semvec/pypi-packages huggingface dataset:
pytest-common-subject 1.1.2
pytest framework for testing different aspects of a common method
License: MIT
Requires Python: <4.0,>=3.9
Keywords: pytest

# pytest-common-subject
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**pytest-common-subject** is a "framework" for organizing tests to reduce boilerplate while writing, improve skimmability when reading, and bolster parallelization when executing the suite.

To utilize this framework, we first choose a single function that our group of tests will all call — in other words, an entry point, or a _common subject_. This function will be automatically called before each of our tests, with args and kwargs that can be customized by overriding fixtures — enabling child test classes to make HTTP requests as a different user, or to use a different cache backend, or to change the value of a monkeypatched method.

The return value of the chosen function will be passed as a fixture to each test. To reap the full benefits of the framework, create separate tests to verify different aspects of the return value. Was the response status code a 200? Did the response contain the expected data? Were the expected rows created in the database? By using separate tests for each of these aspects, we can pinpoint and correct multiple bugs at once, instead of getting sucked into a fix-test-fix cycle with its chorus of "oh, bother, not again!"
visiumhd-utils 0.2.2
Tools for pre-processing and visualizing Visium HD spatial transcriptomics data.
License: MIT
Requires Python: >=3.8

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==============
visiumhd_utils
==============


    Tools for pre-processing and visualizing Visium HD spatial transcriptomics data.


Features
--------
- Read in raw VisiumHD data and convert to SpatialData objects
- Quality control metric plotting and image plotting
- Destripe counts from raw 2um bins
- Write updated counts back to raw VisiumHD data format

Installation
------------

Install from PyPI:

.. code-block:: bash

    pip install visiumhd-utils

Usage
-----

.. code-block:: python

    import visiumhd_utils.read_data as rd 
    import visiumhd_utils.qc_plot as qp
    import visiumhd_utils.destripe as ds
    import visiumhd_utils.write_data as wd

    sdata = rd.to_spatialdata("path/to/data", "id")
    qp.compute_qc_metrics(sdata)
    qp.plot_qc_metrics(sdata, "id", metric="pct_counts_mt")
    ds.destripe_b2c(sdata)
    wd.write_2um_filtered_counts(sdata, "path/to/folder")


Project Status
--------------

This package is in early development. Use with caution; interfaces may change. 


.. _pyscaffold-notes:

Note
====

This project has been set up using PyScaffold 4.6. For details and usage
information on PyScaffold see https://pyscaffold.org/.