semvec/pypi-packages huggingface dataset:
oeis.wrap 1.0.2
A basic API wrapper for OEIS.
License: MIT
Requires Python: >= 3.8.0

oeis.wrap
===========

.. image:: https://img.shields.io/github/license/Infiniticity/oeis.wrap
    :target: https://github.com/Infiniticity/oeis.wrap/blob/main/LICENSE.md
    :alt: license
.. image:: https://img.shields.io/tokei/lines/github/Infiniticity/oeis.wrap
    :target: https://github.com/Infiniticity/oeis.wrap/graphs/contributors
    :alt: lines of code
.. image:: https://img.shields.io/pypi/v/oeis.wrap
    :target: https://pypi.python.org/pypi/oeis.wrap
    :alt: PyPI version info
.. image:: https://img.shields.io/pypi/pyversions/oeis.wrap
    :alt: Python version info


Requirements
------------

This module requires the following modules:

* `requests <https://pypi.python.org/pypi/requests>`_


Installation
------------

**Python 3.8 or higher is required.**

To install the stable version, do the following:

.. code-block:: sh

    # Unix / macOS
    python3 -m pip install "oeis.wrap"

    # Windows
    py -m pip install "oeis.wrap"


To install the development version, do the following:

.. code-block:: sh

    $ git clone https://github.com/Infiniticity/oeis.wrap


Links
-----

- `oeis <https://oeis.org/>`_
- `Documentation <https://oeis.readthedocs.io/>`_
dilbert.py 1.0.1
Fetch comics from Dilbert.
License: MIT
Requires Python: >= 3.8.0

dilbert.py
===========

.. image:: https://img.shields.io/github/license/Infiniticity/dilbert.py
    :target: https://github.com/Infiniticity/dilbert.py/blob/main/LICENSE.md
    :alt: license
.. image:: https://img.shields.io/tokei/lines/github/Infiniticity/dilbert.py
    :target: https://github.com/Infiniticity/dilbert.py/graphs/contributors
    :alt: lines of code
.. image:: https://img.shields.io/pypi/v/dilbert.py
    :target: https://pypi.python.org/pypi/dilbert.py
    :alt: PyPI version info
.. image:: https://img.shields.io/pypi/pyversions/dilbert.py
    :alt: Python version info


Requirements
------------

This module requires the following modules:

* `beautifulsoup4 <https://pypi.python.org/pypi/beautifulsoup4>`_
* `requests <https://pypi.python.org/pypi/requests>`_


Installation
------------

**Python 3.8 or higher is required.**

To install the stable version, do the following:

.. code-block:: sh

    # Unix / macOS
    python3 -m pip install "dilbert.py"

    # Windows
    py -m pip install "dilbert.py"


To install the development version, do the following:

.. code-block:: sh

    $ git clone https://github.com/Infiniticity/dilbert.py


Links
-----

- `dilbert <https://dilbert.com/>`_
- `Documentation <https://dilbert.readthedocs.io/>`_
snappi-convergence 0.4.1
A snappi extension for measuring network convergence
License: MIT
Requires Python: >=2.7, <4
Keywords: snappi testing open traffic generator automation

# snappi-convergence

[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
![GitHub](https://img.shields.io/github/license/open-traffic-generator/snappi-convergence)
[![release)](https://img.shields.io/github/v/release/open-traffic-generator/snappi-convergence)](https://github.com/open-traffic-generator/snappi-convergence/releases/latest)
[![build](https://github.com/open-traffic-generator/snappi-convergence/workflows/cicd/badge.svg)](https://github.com/open-traffic-generator/snappi-convergence/actions)
[![LGTM Grade](https://img.shields.io/lgtm/grade/python/github/open-traffic-generator/snappi-convergence)](https://lgtm.com/projects/g/open-traffic-generator/snappi-convergence/context:python)
[![LGTM Alerts](https://img.shields.io/lgtm/alerts/github/open-traffic-generator/snappi-convergence)](https://lgtm.com/projects/g/open-traffic-generator/snappi-convergence/?mode=list)

A snappi extension for measuring network convergence.

### Install

```bash
python -m pip install --upgrade "snappi[convergence]"
```

### Development Setup

```bash
git clone --recurse-submodules https://github.com/open-traffic-generator/snappi-convergence.git && cd snappi-convergence
python do.py setup && python do.py init
```
kobodata 0.0.9
Python Tool for accessing online data from KOBO TOOLBOX.
License: MIT

<samp>

# [kobodata](https://pypi.org/project/kobodata/)

[![Made in Tanzania](https://img.shields.io/badge/made%20in-tanzania-008751.svg?style=flat-square)](https://github.com/Tanzania-Developers-Community/made-in-tanzania)
[![Downloads](https://pepy.tech/badge/kobodata)](https://pepy.tech/project/kobodata)
[![Downloads](https://pepy.tech/badge/kobodata/month)](https://pepy.tech/project/kobodata)
[![Downloads](https://pepy.tech/badge/kobodata/week)](https://pepy.tech/project/kobodata)

A python wrapper for [**Kobo Data Tool Kit**](https://www.kobotoolbox.org/)

## Why Kobodata

- This helps get remote data collected easily via kobo forms via consuming the APIS from [*.kobotoolbox.org](https://www.kobotoolbox.org/) sites.

There are several accounts , you can signup for one:

- [Humanitarian Organisation Accounts](https://kobo.humanitarianresponse.info/)
- [Researchers, Aid Workers & Everyone Else Accounts](https://kf.kobotoolbox.org/)

## Getting started

To get started with **kobodata**, you have to firstly install the library either directly or using *pip*.

### Installation directly

Use git to clone or you can also manually download the project repository just as shown below;

```bash
$ git clone https://github.com/kalokola/kobodata
$ cd kobodata
kobodata $ python setup.py install 
```

### Installing from pip

```bash
# For Windows 

pip install  --upgrade kobodata

#For Linux | MAC 

pip3 install --upgrade kobodata
```

# Get Account Credentials
1. You have to sign up at [Kobo ToolBox](https://www.kobotoolbox.org/) and create your first form. 
2. To obratin [account_token]() got to your account settings and you will see an API Token section, view the token and copy it to your cip board. The API Token looks like [bd1f68af664306q82d62w1412873d3b76b4321]()
3. To obtain the [dataset_uuid]() navigate to your kobo project, select [DATA] to view the table. Inspect the link to your table and copy a section that looks like [agLCVHnDkbXRkEuhtp4oUF]()
4. Specify the [account_domain]() for your account [kf.kobotoolbox.org]() or [kobo.humanitarianresponse.info]()

Once you have got the credentials you can proceed as follows. 

## How to Use (Code Exmaple).

Here how to fetch real time data

```python
>>> from kobodata import KoboData 
>>> account_token = "bd1f68af664306q82d62w1412873d3b76b4321"
>>> dataset_uuid = ""
>>> account_domain = "kf.kobotoolbox.org"
>>> dataset = KoboData(
            account_subdomain,
            dataset_uuid,
            account_token     
        )

# get number observations
>>> dataset.counts
    784 rows

# return a dictionary of results
>>> dataset.get_data
```

## All the credit

1. [kalokola](https://github.com/kalokola)
2. All other contributors
</samp>