Error deploying streamlit application-how to fix it?

creativitylab · April 19, 2022, 8:15pm

I am trying to deploy this application: GitHub - creativitylabb/prediction_app
I am using python 3.7 and conda to install the requirements. I tried running the installation with conda env update --file environment.yml --prune in a separate python environment, locally and I managed to start the streamlit server. However, when I try to deploy the application I get this errors:

[manager] Error during processing dependencies! Please fix the error and push an update, or try restarting the app.

[manager] Streamlit server consistently failed status checks

[manager] Please fix the errors, push an update to the git repo, or reboot the app.

Also here is the log:


[client] Provisioning machine...
[client] Preparing system...
[client] Spinning up manager process...
e[32m[manager] e[0mStarting up repository: 'prediction_app', branch: 'main', main module: 'main.py'
e[32m[manager] e[0mCloning repository...
e[32m[manager] e[0mCloning into '/app/prediction_app'...
Filtering content:  66% (2/3)
Filtering content: 100% (3/3)
Filtering content: 100% (3/3), 225.43 KiB | 161.00 KiB/s, done.

e[32m[manager] e[0mCloned repository!
e[32m[manager] e[0mPulling code changes from Github...
e[32m[manager] e[0mProcessing dependencies...
Collecting package metadata (repodata.json): ...working... [2022-04-20 13:59:56.885095] done
Solving environment: ...working... [2022-04-20 14:01:46.076756] done

Downloading and Extracting Packages
Verifying transaction: ...working... [2022-04-20 14:04:25.707580] done
Executing transaction: ...working... [2022-04-20 14:05:02.766052] Enabling notebook extension jupyter-js-widgets/extension...
      - Validating: e[32mOKe[0m

done
Installing pip dependencies: ...working... [2022-04-20 14:06:35.207806] bash: line 3:    16 Killed                  /home/appuser/.conda/bin/conda env update -n base --file environment.yml
e[32m[manager] e[0minstaller returned a non-zero exit code
e[32m[manager] e[0mError during processing dependencies! Please fix the error and push an update, or try restarting the app.

What am I doing wrong in deploying the app?
This is how I created the environment file:

conda env export > environment.yml

After some conflicts, I modified the environment file and this is how the environment.yml file looks like:

name: multivarPrpohetVar2
channels:
  - msys2
  - anaconda
  - conda-forge
  - defaults
dependencies:
  - aiohttp=3.8.1
  - pystan=2.19.1.1
  - aiosignal=1.2.0
  - argon2-cffi=21.3.0
  - argon2-cffi-bindings=21.2.0
  - arviz=0.11.2
  - async-timeout=4.0.1
  - asynctest=0.13.0=py_0
  - attrs=21.4.0
  - backcall=0.2.0
  - blas=1.0=mkl
  - bleach=4.1.0
  - certifi=2021.10.8
  - cffi=1.15.0
  - cftime=1.6.0
  - charset-normalizer=2.0.4
  - colorama=0.4.4
  - convertdate=2.4.0
  - cryptography=36.0.0
  - curl=7.82.0
  - cycler=0.11.0
  - cython=0.29.28
  - debugpy=1.5.1
  - decorator=5.1.1
  - defusedxml=0.7.1
  - elasticsearch=7.13.3
  - entrypoints=0.3
  - ephem=3.7.7.1
  - fbprophet=0.7.1
  - freetype=2.10.4
  - frozenlist=1.2.0
  - hdf4=4.2.15
  - hdf5=1.12.1
  - hijri-converter=2.2.3
  - holidays=0.13
  - intel-openmp=2021.4.0
  - ipykernel=6.9.1
  - ipython=7.31.1
  - ipython_genutils=0.2.0
  - ipywidgets=7.6.5
  - jbig=2.1
  - jedi=0.18.1
  - jinja2=3.0.3
  - jsonschema=3.2.0
  - jupyter=1.0.0
  - jupyter_client=7.1.2
  - jupyter_console=6.4.3
  - jupyter_core=4.9.2
  - jupyterlab_pygments=0.1.2=py_0
  - jupyterlab_widgets=1.0.0
  - kiwisolver=1.4.0
  - korean_lunar_calendar=0.2.1
  - lcms2=2.12
  - libbrotlicommon=1.0.9
  - libbrotlidec=1.0.9
  - libbrotlienc=1.0.9
  - libcurl=7.82.0
  - libdeflate=1.10
  - libnetcdf=4.8.1
  - libpng=1.6.37
  - libssh2=1.10.0
  - libtiff=4.3.0
  - libwebp=1.2.2
  - libwebp-base=1.2.2
  - libxcb=1.13
  - libzip=1.8.0
  - libzlib=1.2.11
  - lunarcalendar=0.0.9=py_0
  - markupsafe=2.0.1
  - matplotlib=3.5.1
  - matplotlib-base=3.5.1
  - matplotlib-inline=0.1.2
  - mistune=0.8.4
  - mkl-service=2.4.0
  - mkl_fft=1.3.1
  - mkl_random=1.2.2
  - munkres=1.1.4=pyh9f0ad1d_0
  - nbclient=0.5.11
  - nbconvert=6.1.0
  - nbformat=5.1.3
  - nest-asyncio=1.5.1
  - netcdf4=1.5.8
  - notebook=6.4.8
  - numpy-base=1.21.5
  - openssl=1.1.1n
  - packaging=21.3=pyhd8ed1ab_0
  - pandas=1.3.4
  - pandocfilters=1.5.0
  - parso=0.8.3
  - patsy=0.5.2
  - pickleshare=0.7.5=pyhd3eb1b0_1003
  - pillow=9.0.1
  - pip=21.2.4
  - plotly=5.6.0
  - prometheus_client=0.13.1
  - prompt-toolkit=3.0.20
  - prompt_toolkit=3.0.20
  - pthread-stubs=0.4
  - pycparser=2.21
  - pygments=2.11.2
  - pymeeus=0.5.10
  - pyopenssl=22.0.0
  - pyparsing=3.0.7
  - pyqt=5.12.3
  - pyqt-impl=5.12.3
  - pyqt5-sip=4.19.18
  - pyqtchart=5.12
  - pyqtwebengine=5.12.1
  - pyrsistent=0.18.0
  - pysocks=1.7.1
  - python=3.7.11
  - python-dateutil=2.8.2
  - python_abi=3.7=2_cp37m
  - pytz=2022.1
  - pywin32=302
  - pyzmq=22.3.0
  - qt=5.12.9
  - qtconsole=5.2.2
  - qtpy=1.11.2
  - scipy=1.7.3
  - send2trash=1.8.0
  - setuptools=58.0.4
  - six=1.16.0
  - sqlite=3.38.0
  - statsmodels=0.13.2
  - tbb=2021.5.0
  - tenacity=8.0.1
  - terminado=0.13.1
  - testpath=0.5.0
  - tk=8.6.12
  - toolz=0.11.2
  - tqdm=4.63.1
  - traitlets=5.1.1
  - unicodedata2=14.0.0
  - wcwidth=0.2.5
  - webencodings=0.5.1
  - wheel=0.37.1
  - widgetsnbextension=3.5.2
  - xarray=0.20.2
  - xorg-libxau=1.0.9
  - xorg-libxdmcp=1.1.3
  - yarl=1.6.3
  - zipp=3.7.0
  - zlib=1.2.11
  - zstd=1.5.2
  - pip:
    - absl-py==1.0.0
    - altair==4.2.0
    - astunparse==1.6.3
    - backports-zoneinfo==0.2.1
    - beautifulsoup4==4.11.1
    - blinker==1.4
    - bokeh==2.4.2
    - bs4==0.0.1
    - cached-property==1.5.2
    - cachetools==5.0.0
    - chardet==3.0.4
    - click==8.0.3
    - cmdstanpy==0.9.68
    - compress-pickle==2.1.0
    - docopt==0.6.2
    - flatbuffers==2.0
    - fsspec==2022.3.0
    - gast==0.5.3
    - gitdb==4.0.9
    - gitpython==3.1.27
    - gluonts==0.9.3
    - google-auth==2.6.3
    - google-auth-oauthlib==0.4.6
    - google-pasta==0.2.0
    - grpcio==1.44.0
    - h5py==3.6.0
    - hydralit-components==1.0.9
    - idna==2.6
    - joblib==1.1.0
    - keras==2.8.0
    - keras-preprocessing==1.1.2
    - libclang==13.0.0
    - lightgbm==3.0.0
    - llvmlite==0.38.0
    - lxml==4.8.0
    - markdown==3.3.6
    - multitasking==0.0.10
    - nbeats-keras==1.7.0
    - nbeats-pytorch==1.6.0
    - nfoursid==1.0.0
    - numba==0.55.1
    - numpy
    - oauthlib==3.2.0
    - opt-einsum==3.3.0
    - pickle5==0.0.12
    - pipreqs==0.4.11
    - pmdarima==1.8.5
    - prophet==1.0.1
    - protobuf==3.20.0
    - pyarrow==7.0.0
    - pyasn1==0.4.8
    - pyasn1-modules==0.2.8
    - pydantic==1.9.0
    - pydeck==0.7.1
    - pydeprecate==0.3.2
    - pympler==1.0.1
    - python-dotenv==0.19.2
    - pytorch-lightning==1.6.1
    - pytz-deprecation-shim==0.1.0.post0
    - pyyaml==6.0
    - requests
    - requests-oauthlib==1.3.1
    - rsa==4.8
    - scikit-learn==1.0.2
    - semver==2.13.0
    - setuptools-git==1.2
    - simplejson==3.17.6
    - sklearn==0.0
    - smmap==5.0.0
    - soupsieve==2.3.2
    - statsforecast==0.5.3
    - streamlit==1.8.1
    - streamlit-aggrid==0.2.3.post2
    - tbats==1.1.0
    - tensorboard==2.8.0
    - tensorboard-data-server==0.6.1
    - tensorboard-plugin-wit==1.8.1
    - tensorflow==2.8.0
    - tensorflow-io-gcs-filesystem==0.24.0
    - termcolor==1.1.0
    - tf-estimator-nightly==2.8.0.dev2021122109
    - threadpoolctl==3.1.0
    - toml==0.10.2
    - torch==1.11.0
    - torchmetrics==0.8.0
    - typing-extensions==4.1.1
    - tzdata==2022.1
    - tzlocal==4.2
    - ujson==5.2.0
    - urllib3==1.22
    - validators==0.18.2
    - watchdog==2.1.7
    - werkzeug==2.1.1
    - wrapt==1.14.0
    - xgboost==1.5.2
    - yarg==0.1.9
    - yfinance==0.1.70

Can you please offer me some suggestions? I’m out of ideas on what is wrong in deploying my app…

gerardrbentley · April 20, 2022, 4:21pm

Hey @creativitylab , my first guess would be the dependencies are too big for Streamlit Cloud.

You can try a tool like pipreqs to slim down your install (you can still use conda, which is probably a good idea). This is what it popped out for your project for me (now i want to turn this into a streamlit app…):

My suggestions would be:

searching how people got each package running in Streamlit Cloud or look to examples in the gallery (perhaps for prophet for example)
use lighter versions of the packages (cpu only)
slimming down your app to not use as many big packages (less fun )

darts==0.19.0
elasticsearch==8.1.2
fbprophet==0.7.1
keras==2.8.0
matplotlib==3.5.1
numpy==1.22.3
pandas==1.4.2
Pillow==9.1.0
plotly==5.7.0
scikit_learn==1.0.2
streamlit==1.8.1
tensorflow==2.8.0
u8darts==0.17.1

randyzwitch · April 20, 2022, 6:48pm

Lines such as these are why it fails, as your conda env specification has Windows-specific packages in it, which of course don’t exist on a Linux server (Streamlit Cloud uses a Debian base image).

However, the solution is the same as @gerardrbentley proposed, which is to use a tool like pipreqs to create a requirements file that only has the packages you personally import, not the structure of the entire environment.

Best,
Randy

creativitylab · April 21, 2022, 6:57am

Thanks for your responses! I finally found a way to deploy the application. The structure of the environment.yml (which was successful) is below, if anybody else has problems with conda:

name: minimal-streamlit-example
channels:
- defaults
- conda-forge
- ericmjl
dependencies:
- python=3.7
- conda
- pystan=2.19.1.1
- elasticsearch=7.13.3
- fbprophet=0.7.1
- hdf5=1.12.1
- matplotlib=3.5.1
- matplotlib-base=3.5.1
- matplotlib-inline=0.1.2
- pandas=1.3.4
- patsy=0.5.2
- pillow=9.0.1
- pip=21.2.4
- plotly=5.6.0
- scipy=1.7.3
- statsmodels=0.13.2
- keras==2.8.0
- numpy
- pickle5==0.0.12
- pip:
  - streamlit
  - scikit-learn==1.0.2
  - sklearn==0.0
  - tensorflow==2.8.0
  - setuptools-git==1.2
  - cmdstanpy==0.9.5

ritik27-santosh11 · January 28, 2023, 3:12am

Hello team streamlit hope you will be fine
I am having issues while deploying my web application
on share.streamlit.io. The server goes into error when ever
i try to deploy

Kindly help me
Thank you

filxy · February 26, 2023, 2:09pm

I am having a similar issue can someone tell me how O can reduce dependencies in my environment.yml and reduce usage.

github.com

filxy/DeepFake-Detection-app/blob/main/environment.yml

channels:
  - anaconda
  - conda-forge
  - defaults
dependencies:
    - dlib
    - numpy
    - scipy
    - cmake
    - pip
    - pip:
        - tensorflow==2.4.0
        - streamlit
        - opencv-python-headless
        - pillow
        - pytube
        - matplotlib
        - cuda-python
        - cudnn--python-wrappers

Franky1 · February 26, 2023, 2:51pm

remove cmake and the cuda/cudnn packages and try again

filxy · February 26, 2023, 5:24pm

well that didn’t work and I am very sure my app won’t work after removing cuda/cudnn packages

Franky1 · February 26, 2023, 5:32pm

What is the error message?

Afaik streamlit cloud hast no GPU support in its runtime engine.

filxy · February 28, 2023, 12:21am

this is what i am getting

filxy · February 28, 2023, 12:52am

this is my latest log where it is stuck on spinner

Franky1 · February 28, 2023, 12:18pm

I forked your streamlit app and took a look.
Not to be offended, but the app is quite a mess and there are quite a few issues to resolve.
I have tried a few things but it is taking me too much time now. The app can now at least be successfully deployed to streamlit cloud, but it doesn’t work properly yet. This is my intermediate result:

system · February 28, 2024, 12:19pm

This topic was automatically closed 365 days after the last reply. New replies are no longer allowed.

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Error deploying streamlit application-how to fix it?

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