Sometimes you’ll get a segmentation fault in Python and your process will crash, this is due to a C module attempting to access memory beyond reach. How to debug a “Segmentation fault” in Python This entry was posted in Development and tagged ci, gitlab, gitlab-ci, python, tox, travis-ci on by richard. A small price to pay to free your project from Github ) The only downside with this is the extra time it takes to install pyenv and the interpreter of choice. apt-get install -y make build-essential libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm libncurses5-dev libncursesw5-dev xz-utils tk-dev You can achieve something similar with Gitlab CI through the following. With Travis-CI you can setup a CI build to run against multiple Python versions fairly easily. How to migrate from multi-version Python Travis-CI builds to Gitlab CI This entry was posted in Uncategorized and tagged environment, ide setup, python, software-development on Novemby richard. I hope this is useful to someone, if you have any suggested improvements please comment below, or Tweet me! That’s it, it’s quite boring but has stood the test of time. To save a huge amount of time while doing TDD I use this tool avoid switching around my development environment. It’s the industry standard right now and much better than the alternatives (nose, unittest). I use pytest for all Python unit and integration tests. I use Fish for its intelligent tab completion. I use the built-in terminal emulator within VSCode, along with Fish shell. “ Settings Sync” this keeps your editor config in the ‘cloud’ meaning you can log in to any computer and sync that VSCode installation and you’re good to go in seconds.One, in particular, makes this choice a no brainer. I use VSCode, because it’s fast and easy to use from day one. This takes the pain out of releasing packages, automating the version number bumping, HISTORY updates, tagging etc. I use requirements-dev.txt to hold development/test packages. New tools have waded-in in recent years, but pip works for me and is still the most widely used tool.Īlong with pip, I use requirements.txt (with fixed versions if it’s an application repo, supported version ranges if it’s a package/shared library project). Installing Packages & managing their versions If you need this functionality and you’re not using pyenv, you’re missing out. I consider this the best as I can install and switch between any Python version (including conda) I like with ease. But here’s what I’ve settled on after working with Python constantly since 2012.
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