semvec/pypi-packages huggingface dataset:
aviral 1.0
Api wrapper for IIIT Allahabad aviral portal
License: MIT
Keywords: IIITA,Aviral,IIIT-A,indian institute of information technology allahabad

Use aviral in your python application with ease, check marks, get details or make a sign in with aviral option in your application. This bypasses the static content calls so response is much faster then aviral website. Get your marks in less then 1 second even during when the main site is running slow.   for full api documentation [Click HERE.](https://shivamhw.github.io/aviral)
pytubes 0.8.1
A library for efficiently loading data into Python
License: MIT

pytubes
=======

Source: https://github.com/stestagg/pytubes

Pytubes is a library that optimizes loading datasets into memory.

At it’s core is a set of specialized C++ classes that can be chained together to load and manipulate data using a standard iterator pattern. Around this there is a cython extension module that makes defining and configuring a tube simple and straight-forward.



Simple Example
--------------

>>> from tubes import Each
>>> import glob
>>> tube = (Each(glob.glob("*.json"))   # Iterate over some filenames
        .read_files()                   # Read each file, chunk by chunk
        .split()                        # Split the file, line-by-line
        .json()                         # parse json
        .get('country_code', 'null'))   # extract field named 'country_code'
>>> set(tube)                           # collect results in a set
{'A1', 'AD', 'AE', 'AF', 'AG', 'AL', 'AM', 'AO', 'AP', ...}

More Complex Example
--------------------

>>> from tubes import Each
>>> import glob

>>> x = (Each(glob.glob('*.jsonz'))
        .map_files()
        .gunzip()
        .split(b'\n')
        .json()
        .enumerate()
        .skip_unless(lambda x: x.slot(1).get('country_code', '""').to(str).equals('GB'))
        .multi(lambda x: (
            x.slot(0),
            x.slot(1).get('timestamp', 'null'),
            x.slot(1).get('country_code', 'null'),
            x.slot(1).get('url', 'null'),
            x.slot(1).get('file', '{}').get('filename', 'null'),
            x.slot(1).get('file', '{}').get('project'),
            x.slot(1).get('details', '{}').get('installer', '{}').get('name', 'null'),
            x.slot(1).get('details', '{}').get('python', 'null'),
            x.slot(1).get('details', '{}').get('system', 'null'),
            x.slot(1).get('details', '{}').get('system', '{}').get('name', 'null'),
            x.slot(1).get('details', '{}').get('cpu', 'null'),
            x.slot(1).get('details', '{}').get('distro', '{}').get('libc', '{}').get('lib', 'null'),
            x.slot(1).get('details', '{}').get('distro', '{}').get('libc', '{}').get('version', 'null'),
        ))
    )
>>> print(list(x)[-3])
(15,612,767, '2017-12-14 09:33:31 UTC', 'GB', '/packages/29/9b/25ef61e948321296f029f53c9f67cc2b54e224db509eb67ce17e0df6044a/certifi-2017.11.5-py2.py3-none-any.whl', 'certifi-2017.11.5-py2.py3-none-any.whl', 'certifi', 'pip', '2.7.5', {'name': 'Linux', 'release': '2.6.32-696.10.3.el6.x86_64'}, 'Linux', 'x86_64', 'glibc', '2.17')
oomf 0.0.12
Obvious Open Mining Format
License: MIT
Requires Python: >=3.6

# Obvious Open Mining Format (OOMF)

The Open Mining Format (OMF) is an attempt at standardizing the way mining (and more general geoscience data) is serialized and managed.
Goals shared ont he [OMF read the docs page](https://omf.readthedocs.io/en/latest/):

> - The goal of Open Mining Format is to standardize data formats across the mining community and promote collaboration
> - The goal of the API library is to provide a well-documented, object-based interface for serializing OMF files

OMF is based around the [properties](https://github.com/seequent/properties) project developed by Seequent, and naturally Seequent is one of the biggest supporters of OMF.

This is a fantastic idea. Sharing data, geologic models, variograms etc across commercial software platforms and open source tools can be challenging. The OMF library Python API does not lack functionality but it is simply diffcult to use. OOMF is an attempt to provide a wrapper to the OMF API and making this format a bit more approachable.

If you find yourself using this little tool please feel free to log any issues, contribute etc.

To install:
`pip install oomf`

A short blog post with a few example: [here](https://geostats.dev/mining/omf/seequent/open%20mining%20format/geostatistics/2020/11/08/Oomf.html)
uberduckapi 0.1.18
Python wrapper for uberduck API
License: MIT
Requires Python: >=3.7,<4.0

# Python wrapper for the [UberDuck](https://uberduck.ai) API
This is a python wrapper for the uberduck api. You must have api access to use.

# How this works?
Well you first initialize a job by sending a request with your api key, secret, text, and voice name.\
After sending the request uberduck will issue a response with the status of the job.
So the api will poll this endpoint till a result is produced. the result is another url to the sound file that was created

Check the example.py for code