semvec/pypi-packages huggingface dataset:
PeptideSearch 0.1
Search a list of peptides in a fasta file (or proteome) and returns exact matches or hits with one mismatch
License: MIT
Keywords: Peptide Search,Peptide Match,One Mismatch,Exact Match,python,Peptide,Protein

Useful tools to work with Elastic stack in Python

# Description
    
This tool consists one module:

- `PeptideSearch`: this tool searches for peptides in a fasta file including proteins, it can find Exact Match or Marches with up to One Mismatch 

# Installation
 
## Normal installation

```bash
pip install PeptideSearch
```

## Development installation

```bash
git clone https://github.com/khaledianehdieh/PeptideSearch.git
```

# Change log

## [0.1] - 2021-08-02
- Created
xicsrt-contrib 0.7.0
Contributed modules for the xicsrt raytracing code.
License: MIT
Requires Python: >=3.8

XICSRT: Contributed Modules
===========================
 
Git Repository: https://bitbucket.org/amicitas/xicsrt_contrib  
Git Mirror: https://github.com/PrincetonUniversity/xicsrt_contrib


Purpose
-------
A collection of community contributed modules for extension of the XICSRT 
raytracing code.

The optic, source and filter objects in this repository are meant for use with
XICSRT. These are extra objects that may be useful to an XICSRT user but have 
not been included as built-in objects for one of the following reasons:

- Usage is too specific for general use.
- Non-standard external dependencies.
- Performance and stability not at production quality.

Some of these objects may eventually be moved into the main repository as their
development advances.


Installation
------------
The XICSRT contributed modules can be simply installed using `pip`

    pip install xicsrt_contrib

Alternatively it is possible to install from source using `setuptools`

    python setup.py install

After installation xicsrt should natively see all available contributed objects
in the same way as built-in objects.


Usage
-----
Use xicsrt normally; after installation the contributed objects are natively 
available.