Docs: clarify picklable requirement for st.cache_resource #1398
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…picklable requirement for st.cache_resource Clarifies that `st.cache_resource` requires pickle-able objects in addition to being hashable, aligning the documentation with current caching behavior and addressing confusion reported in streamlit/streamlit#13480.
| **hashable**. Objects that contain non-pickleable elements (such as functions) | ||
| may raise errors like `TypeError: cannot pickle 'function' object`. | ||
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This seems OK to me, it might be good to go into a bit more detail on the reason for the implementation. For example,
Streamlit's rerun model requires content-based hashing which is provided by python's
__reduce__()method which means that objects must not only be hashable but also pickle-able. Objects that contain non-pickleable elements (such as functions) may raise errors likeTypeError: cannot pickle 'function' object.
I am wondering whether we should change the actual error. Do you have any suggestions @sfc-gh-dmatthews
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I might go with a little less detail in this case. I updated the docstrings for both st.cache_data and st.cache_resource:
A function's arguments must be hashable to cache it. Streamlit makes a best effort to hash a variety of objects, but the fallback hashing method requires that the argument be pickleable, also. If you have an unhashable argument (like a database connection) or an argument you want to exclude from caching, use an underscore prefix in the argument name. In this case, Streamlit will return a cached value when all other arguments match a previous function call. Alternatively, you can declare custom hashing functions with hash_funcs.
@sfc-gh-lwilby From your discussions, it sounds like it's only the fallback method that requires the object to be pickable, so I went with that as the point to highlight. "We hash most things just fine, but if that fails, the object must be pickleable." It didn't sound like pickable was actually a requirement...until everything else failed. If I've understood correctly, I would specifically catch that error when __reduce__ is used to say that the object is being hashed by a fallback method that requires the item be pickleable. I see that hashing.py has a lot of TODO items around creating more, specific warnings, so I can chat with you to figure something out.
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@sfc-gh-lwilby Thanks for the suggestion! That makes sense. |
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Docs: clarify picklable requirement for st.cache_resource Clarifies that st.cache_resource requires pickle-able objects in addition to 📚 Context This change clarifies a documented requirement mismatch discussed in #1399, 🧠 Description of ChangesAdded a documentation note explaining that st.cache_resource requires This helps prevent confusion around errors such as: TypeError: cannot pickle 'function' object 💥 Impact Size:Small 🌐 References #1399 — Error (TypeError: cannot pickle 'function' object) thrown in 📜 Contribution License Agreement By submitting this pull request, you agree that all contributions to this project |
Docs: clarify why st.cache_resource requires pickleable objects
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Docs: clarify picklable requirement for st.cache_resource
Clarifies that st.cache_resource requires pickle-able objects in addition to
being hashable, aligning the documentation with current caching behavior and
addressing confusion reported in #1399.
📚 Context
This change clarifies a documented requirement mismatch discussed in #1399,
where st.cache_resource requires objects to be pickle-able in addition to
being hashable.
🧠 Description of Changes
Added a documentation note explaining that st.cache_resource requires
pickle-able objects in addition to being hashable.
This helps prevent confusion around errors such as: TypeError: cannot pickle 'function' object
💥 Impact
Size:Small
🌐 References
#1399 — Error (TypeError: cannot pickle 'function' object) thrown in
st.cache_resource is confusing because the documentation previously mentioned
only hashability, while pickle-ability is also required.
📜 Contribution License Agreement
By submitting this pull request, you agree that all contributions to this project
are made under the Apache 2.0 license