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taylorbrazelton.com | ||
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vickiboykis.com
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| | | | | When I'm working with Jupyter notebooks, I often want to work with them from within a virtual environment. The general best practice is that you should always use either virtual environments or Docker containers for working with Python, for reasons outlined in this post, or you're gonna have a bad time. I know I have. The workflow is a little long, so I thought I'd document it for future me here. | |
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janakiev.com
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| | | | | Python's built-in venv module makes it easy to create virtual environments for your Python projects. Virtual environments are isolated spaces where your Python packages and their dependencies live. This means that each project can have its own dependencies, regardless of what other projects are doing. | |
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liquidat.wordpress.com
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| | | | | Nushell is becoming a more and more serious shell every day. One thing missing in the past was the capability to create and use Python virtual environments. This has changed: Nushell was added as another supported shell in the virtualenv package: ??(20:39:55) ~/development? virtualenv ansiblecreated virtual environment CPython3.11.5.final.0-64 in 190mscreator CPython3Posix(dest=/home/liquidat/development/ansible, clear=False, no_vcs_ignore=False, global=False)seeder FromAppData(extra_search_dir=/usr/shar... | |
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enix.io
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| | | This serie of articles deals with solutions for Docker image size optimization. In this first part, we talk about *multi-stage build*. We also explain differences between static and dynamic libraries and why it matters. We also describe the use of the famous Alpine Linux distribution. | ||
