Docker image based on tiangolo/uvicorn-gunicorn-fastapi-docker, with numpy, pandas, scipy, scikit-learn installed
-
python3.8
,python3.8-20210706
(Dockerfile) ~ 547.71 MB compressed -
python3.8-slim
,python3.8-slim-20210706
(Dockerfile) ~ 281.99 MB compressed -
python3.8-20210204
~ 550.91 MB compressed -
python3.8-slim-20210204
~ 277.45 MB compressed
If you use tiangolo/uvicorn-gunicorn-fastapi-docker and has a Dockerfile
like this:
FROM tiangolo/uvicorn-gunicorn-fastapi:python3.8
COPY requirements.txt ./
RUN pip install --requirement requirements.txt
COPY ./app /app
And in your requirements.txt
contains numpy, pandas, scipy, etc. so building your docker image takes a long time.
Change the first line
FROM tiangolo/uvicorn-gunicorn-fastapi:python3.8
to
FROM biggates/uvicorn-gunicorn-fastapi-science:python3.8
The following pip packages are installed, as described in requirements.txt:
- matplotlib
- numpy
- pandas
- pip
- scikit-learn
- scipy
- wfdb
Package Version
----------------- ---------
click 7.1.2
fastapi 0.65.2
gunicorn 20.0.4
joblib 1.0.1
matplotlib 3.4.2
numpy 1.21.0
pandas 1.3.0
pydantic 1.8.2
requests 2.25.1
scikit-learn 0.24.2
scipy 1.7.0
uvicorn 0.13.1
wfdb 3.4.0
Package Version
--------------- ---------
click 7.1.1
fastapi 0.62.0
gunicorn 20.0.4
joblib 1.0.0
matplotlib 3.3.4
numpy 1.20.0
pandas 1.2.1
pydantic 1.7.3
requests 2.25.1
scikit-learn 0.24.1
scipy 1.6.0
uvicorn 0.11.3
wfdb 3.2.0
docker build -t test -f python3.8.dockerfile .
docker tag test biggates/uvicorn-gunicorn-fastapi-science:python3.8
docker image push biggates/uvicorn-gunicorn-fastapi-science:python3.8