Contributing to lasio

lasio is an open source project released under the MIT License. It has grown over the years through the wonderful work of all these contributors:

Thank you also to everyone who has helped via email, in discussions on GitHub, and on software underground!

Your help is very welcome! No contribution is too small. You can help with the documentation, adding example notebooks, posting ideas or feature requests to GitHub, or by working on the code - or anything else!

Places you can help

  • Please don’t hesitate to open a GitHub issue for any problems you are having with lasio, or any ideas for improvements. There are templates to guide you in how to file a bug report, or a request for a new feature or improvement. If you are not sure whether your issue fits under these categories, please go ahead and raise one anyway!
  • Please feel free to contribute suggested changes. The easiest method is to fork lasio on GitHub and submit a pull request against the “main” branch. Don’t worry about getting all the details right, either way it’s still the most convenient way for me or other maintainers to see your changes in context.
  • Example LAS files: if you have an interesting/difficult/silly/standards-challenged LAS file (any version) you would be willing to share with me, please do so! Email it to me at The more examples we can incorporate into lasio’s regression testing, the better. If you have concerns about privacy, I’d suggest obfuscating with find-and-replace on various alpha (or numeric) characters before sending it on, and/or deleting any sensitive header lines.

How to make contributions

Contributions are always welcome to the code, documentation, or example notebooks. If you are making a contribution, please make sure you are working off the latest GitHub main branch. You will want to make your contributions in a branch taken from main, and then when you want to share your changes, you can publish them by “pushing” your branch to your GitHub fork of the lasio repository, and opening a PR (pull request) here.

First, create a fork of the lasio repository using the GitHub website. Then clone your fork locally to your computer:

$ git clone
$ cd lasio

Your fork will be called the “origin” repository - you’ll need to know this for when you push/pull changes to and from your computer.

Adding kinverarity1/lasio as “upstream”

Now also add the kinverarity1/lasio repository as the “upstream” repository. This is so that when other people make changes to kinverarity1/lasio, you can “pull” those changes into your local copy:

$ git remote add upstream

To update the main branch of the local copy you have of your fork from the “upstream” repository:

$ git checkout main
$ git pull upstream main

And to update the GitHub fork from your local copy:

$ git checkout main
$ git push origin main

Making sure you have necessary development dependencies

There are some additional packages you needing for running unit/regression tests (pytest) and formatting Python code (black). You can install these easily by using:

$ pip install --editable ".[test]"

Making changes to the code

First, start by making sure your local copy is using the latest copy of code from “upstream” main (see above). Then create a branch - you can call it whatever is meaningful to you. We switch to main so that your changes are relative to the latest copy of the code in main:

$ git checkout main
$ git checkout -b your-branch-name
Switched to a new branch 'your-branch-name'

(your-branch-name) $

Then you can make your changes. To test them, make sure you have an “editable” installation of lasio in your Python environment. Shift to the root folder of the repository and run:

$ pip install -e .

Then to run all the tests:

$ pytest

Before publishing your changes please make the code is formatted using black:

$ black .

Then you can push your changes to your fork:

$ git push origin your-branch-name

And follow the instructions on your fork’s GitHub page to open a pull request (PR) for lasio!

Making changes to the documentation

Just as valuable as changes to the code, are changes or improvements to the Sphinx documentation! If you would like to help in this regard, you will need Sphinx and IPython installed:

$ pip install sphinx IPython sphinx_rtd_theme

Then create a new branch as above. The documentation is written in RestructuredText, and can be found in the docs/source subfolder of the lasio repository. If you have any changes, you can build a local copy of the HTML repository to test how it looks. First change into the docs folder:

$ cd docs

Then run this to generate a local copy of the HTML docs in the build/html folder:

$ make clean
$ make html

Once you are happy, please publish your branch and open a PR in the same way as above.


Every time lasio’s main branch is updated, automated tests are run using GitHub Actions on Python 3.6, 3.7, 3.8, 3.9 and 3.10 on Ubuntu and Windows. lasio may work on Python 3.3, 3.4, 3.5 but these are not regularly tested.

To run tests yourself:

$ pip install "lasio[test]"
$ pytest

Comparative Benchmarking of performance when reading LAS files

The test file tests/ reads in a large LAS file and is used to generate the data used in the following benchmark comparisons.

To compare two branches, run and store the benchmark from the first branch e.g. main and generate the benchmark from the second branch e.g. dev-branch. Then run the comparison command.

This same basic technique can be used for testing subsquent changes on a branch.

Make benchmark report for first branch:

$ mkdir ../lasio-benchmarks
$ git checkout main
$ pytest tests/ --benchmark-autosave --benchmark-storage ../lasio-benchmarks

Make benchmark report for second branch.

$ git checkout dev-branch
$ pytest tests/ --benchmark-autosave --benchmark-storage ../lasio-benchmarks

List the available benchmark reports. Their names start with an incremented number: 0001, 0002, etc, followed by their git commit.

$ pytest-benchmark  --storage file://../lasio-benchmarks list

Compare two benchmark reports. If the terminal is set to display color then the output will color data green for better performance and red for worse performance.

$ pytest-benchmark  --storage file://../lasio-benchmarks compare 0001 0002

--------------------------------------------------------------------------------------------- benchmark: 2 tests ---------------------------------------------------------------------------------------------
Name (time in ms)                                Min                 Max                Mean            StdDev              Median               IQR            Outliers     OPS            Rounds  Iterations
test_read_v12_sample_big (0001_d39237c)     149.3796 (1.0)      157.5133 (1.00)     150.8693 (1.00)     2.9515 (1.03)     149.5928 (1.0)      0.7392 (2.43)          1;1  6.6283 (1.00)          7           1
test_read_v12_sample_big (0002_ede364a)     149.6045 (1.00)     157.3494 (1.0)      150.8314 (1.0)      2.8771 (1.0)      149.7972 (1.00)     0.3038 (1.0)           1;1  6.6299 (1.0)           7           1

Publishing a new release

  1. Ensure you are on main: $ git checkout main
  2. Ensure you are using the latest copy of main: $ git pull origin main
  3. Check for any local changes to main: $ git status - test locally and push if necessary.
  4. Check that GitHub Actions Python CI for main is passing.
  5. Find changes since last version release: see list of commits.
  6. Summarise these changes in List of changes.
  7. Run the Jupyter Noteook at docs/Add links to GitHub for all issue and PR refs in changelog.ipynb to add hyperlinks for all issue and PR references.
  8. Edit the citation file: CITATION.cff
  9. Commit with a message e.g. Release v1.3
  10. Tag with the same message e.g. git tag v1.3
  11. Push to github - first the commit: git push origin main --tags
  12. Create a universal wheel: python bdist_wheel --universal
  13. This will put a new wheel file in dist/
  14. Also create a source distribution: python sdist
  15. This will put a source distribution archive in dist/
  16. Upload all the new distribution release files (wheel and archive) to PyPI: twine upload -u USERNAME -p PASSWORD dist/file
  17. Create a new GitHub release via - select the tag
  18. Copy the CHANGELOG text in - convert to RST to Markdown quickly by replacing `# with # and removing `_
  19. Copy the wheel and source distribution archive files into the release page.
  20. Publish the release.

That’s it.


Please feel free to email me at with any suggestions, criticisms, questions, example files.

Code of Conduct

Our Pledge

In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.

Our Standards

Examples of behavior that contributes to creating a positive environment include:

  • Using welcoming and inclusive language
  • Being respectful of differing viewpoints and experiences
  • Gracefully accepting constructive criticism
  • Focusing on what is best for the community
  • Showing empathy towards other community members

Examples of unacceptable behavior by participants include:

  • The use of sexualized language or imagery and unwelcome sexual attention or advances
  • Trolling, insulting/derogatory comments, and personal or political attacks
  • Public or private harassment
  • Publishing others’ private information, such as a physical or electronic address, without explicit permission
  • Other conduct which could reasonably be considered inappropriate in a professional setting

Our Responsibilities

Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.

Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.


This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers.


Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at The project team will review and investigate all complaints, and will respond in a way that it deems appropriate to the circumstances. The project team is obliged to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.

Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project’s leadership.


This Code of Conduct is adapted from the Contributor Covenant version 1.4.