semvec/pypi-packages huggingface dataset:
epic-http-py 0.0.1
HTTP wrapper for the Epic/Fortnite APIs.
Requires Python: >=3.10

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

**Still in early development.**

# Epic-HTTP-Py
An asynchronous, object-oriented API wrapper for the Epic/Fortnite HTTP services, written in Python.

# Key Features
- Use of the `asyncio` framework to handle many IO-bound tasks concurrently.
- Automatic, configurable rate limit handling and caching.
- Optimised for speed and memory.

# Basic Example
```py
import asyncio
import epic

async def main():
    async with epic.HTTPClient() as client:
        auth_code = input(f'Enter authorization code from {client.user_auth_path} here: ')

        async with client.create_auth_session(auth_code) as auth_session:
            account = await auth_session.account()

            print(f'Logged in as: {account}')

asyncio.run(main())
```

# Notes
- This package does not support Epic Games' XMPP services. This includes real-time in-game events such as party invites or whispers.

# Disclaimers
- The APIs that this package interacts with are not officially documented, nor are they intended to be used outside the official clients. As a result, the package could experience major breaking changes (or stop working!) at any moment.
pennant 0.1.5
A high-spirited feature-flagging library for Python.


=======
pennant
=======

A feature flagging library that uses decorators and context management to "feature flag"
certain functions or blocks of code. I feel like it's better than a bunch of conditionals,
but I'm often wrong.

Notes
=====
Contrary to how some folks might do it, this library takes and "opt-out" approach where
setting the flag to False prevents the given function or code block from running. As long
as the argument provided to the decorator or content manager evaluates to False,
anything's game.
plasmidin 1.0.0
A package to look at inserting DNA sequences into plasmids for cloning or PCR for SWBio DTP Data Science and Machine Learning Module
Requires Python: >=3.8

# PlamidInsertChecker
Code for SWbioDTP Data Science and Machine Learning module

This is an installable python package that can be used to interrogate DNA sequences for restriction enzyme cutting sites. It can produce:  
    i. a table of cut sites with useful information on the number of cut sites, the cut site locations, the enzyme cut overhang, and the commercial suppliers  
    ii. a figure showing the cut locations on a plasmid or linear section of DNA

## Installation

Create a virtual environment using your favourite tool, clone the repsotiory to obtain the data and install the package using pip

```
virtualenv env_plasmidin
source env_plasmidin/bin/activate
git clone git@github.com:bmm514/PlamidInsertChecker.git
pip install plasmidin
```

## Basic useage
1. Import required plasmidin Classes
```
from plasmidin.plasmidin import RSInserter
from plasmidin.plasmid_diagrams import PlasmidDrawer
```

2. Input fasta file or bio python Seq() for plasmid and insert
```
plasmid_seq = 'path/to/plasmid_fasta.fa'
plasmid_linear = False
insert_seq = 'path/to/insert_fasta.fa'
insert_linear = True
remove_ambiguous_enzymes = True
```

3. Run analysis on these to find restriction enzyme cut sites and 
show the enzymes of interest i.e. single cut enzymes
```
rsinserter = RSInserter(plasmid_seq, plasmid_linear, insert_seq, insert_linear, remove_ambiguous_enzymes)

rsinserter_XbaI_BamHI.shared_single_enzymes
```

4. Select from the list appropriate restriction enzymes to cut
```
plasmid_cut_enzymes = ('EnzymeA', 'EnzymeB')
insert_cut_enzymes = ('EnzymeA', 'EnzymeB')
```

5. Integrate insert sequence into plasmid sequence 
```
rsinserter.integrate_seq(plasmid_cut_enzymes, insert_cut_enzymes)
```

6. Analyse the output restriction sites and save a table of the restriction sites present
```
integrated_table = '/path/to/restriction_enzymes.csv'

rsinserter.integrated_rsfinder.save_enzyme_table(integrated_table, delimiter = ',')
```

7. Create plasmid map for the integrated sequence
```
input_seq = rsinserter.integrated_rsfinder.input_seq
feature_info = rsinserter.integrated_rsfinder.feature_info
integrated_figure = '/path/to/integrated_restriction_map.pdf'

plasmid_drawer = PlasmidDrawer(input_seq, 'IntegratedSeq', feature_info)
plasmid_drawer.draw_gd_diagram(integrated_figure, 'circular', {'pagesize' : 'A4', 'circle_core' : 0.5, 'track_size' : 0.1})
```
## Examples

See plasmidin_example.py for code to run and produce output from PlasmidInsertChecker:
```
python3 scripts/plasmidin_examples.py
```

This will use the example fasta files in ```data/``` directory and produce output into ```plasmidin_output```