Metadata-Version: 2.1
Name: pacsanini
Version: 0.2.1
Summary: A package for DICOM utilities.
License: Apache 2.0
Keywords: DICOM,PACS,medical imagery
Author: Aurélien Chick
Author-email: achick@therapixel.com
Maintainer: Aurélien Chick
Maintainer-email: achick@therapixel.com
Requires-Python: >=3.7.1,<4.0.0
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Build Tools
Requires-Dist: PyYAML (>=5.4)
Requires-Dist: SQLAlchemy-Utils (>=0.37.8,<0.38.0)
Requires-Dist: SQLAlchemy[mypy] (>=1.4.22,<2.0.0)
Requires-Dist: alembic (>=1.7.4,<2.0.0)
Requires-Dist: click (>=7.1.2,<8.0.0)
Requires-Dist: dash (>=2.0.0,<3.0.0)
Requires-Dist: loguru (>=0.5.3,<0.6.0)
Requires-Dist: pandas (>=1.2.4,<2.0.0)
Requires-Dist: prefect (>=0.15.6,<0.16.0)
Requires-Dist: pydantic (>=1.7.4)
Requires-Dist: pydicom (>=2.1.2,<3.0.0)
Requires-Dist: pynetdicom (>=1.5.7,<2.0.0)
Description-Content-Type: text/markdown

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# pacsanini

`pacsanini` 🎻 is a package designed to help with the collection of DICOM files and the extraction
of DICOM tags (metadata) for structuring purposes.

`pacsanini`'s functionalities come out of a desire to facilitate research in
medical imagery by easing the process of data collection and structuring.
The two main pain points for this are:

* acquiring data from a PACS
* extracting metadata from DICOM files in research-ready formats (eg: csv)

The project seeks to target medical/research professionals that are not necessarily
familiar with coding but wish to obtain data sets and software engineers that wish to
build applications with a certain level of abstraction.

## Documentation

Check out the complete documentation on [readthedocs](https://pacsanini.readthedocs.io/en/latest/).
You will be able to find examples on how to use the `pacsanini` API from within you Python application
and as a command line tool.

## Contributing and Code of Conduct

All contributions to improve `pacsanini` are welcome and valued. For more information on how you can contribute,
please read the [Contributing](CONTRIBUTING.md) document and make sure that you are familiar with our
[Code of Conduct](CODE_OF_CONDUCT.md).

You are also more than welcome to open a discussion on our [GitHub discussions](https://github.com/Therapixel/pacsanini/discussions) page.

## Installation

To install a particular release version, check out the available versions of `pacsanini` on [PyPI](https://pypi.org/project/pacsanini/)
or simply run the following command to obtain the latest release:

```bash
pip install pacsanini
```

To obtain the cutting edge version of `pacsanini`, you can use `pip` or `poetry` in the following way:

```bash
pip install git+https://github.com/Therapixel/pacsanini.git
# or
poetry add git+https://github.com/Therapixel/pacsanini.git
```
### For development

`poetry` is the only supported build tool for installing `pacsanini` in a development context.
See the previous section on how to install `poetry`.

```bash
git clone https://github.com/Therapixel/pacsanini.git
cd pacsanini
poetry install --no-root --no-dev
# or, to install the project and its development dependencies:
poetry install --no-root
```

### Usage with docker

A docker image can be built locally to run `pacsanini` within an isolated environment.

```bash
docker image build -t pacsanini:latest .
docker run pacsanini --help
```

## Roadmap

The following topics are the main areas where `pacsanini` can improve as a library and a tool.
Of course, these topics are up for discussion and such discussions are encouraged in the
[GitHub issues](https://github.com/Therapixel/pacsanini/issues) section.

