Update: I recommend using feather for persisting Pandas DataFrames instead of HDF5.
- Python 3.5 (linked to update with official image)
- HDF5 (quite cumbersome to install from source)
- PyTables (requires HDF5 installed)
- NumPy (compiling takes some time)
- Pandas (requires pytables for hdf5-files and compiling takes some time)
All taken care of...
FROM rcsa/python3-hfd5:latest
ENV PYTHONUNBUFFERED 1
RUN mkdir /code
WORKDIR /code
ADD requirements.txt /code/
RUN pip install -r requirements.txt
ADD . /code/
EXPOSE 5000
CMD ["python", "app.py"]
and app.py like this (see here):
import pandas as pd
#persist dataframe
with pd.HDFStore('file.h5') as store:
store['key'] = pd.DataFrame()
#load dataframe
with pd.HDFStore('file.h5') as store:
df = store['key']