141–150 of 160 posts
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There are I'm sure valid reasons for doing it, but it fragments an already fragmented ecosystem. And IMHO it is ideal for there to be a first-party solution like Ruby/Bundler, Rust/Cargo, Swift/SPM, etc.
Isn't the first party solution NPM?
Yarn 3.0 was released in July 2021 ( https://dev.to/arcanis/yarn-3-0-performances-esbuild-better-... ) Meanwhile, as much as I respect the work of Mael (yarn maintainer) I’ve switched back to npm. Mostly because: - isaacs (original creator of npm) did some commits lately - now backed by GitHub - they introduced workspaces (monorepo support) in npm 7 - it’s still easier to use the standard tooling in dev/ci/prod - lik…
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I think this is a bit much. Pip takes almost no time to set up and use. It ships with MacOS in fact.
As long as you only have pure python dependencies, pip is fine. Unfortunately, that's very uncommon for DS/ML python at least.
pip install pandas
??
Also checking out branches and syncing takes all of 3s versus the massive link process we used to have to do.
Love yarnv2
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IMO, npm is a breeze compared to pip. With npm you know that `npm i && npm start` will start 95% of the projects cross-platform. It allows having different subdependencies versions in a way that just works. It encourages semver but at the same time you have lock file. Is highly customizable with rc files. Perhaps I just don't have that much experience with pip, but it feels more like a tool to install packages, then…
npm is one of the only dependency managers I’ve seen that does more than install packages. Every other package manager: pip, bundler, composer, all do one thing and do it well. npm does everything but nothing well.
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As long as you only have pure python dependencies, pip is fine. Unfortunately, that's very uncommon for DS/ML python at least.
pip install numpy pip install pandas ??
The trouble is firstly that pip will happily install conflicting versions of numpy which breaks your code.
This occurs because pip didn't check dependencies until last year, which is one of the reasons it's a terrible package manager.
Now it just gets stuck spinning it's wheels for ages and then errors out, which is better but still not good.
Conda, while really slow actually handles c level dependencies which makes it usable.
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npm is one of the only dependency managers I’ve seen that does more than install packages. Every other package manager: pip, bundler, composer, all do one thing and do it well. npm does everything but nothing well.
Wow, bold statement. Can you give examples of things it does wrong?
Experienced developers they are not.
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I can. In most ecosystems, I can share package sources between a VM and a host. npm shares mutable content (eg compiled artifacts) with package sources in `node_modules`. That breaks a ton of workflows that are common in other ecosystems. For instance, in ruby apps using bundler, I can commit my dependencies in vendor/cache; there are no network dependencies other than fetching the source code. That makes turning cod…
There's nothing stopping you from running `npm` or `yarn` offline and committing the cache. In fact, both of these package managers have had direct support for this workflow since 2016 ( https://docs.npmjs.com/cli/v7/using-npm/config#offline ) and 2017 ( https://classic.yarnpkg.com/blog/2016/11/24/offline-mirror/ ) respectively.
Yarn 3.0 was released in July 2021 ( https://dev.to/arcanis/yarn-3-0-performances-esbuild-better-... ) Meanwhile, as much as I respect the work of Mael (yarn maintainer) I’ve switched back to npm. Mostly because: - isaacs (original creator of npm) did some commits lately - now backed by GitHub - they introduced workspaces (monorepo support) in npm 7 - it’s still easier to use the standard tooling in dev/ci/prod - lik…
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pip install numpy pip install pandas ??
I'm really really tired of explaining this, tbh. The trouble is firstly that pip will happily install conflicting versions of numpy which breaks your code. This occurs because pip didn't check dependencies until last year, which is one of the reasons it's a terrible package manager. Now it just gets stuck spinning it's wheels for ages and then errors out, which is better but still not good. Conda, while really slow a…
So don't!