PyMuPDF-Utilities
Demos, examples and utilities using PyMuPDF (by pymupdf)
PyMuPDF-Optional-Material
Help file downloads, early ZIP binaries, wheels for retired Python 2.7, 3.5. (by pymupdf)
| PyMuPDF-Utilities | PyMuPDF-Optional-Material | |
|---|---|---|
| 1 | 1 | |
| 476 | 14 | |
| 5.5% | - | |
| 8.2 | 2.6 | |
| about 2 months ago | about 2 years ago | |
| Jupyter Notebook | ||
| GNU Affero General Public License v3.0 | GNU Affero General Public License v3.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
PyMuPDF-Utilities
Posts with mentions or reviews of PyMuPDF-Utilities.
We have used some of these posts to build our list of alternatives
and similar projects.
PyMuPDF-Optional-Material
Posts with mentions or reviews of PyMuPDF-Optional-Material.
We have used some of these posts to build our list of alternatives
and similar projects.
What are some alternatives?
When comparing PyMuPDF-Utilities and PyMuPDF-Optional-Material you can also consider the following projects:
PyMuPDF - PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.
cheat-sheet-pdf - 📜 A Cheat-Sheet Collection from the WWW
konfuzio-sdk - OCR, extract and classify documents. In addition, annotate documents and build your own NLP and Computer Vision models using Python by downloading the data. Find examples in our Colab Notebooks, e. g. how to fine-tune Flair.