Jul-09-2023, 02:56 PM
Most common to use pip from command line,also install packages from PyPi.
If use eg JupyterLab Notebooks then can install with pip and run code in one place.
Example NoteBook.
In your previous Thread they just use the code directly from Repo.
They could have make package,but have not done that as many of these ML is more of one time test or proof of concept.
There is setup.py so if i do quick build.
If use eg JupyterLab Notebooks then can install with pip and run code in one place.
Example NoteBook.
In your previous Thread they just use the code directly from Repo.
They could have make package,but have not done that as many of these ML is more of one time test or proof of concept.
There is setup.py so if i do quick build.
(suspender_env) G:\div_code\suspender_env\notears (master) λ pip install -q build (suspender_env) G:\div_code\suspender_env\notears (master) λ python -m build * Creating venv isolated environment... * Installing packages in isolated environment... (setuptools >= 40.8.0, wheel) * Getting build dependencies for sdist... # Now have a wheel that install (suspender_env) G:\div_code\suspender_env\notears\dist (master) λ pip install notears-3.0-py3-none-any.whl .....Now will the import works,not document because they did not do this step.
(suspender_env) G:\div_code\suspender_env\notears\dist (master) λ ptpython >>> from notears import utils >>> >>> utils.simulate_linear_sem <function simulate_linear_sem at 0x000001E2FF460FE0> >>> exit()Look at Shiny there can easily compare Python and R code.