semvec/pypi-packages huggingface dataset:
datatransformpackage 1.0
POC of a Python library that will help Data Scientist do transform their data
Requires Python: <4.0,>=3.12

# DataTransformLib

DataTransformLib is a Python library designed to assist data scientists with common data transformation tasks. This library provides functions to transpose matrices, generate time series windows, and perform 2D convolutions, making it easier to handle and manipulate data efficiently.

## Features

- **Transpose Matrices**: Transpose 2D matrices provided as lists or file paths.
- **Time Series Windowing**: Generate overlapping windows from a 1D input array.
- **2D Convolution**: Perform 2D convolution on matrices with a specified kernel and stride.

## Installation

You can install DataTransformLib from PyPI using `pip`:

```sh
pip install DataTransformLib
etypes 1.0.4
A python module to store, encrypt and decrypt type hinted strings in a python file
Requires Python: <4.0,>=3.10
Keywords: encrypt, secret string, secret, decrypt, env var

## ETYPES

This package allows for encrypting secret strings in python files in a human readable way using type hints. 
it also supports dynamic loading of python files which contain encrypted strings, providing the password via an environment variable
 
## Installation

`$ pip install etypes`

or

`$ poetry add etypes`

## Example
Define a variable with the type hint DecryptedSecret
```
from etypes import DecryptedSecret
SECRET_VAR: DecryptedSecret = "some-secret-value"
```

### encrypt
To encrypt the file, run the following

`$ etypes encrypt -p PASSWORD ./path/to/python_file.py`

or 

`$ etypes encrypt -pf ./path/to/password_file ./path/to/python_file.py`

results in 

```
from etypes import EncryptedSecret
SECRET_VAR: EncryptedSecret = "gAAAAABmT9yA6HQOXF4BM6gvUG_ryKqrXK9BEgRY2W4lNQvDNBVbiCEOz50-viDLEMXA71upgcGgRbqvC-IAltbjE8w5MbSooJN5EV-8sVe1q3LndfBNzEg="
```

### decrypt

To decrypt the file run 

`$ etypes decrypt -p PASSWORD ./path/to/python_file.py`

or 

`$ etypes v -pf ./path/to/password_file ./path/to/python_file.py`

## Autoloader

To import this python file in your project and have it decrypt itself seamlessly when accessed.

You must import the AutoLoader
and configure it to accept a password via a environment variable or to look for a file at a path.

```
# app/settings/secrets.py

from etypes import EncryptedSecret, AutoLoader
SECRET_VAR: EncryptedSecret = "gAAAAABmT9yA6HQOXF4BM6gvUG_ryKqrXK9BEgRY2W4lNQvDNBVbiCEOz50-viDLEMXA71upgcGgRbqvC-IAltbjE8w5MbSooJN5EV-8sVe1q3LndfBNzEg="

AutoLoader(locals(), password_var_name="SOME_ENV_VAR_WHICH_CONTAINS_PASSWORD")
# or
AutoLoader(locals(), password_file="/path/to/your/secret_file")

```
import your settings/secrets file normally.

```
# app/main.py

from .settings import secrets
print(secrets.SECRET_VAR)
```

Run your application providing the password declaring in your AutoLoader
`$ SOME_ENV_VAR_WHICH_CONTAINS_PASSWORD="PASSWORD" ./main.py`




> TODO: Add support for the environs package 

## Changelog

1.0.4
- fix ansible implementation and tests


1.0.2, 1.0.3
- doc updates


1.0.1 breaking changes but still initial 1.0 release
- rename hits EncryptedSecret and DecryptedSecret


1.0 release
- basic functionality
pynenv 0.2.6
General helper functions for environments
Requires Python: <4.0,>=3.12

# Pynenv

A collection of common helper functions for your environment.

## Install

```bash
pip install pynenv
```

## Example Useage

```python
from pynenv.environment import get_environment_variable, json2dict, yaml2dict

my_env_var = get_environment_variable('HOME')
json_dict = json2dict('test_json.json')
yaml_dict = yaml2dict('test_yaml.yaml')
```

## Build

* Adjust version in ```pyproject.toml```
* Run ```poetry build```
* Run ```poetry publish```
csv-identifier 0.1.2
A package to read CSV and assign unique IDs to a specified column
Requires Python: >=3.6

# csv_identifier

`csv_identifier` is a Python package that reads a CSV file, Excel file, or DataFrame, converts it to a DataFrame if necessary, and assigns a unique identifier to a specified column.

`csv_identifier` は、CSV ファイル、Excel ファイル、または DataFrame を読み込み、必要に応じて DataFrame に変換し、指定したカラムに一意な識別子を割り当てる Python パッケージです。

## Installation

You can install the package using pip:

パッケージはpipを使用してインストールできます：
```sh
pip install csv_identifier
```

## Usage

Here is an example of how to use the package:

パッケージの使用例は以下の通りです：

```python
from csv_identifier import assign_unique_ids
import pandas as pd

# Path to your CSV file
csv_file_path = 'path/to/your/file.csv'

# Path to your Excel file
excel_file_path = 'path/to/your/file.xlsx'

# Example DataFrame
data = {'column_name': ['A', 'B', 'A', 'C']}
df = pd.DataFrame(data)

# Column to which you want to assign unique IDs
column_name = 'column_name'

# Assign unique IDs from CSV file
df_from_csv = assign_unique_ids(csv_file_path, column_name)
print(df_from_csv)

# Assign unique IDs from Excel file
df_from_excel = assign_unique_ids(excel_file_path, column_name)
print(df_from_excel)

# Assign unique IDs from DataFrame
df_from_df = assign_unique_ids(df, column_name)
print(df_from_df)
```

## Function

### assign_unique_ids

```python
assign_unique_ids(data, column_name)
```

- **data**
  - Path to the CSV/Excel file or a DataFrame.
  - CSV/ExcelファイルのパスまたはDataFrame
- **column_name**
  - The column to which you want to assign unique IDs.
  -  一意のIDを割り当てたいカラム


This function reads the data, assigns unique IDs to the specified column, and returns the modified DataFrame.

この関数はデータを読み込み、指定されたカラムに一意のIDを割り当て、変更されたDataFrameを返します。
walletconstructor 0.1.0
Module gestion wallet basee sur la blockchain ethereurm
Requires Python: >=3.6


# Wallet Constructor

## Importer le Module

Pour utiliser le module `walletconstructor`, importez-le comme suit :

```python
import walletconstructor as wc
```

## Initialisation du Wallet

Vous pouvez initialiser le wallet de deux façons :

### 1. Importer la Clé Privée

```python
kwargs = {'private_key': "your_private_key"}
wallet = wc.get_wallet(**kwargs)
```

### 2. Création par Nom et Mot de Passe

```python
kwargs = {'name': 'your_name', 'password': 'your_password'}
wallet = wc.get_wallet(**kwargs)
```

**ATTENTION** : La création par nom et mot de passe peut également servir de connexion. Si le nom existe déjà, il se connectera au compte existant. Il y a une base de données nommée `.key_database` dans le dossier `walletconstructor` du module pour gérer ces informations.

## Classe Principale

### Sécurité

Importez et initialisez la classe `Security` :

```python
from walletconstructor.security.security import Security

security = Security(**kwargs)
```

### Wallet

Importez et initialisez la classe `Wallet` en utilisant l'objet `Security` :

```python
from walletconstructor.wallet.wallet import Wallet

wallet = Wallet(security)
```

## Licence

Ce projet est sous licence MIT. Consultez le fichier [LICENSE](LICENSE) pour plus de détails.

## Auteur

- **kikakop** - *Initial work* - [kikakop](https://gitlab.com/kikakopjunior)

## Remerciements

- Remerciements spéciaux à tous ceux qui ont contribué à ce projet.
wayz-rlsdk-python 0.1.1
RLSDK modifications I made to train with Python.
Requires Python: <4.0,>=3.11

# RLSDK Python

This is reverse engineered python SDK package aiming to read data from RocketLeague.exe.

## How does it works 
This SDK uses [PyMem](https://pypi.org/project/Pymem/) to read game memory and [frida](https://frida.re/docs/home/) to hook game functions. 

## Installation

```bash
pip install wayz_rlsdk_python
```
Or
```bash
poetry add wayz_rlsdk_python
```

## Usage

```python
from rlsdk_python import RLSDK, EventTypes
import sys

rlsdk = RLSDK(hook_player_tick=True)


def on_tick(event):
    game_event = rlsdk.get_game_event()

    if game_event:
        cars = game_event.get_cars()
        
        for car in cars:
            pri = car.get_pri()
            player_name = pri.get_player_name()

            # Display car position

            x,y,z = car.get_location().get_xyz()

            print(f"{player_name} is at {x},{y},{z}")

rlsdk.event.subscribe(EventTypes.ON_PLAYER_TICK, on_tick)

sys.stdin.read()

```

## Events

You can attach a callback function to an event like this:

```python
from rlsdk_python import RLSDK, EventTypes
sdk = RLSDK()
sdk.event.subscribe(EventTypes.ON_KEY_PRESSED, on_key_pressed)

def on_key_pressed(event):
    print("Key pressed:", event.key)

```

More examples and documentation will be added if users ask for it.




## Project using RLSDK Python

- [RLMarlbot](https://github.com/MarlBurroW/RLMarlbot) - Nexto bot based on my python SDK

## Help needed
I need a way to find GObjects and GNames base offsets, because this offsets changes frequently (on each uptates) and are differents for Epic and Steam
rottentomatoes-reviews-scraper 0.0.8
A Python package to scrape movie data from Rotten Tomatoes, including titles and reviews.
Requires Python: >=3.6

# Rotten Tomatoes Scraper

A Python package to scrape movie data from Rotten Tomatoes, including titles and reviews.

ロッテントマトから映画のレビューをスクレイピングするPythonパッケージです。

## Features / 特徴

- Retrieve the following fields and save them to a CSV file
  - Title
  - Release Date
  - Reviewer
  - Review Date
  - Rating
  - Review Text

- 以下のフィールドを取得しCSVファイルに保存する
  - タイトル
  - 公開日
  - レビュアー
  - レビュー日時
  - 評価
  - レビューテキスト

## Installation / インストール

To install the package, use pip:

パッケージをインストールするには、pipを使用します：

```sh
pip install rottentomatoes-reviews-scraper
```

## Usage / 使い方

After installing the package, you can use the command line interface to scrape data. Here is an example of how to use the package from the terminal:

パッケージをインストールした後、コマンドラインインターフェースを使用してデータをスクレイピングできます。

Set the number of movies to retrieve and the number of reviews to retrieve

取得する映画数と取得するレビュー数を設定します。

```sh
rottentomatoes-reviews-scraper --count_title 20 --count_review 20
```

This command will first scrape 20 movie titles and then scrape 20 reviews for each of those movies.

このコマンドは、最初に20の映画タイトルをスクレイピングし、その後各映画の20のレビューをスクレイピングします。

## Command Line Arguments / コマンドライン引数

- `--count_title`: Number of movie titles to scrape
- `--count_review`: Number of reviews to scrape per movie

- `--count_title`: スクレイピングする映画タイトルの数
- `--count_review`: 各映画ごとにスクレイピングするレビューの数

## Example / 例

Here is an example of how to run the scraper:

スクレイパーを実行する例を以下に示します：

```sh
rottentomatoes-reviews-scraper --count_title 20 --count_review 20
```