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I basically wanted to test pythonanywhere with a very small flask site that i set up with pipenv and a pipfile. Locally that takes about 15 seconds and 160MB in packages for the venv. Here in the bash im now well into the tarpit and am using about 360 MB with no end in sight after using pipenv install. I have no idea whats going on.

Pipfile: [[source]] url = "https://pypi.org/simple" verify_ssl = true name = "pypi"

[packages] autopep8 = "==1.6.0" certifi = "==2021.10.8" charset-normalizer = "==2.0.7" click = "==8.0.3" et-xmlfile = "==1.1.0" flask = "==2.0.2" idna = "==3.3" itsdangerous = "==2.0.1" jinja2 = "==3.0.2" markupsafe = "==2.0.1" numpy = "==1.21.3" openai = "==0.19.0" openpyxl = "==3.0.9" pandas = "==1.3.4" pandas-stubs = "==1.2.0.35" pycodestyle = "==2.8.0" python-dateutil = "==2.8.2" python-dotenv = "==0.19.2" pytz = "==2021.3" requests = "==2.26.0" six = "==1.16.0" toml = "==0.10.2" tqdm = "==4.62.3" urllib3 = "==1.26.7" werkzeug = "==2.0.2"

[dev-packages]

[requires] python_version = "3.8"

If you're in the tarpit, then things take longer and the space used during an install can be greater than the space that is used once the install is done.

I know that, but it shouldnt take that long in the first place. To make that clear: the "pipenv install" was basically the first command I ever executed and it consumed all resources available in the test subscription. That's laughable. Even with a paid subscription that would mean I couldnt test two deploys in a day... or even one at this rate.

Hello Community,

I'm new to web development and recently encountered a challenge with setting up a project environment using Pipenv. I'm reaching out for insights or solutions to what I believe might be a performance issue.

I initiated the environment setup with Pipenv, specifying Python 3.10 as follows:

<code> 19:24 ~/Documents/workspace/test $ pipenv --python 3.10</code>

Unexpectedly, this process took approximately 3 minutes to complete. Given that this was a fresh start, the duration seemed unusually long.

To further investigate, I attempted to install two well-known packages, numpy and pandas, using

<code> 19:27 ~/Documents/workspace/test $ pipenv install numpy pandas</code>

However, after mode than 30 minutes, this installation process was still ongoing without completion.

For context, I installed Pipenv locally to avoid any potential conflicts with system-wide packages, using the command:

<code> pip install pipenv --user</code>

I'm puzzled by the slow performance of Pipenv in these scenarios and am seeking advice on how to address this. Could there be a configuration issue, or is this a known behavior with potential workarounds? Any guidance or recommendations would be greatly appreciated.

Thank you in advance for your support.

Since you are using shared resources on PythonAnywhere, it's normal for it to be a bit slower than on your local machine, but that does seem very slow. It's possible that you were in the tarpit after using up your CPU allowance. Could you try again today and see if the problem persists? I would also recommend clearing your cache folder and unused files: https://help.pythonanywhere.com/pages/DiskQuota#cleaning-up-unused-files