semvec/pypi-packages huggingface dataset:
subsplease.py 1.2.1
A simple and asynchronous wrapper for SubsPlease
Requires Python: >=3.9

# subsplease.py 
A simple and asynchronous wrapper for SubsPlease.

# Installation
```
pip install subsplease.py
```

# Implementation
```python
from subsplease import SubsPlease

client = SubsPlease(
    timeout=100 # Optional
)

async def save_new_releases():
    releases = await client.get_latest_magnet()
    with open("magnet.txt", "w") as file:
        file.writelines(f"{release.title}: {release.link}\n" for release in releases)
```
WarzoneStats 0.1.2
Python wrapper for the COD API (Warzone) as well as wzstats.gg, with some useful functions to process and parse the stat responses.
Keywords: python,warzone,tracker,tracker.gg,sbmm,kd


# WarzoneStats

WarzoneStats is a Python wrapper for the COD Warzone Api (https://documenter.getpostman.com/view/5519582/SzzgAefq). There is an additional wrapper for the https://wzstats.gg/ website. There are also some helpful functions to extract useful data from the api responses.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install WarzoneStats.

```bash
pip3 install WarzoneStats
```

## Usage

Before using the COD Api you first need to login to [Activision](https://www.activision.com/) and get the ACT\_SSO\_COOKIE

You can do this in Chrome by going into inspect element -\> Application tab -\> Cookies -\> enter ACT\_SSO\_COOKIE into the filter field

Copy and save this value to use in the package

**You should be caching the return values from both Api and ApiGG so you don't keep sending the same request and end up getting ip banned**
 
### COD Api
```python
from WarzoneStats import Api

username = 'huskerrs#1343'

# Can see the platform values by referencing Api.Platforms
platform = 'battle' 

sso = 'Get this value from the ACT_SSO_COOKIE that is set in Chrome by logging into activision.com'

api = Api(username, platform, sso)

# You can view all sample responses in the Sample Endpoint Responses Folder

# This endpoint returns lifetime stats like kd, gun accuracy, weekly stats, etc
profile = api.get_profile()
print(profile['data']['lifetime']['all']['properties']['kdRation'])

# This endpoint returns 20 recent matches with everything from team name, team placement to the loadouts everyone used
recentMatches = api.get_recentMatches()	
print(recentMatches['data']['summary']['all']['kills'])

# Returns 1000 recent matches, with only the timestamps, matchIds, mapId, and platform
# Useful for using matchIds to get stats of that match (lobby kd etc)
matches = api.get_matches()
matchId = recentMatches['data'][0]['matchId']
print(matchId)

# Returns the details of the specific match per player; each players stats from the loadout they used to the kills they got is listed
matchDetails = api.get_matchDetails(matchId)
print(matchDetails['data']['allPlayers'][0]['player']['username'])
```

### wzstats.gg
```python
from WarzoneStats import ApiGG

username = 'nrg joewo#2631118'
platform = 'acti'

api = ApiGG()

stats = api.get_stats(username, platform)
print(stats)
```

### parser
```python
from WarzoneStats import ApiGG, ParserGG

username = 'nrg joewo#2631118'
platform = 'acti'

api = ApiGG()

stats = api.get_stats(username, platform)

parser = ParserGG()

print(parser.get_average_kd_lobbies(stats))

''' and '''

# Get this from either Api or ApiGG response
match_id = '6702851451945654660'

match = api.get_match(match_id)

print(parser.get_average_lobby_kd(match)


```

## License
[MIT](https://choosealicense.com/licenses/mit/)
poetress 1.0.1
Poetry Storage and Retrieval
Keywords: python,poetess

# Poetess

Poetress is a poetry retrieval and storage system.
It fetches poems from the poetry foundation website and
creates a local copy. Inclues the poem of the day.

## Installation
Use the package manager [pip](https://pip.pypa.io/en/stable/) to install poetress.

```bash
pip install poetress
```
or if you're not into pip you can clone this repo and run this command:
```
git clone https://github.com/bwinnett12/poetress.git
python3 setup.py develop
```

## Usage
Run poetress through command line to store to a designated drive. By default, that will be
stored in "./poetry_storage which isn't anywhere if you installed through pip. If you want a self-
contained solution simply run poetess only there. You can opt to select that storage location
if you run:
```
poetess -c
```
 Otherwise, you are set up. Run poetess with the -d to grab today's poem or -f to select a
 desired specific poem. Example:
 ```
 poetess -d // Fetches the poem of the day
 poetess -f [Specific poem] // Fetches a specific poem
 poetess -c // Config wizard
 ```

If you want to reset the storage location or the max amount of characters per line
with the config wizard using -c

### Contributing
If you want to contribute, by all means make a pull request.

### License
[MIT](https://choosealicense.com/licenses/mit/)
stuffpy 0.0.1
A package for stuff
Requires Python: >=3.10

#Disable
Disable is a context manager that disables output and specified errors. `with Disable(Exception) as (write, flush):` has the following effect: print statements do nothing and all subclasses of Exception do not propagate to the caller if raised. "Write" and "flush" are used for writing and flushing.

#Parallel
Parallel is basically zip and map combined. It can take an iterable of iterables or multiple iterables and zips them. If the func argument is used then it works like map. There is also a strict option.
spol 0.0.1
Pakistan Sindh Police
Keywords: pakistan,sindh,police,complaint,query,search,units

spol
====

A package to check various functions offered by Sindh Police.


Details
-------

Taps into the Sindh Police database.

Package Usage
-------------

import spol

\# check complaint

spol.check_complaint(1)

spol.list_hospitals()

spol.list_units()

spol.list_unit(3)
bdgenomics.adam 1.0
A fast, scalable genome analysis system

# ADAM

ADAM is a library and command line tool that enables the use of [Apache
Spark](https://spark.apache.org) to parallelize genomic data analysis across
cluster/cloud computing environments. ADAM uses a set of schemas to describe
genomic sequences, reads, variants/genotypes, and features, and can be used
with data in legacy genomic file formats such as SAM/BAM/CRAM, BED/GFF3/GTF,
and VCF, as well as data stored in the columnar
[Apache Parquet](https://parquet.apache.org) format. On a single node, ADAM
provides competitive performance to optimized multi-threaded tools, while
enabling scale out to clusters with more than a thousand cores. ADAM's APIs
can be used from Scala, Java, Python, R, and SQL.

## Documentation

ADAM's documentation is hosted at [readthedocs](http://adam.readthedocs.io).

## Python Requirements

ADAM depends on having PySpark installed.