semvec/pypi-packages huggingface dataset:
pyfixtures 1.1.0
Pytest style fixtures outside of Pytest.
License: MIT
Requires Python: >=3.8,<4.0

# PyFixtures

[Pytest](https://docs.pytest.org/en/7.1.x/) style [fixtures](https://docs.pytest.org/en/6.2.x/fixture.html) outside of Pytest.

```python
import asyncio
from pathlib import Path
from pyfixtures import fixture, FixtureScope

@fixture
def tmpdir() -> path:
    path = Path("temp")
    path.mkdir()
    try:
        yield path
    finally:
        path.unlink()



def mk_temp_files(tmpdir: Path):
    tmp_file = tmpdir/"tempfile.txt"
    tmp_file.touch()


async def main():
    async with FixtureScope() as scope:
        operation = await scope.bind(mk_temp_files)
        await operation()


asyncio.run(main())

```
pysoar 1.0.2
A data analysis tool for translocations in nanopores
License: MIT
Keywords: nanopore sensing,single molecule detection,signal processing,data analysis

# PySOAR

PySOAR is a Python (3.9+) package for data analysis of translocation events during nanopore sensing. The main features include:
* Baseline correction function.
* Splitting the current into bins and doing a Poisson fit on that data to help the user visually decide on what threshold should be used for this data.
* Finding peaks function based on the threshold chosen.
* Ability to extract features from the events using both CUSUM and ADEPT methods.
* Histogram plots of peak curretn and dwell time data.

# Installation

To install with pip:
'''

pip install --user pysoar

'''

PySOAR utilises the following external libraries:
* [NumPy](https://numpy.org/)
* [SciPy]((https://scipy.org/))
* [ruptures](https://centre-borelli.github.io/ruptures-docs/)
* [matplotlib](https://matplotlib.org/)

# Acknowledgements
Developed by Vladimir Ivanov as part of the MSci final year project while working with the Edel's group at Imperial College London
goldenhinges 0.2.3
DNA overhang design for Golden Gate etc.
License: MIT
Keywords: DNA assembly overhangs constraint-programming synthetic-biology

Golden Hinges
=============

Golden Hinges (full documentation `here <https://edinburgh-genome-foundry.github.io/GoldenHinges/>`_) is a Python library to find sets of overhangs (also called junctions, or protrusions) for multipart DNA assembly such as Golden Gate assembly.

Given a set of constraints (GC content bounds, differences between overhangs,
mandatory and forbidden overhangs) Golden Hinges enables to find:

- Maximal sets of valid and inter-compatible overhangs.
- Sequence decompositions (i.e. position of cuts) which produce valid and
  inter-compatible overhangs, for type-2S DNA assembly.
- Sequence mutations (subject to constraints) which enable the sequence
  decomposition, in extreme cases where the original sequence does not allow
  for such decomposition.

Infos
-----

**PIP installation:**

.. code:: bash

  pip install goldenhinges

**Web documentation:**

`<https://edinburgh-genome-foundry.github.io/GoldenHinges/>`_

**Github Page (with examples)**

`<https://github.com/Edinburgh-Genome-Foundry/GoldenHinges>`_

**Live demo:**

`<http://cuba.genomefoundry.org/design_overhangs>`_

**License:** MIT, Copyright Edinburgh Genome Foundry

More biology software
---------------------

.. image:: https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/Edinburgh-Genome-Foundry.github.io/master/static/imgs/logos/egf-codon-horizontal.png
  :target: https://edinburgh-genome-foundry.github.io/

Golden Hinges is part of the `EGF Codons <https://edinburgh-genome-foundry.github.io/>`_ synthetic biology software suite for DNA design, manufacturing and validation.