Metadata-Version: 2.4
Name: fastccc-modern
Version: 1.0.1.post1
Summary: Focused, maintained FastCCC runtime for cell-cell communication analysis
Author-email: Svvord <cchousiyu@163.com>
Maintainer: ChatSpatial maintainers
License-Expression: MIT
Project-URL: Homepage, https://github.com/cafferychen777/FastCCC
Project-URL: Source, https://github.com/cafferychen777/FastCCC
Project-URL: Original project, https://github.com/Svvord/FastCCC
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: <3.15,>=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: NOTICE.md
Requires-Dist: anndata<0.14,>=0.10
Requires-Dist: loguru<0.8,>=0.7.2
Requires-Dist: numpy<2.6,>=1.24
Requires-Dist: pandas<3.1,>=2.2.3
Requires-Dist: psutil<8,>=6.1.1
Requires-Dist: scanpy<2,>=1.10.3
Requires-Dist: scipy<2,>=1.14.1
Dynamic: license-file

# fastccc-modern

`fastccc-modern` is a focused, maintained distribution of the FastCCC
permutation-free cell-cell communication runtime. It keeps the two statistical
analysis entry points used by ChatSpatial while removing reference-building,
browser documentation, notebooks, bundled reference data, visualization, and
HTML report generation.

The import name remains `fastccc`:

```python
import fastccc

fastccc.statistical_analysis_method(...)
```

## Why this distribution exists

FastCCC 1.0.1 requires Jinja2 3.1.6 solely for its optional HTML report layer.
CellRank 2.3.2 depends on the PyPI release of pyGPCCA 1.0.4, whose metadata pins
Jinja2 3.0.3 for a historical linting workaround even though pyGPCCA does not
import Jinja2 at runtime. Those metadata constraints make the two scientific
runtimes impossible to install together.

This distribution removes FastCCC's unused report layer and therefore has no
Jinja2 dependency. Its statistical runtime can coexist with CellRank and
pyGPCCA in a standard pip environment without dependency overrides.

## Scope

Included:

- single-method FastCCC statistical analysis;
- Cauchy combination analysis;
- CellPhoneDB-format input preprocessing;
- interaction strength and analytical p-value calculations.

Not included:

- HTML report generation and plotting;
- bundled databases or tissue reference panels;
- reference-panel construction and query tooling;
- notebooks and documentation-site assets.

ChatSpatial downloads and validates the CellPhoneDB tables separately, so
shipping duplicate databases in this wheel is unnecessary.

## Attribution

The algorithms and original implementation are from
[Svvord/FastCCC](https://github.com/Svvord/FastCCC). See `NOTICE.md` and
`LICENSE` for details.
