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Option to cache requests #83

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fgenoese
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This is a proposal to have the option to cache the response of requests using the library "requests_cache".

The way it is implemented is:

  • additional parameter named 'cache_expire_after' when creating a client (measured in seconds)
  • library will automatically store request in a file named entsoe-py_cache.sqlite
  • library will automatically remove expired responses; a check is done

code example:

from entsoe import EntsoeRawClient
client = EntsoeRawClient(api_key=<YOUR API KEY>, cache_expire_after=3600) ##seconds
start = pd.Timestamp('20171201', tz='Europe/Brussels')
end = pd.Timestamp('20180101', tz='Europe/Brussels')
country_code = 'BE'  # Belgium
client.query_load(country_code, start, end)

This is for discussion, let me know what you think.

@JrtPec
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JrtPec commented Nov 19, 2020

What if we just use functools' lru_cache?

just put something like @functools.lru_cache(maxsize=128, typed=False) above the base request call? See https://docs.python.org/3/library/functools.html#functools.lru_cache

@pee-po
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pee-po commented Feb 5, 2024

I know this is old but I'll weigh in. It's a cool idea but changing things globally would be a burden for users. The package already allows for dependency injection and it would be better for the users to configure persistently cached session (from the same package that @fgenoese proposed).

However what can be done is some sensible cache filter. Also - caching is a good idea for automated tests.

@pee-po pee-po mentioned this pull request Feb 5, 2024
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@fleimgruber
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Another strategy is implementing caching in user code using e.g. https://pypi.org/project/diskcache. The library has a small API surface and can be used in slim functions wrapping the entsoe-py API. We use it for caching the pandas DataFrames as returned from EntsoePandasClient and the experience is good so far.

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@fgenoese @JrtPec @pee-po @fleimgruber