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streamlit-issues

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MDU6SXNzdWU1ODY4Mjk0ODk=

Hybrid select box / text_input widget (use text input to create new options)

closed

CONTRIBUTOR

### Problem tokestermw on the forum writes: "Hi, it’s frequently the case that the user would like a pre-canned list, but the option to enter anything custom (e.g. model paths). It would be great if the selectbox can be also used as text_input. I know it’s possible to add both of them and add some backend logic, but I thought it would be cleaner this way." ### Solution **MVP:** <tbd> ### Additional context From forum post at https://discuss.streamlit.io/t/a-selectbox-that-doubles-as-text-input/2235

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MDU6SXNzdWU1ODY4MjgyNDU=

Allow text to copied out of select boxes

closed

CONTRIBUTOR

### Problem tokestermw on the forum writes: "It's currently not possible to copy and paste the text inside the selectbox. It would be great if we can!" ### Solution **MVP:** <tbd> ### Additional context From forum post at https://discuss.streamlit.io/t/a-selectbox-that-doubles-as-text-input/2235 --- Community voting on feature requests enables the Streamlit team to understand which features are most important to our users. **If you'd like the Streamlit team to prioritize this feature request, please use the 👍 (thumbs up emoji) reaction in response to the initial post.**

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MDU6SXNzdWU1ODY0NTA1NzI=

Importing streamlit adds StreamHandler to root logger

closed

NONE

### Problem When importing streamlit (without calling it via the cli), a `StreamHandler` is registered to the root logger. In my current project, I import Streamlit, but the script is not always executed as streamlit app - when running headless, it is not used. ``` python import logging print(logging.getLogger().handlers) # outputs '[]' import streamlit print(logging.getLogger().handlers) # now outputs '[<StreamHandler <stderr> (NOTSET)>]' ``` In my opinion, no handler should be registerd when the library is just imported (should only happen when the script is executed via streamlit). ### Solution Would it be possible to only add the handler when the script is called via the `streamlit run` command? ### Additional context Since I am beginner using logging as well as streamlit, I am not sure whether this is in fact the intended behavior, but I did not expect the import of streamlit to change logging settings. #### Version 0.56.0 ``` $ pip freeze | grep streamlit streamlit==0.56.0 ```

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MDExOlB1bGxSZXF1ZXN0MzkyNTE5Mzk3

MediaFileManager: fix "Content-Type" header

closed

COLLABORATOR

Just removes a stray colon :)

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MDU6SXNzdWU1ODYzMjUxNDE=

ImportError: cannot import name 'SQLALchemy' from 'flask_sqlalchemy'

closed

NONE

i m running this code ``` from flask import Flask, render_template, url_for from flask_sqlalchemy import SQLALchemy from datetime import datetime app = Flask(name) app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///test.db' db = SQLALchemy(app) class Todo(db.Model): id = db.Column(db.Integer, primary_key=True) content = db.Column(db.Integer, default = 0) data_created = db.Column(db.datetime, default=datetime.utcnow) def __repr__(self): return '<Task %r>' % self.id @app.route("/") def index(): return render_template("index.html") if name == "main": app.run(debug=True) ``` and when i run it > ImportError: cannot import name 'SQLALchemy' from 'flask_sqlalchemy' Please help

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MDU6SXNzdWU1ODYyNzc0NDc=

Need hash_funcs for type PyCapsule

closed

NONE

# Summary I cannot use caching while instantiating a Pytorch model via ```torchvision.models.__dict__```, while it does work with ```torchvision.models.resnet18```. # Steps to reproduce ```python import streamlit as st import torchvision @st.cache(allow_output_mutation=True) def fun(): model = torchvision.models.__dict__['resnet18'](pretrained=True) return model model = fun() ``` ## Expected behavior: It should work just fine as this does work: ```python def fun(): model = torchvision.models.resnet18(pretrained=True) return model ``` ## Actual behavior: The app throws the following error: ``` UnhashableType: Cannot hash object of type PyCapsule ``` ## Is this a regression? NA # Debug info - Streamlit version: Streamlit, version 0.56.0 - Python version: Python 3.6.8 :: Anaconda, Inc. - Using Conda . - OS version: macOS 10.14.6 - Browser version: Safari 13.0.4 # Additional information ```python import streamlit as st from types import MappingProxyType class C(): a = 1 @st.cache(allow_output_mutation=True) def f(): return C.__dict__['a'] f() ``` raises ```UnhashableType: Cannot hash object of type mappingproxy``` which I can resolve with adding ```hash_funcs={MappingProxyType: id}``` to st.cache arguments.

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MDU6SXNzdWU1ODYxNjI0NTE=

ImportError: Dynamic module does not define module export function(PyInit_bz2)

closed

NONE

# Summary I have setup python3 env and install streamlit . everything is working file even hello program is also running fine . but while i use run command wit my real program found below error . ImportError: Dynamic module does not define module export function(PyInit_bz2) not able to resolved , need help

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MDU6SXNzdWU1ODYxNTY4MTk=

import error

closed

NONE

# Summary Type here a clear and concise description of the bug. Aim for 2-3 sentences. # Steps to reproduce What are the steps we should take to reproduce the bug: 1. Go to '...' 2. Click on '....' 3. Scroll down to '....' ## Expected behavior: Explain what you expect to happen when you go through the steps above, assuming there were no bugs. ## Actual behavior: Explain the buggy behavior you experience when you go through the steps above. If applicable, add screenshots to help explain your problem. ## Is this a regression? That is, did this use to work the way you expected in the past? yes / no # Debug info - Streamlit version: (get it with `$ streamlit version`) - Python version: (get it with `$ python --version`) - Using Conda? PipEnv? PyEnv? Pex? - OS version: - Browser version: # Additional information If needed, add any other context about the problem here. For example, did this bug come from https://discuss.streamlit.io or another site? Link the original source here!

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MDU6SXNzdWU1ODYwOTAyOTk=

Animation of matplotlib figures not working anymore

closed

NONE

# Summary [Here](https://discuss.streamlit.io/t/how-to-animate-a-line-chart/164) is a discussion of how to have matplotlib figures inside streamlit be updated to have an animation like character. I recently tested the code provided over there and found that it was not working anymore with the most recent streamlit version. # Steps to reproduce Take the gist from the above mentioned discussion and run it with different streamlit versions. ## Expected behavior: Expected would be that you see an animated line plot, like it is for streamlit version 0.51.0 (the most recent under which it seems to work for me). ## Actual behavior: For version 0.52.0 I get an error message "Bad message format: Tried to use SessionInfo before it was initialized!" and for versions 0.52.2 and up, there is no error message anymore but an white/empty placeholder for an matplotlib plot (recognizeable by the small zoom errors provided by streamlit). ## Is this a regression? As explained above, this is a regression as it worked in 0.51.0 and before (so the gist was working as the time of writing, of course). # Debug info - Streamlit version: tested multiple, see above - Python version: 3.7.5 - Using Conda? PipEnv? PyEnv? Pex? Is `python -m venv` a PipEnv? Anyway, I use venv and pip for installing packages like streamlit and matplotlib. - OS version: Ubuntu 19.10 - Browser version: Chrome

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MDExOlB1bGxSZXF1ZXN0MzkyMTI1Njcz

Add experimental and beta namespaces

closed

CONTRIBUTOR

Add `st.beta` and `st.experimental`, so we can push early features to users by putting them under those namespaces. For now `st.beta` is empty, and `st.experimental` has only `st.experimental.show` (which was moved from `st.show`. This is OK since that was a hidden/undocumented feature).

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MDExOlB1bGxSZXF1ZXN0MzkyMTI0OTA3

Version 0.57.0 - closed due to weird Github thing... Creating new one.

closed

CONTRIBUTOR

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MDU6SXNzdWU1ODU1MzMwMjg=

How to put multiple apps together

closed

NONE

such as `streamlit hello` 

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How to get?

closed

NONE


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MDU6SXNzdWU1ODQ4NzY3MDk=

Integrate with Pyecharts

closed

NONE

Pyecharts is a great framewok for Data visualization [https://github.com/pyecharts/pyecharts](https://github.com/pyecharts/pyecharts)

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MDExOlB1bGxSZXF1ZXN0MzkxMzQ2NDcz

Update the CORS check for proxying from same server

closed

CONTRIBUTOR

Issue: #1234 Description: This is a follow up to #964 and #965. The Websocket now works for most of the cases when the HOST and ORIGIN are on the same server. However, there are cases, for example with a proxy in front of the real server, serving different ports on the HOST and ORIGIN. Changes This will enhance the previous implementation, checking whether HOST and ORIGIN are equal, in case they are the same server, (severing different ports), it will pass. Otherwise, it will proceed with the configured URL check. Contribution License Agreement By submitting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.

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MDU6SXNzdWU1ODQ4MzU4Nzg=

WebSocket is not working for same server however with proxying ports

closed

CONTRIBUTOR

Summary WebSocket is now working most of the time when host and origin are the same. However, there is a special situation, when there is a proxy, for example, serving from different ports, it will not work. Steps to reproduce What are the steps we should take to reproduce the bug: Deploy streamlit to any server (non-localhost) Put a proxy before streamlit Invoke the streamlit app from proxy server address, as such HOST and ORIGIN will be the same when calling streamlit WebSocket. However, the HOST and ORIGIN are from different ports. Expected behavior: Streamlit should work. Actual behavior: WebSocket will not work, complaining about response code 403. Debug info Streamlit version: 0.50.2 Python version: 3.8 Using PipEnv OS version: Browser version: Chrome 79.0.3945.117 

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MDExOlB1bGxSZXF1ZXN0MzkwNjk0NjY1

Update vega packages, and do proper view finalization

closed

COLLABORATOR

This should fix #755, but I'd love to get @domoritz's opinion if he's available. I'm looking at this issue now because there have been some reports of long-running Streamlit apps blowing up browser memory: - https://github.com/streamlit/streamlit/issues/1148 - https://discuss.streamlit.io/t/animation-to-show-only-the-last-n-datapoints/1686/9 In @domoritz's original bug, he suggested that we were using `view.finalize()` incorrectly, though in the version of `vega-embed` we were previously on, there was no separate `finalize` returned from `embed`. Regardless, I've updated vega, vega-lite, and vega-embed to their latest, and we're now using that finalizer. This PR also performs finalization at `componentWillUnmount` time, which is consistent with what `react-vega` does: https://github.com/vega/react-vega/blob/778596cb9209d9ee48c43ceac699fcd4ca5ac30a/packages/react-vega/src/VegaEmbed.tsx#L89

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MDExOlB1bGxSZXF1ZXN0MzkwNjYyMTU4

Add default hash func for regex patterns

closed

CONTRIBUTOR

Issue #1189

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MDU6SXNzdWU1ODM5NTM5NjU=

Add Cypress job to develop on CircleCI

closed

CONTRIBUTOR

### Problem There's no Cypress job when we test against develop ### Solution Add Cypress job

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st_in_cache_warning test is not working

closed

CONTRIBUTOR

# Summary st_in_cache_warning.py is not working as expected . The three different cached functions that should do a st.write() are not doing anything. # Steps to reproduce 1. run `streamlit run e2e/scripts/st_in_cache_warning.py` 2. see ## Expected behavior: We should see two different paragraphs and one button. ## Actual behavior: I'm only seeing the message: ``` If this is failing locally, it could be because you have a browser with Streamlit open. Close it and the test should pass. ``` ## Is this a regression? That is, did this use to work the way you expected in the past? yes # Additional information https://4870-204086862-gh.circle-artifacts.com/0/frontend/cypress/videos/st_in_cache_warning.spec.ts.mp4

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MDU6SXNzdWU1ODMyODg2NDM=

H3HexagonLayer in pydeck doesn't display

closed

NONE

I previously posted this as a feature request but realized it's a bug. Data loaded in an H3HexagonLayer in pydeck doesn't display. The data I'm hoping to visualize has lat long and hex features. Loading the lat longs into a HexagonLayer works, loading the hex feature into an H3HexagonLayer does not. There's no error message - the map displays with no data overlay. I ran the same code in a notebook without streamlit and it works as expected, so this isn't a pydeck bug. Here's the relevant code: ``` st.write( pdk.Deck( mapbox_key='my_key', map_style="mapbox://styles/mapbox/light-v9", tooltip={"text": "Trips: {count}"}, initial_view_state=pdk.ViewState( latitude=40.763781, longitude=-111.894560, zoom=10, bearing=0, pitch=50 ), layers=[ pdk.Layer( "H3HexagonLayer", df, pickable=True, stroked=True, filled=True, extruded=True, get_hexagon="hex", get_fill_color=f"[255, (1 - count / {max_count}) * 255, 0]", get_elevation='count * 20', get_line_color=[255, 255, 255], line_width_min_pixels=2, ), ], ) ) ``` Here's df.head():   hex | start_hour | count -- | -- | -- 8926960292fffff | 0 | 1 8926960440bffff | 0 | 1 8926960444bffff | 0 | 1 89269604457ffff | 0 | 1 892696044cfffff | 0 | 1

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MDU6SXNzdWU1ODI5NTI0MzY=

st.pyplot throwing IndexError and KeyError under heavy user load

closed

NONE

# Summary See pennsignals/chime#9 and pennsignals/chime#52 for more details. This issue only occurs under heavy user load which makes it especially hard to debug. It is not reproducible in development mode. # Steps to reproduce What are the steps we should take to reproduce the bug: 1. Go to http://penn-chime.phl.io/ 2. Click on buttons in the sidebar a few times quickly to force the graphs to be regenerate (or really any of the elements that regenerate the plots) 3. Scroll down to the plots ## Expected behavior: No exceptions ## Actual behavior: See attached tickets above. ## Is this a regression? That is, did this use to work the way you expected in the past? No # Debug info - Streamlit version: 0.56.0 - Python version: python-3.7.6 - Using Pipenv - OS version: Heroku - Browser version: Any browser (Chome/Firefox) # Additional information https://discuss.streamlit.io/t/streamlit-unstable-under-heavy-load/2200

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MDU6SXNzdWU1ODI5MDA1MzI=

Bokeh Charts are not displayed

closed

NONE

Bokeh Charts are not displayed, not even the simple Example from the Documentation. The Bokeh Chart Object is working, as can be seen using bokeh.plotting.show(). Running on a Linux Ubuntu System. What are the steps we should take to reproduce the bug: Load the Example from https://docs.streamlit.io/api.html#display-charts. Ony my System an empty website is opened and nothing else happens # Debug info - Streamlit version: 0.56.0 - Python version: 3.6.9 - Using PipEnv - OS version: Linux Ubuntu - Browser version: Mozilla Firefox 74.0 (Linux) Microsoft Edge 44.18362.449.0 (Windows) Mozilla Firefox 60.7.2esr (Windows)

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MDU6SXNzdWU1ODI3NjAzNTc=

Add H3HexagonLayer for pydeck

closed

NONE

It seems that H3HexagonLayer isn't implemented, I'd really appreciate adding it and I don't think it would be particularly difficult

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MDU6SXNzdWU1ODI3MDgwNzA=

Can't cache a dataframe that contains tuples

closed

NONE

# Summary I got an internal hash error when I wrote a cached function that returns a dataframe containing tuples. This is the error message: InternalHashError: setting an array element with a sequence Usually this means you found a Streamlit bug! If you think that's the case, please file a bug report here. In the meantime, you can try bypassing this error by registering a custom hash function via the hash_funcs keyword in @st.cache(). For example: @st.cache(hash_funcs={pandas.core.frame.DataFrame: my_hash_func}) def my_func(...): ... Please see the hash_funcs documentation for more details. Traceback: File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/ScriptRunner.py", line 314, in _run_script exec(code, module.__dict__) File "/Users/mysterefrank/surge_sim/vis/sample_data/streamlit_v1.py", line 42, in <module> df = load_data(file_path) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/caching.py", line 464, in wrapped_func return get_or_set_cache() File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/caching.py", line 457, in get_or_set_cache hash_funcs=hash_funcs, File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/caching.py", line 294, in _write_to_cache _write_to_mem_cache(key, value, allow_output_mutation, hash_funcs) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/caching.py", line 231, in _write_to_mem_cache hash = get_hash(value, hash_funcs=hash_funcs) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/hashing.py", line 134, in get_hash hasher.update(f, context) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/hashing.py", line 280, in update self._update(self.hasher, obj, context) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/hashing.py", line 323, in _update b = self.to_bytes(obj, context) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/hashing.py", line 307, in to_bytes b = self._to_bytes(obj, context) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/hashing.py", line 500, in _to_bytes raise InternalHashError(msg).with_traceback(e.__traceback__) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/streamlit/hashing.py", line 398, in _to_bytes return pd.util.hash_pandas_object(obj).sum() File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/pandas/core/util/hashing.py", line 115, in hash_pandas_object h = _combine_hash_arrays(hashes, num_items) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/pandas/core/util/hashing.py", line 33, in _combine_hash_arrays first = next(arrays) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/pandas/core/util/hashing.py", line 104, in <genexpr> hashes = (hash_array(series.values) for _, series in obj.iteritems()) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/pandas/core/util/hashing.py", line 289, in hash_array return _hash_categorical(cat, encoding, hash_key) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/pandas/core/util/hashing.py", line 209, in _hash_categorical categorize=False) File "/Users/mysterefrank/miniconda3/lib/python3.6/site-packages/pandas/core/util/hashing.py", line 295, in hash_array vals = hashing.hash_object_array(vals.astype(str).astype(object), The error goes away when I removed the tuple columns in my df.

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MDExOlB1bGxSZXF1ZXN0Mzg5NTc5MDA5

Fix face gan demo

closed

CONTRIBUTOR

Accept both a type and a fqn string as the key for a hash func, because we always remove user-written modules from memory when rerunning a script, in order to reload it and grab the latest code changes. (See LocalSourcesWatcher.py:on_file_changed) This causes type comparisons to fail, however the fqn is the same.

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MDExOlB1bGxSZXF1ZXN0Mzg5NTc4OTYz

Missing module in pipfile

closed

CONTRIBUTOR

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MDExOlB1bGxSZXF1ZXN0Mzg5Mzg2Njcx

Fixing test_just_script pytest

closed

CONTRIBUTOR

**Issue:** test_just_script was failing **Description:** When we get the type from the same method we are having `Class 'function'` but if we get the type from another method of the same class we are gonna be having `Class 'method'`. --- **Contribution License Agreement** By submiting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.

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MDExOlB1bGxSZXF1ZXN0Mzg4MTMwMDA2

Bump acorn from 5.7.3 to 5.7.4 in /frontend

closed

CONTRIBUTOR

Bumps [acorn](https://github.com/acornjs/acorn) from 5.7.3 to 5.7.4. <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/acornjs/acorn/commit/6370e90067552022710190319cbbbd8c43001957"><code>6370e90</code></a> Mark version 5.7.4</li> <li><a href="https://github.com/acornjs/acorn/commit/fbc15b1344f6dfb992f67b4bbf1357436247c8a0"><code>fbc15b1</code></a> More rigorously check surrogate pairs in regexp validator</li> <li>See full diff in <a href="https://github.com/acornjs/acorn/compare/5.7.3...5.7.4">compare view</a></li> </ul> </details> <br /> [](https://help.github.com/articles/configuring-automated-security-fixes) Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting `@dependabot rebase`. [//]: # (dependabot-automerge-start) [//]: # (dependabot-automerge-end) --- <details> <summary>Dependabot commands and options</summary> <br /> You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) - `@dependabot use these labels` will set the current labels as the default for future PRs for this repo and language - `@dependabot use these reviewers` will set the current reviewers as the default for future PRs for this repo and language - `@dependabot use these assignees` will set the current assignees as the default for future PRs for this repo and language - `@dependabot use this milestone` will set the current milestone as the default for future PRs for this repo and language You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/streamlit/streamlit/network/alerts). </details>

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MDExOlB1bGxSZXF1ZXN0Mzg3OTQzMTE1

reset test_run_count

closed

CONTRIBUTOR

**Issue:** Fixing reuse_label test. **Description:** Fixing -1 to initial state --- **Contribution License Agreement** By submiting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.

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MDU6SXNzdWU1ODA1NTExNjM=

TypeError in 'streamlit hello' application

closed

NONE

Hi, I've just installed streamlit in python 3.5.2 with pip (streamlit==0.56.0), and when I executed `streamlit hello` and click the link, a webpage was openned. I choose "Plotting Demo" from the dropdown menu and I got this bug **"TypeError: 'ellipsis' object is not iterable"** I include the full traceback ``` TypeError: 'ellipsis' object is not iterable Traceback: File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/streamlit/ScriptRunner.py", line 314, in _run_script exec(code, module.__dict__) File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/streamlit/hello/hello.py", line 364, in <module> File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/streamlit/hello/hello.py", line 99, in run demo() File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/streamlit/hello/demos.py", line 195, in plotting_demo chart = st.line_chart(last_rows) File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/streamlit/DeltaGenerator.py", line 131, in wrapped_method return dg._enqueue_new_element_delta(marshall_element, delta_type, last_index) File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/streamlit/DeltaGenerator.py", line 360, in _enqueue_new_element_delta rv = marshall_element(msg.delta.new_element) File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/streamlit/DeltaGenerator.py", line 129, in marshall_element return method(dg, element, *args, **kwargs) File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/streamlit/DeltaGenerator.py", line 895, in line_chart import streamlit.elements.altair as altair File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/streamlit/elements/altair.py", line 25, in <module> import altair as alt File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/altair/__init__.py", line 4, in <module> from .vegalite import * File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/altair/vegalite/__init__.py", line 2, in <module> from .v4 import * File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/altair/vegalite/v4/__init__.py", line 3, in <module> from .api import * File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/altair/vegalite/v4/api.py", line 15, in <module> from .display import renderers, VEGALITE_VERSION, VEGAEMBED_VERSION, VEGA_VERSION File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/altair/vegalite/v4/display.py", line 4, in <module> from ..display import Displayable File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/altair/vegalite/display.py", line 1, in <module> from ..utils.display import Displayable, default_renderer_base, json_renderer_base File "/home/ricardo/Documentos/Repos_varios/avocado-prediction/heroku_local/lib/python3.5/site-packages/altair/utils/display.py", line 20, in <module> class RendererRegistry(PluginRegistry[RendererType]): File "/usr/lib/python3.5/typing.py", line 1025, in __getitem__ tvars = _type_vars(params) File "/usr/lib/python3.5/typing.py", line 284, in _type_vars _get_type_vars(types, tvars) File "/usr/lib/python3.5/typing.py", line 279, in _get_type_vars t._get_type_vars(tvars) File "/usr/lib/python3.5/typing.py", line 786, in _get_type_vars _get_type_vars(self.__args__, tvars) File "/usr/lib/python3.5/typing.py", line 277, in _get_type_vars for t in types: ```

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MDExOlB1bGxSZXF1ZXN0Mzg3NTg0ODAy

Master

closed

NONE

## Before contributing (PLEASE READ!) ⚠️ **As with most projects, prior to starting to code on a bug fix or feature request, please post in the issue saying you want to volunteer, and then wait for a positive response.** And if there is no issue for it yet, create it first. This helps make sure (1) two people aren't working on the same thing, (2) this is something Streamlit's maintainers believe should be implemented/fixed, (3) any API, UI, or deeper architectural changes that need to be implemented have been fully thought through by Streamlit's maintainers. More information in our wiki: https://github.com/streamlit/streamlit/wiki/Contributing --- **Issue:** Please include a link to the issue you're addressing. If no issue exists, create one first and then link it here. **Description:** Describe the changes you made to the code, so it's easier for the reader to navigate your pull request. Usually this is a bullet list. --- **Contribution License Agreement** By submiting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.

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MDExOlB1bGxSZXF1ZXN0Mzg3NDUwMjQ3

Fixing BokehChart

closed

CONTRIBUTOR

**Issue:** This fixes #1134 **Description:** BokehChart was not working --- **Contribution License Agreement** By submiting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.

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MDU6SXNzdWU1Nzk1ODMxNjU=

Error generated when editing source file on GAN demo

closed

CONTRIBUTOR

# Summary If you install and run the GAN Demo, when you edit the source file you receive an error message. # Steps to reproduce Do the following: ``` git clone https://github.com/streamlit/demo-face-gan.git cd demo-face-gan pip install -r requirements.txt streamlit run app.py ``` Edit any of the source file after running the above. ## Expected behavior: If you install and run the GAN Demo it should continue to run when you edit the source file. ## Actual behavior: If you edit the source file, it throws an error message.

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MDExOlB1bGxSZXF1ZXN0Mzg2ODIyMDk5

#1154 | Plotly fullscreen bug

closed

CONTRIBUTOR

**Issue:** Closes #1154 **Description:** Adding a key in order to force the re-render of Plot Component --- **Contribution License Agreement** By submiting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.

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MDU6SXNzdWU1NzkwNzg5ODk=

stop connecting unpkg.com in the very begging

closed

NONE

I'm trying to implement streamlit in a LAN without internet. when open streamlit in firefox, it spent too much time in opening unpkg.com, Is there're any way to close it ?

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MDU6SXNzdWU1NzkwNTQyNzA=

running as systmd service - EXCEPTION! 'NoneType' object has no attribute 'strip'

closed

NONE

# Summary Same bug like mentioned in #554 but I do not use docker, instead I want to run it as a service on ubuntu. # Steps to reproduce Create a bash `init_bug_report_service` script like this: ``` #!bin/bash cd /data/projects/myenv/streamlit /data/anaconda3/envs/myenv/bin/streamlit run bug_report.py ``` create a systemd service like this: ``` [Unit] Description=My Service [Service] Type=simple ExecStart=/scripts/<my-project>/init_bug_report_service [Install] WantedBy=multi-user.target ``` Try to start the service with `systemctl start chatbot-bug-report`. Note: If you run the bash file on its own streamlit starts without problems, if you want to run it as a service it won´t. ## Expected behavior: running streamlit as a service ## Actual behavior: ``` Mar 11 07:43:27 init_bug_report_service[4334]: Did not auto detect external IP. Mar 11 07:43:27 init_bug_report_service[4334]: Please go to https://docs.streamlit.io/ for debugging hints. Mar 11 07:43:27 init_bug_report_service[4334]: Please report this bug at https://github.com/streamlit/streamlit/issues. Mar 11 07:43:27 init_bug_report_service[4334]: EXCEPTION! 'NoneType' object has no attribute 'strip' Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/bin/streamlit", line 8, in <module> Mar 11 07:43:27 init_bug_report_service[4334]: sys.exit(main()) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/click/core.py", line 764, in __call__ Mar 11 07:43:27 init_bug_report_service[4334]: return self.main(*args, **kwargs) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/click/core.py", line 717, in main Mar 11 07:43:27 init_bug_report_service[4334]: rv = self.invoke(ctx) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/click/core.py", line 1137, in invoke Mar 11 07:43:27 init_bug_report_service[4334]: return _process_result(sub_ctx.command.invoke(sub_ctx)) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/click/core.py", line 956, in invoke Mar 11 07:43:27 init_bug_report_service[4334]: return ctx.invoke(self.callback, **ctx.params) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/click/core.py", line 555, in invoke Mar 11 07:43:27 init_bug_report_service[4334]: return callback(*args, **kwargs) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/streamlit/cli.py", line 235, in main_run Mar 11 07:43:27 init_bug_report_service[4334]: _main_run(target, args) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/streamlit/cli.py", line 260, in _main_run Mar 11 07:43:27 init_bug_report_service[4334]: bootstrap.run(file, command_line, args) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/streamlit/bootstrap.py", line 233, in run Mar 11 07:43:27 init_bug_report_service[4334]: ioloop.start() Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/tornado/platform/asyncio.py", line 132, in start Mar 11 07:43:27 init_bug_report_service[4334]: self.asyncio_loop.run_forever() Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/asyncio/base_events.py", line 534, in run_forever Mar 11 07:43:27 init_bug_report_service[4334]: self._run_once() Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/asyncio/base_events.py", line 1771, in _run_once Mar 11 07:43:27 init_bug_report_service[4334]: handle._run() Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/asyncio/events.py", line 88, in _run Mar 11 07:43:27 init_bug_report_service[4334]: self._context.run(self._callback, *self._args) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/tornado/ioloop.py", line 758, in _run_callback Mar 11 07:43:27 init_bug_report_service[4334]: ret = callback() Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/tornado/stack_context.py", line 300, in null_wrapper Mar 11 07:43:27 init_bug_report_service[4334]: return fn(*args, **kwargs) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/tornado/gen.py", line 326, in wrapper Mar 11 07:43:27 init_bug_report_service[4334]: yielded = next(result) Mar 11 07:43:27 init_bug_report_service[4334]: File "/data/anaconda3/envs/rasa/lib/python3.7/site-packages/streamlit/server/Server.py", line 343, in _loop_coroutine Mar 11 07:43:27 init_bug_report_service[4334]: traceback.print_stack(file=sys.stdout) ``` # Debug info - Streamlit version: 0.56.0 - Python version: 3.7.5 - Conda version: 3.7.12 - OS version: Ubuntu 18.04.3 LTS - Local Browser Version: Chrome Version 78.0.3904.108

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MDExOlB1bGxSZXF1ZXN0Mzg2Mzg0MTg2

Another attempt at test_multiple_scriptrunners timeouts

closed

COLLABORATOR

- Shutdown the first scriptrunner before starting the next 3 - Longer infinite-loop sleep time in widgts_script.py, so we don't wake up too frequently - Increase our wait_for_widgets_script_deltas timeout to 15 seconds (from 5) - Throw a detailed error from wait_for_widgets_script_deltas - On wait_for_widgets timeout, shutdown the scriptrunners so that the Circle job doesn't hang forever.

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MDExOlB1bGxSZXF1ZXN0Mzg2MjQ0MjIz

When on CircleCI, use "yarn run test --runInBand"

closed

COLLABORATOR

Per https://jestjs.io/docs/en/troubleshooting#tests-are-extremely-slow-on-docker-andor-continuous-integration-ci-server

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MDExOlB1bGxSZXF1ZXN0Mzg2MTkzMjAz

Cypress flaky

closed

CONTRIBUTOR

Separate flaky Cypress tests into their own folder and run them in a separate workflow on CircleCI. Make tests that are working as expected required in CircleCI for PRs to be mergeable and for nightly builds to occur. Make flaky tests optional.

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MDExOlB1bGxSZXF1ZXN0Mzg1OTA2ODI3

Fix st.cache

closed

COLLABORATOR

This fixes breakage that I introduced in #1152 Rather than creating the cache as a local variable in the st.cache wrapper, we instead manage all caches in a global `_MemCaches` class. Each cache is keyed off its wrapped function's fully qualified name, and its contents. There's a new `ScriptRunner` test that makes sure that caches are reused across multiple runs of the same script.

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MDU6SXNzdWU1NzgyMjAzNTA=

Checkbox

closed

NONE

# Summary I have an issue where the checkbox always defaults to True. marine_matrix = st.sidebar.checkbox(label="Run Full Marine Matrix", value="False") # Steps to reproduce marine_matrix = st.sidebar.checkbox(label="Run Full Marine Matrix", value="False") 1. Go to '...' 2. Click on '....' 3. Scroll down to '....' ## Expected behavior: I would like this checkbox to show False instead of True ## Actual behavior: This checkbox shows True ## Is this a regression? I don't know. # Debug info - Streamlit version: 0.56 - Python version: 3.6.9 - Using Conda - OS version: Windows 10 - Browser version: Chrome # Additional information If needed, add any other context about the problem here. For example, did this bug come from https://discuss.streamlit.io or another site? Link the original source here!

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MDU6SXNzdWU1NzgxODAwNDA=

Add option to resize and zoom plots (Similar to %matplotlib notebook)

open

NONE

First of all, thank you for this awesome project ! I am not a fan of the Jupyter notebook since I prefer writing scripts and its a bit cumbersome to replicate the exact training data pipeline when displaying some results or data analysis in notebooks. Streamlit is perfect for my use case since I can create a new code path for it in my codebase and easily replicate the training environment while having a nice interface to visualize results/data. ### Problem Plots can't be resized once they are rendered. We also can't zoom on certain part of the data. ### Solution In jupyter notebook, using the "magic command" `%matplotlib notebook` adds a little overlay over the plots that permit resizing & zooming:  **MVP:** I am not familiar with how this is implemented in jupyter notebook. It might be an ipywidgets (Not sure). Having support to embed ipywidgets might be an easy way to get this feature and many others at the same time. ipywidget support is already referenced in #604 Supporting ipywidgets might be a lot of work, a streamlit zoom & resize function would also work ! --- Community voting on feature requests enables the Streamlit team to understand which features are most important to our users. **If you'd like the Streamlit team to prioritize this feature request, please use the 👍 (thumbs up emoji) reaction in response to the initial post.**

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MDU6SXNzdWU1NzgxNjQ1Mjk=

Inconsistent behavior of Area Plots

closed

NONE

Area plot stacks the plot if the index of the dataframe is of type `datetime` but it doesn't stack the plots when the index of the dataframe is of type `int`. See examples below: ``` import datetime as dt import numpy as np chart_data = pd.DataFrame([[1, 2, 1], [0, 2, 1], [1, 3, 5]], columns=['a', 'b', 'c'], index=[1, 2, 3]) st.area_chart(chart_data) ``` Result:  ``` import datetime as dt import numpy as np chart_data = pd.DataFrame([[1, 2, 1], [0, 2, 1], [1, 3, 5]], columns=['a', 'b', 'c'], index=[dt.datetime(2017, 1, 1), dt.datetime(2018, 1, 2), dt.datetime(2019, 1, 3)]) st.area_chart(chart_data) ``` Result: 

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MDExOlB1bGxSZXF1ZXN0Mzg1Nzg4MDEz

BytesIO and StringIO hashing

closed

COLLABORATOR

Makes `BytesIO` and `StringIO` first class hashing citizens. The stream seek position (via `tell()`) is included in the hash. (For readability, this also changes the name of `CodeHasher._update()` to `CodeHasher._update_hasher()` -- it updates a supplied hasher object and not the CodeHasher itself.)

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MDU6SXNzdWU1NzgxMTM5NjU=

Need hash_func for type tf.Session

closed

CONTRIBUTOR

# Summary These are all types from the GAN demo that shouldn't be hashed by Streamlit. # Full error message No included error message, but [here](https://github.com/streamlit/demo-face-gan/blob/master/app.py#L15) are the associated lines in the GAN demo.

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MDU6SXNzdWU1NzgwNTUwNzY=

FileUploader API enhancements

closed

COLLABORATOR

File Uploader was released but has since accumulated several bugs and feature requests. This project will iterate on the file uploader and address items that were passed over as part of the MVP and items identified by the community. Changes include the following: - [x] Support multiple file uploads. Return a list if multiple files allowed. Otherwise return a singleton. - [x] Return a binary buffer with the following attributes 1. file name 2. file type 3. size - [x] Update the UX to provide file upload progress and file information - [x] Map file extension aliases (i.e. jpg + jpeg, xls + xlsx) - [x] Create disabled state - [ ] Ensure binary buffers are reset to the beginning after being read - [ ] Add a check to make sure backend and frontend are in sync - [ ] Optimize caching - [ ] Bug fixes for mobile support Nice to haves - [ ] Allow a max upload size less than 1 MB - [ ] Keep file display list a constant height so actions within file display does not shift the page up/down (i.e. paginating between pages with 2 vs 3, deleting 5th item) - [ ] Toggle to show/hide uploaded files for multiple file uploader - [ ] Make file a link to download/open - [ ] When in single-file mode, keep the gray box and the "browse" buttons, but then replace everything else with the uploaded file so users can replace a file in one action.

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MDU6SXNzdWU1NzgwMTMxNTA=

Prevent reporting _thread._local as the offending object when it's not

closed

CONTRIBUTOR

# Summary When reporting error messages for `hash_funcs`, there are times we report `_thread._local` as the offending object when it's not. This also occurs with `_thread.RLock`. Ideally, we'd identify some kind of operating-system-level object which we're encountering *on the way* to hashing these threading objects, and we'd write specific hash_funcs for those in order to prevent these kinds of errors from bubbling up. # Example error messages: _thread._local: 

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MDU6SXNzdWU1Nzc5MzUwNDk=

Big memory consumption when displaying dataframes

closed

NONE

# Summary When i start up a streamlit application and use st.dataframe or st.write on the full dataset it keeps increasing and increasing the used memory untill it overpasses my 16GB memory. Edit: When loading a 3KB .csv file and using st.write(df) on that loaded data, it results in the application consuming 87MB. (x29.000) If i apply that factor, to the 300MB .csv file im trying to display. This results in 8700 GB allocated memory. (theoretically) Is this the expected behaviour ? # Steps to reproduce Run a python file as a streamlit application. use : st.dataframe(df) st.write(df) ## Actual behavior: It just "Runs" forever untill i have to close the application. # Debug info - Windows 10 - Streamlit version: 0.56.0 - Python version: 3.8.1 - Conda - OS version: Win10 - Browser version: Chrome Version 80.0.3987.132 

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MDU6SXNzdWU1Nzc3MTM4ODI=

Add Pyecharts support

closed

COLLABORATOR

See: https://discuss.streamlit.io/t/any-plan-to-add-pyecharts/2050

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MDU6SXNzdWU1Nzc3MDExNzg=

Use Streamlit elements in dataframe cells

open

COLLABORATOR

Ability to use `st.foo` in tables, dataframes, etc. See: https://discuss.streamlit.io/t/can-i-create-a-table-with-dropdown-menu-as-rows/2094 --- Community voting on feature requests enables the Streamlit team to understand which features are most important to our users. **If you'd like the Streamlit team to prioritize this feature request, please use the 👍 (thumbs up emoji) reaction in response to the initial post.**

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MDU6SXNzdWU1Nzc2OTg0ODM=

Select multiple options using autocomplete

open

COLLABORATOR

Ability to select all options starting with `foo` in `st.multiselect`. See: https://discuss.streamlit.io/t/multiselect-select-multiple-from-the-suggestions/2109 --- Community voting on feature requests enables the Streamlit team to understand which features are most important to our users. **If you'd like the Streamlit team to prioritize this feature request, please use the 👍 (thumbs up emoji) reaction in response to the initial post.**

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MDU6SXNzdWU1NzczMzUyMDA=

Altair chart does not render correctly when created from a dictionary

closed

NONE

# Summary When I create an Altair chart from a dictionary, it does not get rendered correctly in Streamlit. # Steps to reproduce 1. Create a chart from a dictionary 2. Try to render it ## Expected behavior: The chart should render correctly. ## Actual behavior: The data of the chart does not get rendered. ## Is this a regression? I don't know. It's the first time I have tried it. # Debug info - Streamlit version: 0.56.0 - Python version: 3.7.4 - Using Conda? PipEnv? PyEnv? Pex? Nope - OS version: MacOS 10.15.3 - Browser version: Safari 13.0.5 # Additional information **Code** ``` import pandas as pd import altair as alt df = pd.DataFrame({'a': [1, 2, 3, 4, 5], 'b': [1, 3, 5, 7, 9]}) chart = alt.Chart(df).mark_line().encode( x='a', y='b' ) chart chart_dict = chart.to_dict() chart2 = alt.Chart.from_dict(chart_dict) chart2 ``` **Output** <img width="1792" alt="Screenshot 2020-03-07 at 20 28 49" src="https://user-images.githubusercontent.com/17554280/76144385-4f5a8900-60b2-11ea-99e8-598ba7fd9f50.png"> The same code renders correctly in Jupyter Notebook / Lab.

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MDExOlB1bGxSZXF1ZXN0Mzg1MDQ3MDQz

De-flake ScriptRunner_test.py

closed

CONTRIBUTOR

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MDExOlB1bGxSZXF1ZXN0Mzg0OTY0MTEw

Pypi nightly

closed

CONTRIBUTOR

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MDExOlB1bGxSZXF1ZXN0Mzg0OTQ3MDYy

Pypi nightly

closed

CONTRIBUTOR

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MDU6SXNzdWU1NzY5NDIyOTk=

Plotly Express Treemap from DataFrame does not render

closed

NONE

# Summary Plotly Express Treemap from a pandas dataframe does not render # Steps to reproduce 1. ```python import streamlit as st import plotly.express as px df = px.data.tips() fig = px.treemap(df, path=['day', 'time', 'sex'], values='total_bill') st.plotly_chart(fig) ``` 2. Page is empty ## Expected behavior: It should look like this: https://plot.ly/python/treemaps/#treemap-of-a-rectangular-dataframe-with-plotlyexpress ## Actual behavior: No treemap is rendered. An empty plotly canvas appears. ## Is this a regression? No # Debug info - Streamlit version: Streamlit, version 0.56.0 - Python version: Python 3.7.4 - Using Conda? PipEnv? PyEnv? Pex? Nope - OS version: Windows 10 1803 - Browser version: Chrome Version 80.0.3987.122 # Additional information Similar to #578 that has been solved, where an explicit go.Figure and go.Treemap has been used. However, this is in relation to Plotly Express in combination with a rectangular data frame.

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MDU6SXNzdWU1NzY2ODEyNzQ=

Need hash_func for type _io.StringIO

closed

CONTRIBUTOR

# Summary A community member noticed a "cannot hash of type" issue. More information can be found in [this forum discussion](https://discuss.streamlit.io/t/hash-function-error-for-uploaded-text-file/2058). # Full error message This is the error the community member received: ```UnhashableType: Cannot hash object of type _io.StringIO```

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MDU6SXNzdWU1NzY2Nzc4OTE=

Need hash_func for type <class ‘sqlalchemy.engine.base.Engine’>

closed

CONTRIBUTOR

# Summary A community member noticed a "cannot hash of type" issue. More information can be found in [this forum discussion](https://discuss.streamlit.io/t/streamlit-cannot-hash-an-object-of-type-class-sqlalchemy-engine-base-engine/1437). # Full error message This is the error the community member received: ```Streamlit cannot hash an object of type <class ‘sqlalchemy.engine.base.Engine’>```

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MDU6SXNzdWU1NzY2NzU5MDE=

Need hash_func for type re.Pattern

closed

CONTRIBUTOR

# Summary A community member noticed a "cannot hash of type" issue. More information can be found in [this forum discussion](https://discuss.streamlit.io/t/help-us-stress-test-streamlit-s-latest-caching-update/1944/9). # Full error message This is the error the community member received:```UnhashableType: Cannot hash object of type re.Pattern```

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MDU6SXNzdWU1NzY2NzQ3MDk=

Need hash_func for type CompiledFFI

closed

CONTRIBUTOR

# Summary A community member noticed a "cannot hash of type" issue. More information can be found in [this forum discussion](https://discuss.streamlit.io/t/help-us-stress-test-streamlit-s-latest-caching-update/1944/5). # Full error message This is the error the community member received:```UnhashableType: Cannot hash object of type CompiledFFI```

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MDU6SXNzdWU1NzY2NzI2ODI=

Need hash_func for type unknown

closed

CONTRIBUTOR

# Summary A community member noticed a "cannot hash of type" issue. More information can be found in [this forum discussion](https://discuss.streamlit.io/t/help-us-stress-test-streamlit-s-latest-caching-update/1944/4). # Full error message This is the error the community member received:```UnhashableType: Cannot hash object of type _thread.RLock```

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MDU6SXNzdWU1NzY2NjkzNjg=

Need hash_func for type google.protobuf.pyext._message.RepeatedScalarContainer

closed

CONTRIBUTOR

# Summary A community member noticed a "cannot hash of type" issue. More information can be found in [this forum discussion](https://discuss.streamlit.io/t/help-us-stress-test-streamlit-s-latest-caching-update/1944/2). # Full error message This is the error the community member received:```UnhashableType: Cannot hash object of type google.protobuf.pyext._message.RepeatedScalarContainer```

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MDU6SXNzdWU1NzY1OTc1OTY=

Cannot cache a sklearn.pipeline.Pipeline fit

closed

NONE

# Summary Error when try to caching sklearn Pipeline fit method (the function I "implemented" has no more methods). # Steps to reproduce What are the steps we should take to reproduce the bug: ```python from sklearn.preprocessing import OneHotEncoder from xgboost import XGBClassifier from sklearn.pipeline import Pipeline @st.cache def fit_model(model: Pipeline, features: pd.DataFrame, label: pd.DataFrame) -> Pipeline: """Alias for `fit` methods of `Pipeline` object and implements streamlit cachi so we haven't to load the data all of the times that we rerun """ model.fit(features, label) return model X, y = make_classification( n_informative=5, n_redundant=0, random_state=42 ) enc = OneHotEncoder(drop='first') xgb = XGBClassifier() pipeline = Pipeline([('one_hot_encoder', enc), ('xgboost', xgb)]) fit_model(pipeline, X, y) ``` ## Expected behavior: Works perfectly like the non-caching version ## Actual behavior: InternalHashError: unhashable type: 'bytearray' ## Is this a regression? No, it's the first time I tested it # Debug info - Streamlit version: Streamlit, version 0.56.0 - Python version: Python 3.6.10 :: Anaconda, Inc. - Using Conda? YES - OS version: NAME="Ubuntu" VERSION="18.10 (Cosmic Cuttlefish)" - Browser version: Firefox 67.0.4 (64-bit) PD: Sorry for my english!

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MDU6SXNzdWU1NzY1ODk1MTU=

Need hash_func for type unknown

closed

CONTRIBUTOR

# Summary A community member noticed a "cannot hash of type" issue. More information can be found in [this forum discussion](https://discuss.streamlit.io/t/unhashabletype-cannot-hash-object-of-type-thread-local/1917). # Full error message 

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MDExOlB1bGxSZXF1ZXN0MzgzOTcyMDky

file_uploader: support for multiple files

closed

COLLABORATOR

This adds basic support for uploading multiple files to a single st.file_uploader - `st.file_uploader` now has a new flag, `accept_multiple_files`. It defaults to false. - When `accept_multiple_files` is true, the frontend widget will accept multiple files, and the Python API will return a list of BytesIO/StringIO objects if 1 or more files are uploaded to the widget. (That is, even if the user uploads a single file, the multi-file uploader will always return a list. The single-file variant will never return a list.) - `UploadedFileManager` now stores lists of files by `session_id/widget_id` key, instead of just single files. - The e2e test validates the entire round trip of both single and multiple file uploads. Closes #912 (there are additional API changes to make to file_uploader, but we're going to be addressing them in future PRs.)

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MDExOlB1bGxSZXF1ZXN0MzgzOTA4NzQ1

Adding custom filterOptions function to SelectBox

closed

COLLABORATOR

**Issue:** https://github.com/streamlit/streamlit/issues/1010 **Description:** Adding a custom `filterOptions` to make the selectbox filter options based on the labels only. The default `filterOptions` function in baseweb filters based on labels or indeces at the same time. --- **Contribution License Agreement** By submiting this pull request you agree that all contributions to this project are made under the Apache 2.0 license.

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MDU6SXNzdWU1NzU3ODE4OTc=

`super()` inside a cached function results in a UserHashError

open

COLLABORATOR

This code: ```python import streamlit as st class Parent: def test(self): return "parent" @st.cache def state(): class Child(Parent): def test(self): # This breaks: return super().test() + ".child" return Child().test() st.text(state()) ``` Results in `UserHashError: 'class'`: <img width="730" alt="Screen Shot 2020-03-04 at 1 24 02 PM" src="https://user-images.githubusercontent.com/709022/75924261-76e3f400-5e1b-11ea-99ad-005214e7a2b6.png"> Removing the call to `super()` in `Child.test()` makes the error go away. Related discussion: https://discuss.streamlit.io/t/help-us-stress-test-streamlit-s-latest-caching-update/1944/11?u=tim

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MDU6SXNzdWU1NzU3MDY0NTQ=

Need hash_func for type _io.StringIO

closed

COLLABORATOR

This should work out of the box: ``` @st.cache def do_a_thing_with_uploaded_file(value): pass uploaded_file = st.file_uploader("Label") do_a_thing_with_uploaded_file(uploaded_file) ``` https://discuss.streamlit.io/t/hash-function-error-for-uploaded-text-file/2058/7?u=tim

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MDU6SXNzdWU1NzU2NjI3NDM=

The url wont launch Streamlit app on browser unless computer is restarted

closed

NONE

# Summary I now need my computer restarted to get the url generated from the terminal to run the Streamlit app on the browser. To test the server I tried other similar applications like jupyter notebooks with urls from terminal and they run fine in browsers. Streamlit app however wont run unless I restart the computer. # Steps to reproduce What are the steps we should take to reproduce the bug: 1. Run the command `streamlit run app.py' in the terminal 2. Copy the url link on the browser 3. The Streamlit app should launch ## Expected behavior: Expected the url to launch the Streamlit app as before. ## Actual behavior: The url generated in the terminal when copied in the browser wont run the streamlit app. ## Is this a regression? yes, this was working just fine a while ago. # Debug info - Streamlit version: 0.53.0 - Python version: 3.7.6 - Using virtualenv - OS version: Win 10 - Browser version: all browsers (IE, Firefox 68.5.0esr (64-bit)) # Additional information This issue emerged only now. It was running fine just a while ago where as soon as I hit the command `streamlit run app.py' it would lauch the app on IE browser. I'm working on st.cacheing so I wonder if it has anything to do? I tried browser cookie clearing to no avail.

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MDU6SXNzdWU1NzU1OTc2NTQ=

`st.write` should support StringIO/BytesIO

open

COLLABORATOR

I want to be able to do: ``` result = st.file_uploader("upload a file") st.write(result) ``` Currently, this just prints out something like `<_io.StringIO object at 0x1170fab90>`; but what I want to see is the contents of that StringIO --- Community voting on feature requests enables the Streamlit team to understand which features are most important to our users. **If you'd like the Streamlit team to prioritize this feature request, please use the 👍 (thumbs up emoji) reaction in response to the initial post.**

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