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@@ -7,16 +7,15 @@ version: 2
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# Set the version of Python and other tools you might need
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build:
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os: ubuntu-lts-latest
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os: ubuntu-20.04
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tools:
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python: "3.13"
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python: "3.10"
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jobs:
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pre_install:
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- pip install --upgrade pip
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- pip install --upgrade --upgrade-strategy only-if-needed --group doc .
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# build:
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# html:
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# - python -m sphinx -T -b html -d _build/doctrees -D language=en . $READTHEDOCS_OUTPUT/html
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build:
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html:
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python -m sphinx -T -b html -d _build/doctrees -D language=en . $READTHEDOCS_OUTPUT/html
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post_build:
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- echo "Command run at 'post_build' step"
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- echo `date`
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@@ -1,6 +1,4 @@
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# Contributing
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Contributions to `ptulsconv` are welcome!
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# Contributing to ptulsconv
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## Testing
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@@ -9,35 +7,3 @@ Before submitting PRs or patches, please make sure your branch passes all of the
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```sh
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~/ptulsconv$ pytest
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```
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## Regarding use of Agents
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`ptulsconv` is an open-source project that is offered free for no commerical gain, and
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is developed and maintained for educational and creative reasons.
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If you use an agent or LLM to produce code for it you are missing out on the benefits
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of contributing to an open-source project, particularly community, collaboration with
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other developers and designers, and being able to learn and experiment without the
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burden of deadlines or worrying about business cases or profits.
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This project is supposed to be fun, do not let machines have fun for you.
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We can't prevent you from using LLMs to contribute to this project but we ask you
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abide by the following eitiquette when doing so:
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* All communication with the maintainers must be written by a human in their own
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voice. Never use an LLM to craft thread comments, discussion posts, issues, emails
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or other correspondence with other developers or the maintainers.
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* PRs must be submitted by a person. Do not allow an agent to submit its own PRs to
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this project.
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* Especially if you are a new contributor to this project, please submit only one PR
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at a time and please restrict the subject matter of the PR to a specific unit,
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module or tool. All submissions have to be reviewed and understood by the
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maintainers before they can be merged.
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Obviously we can't verify if you follow all of these rules but certain telltale
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traits of LLM-predicted text or code will raise a flag: lack of brevity in
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descriptions or code comments, large amounts of text describing your process or
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steps that add little to understanding the changes you've made, use of an
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obsequious tone or being excessively accomodating, immediately doing requests
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without further discussion or clarifications.
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