@JayR the thing is you will have to find the right combination of Python version and packages that would work with KNIME as well as your individual packages
What I would do
- install Miniconda on your system (how to manage environments)
- Choose a major Python version (like 3.8) that would most likely work with you package
- look up a suitable YML file provided by KNIME (python version and operating system)
- edit the file so it would suite your initial needs. Use only ‘conda-forge’ and add additional packages at the end and packages that are only available via PIP under the entry
For MacOS it might look like this:
name: py38_knime_2022 # Name of the created environment
channels: # Repositories to search for packages
- conda-forge
dependencies: # List of packages that should be installed
- pip
- python>=3.8,<3.9 # Python version
- py4j # used for KNIME <-> Python communication
- nomkl # Prevents the use of Intel's MKL
- pandas # Table data structures
- jedi # Python script autocompletion
- python-dateutil # Date and Time utilities
- numpy # N-dimensional arrays
- cairo # SVG support
- pillow # Image inputs/outputs
- pyarrow=6.0 # Arrow serialization
- IPython # Notebook support
- nbformat # Notebook support
- scipy # Notebook support
- jpype1 # Databases
- python-flatbuffers<2.0 # because tensorflow expects a version before 2
- h5py<3.0 # must be < 3.0 because they changed whether str or byte is returned
- protobuf>3.12
- libiconv # MDF Reader node
- asammdf=5.19.14 # MDF Reader node
# ----------------------------------------------------
- openpyxl # Excel Reader
- scikit-learn # Machine Learning
# Visualization
- matplotlib
- bokeh
- seaborn
- pip: # add packages that would be installed thru PIP
- snscrape # scraper for social networking services
Create the environment via the miniconda prompt.
You can read more about how to use KNIME and Python in the guide:
https://docs.knime.com/latest/python_installation_guide/index.html#_introduction