出地点
- 誓言:从github生成的个人誓言令牌
➜ devml git:(master) ✗ cat project/config.json { "project" : { "org":"pallets", "checkout_dir": "/tmp/checkout", "oath": "<keygenerated from Github>" } }
基本命令行用法
您可以查找签出或签出目录的统计信息 遵循
dml gstats author --path ~/src/mycompanyrepo(s) Top Commits By Author: author_name commits 0 John Smith 30591 Sally Joe 29952 Greg Mathews 21943 Jim Mayflower 1448
基本的api使用(将repo树转换为pandas数据帧)
In [1]: from devml import (mkdata, stats) In [2]: org_df = mkdata.create_org_df(path=/src/mycompanyrepo(s)") In [3]: author_counts = stats.author_commit_count(org_df) In [4]: author_counts.head() Out[4]: author_name commits 0 John Smith 3059 1 Sally Joe 2995 2 Greg Mathews 2194 3 Jim Mayflower 1448 4 Truck Pritter 1441
使用api
克隆github中的所有repoIn [1]: from devml import (mkdata, stats, state, fetch_repo) In [2]: dest, token, org = state.get_project_metadata("../project/config.json") In [3]: fetch_repo.clone_org_repos(token, org, dest, branch="master") 017-10-14 17:11:36,590 - devml - INFO - Creating Checkout Root: /tmp/checkout 2017-10-14 17:11:37,346 - devml - INFO - Found Repo # 1 REPO NAME: flask , URL: git@github.com:pallets/flask.git 2017-10-14 17:11:37,347 - devml - INFO - Found Repo # 2 REPO NAME: pallets-sphinx-themes , URL: git@github.com:pallets/pallets-sphinx-themes.git 2017-10-14 17:11:37,347 - devml - INFO - Found Repo # 3 REPO NAME: markupsafe , URL: git@github.com:pallets/markupsafe.git 2017-10-14 17:11:37,348 - devml - INFO - Found Repo # 4 REPO NAME: jinja , URL: git@github.com:pallets/jinja.git 2017-10-14 17:11:37,349 - devml - INFO - Found Repo # 5 REPO NAME: werkzeug , URL: git@githu In [4]: !ls -l /tmp/checkout total 0 drwxr-xr-x 21 noahgift wheel 672 Oct 14 17:11 click drwxr-xr-x 25 noahgift wheel 800 Oct 14 17:11 flask drwxr-xr-x 11 noahgift wheel 352 Oct 14 17:11 flask-docs drwxr-xr-x 12 noahgift wheel 384 Oct 14 17:11 flask-ext-migrate drwxr-xr-x 8 noahgift wheel 256 Oct 14 17:11 flask-snippets drwxr-xr-x 14 noahgift wheel 448 Oct 14 17:11 flask-website drwxr-xr-x 18 noahgift wheel 576 Oct 14 17:11 itsdangerous drwxr-xr-x 23 noahgift wheel 736 Oct 14 17:11 jinja drwxr-xr-x 18 noahgift wheel 576 Oct 14 17:11 markupsafe drwxr-xr-x 4 noahgift wheel 128 Oct 14 17:11 meta drwxr-xr-x 10 noahgift wheel 320 Oct 14 17:11 pallets-sphinx-themes drwxr-xr-x 9 noahgift wheel 288 Oct 14 17:11 pocoo-sphinx-themes drwxr-xr-x 15 noahgift wheel 480 Oct 14 17:11 website drwxr-xr-x 25 noahgift wheel 800 Oct 14 17:11 werkzeug
高级cli搅动:按文件类型获取搅动
获取按流失计数排序的前十个文件,扩展名为.py:
✗ dml gstats churn --path /Users/noahgift/src/flask --limit 10 --ext .py 2017-10-15 12:10:55,783 - devml.post_processing - INFO - Running churn cmd: [git log --name-only --pretty=format:] at path [/Users/noahgift/src/flask] files churn_count line_count extension \ 1 b'flask/app.py' 316 2183.0 .py 3 b'flask/helpers.py' 176 1019.0 .py 5 b'tests/flask_tests.py' 127 NaN .py 7 b'flask.py' 104 NaN .py 8 b'setup.py' 80 112.0 .py 10 b'flask/cli.py' 75 759.0 .py 11 b'flask/wrappers.py' 70 194.0 .py 12 b'flask/__init__.py' 65 49.0 .py 13 b'flask/ctx.py' 62 415.0 .py 14 b'tests/test_helpers.py' 62 888.0 .py relative_churn 1 0.14 3 0.17 5 NaN 7 NaN 8 0.71 10 0.10 11 0.36 12 1.33 13 0.15 14 0.07
获取extension.py的描述性统计信息并与另一个存储库进行比较
在这个例子中,flask、repo和cpython都被比较为 中位数的波动。
(.devml) ➜ devml git:(master) dml gstats metachurn --path /Users/noahgift/src/flask --ext .py --statistic median 2017-10-15 12:39:44,781 - devml.post_processing - INFO - Running churn cmd: [git log --name-only --pretty=format:] at path [/Users/noahgift/src/flask] MEDIAN Statistics: churn_count line_count relative_churn extension .py 2 85.0 0.13 (.devml) ➜ devml git:(master) dml gstats metachurn --path /Users/noahgift/src/devml --ext .py --statistic median 2017-10-15 12:40:10,999 - devml.post_processing - INFO - Running churn cmd: [git log --name-only --pretty=format:] at path [/Users/noahgift/src/devml] MEDIAN Statistics: churn_count line_count relative_churn extension .py 1 62.5 0.02 (.devml) ➜ devml git:(master) dml gstats metachurn --path /Users/noahgift/src/cpython --ext .py --statistic median 2017-10-15 12:42:19,260 - devml.post_processing - INFO - Running churn cmd: [git log --name-only --pretty=format:] at path [/Users/noahgift/src/cpython] MEDIAN Statistics: churn_count line_count relative_churn extension .py 7 169.5 0.1
比较cpython活动比率和linux活动比率
# Linux Development Active Ratio dml gstats activity --path /Users/noahgift/src/linux --sort active_days author_name active_days active_duration active_ratio 14541 Takashi Iwai 1677 4590 days 0.370000 4382 Eric Dumazet 1460 4504 days 0.320000 3641 David S. Miller 1428 4513 days 0.320000 7216 Johannes Berg 1329 4328 days 0.310000 8717 Linus Torvalds 1281 4565 days 0.280000 275 Al Viro 1249 4562 days 0.270000 9915 Mauro Carvalho Chehab 1227 4464 days 0.270000 9375 Mark Brown 1198 4187 days 0.290000 3172 Dan Carpenter 1158 3972 days 0.290000 12979 Russell King 1141 4602 days 0.250000 1683 Axel Lin 1040 2720 days 0.380000 400 Alex Deucher 1036 3497 days 0.300000 # CPython Development Active Ratio author_name active_days active_duration active_ratio 146 Guido van Rossum 2256 9673 days 0.230000 301 Raymond Hettinger 1361 5635 days 0.240000 128 Fred Drake 1239 5335 days 0.230000 47 Benjamin Peterson 1234 3494 days 0.350000 132 Georg Brandl 1080 4091 days 0.260000 375 Victor Stinner 980 2818 days 0.350000 235 Martin v. Löwis 958 5266 days 0.180000 36 Antoine Pitrou 883 3376 days 0.260000 362 Tim Peters 869 5060 days 0.170000 164 Jack Jansen 800 4998 days 0.160000 24 Andrew M. Kuchling 743 4632 days 0.160000 330 Serhiy Storchaka 720 1759 days 0.410000 44 Barry Warsaw 696 8485 days 0.080000 52 Brett Cannon 681 5278 days 0.130000 262 Neal Norwitz 559 2573 days 0.220000 In this analysis, Guido of Python has a 23% probability of working on a given day, and Linux has a 28% chance.
删除统计
从存储库中查找所有删除文件
dml gstats deleted --path /Users/noahgift/src/flask DELETION STATISTICS files ext 0 b'tests/test_deprecations.py' .py 1 b'scripts/flask-07-upgrade.py' .py 2 b'flask/ext/__init__.py' .py 3 b'flask/exthook.py' .py 4 b'scripts/flaskext_compat.py' .py 5 b'tests/test_ext.py' .py
常见问题
什么是搅动,我为什么在乎?
代码搅动是文件被修改的次数。相对的 搅动是相对于 代码。对软件缺陷的研究表明,相关代码 客户流失对缺陷的预测能力很强,即相对的 搅动数越高的缺陷数量。
“相对代码流失量的增加伴随着 系统内缺陷密度;“
你可以在这里阅读整个研究: https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/icse05churn.pdf