sokrypton / sokrypton/ColabFold

During run Prediction

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Dominant language
Jupyter Notebook
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Description

Expected Behavior

Current Behavior

ModuleNotFoundError Traceback (most recent call last)
in <cell line: 65>()
63
64 download_alphafold_params(model_type, Path("."))
---> 65 results = run(
66 queries=queries,
67 result_dir=result_dir,

5 frames
/content/alphafold/relax/cleanup.py in
20 import io
21
---> 22 import pdbfixer
23 from openmm import app
24 from openmm.app import element

ModuleNotFoundError: No module named 'pdbfixer'


NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.

To view examples of installing some common dependencies, click the
"Open Examples" button below

Steps to Reproduce (for bugs)

Please make sure to reproduce the issue after a "Factory Reset" in Colab.
If running locally ypdate you local installation colabfold_batch to the newest version.
Please provide your input if you can share it.

ColabFold Output (for bugs)

Please make sure to also post the complete ColabFold output. You can use gist.github.com for large output.

Context

Providing context helps us come up with a solution and improve our documentation for the future.

Your Environment

Include as many relevant details about the environment you experienced the bug in.

  • Git commit used
  • If you run it on a local system. Please add the server specifications
  • Operating system and version:

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the failing import in /content/alphafold/relax/cleanup.py and trace how run() reaches it after download_alphafold_params(). Check the Colab setup and the local colabfold_batch installation for the declared dependency. Done means the reported prediction workflow runs without the ModuleNotFoundError in a documented environment.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
bioinformatics
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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