feat : use --no-cache-dir flag to pip in dockerfiles to save space #2357
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Thanks, the develop and travis images are meant for interactive testing and development though, so caching might be useful for those? |
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Are we deleting temporary apt files yet? |
looks like, till now we are not doing. I will raise a separate PR for that. |
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Caching will generally be helpful for all images in terms of reducing size. I added the fix to all files to keep things uniform across files. |
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I was talking about the purpose of the docker images. instead of just using pwntools to run exploits, they are meant to develop pwntools itself which includes touching the dependencies and possibly reinstalling pwntools too. So I thought it would be useful to keep pip's cache enabled for those images. Do you think otherwise? |
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using the "--no-cache-dir" flag in pip install, make sure downloaded packages by pip don't cache on the system. This is a best practice that makes sure to fetch from a repo instead of using a local cached one. Further, in the case of Docker Containers, by restricting caching, we can reduce image size. In terms of stats, it depends upon the number of python packages multiplied by their respective size. e.g for heavy packages with a lot of dependencies it reduces a lot by don't cache pip packages. Further, more detailed information can be found at https://medium.com/sciforce/strategies-of-docker-images-optimization-2ca9cc5719b6 Signed-off-by: Pratik Raj <[email protected]>
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It makes sense, but we don't touch dependencies very often, so in most cases keeping the cache small will helped in terms of space, although I reverted for dev image. |
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This saved about 40mb 👍 |
using the "--no-cache-dir" flag in pip install, make sure downloaded packages by pip don't cache on the system. This is a best practice that makes sure to fetch from a repo instead of using a local cached one. Further, in the case of Docker Containers, by restricting caching, we can reduce image size. In terms of stats, it depends upon the number of python packages multiplied by their respective size. e.g for heavy packages with a lot of dependencies it reduces a lot by don't cache pip packages.
Further, more detailed information can be found at
https://medium.com/sciforce/strategies-of-docker-images-optimization-2ca9cc5719b6
Signed-off-by: Pratik Raj [email protected]