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package-structure-code/intro.md

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# Python package structure information
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# Python package structure information
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If you plan to submit a package for review to pyOpenSci and are looking for
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some guidance on package structure, code formats and style, then this section
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is for you.
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If you plan to submit a package for review to pyOpenSci and are looking for
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some guidance on package structure, code formats and style, then this section
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is for you.
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<!-- TODO: move this either to the top of this section or the landing page?-->
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```{note}
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Have a look at the
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Have a look at the
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bare-minimum [editor checks](https://www.pyopensci.org/peer-review-guide/software-peer-review-guide/editor-in-chief-guide.html#editor-checklist-template) that pyOpenSci
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performs before a review begins. These checks are useful to explore
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for both authors planning to submit a package to us for review and for
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anyone who is just getting started with creating a Python package.
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performs before a review begins. These checks are useful to explore
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for both authors planning to submit a package to us for review and for
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anyone who is just getting started with creating a Python package.
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In general these are basic items that should be in any open software repository.
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In general these are basic items that should be in any open software repository.
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```
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## Guidelines for pyOpenSci's packaging recommendations
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## Guidelines for pyOpenSci's packaging recommendations
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<!-- Might belong on the LANDING page for this entire guide?-->
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Python is a flexible programming language that is used across numerous
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disciplines and domains. Python is so flexible that it is one of the few
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Python is a flexible programming language that is used across numerous
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disciplines and domains. Python is so flexible that it is one of the few
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languages that can be used to wrap around other languages.
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If you are building a pure Python package, then your packaging setup can be
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simple. However, some scientific packages have complex requirements as they may
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If you are building a pure Python package, then your packaging setup can be
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simple. However, some scientific packages have complex requirements as they may
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need to support extensions or tools written in other languages such as C or C++.
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To support the many different uses of Python, there are many ways to create a
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Python package.
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To support the many different uses of Python, there are many ways to create a
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Python package.
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The ecosystem is dynamic, and constantly evolving to support
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the numerous needs that developers (and scientists) have using Python.
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the numerous needs that developers (and scientists) have using Python.
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This dynamic yet flexible environment is what many love about Python.
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This dynamic yet flexible environment is what many love about Python.
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## What you will learn here
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## What you will learn here
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In this section of our Python packaging guide, we try to:
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* Provide an overview of the options available to you when packaging your tool
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* Suggest tools and approaches that both meet your needs and also support existing standards.
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* Suggest tools and approaches that will allow you to expand upon a workflow that may begin as a pure Python tool and evolve into a tool that requires addition layers of complexity in the packaging build.
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* Provide an overview of the options available to you when packaging your tool
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* Suggest tools and approaches that both meet your needs and also support existing standards.
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* Suggest tools and approaches that will allow you to expand upon a workflow that may begin as a pure Python tool and evolve into a tool that requires addition layers of complexity in the packaging build.
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* Align our suggestions with the most current, accepted
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[PEPs (Python Enhancement Protocols)](https://peps.python.org/pep-0000/) and the [scientific-python community SPECs](https://scientific-python.org/specs/).
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* In an effort to maintain consistency withint our community , we also align with existing best practices being implemented by developers of core Scientific Python packages such as numpy, scipy and others.
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[PEPs (Python Enhancement Protocols)](https://peps.python.org/pep-0000/) and the [scientific-python community SPECs](https://scientific-python.org/specs/).
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* In an effort to maintain consistency withint our community , we also align with existing best practices being implemented by developers of core Scientific Python packages such as numpy, SciPy and others.
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<!--
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These checks include several items
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- **Sufficient Documentation** The package has sufficient documentation available online (README, sphinx docs) to allow us to evaluate package function and scope *without installing the package*. This includes:
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Get started tutorials or vignettes that help a user understand how to use the package and what it can do for them (often these have a name like "Getting started")
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- **API documentation** - this includes clearly written doc strings with variables defined using a standard docstring format -->
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<!--
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<!--
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```{tip}
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### Python packaging resources that we love
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### Python packaging resources that we love
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We think the resources below are excellent but each have particular opinions
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We think the resources below are excellent but each have particular opinions
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that you may or may not find in our packaging guide. For instance, the PyPA
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guide encourages users to store their package in a `src/package-name` directory.
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While we accept that approach many of our community members prefer to not use
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the `src` directory.
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While we accept that approach many of our community members prefer to not use
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the `src` directory.
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* [Python packaging for research software engineers](https://merely-useful.tech/py-rse/)
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* [PyPA packaging guide](https://packaging.python.org/en/latest/)
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```
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-->
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-->

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