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] | closed | false | null | [] | null | 2 | 2020-04-14T22:36:53 | 2022-09-23T13:59:54 | 2022-09-23T13:59:54 | CONTRIBUTOR | null | ```
import streamlit as st
from streamlit.hashing import _CodeHasher
a = {'a': 1, 'b': 2}
b = {'b': 2, 'a': 1}
c = _CodeHasher()
st.write(c.to_bytes(a))
st.write(c.to_bytes(a))
```
```
b'dict:I8\xd2\xb1\xe0\xe7\x9b{\xb2)=M\xfe}\x8fh'
b'dict:\n\xc5L\xdb\xa9\x83A\x1f\x0bv\xbb\x98\xc3\xb5\xb4\x9d
``` | {
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] | closed | false | null | [] | null | 2 | 2020-04-14T20:30:55 | 2020-04-22T23:15:26 | 2020-04-22T23:00:26 | NONE | null | # Summary
If I render a matplotlib chart with pyplot() passing a dpi=NNN parameter, the contents of the plot render as if the correct dpi were set, but the resulting image available in the streamlit UI remains 72 dpi.
# Steps to reproduce
1. Render a matplotlib chart passing the dpi parameter. e.g. st.pyplot(dpi=300). Also note the matplotlib figure size specified.
2. Click on the "wide mode" expansion icon in the streamlit UI
3. Right click on the chart and download the image.
4. Open image in Preview on app, and inspect dimensions/dpi. Note that resulting image does not have dimensions as expected by figure size and dpi parameter.
## Expected behavior:
Image rendered should have more pixels. If width x height was 3in by 3in, and dpi=300 was passed, I should get 900x900 pixel image.
## Actual behavior:
I get a smaller image. Chart appears to be rendered as if dpi settings were set (i.e. some fixed pixel size elements appear smaller at higher dpi parameter values) but the result image is still low res. It appears to be scaled down for display?
## Is this a regression?
Unknown.
# Debug info
- Streamlit version: 0.57.2
- Python version: 3.6.7
- Pipenv
- OS version: Ubuntu 18.04.1 LTS
- Browser version: Chrome Mac 80.0.3987.163 | {
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] | closed | false | null | [] | null | 1 | 2020-04-14T19:53:06 | 2020-07-15T19:04:29 | 2020-07-15T19:04:21 | CONTRIBUTOR | null | Support [HiPlot](https://github.com/facebookresearch/hiplot), an interactive plotting tool that allows to play with high dimensional data. It currently works on Jupyter notebooks (React code embed in an iframe)
Related https://discuss.streamlit.io/t/hiplot-integration/1912/4 | {
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] | closed | false | null | [] | null | 0 | 2020-04-14T18:31:14 | 2021-03-26T15:14:05 | 2021-03-26T15:14:05 | CONTRIBUTOR | null | https://github.com/streamlit/streamlit-old-private/wiki/E2E-Tests
1. The Dockerfile attempts to copy a Pipfile.lock for python 3.7.4 that doesn't exit on my machine. (My python version is 3.8.4). I commented out this line and re-build the image.
2. The Dockerfile attempts to call `make pipenv-lock` which appears to have been removed from the Makefile. I did a `make pipenv-install` instead.
3. The docs say you should run `venv/bin/streamlit` in the container because it doesn't use pipenv, but I think it does use pipenv in the Dockerfile?
4. `yarn start` doesn't work inside the container. I had to chown node_modules/.cache to circleCI.
5. I didn't understand why `make run-circleci` command opened a shell. Took me a while to figured out I'm supposed to type streamlit commands in there. | {
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] | closed | false | null | [] | null | 2 | 2020-04-14T18:15:50 | 2021-03-26T15:13:52 | 2021-03-26T15:13:51 | NONE | null | ### Problem
Unable to find resources on how I could embed my PowerBI/Data Studio dashboard on the Streamlit App. Just Curious to know if its possible.
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] | closed | false | null | [] | null | 6 | 2020-04-14T13:54:19 | 2022-02-01T20:47:39 | 2022-02-01T20:47:39 | NONE | null | # Summary
When trying to display a dataframe with a datetime column, streamlit converts the timestamp by applying a time shift.
This only happens when I run the streamlit app on a server which is in a different timezone. When I run it locally on a laptop, the output is correct.
# Steps to reproduce
The minimal working example that illustrates the issue:
```
import streamlit as st
import pandas as pd
df = pd.DataFrame({'ts': ['2020-04-14 00:00:00']})
df['ts2'] = pd.to_datetime(df['ts'])
st.write(df)
st.write('ts2 is actually:', df.loc[0, 'ts2'])
```
The output is as follows:
```
ts ts2
2020-04-14 00:00:00 Apr 14, 2020 8:00 AM
ts2 is actually: 2020-04-14 00:00:00
```
## Expected behavior:
There should not be an 8 hour shift in `ts2` in the dataframe.
## Actual behavior:
`ts2` in the dataframe is shifted by 8 hours when the dataframe is displayed.
## Is this a regression?
do not know
# Debug info
- Streamlit version: 0.57.2
- Python version: Python 3.6.10
- Using Conda? Yes
- OS version: Mac OS 10:14:6
- Browser version: Chrome 80.0.3987.149 (Official Build) (64-bit)
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] | closed | false | null | [] | null | 0 | 2020-04-14T11:50:02 | 2020-04-16T07:21:00 | 2020-04-16T07:21:00 | CONTRIBUTOR | null | Might it be possible to create an editable pandas DataFrame? I'd be keen to help out. Back in 2017/2018 when we were tackling this ourselves we implemented the DataFrame editing in the following way:
https://mybinder.org/v2/gh/SimonBiggs/scriptedforms-examples/master?urlpath=scriptedforms/use/detailed-example.md (scroll down to the "table variables" heading)
In hindsight it would have been far neater/nicer using the following component from BlueprintJS:
https://blueprintjs.com/docs/#table/features.editing
In fact, in saying that, there are a huge range of BlueprintJS components that would be a very nice fit for streamlit. If I wanted to make a BlueprintJS component set for streamlit would that be something that might find itself merged in? | {
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] | closed | false | null | [] | null | 0 | 2020-04-14T11:43:04 | 2020-04-14T11:59:34 | 2020-04-14T11:59:34 | CONTRIBUTOR | null | _(Note, you don't have to fill out every section here. They're just here for guidance. That said, nicely detailed feature requests are more likely to get eng attention sooner)_
### Problem
Is your feature request related to a problem? Please describe the problem here. Ex. I'm always frustrated when [...]
### Solution
**MVP:** What's the smallest possible solution that would get 80% of the problem out of the way?
**Possible additions:** What are other things that could be added to the MVP over time to make it better?
**Preferred solution:** If you don't like the MVP above, tell us why, and what you'd like done instead.
### Additional context
Add any other context or screenshots about the feature request here. For exmaple, did this FR come from https://discuss.streamlit.io or another site? Link the original source here!
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} | [] | closed | false | null | [] | null | 0 | 2020-04-14T01:07:25 | 2020-04-14T08:21:26 | 2020-04-14T08:21:26 | CONTRIBUTOR | null | * Adding `sphinx-markdown-tables` extension to our implementation.
* This is a value add, because we can now render tables using raw markdown. | {
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When a plugin updates its DOM, it calls the "updateFrameHeight" callback, which gets sent back to the Streamlit `PluginInstance` host. | {
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] | open | false | null | [] | null | 5 | 2020-04-13T15:43:08 | 2022-11-15T17:00:26 | null | NONE | null | ### Problem
I want to pre-process requests to the streamlit app using code that is specific to the system I'm developing. I need to do this in a way that doesn't require modifications to the individual streamlit apps being deployed.
### Proposed Solution
Tornado's `HTTPServer` allows for a `request_callback` which will be called on every request. Can streamlit accept this as an optional parameter and pass it through to tornado? https://github.com/tornadoweb/tornado/blob/stable/tornado/httpserver.py#L175. This would be a general purpose mechanism which might have other uses beyond the one I am planning.
Alternatively, if there's a way to configure the tornado HTTPServer outside of streamlit, that would work too. In that case, a mention in the streamlit docs would be great.
---
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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] | open | false | null | [] | null | 2 | 2020-04-13T09:37:09 | 2020-10-07T00:15:10 | null | NONE | null | # Summary
I'm trying to cache function that take custom object with omegaconf.dictconfig.DictConfig type field. This object comes from hydra.cc config library.
It seems that streamlit experiencing some problem with hash function
# Steps to reproduce
What are the steps we should take to reproduce the bug:
1. As far as I understand you should use any argument with `omegaconf.dictconfig.DictConfig` type
## Expected behavior:
I expect that `@st.cache` will work without raising the Exception (InternalHashError)
## Actual behavior:
I get this error in UI of my application
`
InternalHashError: 'Accessing unknown key in a struct : dataset.train.channels.name'
While caching the arguments of summary(), Streamlit encountered an object of type omegaconf.dictconfig.DictConfig, which it does not know how to hash.
`
## Is this a regression?
No
# Debug info
- Streamlit version: 0.57.3
- Python version: 3.7.5
- Native python
- OS version: Ubuntu 19.10
- Browser version: Google Chrome Version 81.0.4044.92 (Official Build) (64-bit)
# Additional information
No additional info
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Getting `st.cache` error when running streamlit in docker container `FROM nvcr.io/nvidia/tensorflow:19.01-py3`
# Steps to reproduce
1. Copy dockerfile and script into a directory:
`Dockerfile`
```FROM nvcr.io/nvidia/tensorflow:19.01-py3
RUN mkdir /work
WORKDIR /work
RUN pip install streamlit
```
`script.py`
```import streamlit as st
@st.cache
def get_model():
model = {}
return model
model = get_model()
st.write("loaded")
```
2. Run `docker build -t streamlit-example . && docker run -v /this/dir:/work -it streamlit-example bash`
3. In container run `streamlit run script.py`
## Actual behavior:
Get the following error:
## Is this a regression?
Haven't tried running streamlit in a container of the image before
# Debug info
```
root@b2e152534f0e:/work# streamlit version
Streamlit, version 0.57.3
root@b2e152534f0e:/work# python --version
Python 3.5.2
root@b2e152534f0e:/work# uname -a
Linux b2e152534f0e 5.3.0-46-generic #38~18.04.1-Ubuntu SMP Tue Mar 31 04:17:56 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux
```
Seeing this in Firefox and Chrome.
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] | null | 0 | 2020-04-12T20:34:52 | 2020-10-07T01:16:32 | null | CONTRIBUTOR | null | When the external data is declared below the nested function there is a caching error.
```
def get_metrics():
@st.cache
def get_apps():
df = external_data[['date']].copy()
external_data = ...
get_apps()
```
Caused by:
- Needs investigation
Workaround:
- Declare data above the nested function
```
external_data = None
@st.cache
def get_apps():
```
Notes:
- Works in 0.56, breaks in 0.57.3
To Reproduce:
- `streamlit run metrics_dashboard.py`
Error Message:
```
InternalHashError: Cell is empty
While caching the body of query_unique_apps(), Streamlit encountered an object of type builtins.function, which it does not know how to hash.
In this specific case, it's very likely you found a Streamlit bug so 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={builtins.function: my_hash_func})
def my_func(...):
...
If you don't know where the object of type builtins.function is coming from, try looking at the hash chain below for an object that you do recognize, then pass that to hash_funcs instead:
Object of type builtins.function: <function run_creator_metrics.<locals>.query_unique_apps at 0x130539510>
Object of type builtins.tuple: ('__main__', 'run_creator_metrics.<locals>.query_unique_apps', <function run_creator_metrics.<locals>.query_unique_apps at 0x130539510>)
Please see the hash_funcs documentation for more details.
Traceback:
File "lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _run_script
exec(code, module.__dict__)
File "metrics_dashboard.py", line 1951, in <module>
main()
File "metrics_dashboard.py", line 25, in main
run_creator_metrics()
File "metrics_dashboard.py", line 680, in run_creator_metrics
@st.cache
File "lib/python3.7/site-packages/streamlit/caching.py", line 495, in cache
hash_source=func,
File "lib/python3.7/site-packages/streamlit/hashing.py", line 77, in update_hash
ch.update(hasher, val, context)
File "lib/python3.7/site-packages/streamlit/hashing.py", line 308, in update
b = self.to_bytes(obj, context)
File "lib/python3.7/site-packages/streamlit/hashing.py", line 282, in to_bytes
b = b"%s:%s" % (tname, self._to_bytes(obj, context))
File "lib/python3.7/site-packages/streamlit/hashing.py", line 358, in _to_bytes
self.update(h, item, context)
File "lib/python3.7/site-packages/streamlit/hashing.py", line 308, in update
b = self.to_bytes(obj, context)
File "lib/python3.7/site-packages/streamlit/hashing.py", line 297, in to_bytes
raise InternalHashError(e, obj)
File "lib/python3.7/site-packages/streamlit/hashing.py", line 282, in to_bytes
b = b"%s:%s" % (tname, self._to_bytes(obj, context))
File "lib/python3.7/site-packages/streamlit/hashing.py", line 451, in _to_bytes
context = _get_context(obj)
File "lib/python3.7/site-packages/streamlit/hashing.py", line 179, in _get_context
zip(code.co_freevars, map(lambda c: c.cell_contents, func.__closure__)) # type: ignore[no-any-return]
File "lib/python3.7/site-packages/streamlit/hashing.py", line 179, in <lambda>
zip(code.co_freevars, map(lambda c: c.cell_contents, func.__closure__)) # type
```
Potential fix (untested):
```
if code.co_freevars:
assert len(code.co_freevars) == len(func.__closure__)
for i, name in enumerate(code.co_freevars):
closure = func.__closure__[i]
try:
val = closure.cell_contents
except ValueError:
continue
cells[name] = val
```
Possibly caused by
- https://github.com/streamlit/streamlit/blob/908827b8230222621e385a3ee548d529ed9e740d/lib/streamlit/caching.py#L466
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} | [] | closed | false | null | [] | null | 2 | 2020-04-12T17:24:35 | 2022-01-22T22:11:48 | 2020-04-24T13:23:31 | NONE | null | How can I add a pop-up/modal using streamlit?? Any samples? | {
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https://api.github.com/repos/streamlit/streamlit/issues/1336 | https://api.github.com/repos/streamlit/streamlit | https://api.github.com/repos/streamlit/streamlit/issues/1336/labels{/name} | https://api.github.com/repos/streamlit/streamlit/issues/1336/comments | https://api.github.com/repos/streamlit/streamlit/issues/1336/events | https://github.com/streamlit/streamlit/issues/1336 | 598,230,059 | MDU6SXNzdWU1OTgyMzAwNTk= | 1,336 | Cache Keras trained model | {
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] | closed | false | null | [] | null | 2 | 2020-04-11T09:34:41 | 2020-04-12T06:25:51 | 2020-04-12T06:25:51 | NONE | null | # Summary
Hi folks,
I have trained a model (via Keras framework), exported it with model.save('model.hdf5') and now I want to integrate it with the awesome Streamlit.
Obviously, I do not want to load the model every time the end-user insert a new input, but to load it once and for all. Seems that the st.cache decorator fails.
# Steps to reproduce
so my code looks something like that:
```@st.cache
def load_my_model():
model = load_model('model.hdf5')
model.summary()
return model
if __name__ == '__main__':
st.title('My first app')
sentence = st.text_input('Input your sentence here:')
model = load_my_model()
if sentence:
y_hat = model.predict(sentence)
```
## Expected behavior:
Predict via the loaded model whatever I want without loading it every time (when no caching used - but loaded every time, the whole flow works just fine).
## Actual behavior:
In that way I got this exception:
> “streamlit.errors.UnhashableType: <exception str() failed>”
I tried to use ```@st.cache(allow_output_mutation=True)``` and when I run a query at the streamlit page I got:
> “TypeError: Cannot interpret feed_dict key as Tensor: Tensor Tensor(“input_1:0”, shape=(?, 80), dtype=int32) is not an element of this graph.”
I tried to use ```@st.cache(hash_funcs={keras.engine.training.Model: id})``` and when I run a query at the streamlit page I got:
> ValueError: Tensor Tensor("softmax/Softmax:0", shape=(?, 64), dtype=float32) is not an element of this graph.
## Is this a regression?
No, a sequence model.
# Debug info
- Streamlit version: 0.55.2
- Python version: 2.7 (unfortunately the src cannot be migrated to 3.7)
- Using PyEnv
- OS version: Ubuntu 18.04
- Browser version: Chrome
- Keras ver: 2.1.3
- Tensorflow ver: 1.3.0
Thank you!
| {
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] | closed | false | null | [] | null | 3 | 2020-04-11T03:40:50 | 2020-05-21T19:51:34 | 2020-05-21T19:51:33 | NONE | null | Hi all,
Thank you so much for the work. Streamlit is so awesome!
I am developing a NLP app use it.
I have two questions:
1) how to make text_area box larger?
if someone can point me to the line to change this, it will be great.
2) how to layout each text area? if I want to text_area to be vertical, what should I do?
Thanks so much for the help! | {
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} | [] | closed | false | null | [] | null | 1 | 2020-04-10T17:55:53 | 2020-04-29T20:29:11 | 2020-04-29T20:29:11 | CONTRIBUTOR | null | Release 0.58.0
## Version 0.58.0
_Release date: April 22, 2020_
**Highlights:**
- 💼 Made `st.selectbox` filtering case-insensitive.
- ㈬ Better support for Tensorflow sessions in `@st.cache`.
- 📊 Changed behavior of `st.pyplot` to auto-clear the figure only when using
the global Matplotlib figure (i.e. only when calling `st.pyplot()` rather
than `st.pyplot(fig)`).
---
**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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] | closed | false | null | [] | null | 2 | 2020-04-09T10:15:27 | 2020-04-20T14:28:49 | 2020-04-20T14:28:49 | NONE | null | # Summary
Using st.altair_chart to view a multilayer chart with tooltip for any layer, I can see only a tooltip of a layer.
This issue there isn't in version 0.56.0
# Description
Here is the code:
```python
base_raffronto = alt.Chart(df_raffronto).encode(
x=alt.X('monthdate(data):O', axis=alt.Axis(title='month-day'))
)
bar_tamponi = base_raffronto.mark_bar(opacity=.4,color='orange').encode(
alt.Tooltip(['data:T', 'Scostamento tamponi:Q']),
y=alt.Y('Scostamento tamponi:Q',axis=alt.Axis(title='tests (orange bars)'))
)
bar_nuovi_pos = base_raffronto.mark_bar(opacity=.4,color='blue').encode(
alt.Tooltip(['data:T', 'nuovi_positivi:Q']),
y=alt.Y('nuovi_positivi:Q',axis=alt.Axis(title='New positives (blue bars)'))
)
line_perc = base_raffronto.mark_line(opacity=.7,color='red',point=True).encode(
tooltip = [{'type':'temporal','field':'data'},{'type':'quantitative','field':'perc_positivi','format':'.2f'}],
y=alt.Y('perc_positivi:Q',axis=alt.Axis(title='Percentage of new positives on tests (red line)'),scale=alt.Scale(domain=(0,100)))
)
layer_bars = alt.layer(bar_tamponi,bar_nuovi_pos)
st.altair_chart(alt.layer(layer_bars,line_perc).resolve_scale(y='independent').properties(width=650,height=400).interactive())
```
The result is:
to view it in action:
[Interactive version](http://covid-19-ita-mg.herokuapp.com/)
In javascript console of the browser there is this warning:
The input spec uses Vega-Lite v4.8.1, but the current version of Vega-Lite is v4.7.0.
Could this be the problem?
## Expected behavior:
To see all tooltip of any layers
## Actual behavior:
to see above
## Is this a regression?
Probably
# Debug info
- Streamlit version: 0.57.2
- Python version: 3.7.3
- OS version: windows 10
- Browser version: chrome 80.0.3987.149
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] | closed | false | null | [] | null | 2 | 2020-04-09T04:51:35 | 2020-05-28T20:33:58 | 2020-05-28T20:33:58 | NONE | null | _(Note, you don't have to fill out every section here. They're just here for guidance. That said, nicely detailed feature requests are more likely to get eng attention sooner)_
### Problem
Is your feature request related to a problem? Please describe the problem here. Ex. I'm always frustrated when [...]
### Solution
**MVP:** What's the smallest possible solution that would get 80% of the problem out of the way?
**Possible additions:** What are other things that could be added to the MVP over time to make it better?
**Preferred solution:** If you don't like the MVP above, tell us why, and what you'd like done instead.
### Additional context
Add any other context or screenshots about the feature request here. For exmaple, did this FR come from https://discuss.streamlit.io or another site? Link the original source here!
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Title is self-explanatory
# Steps to reproduce
```python3
import pandas as pd
import streamlit as st
pd.DataFrame([pd.NaT]).pipe(st.write)
```
## Expected behavior:
Maybe show `NaT`?
## Actual behavior:
# Debug info
- Streamlit version: `Streamlit, version 0.57.3`
- Python version: `Python 3.7.7`
- Using `conda` and `poetry`.
- OS version: `Ubuntu 18.04.4 LTS`
- Browser version: `Version 80.0.3987.149 (Official Build) (64-bit)`
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Fixes #1304 | {
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] | open | false | null | [] | null | 18 | 2020-04-08T20:15:32 | 2022-11-15T17:00:27 | null | COLLABORATOR | null | If you create a thread from your Streamlit script, and call streamlit functions from within that thread, you need to attach a `ReportContext` to it or else your `st.foo()` calls won't do anything, and you'll get a warning message that looks something like this:
“Thread ‘Thread-7’: missing ReportContext”
We should improve the error message to tell the user how to fix this! (We may just want an FAQ entry that we can link to from the error message.)
(The fix is to use `add_report_ctx` on the thread immediately after it's created:)
```python
from streamlit.ReportThread import add_report_ctx
thread = threading.Thread(target=...)
add_report_ctx(thread)
thread.start()
```
Related discussion: https://discuss.streamlit.io/t/how-to-run-a-subprocess-programs-using-thread-inside-streamlit/2440
(2022 edit: please see my comments [here](https://github.com/streamlit/streamlit/issues/1326#issuecomment-1024399877) - this is an internal Streamlit API and has some major caveats. In particular, please *do not* call `st.foo` commands from other threads - at least in production code that needs to be stable.)
---
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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- Uses HTML5 color input:
`st.color_picker("Pick A Color", "#000") that produces <input type="color" value="#000" name="Pick A Color"/>`
- Default color to `#000`
Possible additions:
- Consider other color formats: RGB, HSL
- Consider setting opacity
- Also recommends shades: When given a color, the Picker shows two extra color that's one shade lighter and one shade darker. Also their hex codes. | {
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### Idea
Some users would like to add a color picker to Streamlit apps. For example: [https://discuss.streamlit.io/t/is-it-possible-to-add-a-color-picker/1999](this request).
### Solution
**MVP:**
- Uses HTML5 color input:
`st.color_picker("Pick A Color", "#000")` that produces `<input type="color" value="#000" name="Pick A Color"/>`
- Default color to `#000`.
**Possible additions:**
- Consider other color formats: RGB, HSL
- Consider setting opacity
- Also recommends shades: When given a color, the Picker shows two extra color that's one shade lighter and one shade darker. Also their hex codes.
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We currently load `leaflet.css` and `leaflet.js` in `index.html` on app launch, but this breaks for users running Streamlit without internet access.
Either move `leaflet.js/css` into `public/vendor` so it's bundled with Streamlit, or perhaps we can remove it all together since we have `leaflet` and `react-leaflet` in our `package.json`? | {
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Also:
- PluginWrapper is now a higher-order component
- Added error handling for plugins
- Plugin args in Python are passed via **kwargs (to be discussed in tomorrow's meeting) | {
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Thank you very much for this incredible framework ! I was very excited to use it for my professional projects in Materials Science but I encountered a huge problem. I couldn’t find any solution to visualize 3d structures (of crystals, molecules…). In jupiter notebook, the visualization is generally done via ase python package and nglviewer ( https://wiki.fysik.dtu.dk/ase/ase/visualize/visualize.html 5 ).
Do you think adding support of ngl is possible in Streamlit ?
I would like to transfer my current GUI in Jupyter notebook to streamlit for better accessibility from different teams.
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**Description:** In order to upgrade BaseWeb we need to re-theme our project using the new primitives from it as it shown [here](https://baseweb.design/guides/theming/#lighting).
---
**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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Type here a clear and concise description of the bug. Aim for 2-3 sentences.
Trying the example code at https://github.com/streamlit/streamlit/blob/develop/docs/tutorial/create_a_data_explorer_app.md
# Steps to reproduce
What are the steps we should take to reproduce the bug:
Copied and pasted the full code from the end of the MD into PyCharm 2019.2 ran streamlit run UBER.py (my name for it) in a pycharm terminal window
## Expected behavior:
Explain what you expect to happen when you go through the steps above, assuming there were no bugs.
Expected to see the NY Uber histogram.
## Actual behavior:
The web page is present with the expected heading followed by the InternalHashError: Type aliases cannot be used with isinstance().
Explain the buggy behavior you experience when you go through the steps above.
If applicable, add screenshots to help explain your problem.
This is too long to capture it all in one go but after line 2 in the traceback it looks like everything is internal to streamlit.
## Is this a regression?
That is, did this use to work the way you expected in the past?
yes / no
Unknown - my first foray into streamlit.
# Debug info
- Streamlit version: (get it with `$ streamlit version`) 0.57.3
- Python version: (get it with `$ python --version`) 3.5
- Using Conda? PipEnv? PyEnv? Pex? PyCharm 2019.2
- OS version: Windows 10 OS Build 18362.720
- Browser version: Firefox 74.01 (64 bit)
# Additional information
numpy 1.18.2
pandas 0.24.2
altair 4.0.1
If I comment out the st.cache decorator I get a new error:-
TypeError: 'ellipsis' object is not iterable which appears to originate from st.bar_chart(hist_values)
Should I log a bug report for that too?
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!
https://github.com/streamlit/streamlit/blob/develop/docs/tutorial/create_a_data_explorer_app.md
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**Name of the Streamlit feature whose docs need improvement:**
**What you think the docs should say:**
graph = graphviz.Digraph() # there is a DiGraph in nx package
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] | open | false | null | [] | null | 1 | 2020-04-03T19:48:29 | 2022-11-15T17:00:28 | null | CONTRIBUTOR | null | ### Problem
*As a user:* I want to format my number as I do with Python.
For example:
```python
x = 1000000
print(f"{x:,}")
# 1,000,000
```
### Additional context
https://discuss.streamlit.io/t/format-integer-with-comma-using-python-printf/2344
---
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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When changing the aspect ratio in a bokeh-plot, toggling full screen for that plot in the brwoser does not scale the plot window to the window size. Only the width is matched to the full screen window. The height is kept according to the chosen aspect ratio.
# Steps to reproduce
What are the steps we should take to reproduce the bug:
1. create a new figure and choose some aspect ratio
```python
fig = bokeh.plotting.figure(aspect_ratio= 16/9)
# plot something ...
st.bokeh_chart(fig, use_container_width=True)
```
2. Run script with streamlit.
3. Click full-screen button for your plot.
## Expected behavior:
The height and width should be scaled/streched to the full-screen size.
## Actual behavior:
Only the width is matched to the full-screen size. The height is kept according to the aspect ratio.
## Is this a regression?
no
# Debug info
- Streamlit version: 0.57.2
- Python version: 3.8.2
- Using PipEnv
- OS version: Windows 10 - 1803
- Browser version: Firefox 74.0
# Additional informatiom
- none
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Analogous to `streamlit run app.py --server.enableCORS False `
i tried to set:
`streamlit run app.py --server.gatherUsageStats False`
it gives me the error, that the parameter is not known.
Can you set this parameter at all via streamlit run? If so, what is the correct name? I did not find a documentary about it either (or any documentary regarding the parameter to set via streamlit run
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] | closed | false | null | [] | null | 4 | 2020-04-03T06:33:51 | 2020-12-07T12:30:13 | 2020-04-04T20:06:55 | NONE | null | # Summary
When using the file_uploader widget to upload files on first page load, streamlit does not detect that the file is uploaded and the subsequent code does not run at all. Only after refreshing the page does the file uploader widget work correctly.
# Steps to reproduce
Code:
```
import streamlit as st
uploaded_file = st.file_uploader("Choose a document: ", type="pdf")
show_file = st.empty()
if uploaded_file is not None:
show_file.info("File received!")
```
1. Run streamlit app `streamlit run app.py`
2. Browser loads http://localhost:8501
3. Upload pdf file using file uploader widget
4. Nothing happens
5. Refresh page
6. Upload pdf file using file uploader widget
7. Message "File received!" is displayed.
## Expected behavior:
File uploading should work right off the bat without page refresh.
## Actual behavior:
See steps to reproduce for description.
Screenshots
First Load:
Nothing happens after.
After Refresh:
## Is this a regression?
That is, did this use to work the way you expected in the past?
no
# Debug info
- Streamlit version: 0.57.2
- Python version: Python 3.7.1
- Using Conda? PipEnv? PyEnv? Pex? -- No
- OS version: Windows 10 Enterprise
- Browser version: Chrome Version 79.0.3945.117 (Official Build) (64-bit)
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] | closed | false | null | [] | null | 1 | 2020-04-03T06:00:51 | 2020-04-03T06:20:21 | 2020-04-03T06:20:21 | NONE | null | # Summary
After upgrading to 0.57 I got the following warning:
```
WARNING:param: Setting non-Parameter class attribute opts.Segments = <classmethod object at 0x1188ce610>
```
With version 0.55 which was installed before the upgrade no warning was issued.
# Steps to reproduce
In a fresh environment and simple app I did not have the warning.
It only appeared in an existing environment/project.
## Is this a regression?
yes
# Debug info
- Streamlit version: 0.57.2
- Python version: 3.7.6
- Using Conda
- OS version: macOS 10.15.4
- Browser version: Chrome 80.0.3987.149 | {
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} | [] | closed | false | null | [] | null | 1 | 2020-04-03T00:01:02 | 2020-04-08T20:19:11 | 2020-04-08T20:19:11 | CONTRIBUTOR | null | "Replace the line `st.write('Done!')` with this:" -> "Replace the line `data_load_state.text('Loading data...done!')` with this:"
`st.write('Done!')` isn't used in the data explorer demo app, replaced parts where it's referenced with appropriate text.
PS Absolutely beautiful documentation. Looking more and more forward to using Streamlit for my own apps :)
---
**Issue:** Doc fix
**Description:** Small documentation update to maintain consistency of language/code.
---
**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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} | [] | closed | false | null | [] | null | 6 | 2020-04-02T23:34:00 | 2020-05-28T20:11:43 | 2020-05-27T22:20:36 | CONTRIBUTOR | null | **Issue:** Fix #1136 #812
**Description:** As it is not possible to render a Mapbox without any token we are delimiting the use locally.
- Prevent fetching token when it's not localhost or hello.py
- Using axios instead of fetch
- Added new step for cypress job in which we set the mapbox token
- Unittest
---
**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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The site randomly shows "0" for images inserted via st.image() and MediaFileManager logs "Missing file".
## More information
I have a couple of jpg images embedded with st.image() and randomly they will not render, instead there will just be a 0 shown instead. Reloading the page or rerunning the code fixes the problem. When I reload the page often enough one ore several of the images will break again and just show a 0.
In the terminal with --log_level error I receive
MediaFileManager: Missing file d8a7ff62725a8ab1609c9335ba2e85375f491027d91b3badb27a6ccd
In my complex multi-page streamlit app this happens very often, if I reload the page two or three times, one out of five images is likely broken. The simpler toy example below takes much longer to show the undesired behaviour, but it does so fairly consistently.
# Steps to reproduce
Run this code (ideally with --log_level error):
```python
import streamlit as st
if st.checkbox('checkbox'):
st.image("foo.jpg")
```
Toggle that checkbox repeatedly (this method is quicker than reloading the page) and look at the console output. Maybe rerun the code once in a while. (Of course you need to put any jpg image named "foo.jpg" in the same folder).
## Actual behaviour
Sooner or later (5-50 clicks) the image will *not* be shown. Instead, in its place a 0 appears. A "MediaFileManager: Missing file" error is shown in the terminal.
## Expected behaviour
Images should always be shown.
## Debug info
- Streamlit version: 0.57.1
- Python version: 3.6.9 | {
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Issue to display geomap
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 1.1`)
- Python version: (get it with `$ python --version 3.6`)
- 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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] | closed | false | null | [] | null | 7 | 2020-04-02T11:16:46 | 2022-12-21T10:59:36 | 2020-04-05T16:18:22 | NONE | null | # Summary
**Error: Streamlit requires raw Python (.py) files, not .**
I checked the file format, it is python, not others.
The streamlit version is 0.56.0
The python version is 3.7
How can I solve this?
# 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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] | open | false | null | [] | null | 28 | 2020-04-02T06:33:39 | 2022-11-29T23:10:40 | null | NONE | null | ### Problem
I'm more productive when I can use keyboard shortcuts.
E.g. press left/right to move to previous / next image. Press space to toggle some viz. Press j/k to move up/down some slider.
### Solution
**MVP:** Provide a way to map 80% of the keys to custom actions. It could be an optional argument to `streamlit.button`, `streamlit.slider` (two keys for up/down one step), etc.
**Possible additions:** Allow to map most keys, inclluding remapping 'c' which currenty clears the streamlit cache.
### Additional context
Comes form personal need. Also mentioned here: https://discuss.streamlit.io/t/idea-keyboard-bindings/1976 .
---
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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https://github.com/streamlit/hello-data/tree/master/v1
That's their new home from now on! So I've updated the Hello pydeck example to match.
Let's delete the old /examples/data in September this year, to give users enough time to upgrade.
---
Related: #1278 | {
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I get a the following error when trying to display a dataframe with datetime values:
`AmbiguousTimeError: Cannot infer dst time from %r, try using the 'ambiguous' argument`
# Steps to reproduce
1. Have a panda dataframe with a column Series with datetime stamps over the whole year, so including the daylight saving time times and winter times.
2. `st.dataframe(df)`
## Expected behavior:
Display the dataframe with the time series in the Streamlit app.
## Actual behavior:
Probably there ia a timestamp in there that is ambigious, like 2019-27-10 2:30 when the time shifted from 3.00 back to 2:00, so the system might not be sure when the actual timestamp is. The error `AmbiguousTimeError: Cannot infer dst time from %r, try using the 'ambiguous' argument` is thrown.
## Is this a regression?
No
# Debug info
- Streamlit version: 0.57.2
- Python version: 3.8.1
- Using Conda? PipEnv? PyEnv? Pex? No
- OS version: Mac 10.14.6
- Browser version: Chrome 80.0.3987.149
# Additional information
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] | closed | false | null | [] | null | 1 | 2020-04-01T04:03:28 | 2021-03-26T15:04:03 | 2021-03-26T15:04:03 | CONTRIBUTOR | null | Flaky tests currently live alongside non flaky ones as siblings in the root folder.
Move them under a parent folder using one of the following approaches
- e2e/flaky/specs, e2e/flaky/scripts
- e2e/specs/flaky/foo.spec.ts, e2e/scripts/flaky/foo.py
- e2e/specs/flaky_foo.spec.ts, e2e/scripts/flaky_foo.py
Questions:
non flaky tests go where in the first two options? | {
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We should test all pages so we can catch issues like #1277 | {
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A message we display is confusing and could cause unfounded security concerns among users.
Before the websocket connection is established, the user sees "connecting with Streamlit Server." Streamlit user @2mol thought that this meant one of our own servers rather than the just-created local server #1279.
## Better behavior
Say "Connecting to local Streamlit server."
- "Connecting to" is more idiomatic than "connecting with"
- "local Streamlit server" fixes the confusion described above about where this server is **<- this is the key change**
- "server" doesn't need to be capitalized
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1. `streamlit hello`
2. ...a browser tab automatically opens. Leave that tab as it is!
3. Open a second browser tab pointing at the app (i.e. localhost:8501)
## Expected behavior:
Both tabs work just fine!
## Actual behavior:
The second tab sometimes shows a dialog saying "Tried to use SessionInfo before it was initialized".
## Is this a regression?
yes
# Debug info
- Streamlit version: 0.57.0
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The Streamlit <-> iframe communication plumbing doesn't exist yet.
You can run `examples/plugin_example.py` to see it in action. (But the arg passing doesn't do anything yet.)
Everything inside the `plugin_template` directory is just the template created by `create-react-app`; there are no custom bits in there yet. | {
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I am following the Azure deployment guide [here](https://towardsdatascience.com/deploying-a-streamlit-web-app-with-azure-app-service-1f09a2159743) and I get to the issue where the app is on "Please wait..." forever. On the top right it shows "Connecting to Streamlit Server".
I couldn't find any mention in the documentation or FAQ about why this needs to be the case, so I'm very confused. In case I missed something in the docs I apologise in advance, otherwise I'm happy to send a PR once I understand this myself. | {
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**Description:** Restored the dataset and the corresponding readme | {
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] | closed | false | null | [] | null | 3 | 2020-03-29T13:27:40 | 2020-03-31T18:21:31 | 2020-03-31T18:21:31 | CONTRIBUTOR | null | # The data source (/examples/data) is no longer present in the repo.
# Steps to reproduce
1. `streamlit hello`
2. Run mapping demo
## Expected behavior:
Run the demo.
## Actual behavior:
Deceiving error message:
> This demo requires internet access.
> Connection error: Not Found
## Is this a regression?
yes
# Debug info
- Streamlit version: > 0.57
# 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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- True by default if `fig` is not set
- False by default if `fig` is set
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] | null | 2 | 2020-03-29T07:38:19 | 2020-07-16T23:30:33 | 2020-07-16T20:14:56 | NONE | null | - methods _repr_jpeg_ or _repr_png_ are invoked if they exist
- this includes the likes of fastai.vision.image.Image
## 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.
https://github.com/streamlit/streamlit/issues/1273
**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.
Check if the format (e.g. JPEG or PNG) _repr_jpeg_ or _repr_png_ method exists and if so substitute the input with the result of calling that 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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] | open | false | null | [] | null | 0 | 2020-03-29T07:37:30 | 2022-11-15T17:00:29 | null | NONE | null | ### Problem
A lot of image classes out there support ipython.display's _repr_jpeg_ or _repr_png_.
Is your feature request related to a problem? Please describe the problem here. Ex. I'm always frustrated when [...]
Yes, I expected that when I passed a fastai.vision.image.Image to streamlit it would display it.
It did not.
### Solution
**MVP:** What's the smallest possible solution that would get 80% of the problem out of the way?
I have coded the solution.
**Possible additions:** What are other things that could be added to the MVP over time to make it better?
**Preferred solution:** If you don't like the MVP above, tell us why, and what you'd like done instead.
---
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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] | null | 2 | 2020-03-28T14:23:37 | 2020-05-22T15:42:42 | 2020-05-22T15:42:42 | NONE | null | Could not hash a fit_model output:
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] | null | 2 | 2020-03-28T09:27:40 | 2020-04-23T17:57:08 | 2020-04-23T17:57:08 | NONE | null | # Summary
Hi, think I found a bug in Streamlit's caching mechanism that has been introduced somewhere after version 0.53.0. Compare the output of the following code between versions 0.53.0 and 0.54.0:
# Steps to reproduce
```
import numpy as np
import streamlit as st
class C:
def __init__(self, x):
self.x = x
@st.cache
def f(c):
return c.x
for x in 1000 / np.arange(1, 10):
c = C(x)
y = f(c)
print(y)
```
## Expected behavior:
The correct output of version 0.53.0 is:
```
1000.0
500.0
333.3333333333333
250.0
200.0
166.66666666666666
142.85714285714286
125.0
111.11111111111111
```
## Actual behavior:
Version 0.54.0 mistakenly caches some of the function calls, returning the following incorrect output:
```
1000.0
1000.0
333.3333333333333
1000.0
1000.0
166.66666666666666
142.85714285714286
1000.0
111.11111111111111
```
## Is this a regression?
yes
# Debug info
- Streamlit version: 0.54.0
- Python version: 3.6.8.
- OS version: macOS 10.15.2
# Additional information
Interestingly, 0.54.0 shows the desired behavior when the value `1000` in the code above is replaced with the value `1`.
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**Description:** Fixing and adding test
---
**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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A community member noticed a "cannot hash of type" issue. More information can be found in [this forum discussion](https://discuss.streamlit.io/t/caching-pytorch-variables/2280).
# Full error message
This is the info provided by hertzmann:
```
“UnhashableType: Cannot hash object of type torch._C._TensorBase”.
```
"I’m trying to cache initialization of a StyleGAN2 class datastructure (which includes loading model weights from a file or online). I don’t want the model weights to be reloaded (and other data structures re-initialized) every time a new image is created.
I tried refactoring my code so that @st.cache is in front of a function that only does one thing: torch.load(filename) and the same error occurs."
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A number of users are running into trouble installing Streamlit on Windows because they don't realize they have to manually edit their `$PATH`.
- https://github.com/streamlit/streamlit/issues/1252
- https://discuss.streamlit.io/t/getting-an-error-streamlit-is-not-recognized-as-an-internal-or-external-command-operable-program-or-batch-file/361/10
- https://stackoverflow.com/questions/60866205/python-streamlit-run-issue
## Solution 1
Set the `$PATH` automatically after installation on Windows.
## Solution 2
If Solution 1 is impossible for some reason, then we could increase the discoverability of the message to set the $PATH on Windows, following [this suggestion](https://github.com/streamlit/streamlit/issues/1252#issuecomment-604554710).
Ways to make it stand out:
1. Make sure this message is at the bottom of the installation messages, as much as possible.
2. Use console colors (is this possible on Windows?)
3. Use capital letters. (If #2 doesn't work.)
4. Separate this message from others with a newline above and below.
We don't need to do all of these options, but it'd be nice to have the minimum to improve discoverability. | {
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When using `checkbox`es to hide or show sections of the app, a change in the first checkbox will mess with subsequent checkboxes in terms of their display state (they lose their "checked" state if any)
# Steps to reproduce
With the MWE below:
- Run the app
- Check the "Third checkbox"
- Then, check the "First checkbox"
- The "Third checkbox" reverted to unchecked, although the corresponding `write` is still shown
```python
import streamlit as st
first = st.checkbox('First checkbox')
if first:
st.write('First is checked')
second = st.checkbox('Second checkbox')
if second:
st.write('Second is checked')
third = st.checkbox('Third checkbox')
if third:
st.write('Third is checked')
```
## Expected behavior:
The third checkbox should keep it's "checked" state when box 1 is clicked
## Actual behavior:
The third checkbox is shown as "unchecked" even though it's value is `True` since the text is shown.
## Is this a regression?
Not sure
# Debug info
- Streamlit version: `0.56.0`
- Python version: `3.7.7`
- Using Conda? `yes`
- OS version: macOS Cataline 10.15.3
- Browser version: Chrome 80.0.3987.149
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**Description:**
This PR introduces a sane memory management approach for MediaFileManager files in which we uniquely identify such files along with their "coordinates" in within their respective `element`.
To accomplish this, the DeltaGenerator gets a new private method, `_get_coordinates`, which contains references to the current element's `container`, two-element `path` tuple, and `index` (position).
The coordinates are formatted as a string as "{container}.{(path1, path2)}.{index}".
Additionally, a short time-delay (2 seconds) is introduced before scrubbing files that have had their session_count decremented to 0. This is to prevent 404s caused by the delay between the time the DeltaGenerator creates and ships the element over the WebSocket and the time when the browser will receive the URL of the element and then request it over HTTP.
We may find that we want to make the KEEP_DELAY configurable by users, or we want to increase or decrease it. There are tradeoffs.
---
**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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] | closed | false | null | [] | null | 4 | 2020-03-26T07:38:16 | 2022-07-27T00:37:30 | 2022-07-27T00:37:30 | NONE | null | ### Problem
Consider the following MWE:
```python
import streamlit as st
import pandas as pd
df = pd.DataFrame([[1, 2, 3]], columns=['a', 'b', 'c'])
# we select which columns to display in a pandas dataframe
cols = st.multiselect('Columns to use:', df.columns.tolist(), df.columns.tolist())
df = df[cols] # df gets filtered
# let's ask the user which column should be used as Index
index_column = st.selectbox('Index column:', [None] + cols)
if index_column is not None:
df = df.set_index(index_column)
cols.remove(index_column)
st.write(df)
```
Now this works fine when the `multiselect` is used first, and then the `selectbox` is used second. But, if both are populated, changing the contents of the `multiselect`by removing one or more column names will reset the `selectbox` to its default state (`None`) even if the previously selected option is still in the list of available options (`cols` here).
In this very simple case one could maybe not understand why this is a problem. But in my real applications, I have several widgets depending on each other, and any change to one of the first ones will cascade to subsequent ones and reset them to their default state, which means the user has to go through all of them again each time a change is made.
### Solution
One could imagine to check (compare by value) if the previously selected option is still in the list of available options after the refresh, and in that case to pre-select this value instead of the first item in the `selectbox`.
Let me know if that seems feasible and/or reasonable!
Cheers
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**Description:**
- Setting max width when the table width exceeds the container width
- Giving the remaining space to cells
- Adding more space if the table is within 2/3 of the container width
<img width="450" alt="Screen Shot 2020-03-26 at 2 28 03 PM" src="https://user-images.githubusercontent.com/631997/77677177-18b7b600-6f6e-11ea-8702-9d08a38adeda.png">
---
**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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] | open | false | null | [] | null | 0 | 2020-03-25T18:56:51 | 2022-11-15T17:00:30 | null | CONTRIBUTOR | null | # Steps to reproduce
1. Create config.toml that has a syntax error, like this:
```toml
server.port=
```
2. Run a script with Streamlit (e.g. `streamlit hello`)
## Expected behavior:
We should see an error like this on the console:
```
ValueError: Error parsing ~/.streamlit/config.toml. This is most likely due to a syntax error in the TOML file. Please fix it and try again.
[Original exception from the toml parser goes here]
```
...where the "original exception" is the part of the error below that ends with `toml.decoder.TomlDecodeError: Empty value is invalid (line 1 column 1 char 0)`.
## Actual behavior:
We see this error on the console, which is not super clear:
```
Traceback (most recent call last):
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/toml/decoder.py", line 456, in loads
multibackslash)
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/toml/decoder.py", line 725, in load_line
value, vtype = self.load_value(pair[1], strictly_valid)
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/toml/decoder.py", line 739, in load_value
raise ValueError("Empty value is invalid")
ValueError: Empty value is invalid
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/bin/streamlit", line 5, in <module>
from streamlit.cli import main
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/streamlit/__init__.py", line 103, in <module>
from streamlit.DeltaGenerator import DeltaGenerator as _DeltaGenerator
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/streamlit/DeltaGenerator.py", line 27, in <module>
from streamlit import caching
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/streamlit/caching.py", line 40, in <module>
from streamlit.hashing import Context
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/streamlit/hashing.py", line 40, in <module>
from streamlit.folder_black_list import FolderBlackList
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/streamlit/folder_black_list.py", line 39, in <module>
if config.get_option("global.developmentMode"):
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/streamlit/config.py", line 90, in get_option
parse_config_file()
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/streamlit/config.py", line 888, in parse_config_file
_update_config_with_toml(file_contents, filename)
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/streamlit/config.py", line 810, in _update_config_with_toml
parsed_config_file = toml.loads(raw_toml)
File "/home/tvst/.local/share/virtualenvs/py3.7-gDeIkMOX/lib/python3.7/site-packages/toml/decoder.py", line 458, in loads
raise TomlDecodeError(str(err), original, pos)
toml.decoder.TomlDecodeError: Empty value is invalid (line 1 column 1 char 0)
```
## Is this a regression?
no
# Debug info
- Streamlit version: 0.56.0
- Python version: 3.7
# Additional information
Source: https://discuss.streamlit.io/t/cant-import-streamlit-anymore/2288/2
---
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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- We have bokehjs 2.0 pinned in our package.json
- But pybokeh 2.0 requires python>=3.6
- bokeh is failing on python 3.5
Charts do not appear | {
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] | open | false | null | [] | null | 0 | 2020-03-25T05:14:54 | 2022-11-15T17:00:30 | null | CONTRIBUTOR | null | # 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/1944/15).
# Full error message
This is the error the community member received:
```
UnhashableType: Cannot hash object of type _asyncio.Task
While caching some code, Streamlit encountered an object of type _asyncio.Task.
You’ll need to help Streamlit understand how to hash that type with the hash_funcs argument. For example:
@st.cache(hash_funcs={_asyncio.Task: my_hash_func})
def my_func(...):
...
```
---
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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] | closed | false | null | [] | null | 7 | 2020-03-24T20:48:46 | 2022-05-07T19:30:33 | 2020-03-26T18:22:55 | NONE | null | # Summary
I've run `pip install streamlit` on Anaconda on Windows, but then `streamlit hello` fails to run ("command not found" type errors, "streamlit is not recognized as an internal or external command", etc).
# Steps to reproduce
What are the steps we should take to reproduce the bug:
1. Install Anaconda on Windows 10
2. pip install streamlit
3. streamlit hello
I've tried in Anaconda Powershell (both as user and admin), cmd.exe, and creating an Anaconda environment and then running the terminal in that environment.
## Is this a regression?
This is my first time installing streamlit on Windows.
# Debug info
- Streamlit version: (get it with `$ streamlit version`)
This fails to run, but I just installed streamlit for the first time just now.
- Python version: (get it with `$ python --version`)
I get different answers in different shells. The Anaconda Environment terminal is Python 3.7.7. The Anaconda PowerShell python version is 3.7.6
- OS version:
Windows 10 Home version 1903, OS Build 18362.720
# Path info
From reading forum comments, it sounds like this could be caused by my PATH. I don't see any Python or Anaconda-related directories in my user PATH or system PATH enviornment variables or PSModulePath.
In PowerShell, running echo $Env:Path shows that it includes C:\ProgramData\Anaconda3{,mingw-w64\bin,\usr\bin,bin,Scripts,\Library\bin,condabin} and more. | {
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] | open | false | null | [] | null | 0 | 2020-03-24T17:26:06 | 2020-10-12T19:04:23 | null | CONTRIBUTOR | null | We need to improve the error handling in the code snippet below.
```
try:
reduce_data = obj.__reduce__()
except BaseException as e:
raise UnhashableTypeError(e, obj)
```
Objects can define their own `__getstate__` method which get called by `__reduce__`. Therefore a bug could occur in this `__getstate__` call, the error for which should bubble up to the user.
Currently we're suppressing this error message and type. | {
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