pypyr automation task runner
coveragepy
pypyr automation task runner | coveragepy | |
---|---|---|
6 | 7 | |
571 | 2,831 | |
0.4% | - | |
5.9 | 9.6 | |
5 months ago | 5 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pypyr automation task runner
- Simple task runner for automation pipelines
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This Week in Python
pypyr – automation task runner
- Task-runner for automation pipelines defined in YAML – pypyr
- Just learned implementing decorators
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Comparison of Python TOML parser libraries
The pypyr automation pipeline task-runner open-source project recently added TOML parsing & writing functionality as a core feature. To this end, I researched the available free & open-source Python TOML parser libraries to figure out which option to use.
coveragepy
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An Introduction to Testing with Django for Python
Coverage.py is the go-to tool for measuring code coverage of Python programs. Once installed, you can use it with either unittest or pytest.
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The Uncreative Software Engineer's Compendium to Testing
Code Coverage Analysis assess the code portions tested by the current test suites without altering the code.
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Slipcover: Near Zero-Overhead Python Code Coverage
The PLASMA lab @ UMass Amherst (home of the Scalene profiler) has released a new version of Slipcover, a super fast code coverage tool for Python. It is by far the fastest code coverage tool: in our tests, its average slowdown is just 5% (compare to the widely used coverage.py, average slowdown 218%!). The latest release performs both line and branch coverage with virtually no overhead. Use it to dramatically speed up your tests and continuous integration!
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Unit Tests - what’s the point?
Tests ensure the tested behavior is maintained. It's up to the developers to write tests with sufficient coverage. Determining which lines of code on your project are covered by tests is easily quantifiable using tooling. E.g. https://coverage.readthedocs.io/
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How to make Django package smaller for Serverless deployment
Taking the idea further, if you build robust tests for your API, you could use a dynamic code analyzer like coverage or figleaf to identify and delete unused functions.
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Comparison of Python TOML parser libraries
coverage
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New Ways to Be Told That Your Python Code Is Bad
FWIW, ternary expressions aren't properly detected by coverage: https://github.com/nedbat/coveragepy/issues/509
What are some alternatives?
Ansible - Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to cloud management, in a language that approaches plain English, using SSH, with no agents to install on remote systems. https://docs.ansible.com.
global-chem - A Knowledge Graph of Common Chemical Names to their Molecular Definition
psutil - Cross-platform lib for process and system monitoring in Python
slipcover - Near Zero-Overhead Python Code Coverage
Fabric - Simple, Pythonic remote execution and deployment.
Zappa - Serverless Python
letsencrypt - Certbot is EFF's tool to obtain certs from Let's Encrypt and (optionally) auto-enable HTTPS on your server. It can also act as a client for any other CA that uses the ACME protocol.
pytomlpp - A python wrapper for tomlplusplus
SaltStack - Software to automate the management and configuration of any infrastructure or application at scale. Get access to the Salt software package repository here:
flit - Simplified packaging of Python modules
honcho - Honcho: a python clone of Foreman. For managing Procfile-based applications.
toml - Python lib for TOML