semvec/pypi-packages huggingface dataset:
assembly-stats 0.1.4
Calculates both scaffold and contig statistics (N50, L50, etc.) from a scaffold FASTA file.

# assembly_stats

A Python library that takes a FASTA file as input and calculates both scaffold and contig statistics (N50, L50, etc.) from a scaffold FASTA file. It does this by breaking each scaffold wherever there is more than one N and then calculating statistics for both the scaffolds and contigs.

This is a re-write of [fasta_metadata_parser](https://github.com/pbfrandsen/fasta_metadata_parser) to speed up the old implementation, and -- most importantly -- to learn how to install Python scripts onto the Smithsonian HPC.

## Installation

```
pip install assembly_stats
```

## Usage

```
  $ assembly_stats -h

    usage: assembly_stats [-h] filename

    Calculate statistics about genome assemblies.

    positional arguments:
      filename    Genome file in FASTA format.

    optional arguments:
      -h, --help  show this help message and exit
```

After calculating the statistics for the genome assembly, they will be printed out in JSON format.

Next steps
----------

* Add ability to save NumPy sequence length arrays for further visualization, since generating these are what takes the most time.
deadset 0.2
Deadset is a Python 3 module that implements expiration for Redis Keys items.
Requires Python: >=3.6

# deadset

A python class that provides item level expiration functionality for redis.

# Links to inspiration sources:

[TTL for a Set Member](https://stackoverflow.com/questions/17060672/ttl-for-a-set-member)
[How to expire List Items inRedis](https://quickleft.com/blog/how-to-create-and-expire-list-items-in-redis/)
thresholdmodeling 0.0.1
This package is intended for those who wish to conduct an extreme values analysis. It provides the whole toolkit necessary to create a threshold model in a simple and efficient way, presenting the main methods towards the Peak-Over-Threshold Method and the fit in the Generalized Pareto Distribution. For installing and use it, go to https://github.com/iagolemos1/thresholdmodeling
Requires Python: >=3.6

This package is intended for those who wish to conduct an extreme values analysis. It provides the whole toolkit necessary to create a threshold model in a simple and efficient way, presenting the main methods towards the Peak-Over-Threshold method and the fit in the Generalized Pareto Distribution.