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paweldu.dev | ||
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notes.ghinda.com
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| | | | | I've been using git worktree for at least five years now. Here's how I set things up at work. Say I work on `short_ruby` project. I create a folder called `short_ruby` and inside I have: `short_ruby/main` -> which will always remain as head main `short_ruby/pairing` is where I pull branches for code reviews, dig deeper into changes, or show draft code to a colleague. `short_ruby/feature_` is a new worktree I create for each feature I work on, and I remove it when I'm done. Why these folders: 1. I always keep a local copy of the current main branch. This helps me review changes or start something new, since I can quickly check how production works if main is what's deployed. 2. I also want to quickly access any branch I'm reviewing, while still being able to ... | |
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willj.net
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| | | | | 99 bottles of beer codegolf | |
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tomk32.de
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| | | | | As it happens I tend to try out indexes on the production or staging MongoDB first before adding them to the codebase. While this might not be the proper way, it's the production db that has all that precious data that we work on and thus is the one that will be slow if we don't add the correct indexes. | |
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simpleprogrammer.com
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| | | If you're looking to learn Python - know that you've picked a worthwhile goal. Here's why: Which brings us to the question of how long you'll actually have to spend to become competent in Python programming. Different levels of skill with Python will take you relatively less or more time to achieve. In this article, [...] | ||
