semvec/pypi-packages huggingface dataset:
bitpost 1.1.5
Wrapper for the bitpost API
Requires Python: >=3.6

# Purpose
This package wraps the bitpost API so that it's easier to experiment and play with.

# Install
`pip install bitpost`

# Disclaimer
The code is distributed mostly for demo purposes, don't use it on production without proper review. Beware: HTTP requests are done synchronously!

# More info
* [API documentation](https://docs.bitpost.co)
* [OpenAPI reference](https://apidocs.bitpost.co)
* [Code examples](https://github.com/bitpostAPI/examples)
kodb 0.1.6
kmaasrud's opinionated document builder
Requires Python: >=3.6

<h1 align="center">KODB<br>
    <sup>Kmaasrud's Opinionated Document Builder</sup>
</h2>

<p align="center"><a href="https://github.com/kmaasrud/kodb/wiki/Installation">Installation</a> - <a href="https://github.com/kmaasrud/kodb/wiki/Creating-a-document">Getting started</a></p>

This is my personal and opinionated document builder script, built around my document creation workflow.

Faced with the task of writing a lot of scientific documents at university, I quickly grew tired of the old-fashioned and english-centered LaTeX document system. This led me in the direction of [Pandoc](https://pandoc.org/), and more specifically [Pandoc Markdown](https://github.com/kmaasrud/kodb/wiki/Pandoc-Markdown). Pandoc Markdown is quicker to write, easily readable in it's plain text form, minimally english-centric and simply much more sensible than writing TeX. Pair that with [Tectonic](https://tectonic-typesetting.github.io/) - a self-contained, minimal and modern TeX/LaTeX engine - and I've got the same functionality as LaTeX, but in an arguably much better package. TeX now only works as a sort of assembly language, and I can write in a more sophisticated and minimal markup-language.

However, creating a directory structure for you document, learning the Pandoc command line tool, compiling with Tectonic, keeping track of CSL styles, etc... This sounds like a lot of work, I hear you say. Enter KODB: One single tool that attempts to tie together these excellent typesetting tools, abstract away all the dirty work and give you the freedom to do what you really need to do: writing. Writing KODB was my natural response to discovering the workflow explained above, and I use it almost everyday.

Beware that KODB was initially written for personal use and is quite opinionated, but despite this I hope you too can get as much use out of it as I have. To get started, first [install KODB](https://github.com/kmaasrud/kodb/wiki/Installation) and see the [Getting started page](https://github.com/kodb/wiki/Creating-a-document). Bugs or feature suggestions are to be added as [Issues](https://github.com/kmaasrud/kodb/issues) and if you have any questions, feel free to send me an email: <km@aasrud.com>.
xampy 0.1.4
A Data Science Package written in python.

# XamPy
## Links
- [Code of Conduct](https://github.com/XamNalpak/xampy/blob/main/CODE-OF-CONDUCT.md)
- [Contributing](https://github.com/XamNalpak/xampy/blob/main/CONTRIBUTING.md)
- [Issues](https://github.com/XamNalpak/xampy/issues)
- [License](https://github.com/XamNalpak/xampy/blob/main/LICENSE)
- [Current Functions](https://github.com/XamNalpak/xampy/blob/main/FUNCTIONS.md)



# _Information_


XamPy is a Data Science Package written in Python. 
## Features

- Simplifying the process of analyzing data
- User-Friendly command based sripting package

## Packages Used

XamPy uses a number of open source projects to work properly:

- Pandas - Data manipulation tool for python
- Numpy - awesome tool for matrix/array mathmatics
- MatPlotLib - tool for graphing in python
- vaderSenitment - tool for senitment anaylsis of social media
- nltk - natural language processing and text mining
- textblob - sentiment analysis on a larger size of text
- datetime for date manipulation

# Installation
```
pip install xampy
or
pip3 install xampy
```

# Contributors and Contributions
IF YOU ARE A CONTRIBUTOR AND ARE NOT LISTED PLEASE EMAIL [Max Paul](mailto:maxkpaul21@gmail.com) or submit a new issue.

 - Max Paul 
   - Lead Contributor/Founder
   - Bachelor Of Science In Data Science from Bryant Unversity.
   - Software engineer by day for TJX.

# Example Use

```
import xampy as xp

# reading data and showing information
data = xp.makeData('topcsv.csv')
xp.showInfo(data)

# dropping all the rows that contain nulls get dropped
data = xp.dropnaDim(data,'row')

#counting missing data to show all values have been dropped
xp.countMissing(data)

#conducting sentiment analysis on the text data
data = xp.socialSentiment(data,'Content')

#showing the new dataframe
data.head(10)





```

## License

MIT

**Free Software, Hell Yeah!**
python-generate-mac 1.3.1
Library for generating Ethernet MAC addresses
Requires Python: >=3.4

Python-generate_mac
===================

Python library for working with Ethernet MAC addresses. Functions for generating
transforming and testing MAC addresses.

Uses Wireshark's manuf, or s similarly formated file as input for specific
Vendor ID(VID) bytes, for creating more 

Supported functions:

Generate
--------
**total_random()** - Procedurely generated MAC address, using random function.

**vid_file_random(_file_)** - uses random line from wireshark's manuf file

**vid_file_vendor(_file, vendor name, desc=optional_)** - specify a vendor name,
uses wireshark's manuf file instead of being completely random. May optionally
specify desc, which searches description within the vendor field

**vid_provided(_vid bytes_)** - specify the VID bytes when calling the function.
Random device bytes will be generated.

Test
-------
**list_vendors(_file_)** - return a python set{} of uniqe valid vendors, from
a wireshark manuf file

**is_mac_address(_mac_)** - Takes a string, and checks if it is a valid Ethernet
MAC address. returns True or False(bool type)

Transform
---------
**get_vid_bytes(_mac_)** - Returns the vendor bytes(first three) from a MAC address.

**another_same_vid(_mac_)** - Generates another MAC with diffrent device bytes
with same vendor bytes as input

Usage
-----

Import and set up an object.

```
from generate_mac import generate_mac
```

Procedurely generated Vendor and Host bytes. Checks for broadcast bit

```
generate_mac.total_random()
'7E:CD:60:1E:AC:6E'
```

Read Vendor bytes from random line in a file. This has to be formated the same
as wireshark's manuf file.
```
generate_mac.vid_file_random('/usr/share/wireshark/manuf')
'70:B3:D5:C5:40:49'
```

Read from a manuf file like above, but find Vendor bytes belonging to a specific
vendor, by name.
```
generate_mac.vid_file_vendor('/usr/share/wireshark/manuf',"Motorola")
'40:88:05:4F:CE:82'
```
*OPTIONAL:* this can also now search the description field

```
generate_mac.vid_file_vendor('/usr/share/wireshark/manuf',"Motorola","BSG")
'00:24:37:5C:3A:8B'
```

Provide the vendor bytes in a string. Generate Host bytes only
```
generate_mac.vid_provided('00:06:8C')
'00:06:8C:35:5E:C4'
```

List valid vendor options as a list.
```
generate_mac.list_vendors('/usr/share/wireshark/manuf')
['Vendor1','Vendor2','etc']
```

Check if a MAC address is valid. returns a Bool(True,False)
```
generate_mac.is_mac_address('00:06:8C:35:5E:C4')
True
```

Get the VID bytes from a MAC address
```
generate_mac.get_vid_bytes('00:06:8C:35:5E:C4')
'00:06:8C'
```

Generate another MAC from the same VID bytes as current MAC
```
generate_mac.another_same_vid('00:06:8C:35:5E:C4')
'00:06:8C:3D:C2:F2'
```
just-func 0.0.1
A python interpreter for the just-func language

# just-func-python
[![Python application](https://github.com/justland/just-func-python/actions/workflows/python-app.yml/badge.svg)](https://github.com/justland/just-func-python/actions/workflows/python-app.yml)

Python implementation of [just-func](https://github.com/justland/just-func).

## Develop

```shell
# install dependencies
pip install -r requirements.txt

# run tests
pytest

# run style guide enforcement
flake8 justfunc
```