I currently have a conda environment tf_gpu and I pip installed pipreqs in it to auto generate requirements.txt Now, in my project folder, I have app.py with the imports : Also, predict uses pandas, scipy, numpy, pickle So, but the requirements.txt generated by pipreqs using pipreqs ./ inside the project folder only gets me the following: Why is python-dotenv not
Tag: requirements.txt
Why use requirements.txt in a Docker image
There is a similar question from last year but I don’t think the responses are widely applicable and it’s not accepted. Edit: this is in the context of developing small jobs that will only be run in docker in-house; I’m not talking about sharing work with anyone outside a small team, or about projects getting heavy re-use. What advantage do
Creating requirements.txt in pip compatible format in a conda virtual environment
I have created a conda virtual environment on a Windows 10 PC to work on a project. To install the required packages and dependencies, I am using conda install <package> instead of pip install <package> as per the best practices mentioned in https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#using-pip-in-an-environment In order to distribute my software, I choose to create an environment.yml and a requirements.txt file targeting
pip install via requirements.txt specify a direct GitHub private repo + branch name erroring with exit status 128
I am trying to add a package to my requirements.txt file that is: From a private GitHub repo I’m a member of the private repo I have ssh configured for the private repo From a branch besides master, whose name has a slash in it Using ssh protocol All over the internet, there are questions on this topic. Here are