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  1. Jun 1, 2013 · Execution of a python script would cause the byte code to be generated in memory and kept until the program is shutdown. In case a module is imported, for faster reusability, Python would create a cache .pyc (PYC is 'Python' 'Compiled') file where the byte code of the module being imported is cached.

  2. Jan 3, 2016 · On linux, it is in ~/.cache/pip/http. Files there do not appear to be listed when you do pip cache list. If you ask pip to install comm==0.1.3, it will look in the regular cache and when the network request is made, it will look in the network cache under a hashed key.

  3. Apr 26, 2024 · Bytecode vs Machine Code Show/Hide. Python uses local __pycache__ folders to store the compiled bytecode of imported modules in your project. On subsequent runs, the interpreter will try to load precompiled versions of modules from these folders, provided they’re up-to-date with the corresponding source files.

  4. Jun 19, 2023 · If you're worried about the __pycache__ folder cluttering up your project directory, you can use a simple command to delete all __pycache__ folders recursively. Here's how you can do it: find . -type d -name __pycache__ -exec rm -r {} \+. This command will find all directories named __pycache__ in the current directory and its subdirectories ...

  5. May 13, 2024 · You can instruct Python to store all .pyc files in a centralized cache directory by using the -X pycache_prefix option followed by the path to the desired cache directory. For example: For example:

  6. Disabling caching ¶. pip’s caching behaviour is disabled by passing the --no-cache-dir option. It is, however, recommended to NOT disable pip’s caching unless you have caching at a higher level (eg: layered caches in container builds). Doing so can significantly slow down pip (due to repeated operations and package builds) and result in ...

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  8. Aug 29, 2024 · Python cache recap. Python offers several effective caching mechanisms to help you speed up your code: Create simple caches using Python dictionaries, allowing for O(1) time access to cached values. Use the cachetools module, which includes variants of the Python Standard Library's @lru_cache function decorator, such as LFUCache, TTLCache, and ...

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