semvec/pypi-packages huggingface dataset:
PyTabela 0.0.1.3
Pacote utilizado para criação de tabelas no python
Requires Python: >=3.8

# Pytabela

Uma biblioteca com o intuito de gerar tabelas automaticamente.

## Instalação

### Instalação via pip:

```sh
python -m pip install -U PyTabela
```
## Como Usar

### Importação
```python
from pyTabela import pyTabela
x = pyTabela.PyTabela()
```
### Adição dos campos
```python
x.addCampos(["id", "nome", "sobrenome"])
```
### Adição das linhas
```python
x.addLinha([1, "Pablo", "Silva"])
```

Voce pode adicionar uma linha a qualquer momento, mas é necessario adicionar o nome dos campos primeiramente com `addCampos`.
```python
x = pyTabela.PyTabela()
x.addCampos(["id", "nome", "sobrenome"])
x.addLinha([1, "Pablo", "Silva"])
x.addLinha([2, "Vitória", "Karolina"])
x.addLinha([3, "Fulano", "de Tal"])
print(x)
```

### Exemplo de Mostragem

```txt
+----+---------+-----------+
| id | nome    | sobrenome |
+----+---------+-----------+
| 1  | Pablo   | Silva     |
| 2  | Vitória | Karolina  |
| 3  | Fulano  | de Tal    |
+----+---------+-----------+
```

### Exportar para CSV
```python
a.saveTabela("Nome_Do_Arquivo.csv")
```
### Importar de um arquivo CSV
```python
a.loadTabela("Nome_Do_Arquivo.csv")
```
aowniereweaad 2.0.10
aownierewe
Requires Python: >=3.6, <4
Keywords: sample,setuptools,development

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aowniereweaac 2.0.10
aownierewe
Requires Python: >=3.6, <4
Keywords: sample,setuptools,development

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aowniereweaab 2.0.10
aownierewe
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Keywords: sample,setuptools,development

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csanim 0.0.4
A tool for creating computer science explanatory videos.

# CS Animation

![](https://shields.io/github/license/phuang1024/csanim)
![](https://shields.io/github/issues/phuang1024/csanim)
![](https://shields.io/github/issues-pr/phuang1024/csanim)
![](https://github.com/phuang1024/csanim/workflows/Tests/badge.svg)
![](https://readthedocs.org/projects/csanim/badge/?version=latest)
![](https://shields.io/github/repo-size/phuang1024/csanim)
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![](https://readthedocs.org/projects/piano-video/badge/?version=latest)
![](https://img.shields.io/tokei/lines/github/phuang1024/csanim)

A tool for creating computer science explanatory videos.

Inspired by 3Blue1Brown.
emipy 0.1.1
Python package for emission data analysis based on the E-PRTR database.
Requires Python: >=3.6

[![pipeline status](https://jugit.fz-juelich.de/network-science-group/emipy/badges/dev/pipeline.svg)](https://jugit.fz-juelich.de/network-science-group/emipy/-/commits/dev)
[![coverage report](https://jugit.fz-juelich.de/network-science-group/emipy/badges/dev/coverage.svg)](https://jugit.fz-juelich.de/network-science-group/emipy/-/commits/dev)
[![PyPI version](https://img.shields.io/pypi/v/emipy.svg)](https://pypi.org/project/emipy/)
[![Documentation build status](https://img.shields.io/readthedocs/emipy.svg)](https://readthedocs.org/projects/emipy/builds/)
![Python version](https://img.shields.io/pypi/pyversions/emipy.svg)
![LICENSE](https://img.shields.io/pypi/l/emipy.svg)

# About
emipy is a package for processing data of pollutant releases and pollutant transfers.
It's main target is to enable a fast output of individual data set requests and to provide visualisation options.

The data are provided by the [European Environment Agency](https://www.eea.europa.eu/data-and-maps/data/member-states-reporting-art-7-under-the-european-pollutant-release-and-transfer-register-e-prtr-regulation-23) and [Eurostat](https://ec.europa.eu/eurostat/de/web/gisco/overview).

# Documentation
For the documentation take a look over [here](https://emipy.readthedocs.io/en/latest/).

# Contribution
We are happy about ideas for new features or concrete implementations in emipy. 
Just get in touch and we will hopefully work together on your subject ASAP.

To contribute changes:

1. Fork the project on GitLab
2. Create a feature branch to work in your fork
3. Commit your changes to the feature branch
4. Push the branch to GitLab
5. Create a new pull request from the feature branch on GitLab

# Contact
For contact write a mail to p.boettcher@fz-juelich.de
fwsclient 0.0.1
A python client for FreightWaves
Requires Python: >=3.6

# Install
```sh
git clone https://github.com/freightscience/fwsclient
cd fwsclient
pip install --use-feature=in-tree-build .
```

# Quick start
```python
from fwsclient import Client
fws_client = Client("<FREIGHT_WAVES_USERNAME>", "<FREIGHT_WAVES_PASSWORD>")

indices = fws_client.get_indices()
'''
                                             index_Name    index frequency unit_Type                                        description
0                           DOE Diesel Price Per Gallon      DOE         W       USD                                                   
1             Diesel Truck Stop Actual Price Per Gallon      DTS         D       USD                                                   
2                          Outbound Tender Reject Index     OTRI         D      PCNT  Percentage of Outbound Tenders rejected in the...
3                           Inbound Tender Reject Index     ITRI         D      PCNT  Percentage of Inbound Tenders rejected in the ...
4                        Cass Freight Index - Shipments     CFIS         M      INDX  Overall North American freight volumes index (...
...                                                 ...      ...       ...       ...                                                ...
1836       Capacity Trend Market Score (Carrier) REEFER   CTSCR4         D     INDEX       Capacity Trend Score (Carrier) REEFER 4-Week
1837  Capacity Trend Lane Score (Shipper-Broker) REEFER  CTLSSR4         D     INDEX  Measure of overall shipper-broker market lane ...
1838         Capacity Trend Lane Score (Carrier) REEFER  CTLSCR4         D     INDEX  Measure of overall asset carrier market lane f...
1839                Capacity Trend Market Direction VAN    CTDV4         D     INDEX                Capacity Trend Direction VAN 4-Week
1840             Capacity Trend Market Direction REEFER    CTDR4         D     INDEX             Capacity Trend Direction REEFER 4-Week
'''

qualifiers = fws_client.get_qualifiers_for_index("OTRI")
'''
     index qualifier
0     OTRI    PHXFAT
1     OTRI    CHIPHL
2     OTRI    STLDAL
3     OTRI    MEMIND
4     OTRI    ATLSTL
...    ...       ...
2800  OTRI    FWABMI
2801  OTRI    RDUFWA
2802  OTRI    GYYFSD
2803  OTRI    CMHRIC
2804  OTRI    CHACVG
'''

df = fws_client.get_index("OTRI", "STLDAL", date="2021-01-01")
'''
        data_Timestamp  data_Value index qualifier qualifier_Code
0  2021-01-01T00:00:00       31.29  OTRI    STLDAL        LANESNA
'''
```
LibTwitter 0.0.1
Pacote para pesquisar e processar tweets
Requires Python: >=3.8

LibTwitter
==========

Biblioteca para pesquisa e processamento de tweets.

Para utilizar as funções da bibblioteca é necessário obter as keys da API do Twitter


## Instalação

`pip install libTwitter`

## Funções
- Pesquisar Tweets 
- Publicar Tweets
- Gerar Wordclouds
libTwitter 0.0.7
Pacote para pesquisar e processar tweets
Requires Python: >=3.8

LibTwitter
==========

Biblioteca para pesquisa e processamento de tweets.

Para utilizar as funções da bibblioteca é necessário obter as keys da API do Twitter


## Instalação

`pip install libTwitter`

## Funções
- Pesquisar Tweets 
- Publicar Tweets
- Gerar Wordclouds
giptools 0.0.3
giptools is a library that aims to simplify the functionality of other existing libraries for image processing
Requires Python: >=3.0

giptools
========

#### this package provides some methods for image processing.

## Instalação:

    pip install giptools

### Methods

## GraficPlot
This module aims to simplify the plot of graphics in order to make it more 
intuitive and practical, plotting several images in user-defined axis, 
as well as plotting their histogram. It will also display several graphs 
of the same image and finally create line graphs of the learning metrics
 
## ImageFilters
ImageFilters comes to facilitate the application of filters in an entire 
image dataset, being able to apply a filter to a certain color channel, 
also performing the division of an image base in test, train and validation, 
saving the images in folders so make life easier for the user.

## CreateBox
This module offers the possibility of creating masks and plotting bounding 
boxes on this mask, passed through an xml and csv file, being also able to 
plot the boxes in an image.
tomato-rules 1.0
Additional rules for tomato-engine.
Requires Python: >=3.6

# tomato-rules

This is a public repository for sharing rulesets written for
[tomato-engine](https://codeberg.org/eduardotogpi/tomato-engine).
Everyone is encouraged to share any ruleset they've written (see
**Sharing rulesets** below).

## Installation and usage

You can install this package via pip:
```
pip3 install tomato-rules
```
And import tomato_rules to use any of the rulesets. For instance,
`high_life`:
```
import tomato as tt
from tomato_rules import high_life

board = tt.Board(high_life)
```

## Sharing rulesets

Given that tomato-engine is free software, you might as
well share any ruleset you've written with everyone through this
repository, right?

All you have to do is put your ruleset on files/tomato-rules/, and
write a simple, minimal working example on files/. You can then
share it with us by sending a pull request, or, send me your
example and ruleset through email (eduardosprp@protonmail.com) if
you prefer.

files/README.md and files/tomato-rules/README.md are helpful
guidelines for writing such examples and rulesets respectively.

## Please note:

Every file in this repository is licensed under the GPLv3+
license, unless specified otherwise, by the author, in a header
on each individual file they would prefer to license differently.

Of course, whatever license you choose for your contributions
[must be compatible with the GPLv3](https://www.gnu.org/licenses/license-list.html#GPLCompatibleLicenses).
GPL-compatible licenses include pretty much any Free
Software/Open Source license commonly in use, so you generally
shouldn't worry about that.
hatebase 1.0.3
Python Version of Andrew Welter's Hatebase Wrapper, based on DanielJDufour's implementation
Keywords: conflict,hatespeech,language,nlp,python,tagging

# hatebase
Python Version of Andrew Welter's Hatebase Wrapper
Using the current 4.2 Version of the Hatebase API

# Install
```bash
pip install hatebase
```

# Requirements
```bash
pip install requests
```

# HatebaseAPI functions
### Initialize HatebaseAPI class
```py
from hatebase import HatebaseAPI
key = 'yourHatebaseAPIKeyString'
hatebase = HatebaseAPI({"key": key})
# for more details, set debug to True
hatebase = HatebaseAPI({"key": key, "debug": True})
```

### HatebaseAPI getVocabulary
```py
# set filters for vocabulary query
filters = {"language": "eng"}
format = "json"

response = hatebase.getVocabulary(filters=filters, format=format)

# get some details from response
vocablist = response["result"]
results = response["number_of_results"]
pages = response["number_of_pages"]
```

### HatebaseAPI getVocabularyDetails
```py
format = "json"
details_filters = {'vocabulary_id': vocab_id}

response = hatebase.getVocabularyDetails(filters=details_filters, format=format)
```

### HatebaseAPI getSightings
```py
filters = {'is_about_nationality': '1', 'language': 'eng', 'country_id': 'US'}
format = "json"

response = hatebase.getSightings(filters=filters, format=format)
```

### HatebaseAPI analyze
``` 
# TBD
```
### HatebaseAPI getAnalysis
``` 
# TBD
```

# Examples
#### Get All the Hate Speech in English About Nationality in the US
```py
import json
import requests
from hatebase import HatebaseAPI

hatebase = HatebaseAPI({"key": key})
filters = {'is_about_nationality': '1', 'language': 'eng', 'country_id': 'US'}
format = "json"
json_response = hatebase.getSightings(filters=filters, format=format)
```

#### Get All Arabic Vocabulary
```py
from json 
import requests
import pandas as pd
from hatebase import HatebaseAPI

hatebase = HatebaseAPI({"key": key})
filters = {"language": "ara"}
format = "json"
# initialize list for all vocabulary entry dictionaries
ara_vocab = []
response = hatebase.getVocabulary(filters=filters, format=format)
pages = response["number_of_pages"]
# fill the vocabulary list with all entries of all pages
# this might take some time...
for page in range(1, pages+1):
    filters["page"] = str(page) 
    response = hatebase.getVocabulary(filters=filters, format=format)
    ara_vocab.append(response["result"])

# create empty pandas df for all vocabulary entries
df_ara_vocab = pd.DataFrame()
# fill df
for elem in ara_vocab:
    df_ara_vocab = df_ara_vocab.append(elem)
# reset the df index
df_ara_vocab.reset_index(drop=True, inplace=True)    
```

For more documentation on the API check out https://github.com/hatebase/Hatebase-API-Docs


# Testing
To test the package run
```bash
python -m unittest hatebase.tests.test
```
lshw 0.0.1
lshw is a small tool to extract detailed information on the hardware configuration of the machine.
Requires Python: >=3.6

# lshw
lshw is a small tool to extract detailed information on the hardware configuration of the machine.

### Pip install

```bash
pip install lshw
```

### Example


```python

from lshw.client import ListHardware

list_hardware = ListHardware()
result = list_hardware.read_data(list_hardware.get_nic_data())
print(result)
```

### License

MIT