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Contributing

Contributions to Scanpy are highly welcome!

Before filing an issue

  • Search the repository (also google) to see if someone has already reported the same issue. This allows contributors to spend less time responding to issues, and more time on adding features!
  • Please provide a minimal complete verifiable example for any bug. If you're not sure what this means, check out this blog post by Matthew Rocklin or this definition from StackOverflow.
  • Let us know a bit about your environment. This can be as easy as pasting the results of sc.logging.print_versions().

Contributing code

Coding style

We stick to PEP 8 and to this editorconfig and try to stick to 80-character lines. In some cases, wider lines might improve readability, in most cases, not. Docstrings should always be 80 characters.

Docs

We use the numpydoc style for writing docstrings. Either take a look at any Scanpy or Numpy function or here.

The Params abbreviation is a legit replacement for Parameters.

The Returns section deserves special attention: There are three types of return sections – prose, tuple, and a mix of both.

  1. Prose is for simple cases.
  2. Tuple return sections are formatted like parameters. Other than in numpydoc, each tuple is first characterized by the identifier name and not by its type. You can provide type annotation in the function header or by separation with a colon, as in parameters.
  3. Mix of prose and tuple is relevant in complicated cases, e.g. when you want to describe that you added something as annotation to an AnnData object.

Examples

For simple cases, use prose as in pp.normalize_total

Returns
-------
Returns dictionary with normalized copies of ``adata.X`` and ``adata.layers``
or updates ``adata`` with normalized versions of the original
``adata.X`` and ``adata.layers``, depending on ``inplace``.

You can use the standard numpydoc way of populating it, e.g. as in pp.calculate_qc_metrics. If you just use a plain type name here, there will be an automatically created link.

Returns
-------
one_identifier : some_module.some_type
    Description.
second_identifier : another.module.and_type
    Description 2.

Many functions also just modify parts of the passed AnnData object, like e.g. tl.dpt. You can then combine prose and lists to best describe what happens.

Returns
-------
Depending on `copy`, returns or updates `adata` with the following fields.

If `n_branchings==0`, no field `dpt_groups` will be written.

dpt_pseudotime : :class:`~pandas.Series` (``adata.obs``, dtype ``float``)
    Array of dim (number of samples) that stores the pseudotime of each
    cell, that is, the DPT distance with respect to the root cell.
dpt_groups : :class:`pandas.Series` (``adata.obs``, dtype ``category``)
    Array of dim (number of samples) that stores the subgroup id ('0',
    '1', ...) for each cell. The groups  typically correspond to
    'progenitor cells', 'undecided cells' or 'branches' of a process.

Tests

Write tests for your functions! See here for examples.