semvec/pypi-packages huggingface dataset:
pyprec 1.0.2
Python Package Repository Creator
Requires Python: >=3.9

# PyPReC: Python Package Repository Creator

[![DOI](https://zenodo.org/badge/501281838.svg)](https://zenodo.org/badge/latestdoi/501281838)

This package automates the process of repository creation for Python packages.

## Installation

The package can be installed with Python's pip package manager.

```bash
pip install pyprec
```

Or manually:

```bash
git clone https://github.com/marcorossi5/pyprec.git
cd pyprec
pip install .
```

The last command installs the `pyprec` program into the environment python path.

## Running the code

Package help message:

```bash
$ bash --help
usage: pyprec [-h] [-r RUNCARD] [-l {DEBUG,INFO,WARNING,ERROR,CRITICAL}]

optional arguments:
  -h, --help            show this help message and exit
  -r RUNCARD, --runcard RUNCARD
                        The settings runcard file.
  -l {DEBUG,INFO,WARNING,ERROR,CRITICAL}
                        set logging level
```

If a runcard is specified, settings are loaded from it. Please, find a default
runcard [here](./cards/default_runcard.yaml).

If no runcard is given by the user, the interactive mode is triggered: answer
the prompted questions to proceed.

:warning: **Note:**  
Both modes require that the `prefix_folder` does not contain any `src` folder
inside. This is needed to ensure a clean workspace and avoid unintentional file
deletion.
blumycelium 0.1.0
blumycelium
Keywords: arangodb multithread bluwr multiprocessing async

BLUMYCELIUM: Async micro-services, 100% in python from Bluwr
============================================================

This tool os provided for free by [bluwr.com](https://bluwr.com). We are building a 100% text based publication platform. A calm space free of any addictive feature.

Here are a few things that you can do to support us:
 - Register for early access on [bluwr.com](https://bluwr.com)
 - Buy some awesoms merch on our [store](https://store.bluwr.com)
 - Follow us on social media [instagram](https://www.instagram.com/bluwr_official/), [twitter](https://twitter.com/bluwr_official), [linkedin](https://www.linkedin.com/company/bluwr)
 

**Machine Elf <- Mycelium -> Machine Elf**

PLEASE NOTE: This documentation is a work in progress

BLUMYCELIUM is our tool for arm's-length microservices management and orchestration. It allows for the splitting of a monolithic application into several small parts that run asynchronously in the same environment and can be tested separately. BLUMYCELIUM was developed to be easy to learn and does not require more than python knowledge to achieve results that would normally be implemented using more complex DevOps orchestration tools mediated through REST APIs. To achieve this, Blumycellium relies heavily on python introspection capabilities to follow the flow of variable updates and transparently derives execution and orchestration graphs. By allowing services to be separate programs BLUMYCELIUM applications can also bypass the python GIL. BLUMYCELIUM also remembers the source code of all tasks as well as tracebacks for all exceptions for easy debugging. BLUMYCELIUM is implemented using the flexible multimodal ArangoDB database for storing what we call the: Mycelium. The repository of everything needed for variable execution graphs, source codes, orchestrations and failure reporting.

BLUMYCELIUM allows you to write complex microservice orchestration all in python. You can divide a complex application into many smaller parts that can be tested independtly and ran asynchronously. These smaller parts are agents called *Machine Elves* and the *Mycelium* is the database they use to communicate.


 
Readthedocs documentation
=========================

We provide a full documentation [here](https://blumycelium.readthedocs.io/en/latest/index.html) (work in progress).


Feedback
========

If you have any suggestions about features or feedback about the documentation please open github issues.
logger_sio_client 1.0.4
An amazing sample package!

nanuaddnumb1
========

Node.js module that generates a nanu-addnumb1.

Uses crypto.randomBytes when available, falls back to unsafe methods for node.js <= 0.4.

To increase performance, random bytes are buffered to minimize the number of synchronous calls to crypto.randomBytes.

## Installation

   $ npm install nanu-addnumb1

## Usage

   var add = require('nanu-addnumb1');

   console.log(add(1,3,343,4,34,345));
contentassistant 0.0.1
Manipulação do assistente de conteúdo
Requires Python: >=3.6

# ContentAssistant

## Realize teste em massa e obtenha informações como:

Intenção reconhecida;__
Entidades reconhecidas;__
Score__
Se encontrou alguma resposta no assistente de conteúdo;__
Resposta encontrada.__

```Python
import ContentAssistant

CA = ContentAssistant.Test(AUTH, input)
```

### Para instanciar a classe, é necessário dois parâmetros:

### AUTH: String - Authorization/Key do bot.
### input: Lista ou pd.Series (coluna de DataFrame) - Frases para efetuar o teste.


### Uso com lista

```Python
import ContentAssistant
AUTH = 'KEY_DO_BOT'
input = ['texto1','texto2']
CA = ContentAssistant.Test(AUTH, input)
response = CA.run_test() 
```

### Uso com pd.Series


```Python
import ContentAssistant
import pandas as pd

AUTH = 'KEY_DO_BOT'
df = pd.read_csv('C:\Users\base.csv', sep=';', encoding='utf8') #Abrindo o arquivo
input = df['Frases'] #Selecionando a coluna com as frases
CA = ContentAssistant.Test(AUTH, input)
response = CA.run_test()
```


### Salvando o resultado

Escolha o caminho, nome do arquivo, tipo (csv,txt) e separador, e rode o código abaixo.

```Python
response.to_csv(r'/minha_pasta/resultado_1.csv', sep=";",encoding='utf8') 
```
invarpy-buschinelli 1.0.0
Invariance estiators for Python
Requires Python: >=3.6

# Invpy package v0.0.1

- Package that includes several methods to compute statistical translation non-invariance of primarly, but not limitted to, scalar
cosmological fields.

## Packages needed

- To use 'invpy', you will need only 'numpy' as its base package.
simghg 0.1.2
Package for N2O changing trends in each country in Annex.
Requires Python: >=3.7

# simghg

 ### co2.py
 
##### The CO2 emissions of each country in Annex I Countries is drawn in comparison with Japan. In addition, a comparison with the base year of the United Nations Framework Convention on Climate Change (Kyoto Protocol base year) is drawn. The number of years is from 1990 to 2019.

```
$ python co2.py
1:  Comparison CO2 with Japan
2:  Comparison CO2 with Base year
99:  Stop
>>> 1
Country Name >>> Slovakia
```
![Japan-Germany](/results/result_co2_1.png)

##### Draw The CO2 emissions of each country in Annex I Countries and the base year of the United Nations Framework Convention on Climate Change in that country.
```
$ python co2.py
1:  Comparison CO2 with Japan
2:  Comparison CO2 with Base year
99:  Stop
>>> 2
Country Name >>> Austria
```
![Austria-Base year](/results/result_co2_2.png)


### simghg.py

##### Draw other countries that have similar trends in comparison with the previous year for each country the Annex I Countries.

```
$ python simghg.py Greece
```
![similar-to-Japan](/results/result_n2o.png)
pyfgtconflib 0.0.2
Python FortiGate Config Library
Requires Python: >=3.6

# pyfgtconflib


##### Author :
Don Yao


#### Description : 
A simple and tiny FortiGate Configuration file parser.
It takes FortiGate Configuration as input, and output as python defaultdict.
The core parsing fuctions implemented in less than 100 lines of code.


##### Install :
pip install pyfgtconflib


#### Usage :
In [pyfgtconflib](https://github.com/fortinetps/pyfgtconflib) source repository.

A demo script called [import_export.py](https://github.com/fortinetps/pyfgtconflib/blob/main/tests/import_export.py) in tests folder.
This script open a FortiGate configuration file, parses configuration file into python dictionary, 
and print the dictionary out with nicely formatted text.
You can redirect the output to a file, to compare the original input FortiGate configuration file, 
so you could verify the config paring (import) and config dictionary printing out (export) works.

A demo script called [remove_password.py](https://github.com/fortinetps/pyfgtconflib/blob/main/tests/remove_password.py) in tests folder.
This script open a FortiGate configuration file, parses configuration file into python dictionary, 
when printing the dictionary out, it removes/strips all (encrypted) passwords, private-key, and certificate in configuration, 
it will be a little safer to share the configuration file without these information.

For additional usages/demos/tools, please check this GitHub repo site:
https://github.com/fortinetps/FortiGateConfigTools