semvec/pypi-packages huggingface dataset:
atreign-datamanager 0.0.2
Data Merger: A Python package for merging data from two tables in a MySQL database. The service reads a configuration file that specifies the details of the merge operation, such as the names of the tables, the keys to join on, the type of join, and the output file name. Easy to use and highly flexible, Data Merger simplifies the process of merging data.
Requires Python: ==3.10.*


# Data Merger Service

Data Merger Service is a Python package that provides a simple and flexible way to merge data from two tables in a MySQL database. The service reads a configuration file that specifies the details of the merge operation, such as the names of the tables, the keys to join on, the type of join, and the output file name.

## Installation

You can install DataMerger from PyPI:

```bash
pip install atreign-datamanager
```

## Usage

To use Data Merger Service, you need to create a configuration file in JSON format. Hereâ€™s an example:

```json
{
    "database_config": {
        "server_host": "localhost",
        "server_port": "3306",
        "user_name": "root",
        "user_password": "password",
        "database_name": "database_name"
    },
    "data_merge_operations": [
        {
            "left_data_table": {
                "table_name": "table1",
                "merge_keys": ["key1", "key3"]
            },
            "right_data_table": {
                "table_name": "table2",
                "merge_keys": ["key2", "key4"]
            },
            "merge_type": "inner",
            "column_suffixes": ["_from_left_table", "_from_right_table"],
            "output_file_name": "merged_data_output.csv"
        }
    ]
}
```

Once you have your configuration file, you can perform the merge operation with a single function call:

```python
from data_merger import perform_merge_from_config

perform_merge_from_config('config.json')
```

Replace 'config.json' with the path to your actual configuration file.

## Root Directory Structure
```
data_merger_atlas_reign/
â”‚
â”œâ”€â”€ data_merger/
â”‚   â”œâ”€â”€ __init__.py
â”‚   â”œâ”€â”€ config_loader.py
â”‚   â”œâ”€â”€ database_connector.py
â”‚   â”œâ”€â”€ data_operations.py
â”‚   â””â”€â”€ logger.py
â”‚
â”œâ”€â”€ tests/
â”‚   â”œâ”€â”€ __init__.py
â”‚   â”œâ”€â”€ test_config_loader.py
â”‚   â”œâ”€â”€ test_database_connector.py
â”‚   â””â”€â”€ test_data_operations.py
â”‚
â”œâ”€â”€ server_logs/
â”‚   â””â”€â”€ DataMerger.log
â”‚
â”œâ”€â”€ config.json
â”œâ”€â”€ test_config.json
â”œâ”€â”€ requirements.txt
â”œâ”€â”€ setup.py
â””â”€â”€ main.py

```
## Contributing

If you want to contribute to this project, please submit a pull request.

## License

This project is licensed under the MIT License.
montiege 0.2.0
Usefull librairy to plot graph
Requires Python: >=3.8

# PrintGraph

## Description
PrintGraph is a simple python script that prints a graph.

### Parameters
- listX (list): List of list, each sublist should contain x coordinates of every dot
- listY (list): List of list, each sublist should contain y coordinates of every dot
- listLabel (list) : List of string, label of each curve
- title (str) : Title of the plot
- xLabel (str) : Label of x axis (optional) (default : X Axis)
- yLabel (str) : Label of y axis (optional) (default : Y Axis)
- width (int) : Width of the plot (optional) (default : 10)
- height (int) : Height of the plot (optional) (default : 6)
- xScale (str) : Scale of x axis (optional) (linear, log, symlog, logit) (default : log)
- yScale (str) : Scale of y axis (optional) (linear, log, symlog, logit) (default : log)


## Usage
```python 
xVal = [[10, 100, 1000, 10000, 100000],
          [10, 100, 1000, 10000, 100000, 1000000],
          [10, 100, 1000, 10000, 100000]]

yVal = [[57294, 607418, 6755705, 331559735, 33178671213],
          [45717, 299134, 1715546, 10415336, 157352093, 12800502882], [69268, 2490323, 5273649, 71921675, 3268629864]]
curvesLabel = ["HeapTree", "ArrayList", "HeapArray"]
name = 'Compare sort algorithms on random lists'
xLabel = 'List size'
yLabel = 'Execution time (nano seconds)'
xScale = "log"
yScale = "log"

curves(xVal, yVal, curvesLabel, name, xLabel, yLabel, xScale=xScale, yScale=yScale)
```

### Plot : 

![Plot example](image.png)

### Dependencies
* Python 3.8 or higher
* Matplotlib
examAnalyserINF219v23 0.1.15
Exam analyzer
Keywords: python,education,exam analysis


# Exam analyzer
Exam analyzer is a tool that extract data from json files, and the creates visualizations with descriptive texts.


## Getting started
To run the exam analyzer you need following libraries:
- matlab - pip install matlab
- flask - pip install Flask
- latex and pypandocs - go to the followng link https://www.tug.org/mactex/mactex-download.html, and donwload the package. After it is downloaded run  the command line:  pip install pandoc pypandoc

## running the website
If everthing is donwloaded and updated, you should be able to run the local webpage. When you import the package at run the app the terminal should show up and you can be able to go to the link in the terminal.
delpinos-rabbitmq-api 0.0.3
Delpinos Rabbitmq API - Delpinos Framework
Requires Python: >=3.10
Keywords: delpinos,rabbitmq,api

# Delpinos API Core - Python

![GitHub repo size](https://img.shields.io/github/repo-size/delpinos/delpinos-rabbitmq-api-python?style=for-the-badge)
![GitHub language count](https://img.shields.io/github/languages/count/delpinos/delpinos-rabbitmq-api-python?style=for-the-badge)
![GitHub forks](https://img.shields.io/github/forks/delpinos/delpinos-rabbitmq-api-python?style=for-the-badge)
![GitHub open issues](https://img.shields.io/github/issues-raw/delpinos/delpinos-rabbitmq-api-python?style=for-the-badge)
![GitHub open pull requests](https://img.shields.io/github/issues-pr-raw/delpinos/delpinos-rabbitmq-api-python?style=for-the-badge)


> Base codes for creating python modules
delpinos-rabbitmq 0.0.4
Delpinos Rabbitmq - Delpinos Framework
Requires Python: >=3.10
Keywords: delpinos,rabbitmq

# Delpinos API Core - Python

![GitHub repo size](https://img.shields.io/github/repo-size/delpinos/delpinos-rabbitmq-python?style=for-the-badge)
![GitHub language count](https://img.shields.io/github/languages/count/delpinos/delpinos-rabbitmq-python?style=for-the-badge)
![GitHub forks](https://img.shields.io/github/forks/delpinos/delpinos-rabbitmq-python?style=for-the-badge)
![GitHub open issues](https://img.shields.io/github/issues-raw/delpinos/delpinos-rabbitmq-python?style=for-the-badge)
![GitHub open pull requests](https://img.shields.io/github/issues-pr-raw/delpinos/delpinos-rabbitmq-python?style=for-the-badge)


> Base codes for creating python modules
delpinos-crud-sqlalchemy 0.0.4
Delpinos Crud SqlAlchemy - Delpinos Framework
Requires Python: >=3.10
Keywords: delpinos,crud,sqlalchemy

# Delpinos API Core - Python

![GitHub repo size](https://img.shields.io/github/repo-size/delpinos/delpinos-crud-sqlalchemy-python?style=for-the-badge)
![GitHub language count](https://img.shields.io/github/languages/count/delpinos/delpinos-crud-sqlalchemy-python?style=for-the-badge)
![GitHub forks](https://img.shields.io/github/forks/delpinos/delpinos-crud-sqlalchemy-python?style=for-the-badge)
![GitHub open issues](https://img.shields.io/github/issues-raw/delpinos/delpinos-crud-sqlalchemy-python?style=for-the-badge)
![GitHub open pull requests](https://img.shields.io/github/issues-pr-raw/delpinos/delpinos-crud-sqlalchemy-python?style=for-the-badge)


> Base codes for creating python modules
delpinos-api-flask 0.0.4
Delpinos API - Flask - Delpinos Framework
Requires Python: >=3.10
Keywords: delpinos,api,flask

# Delpinos API Flask - Python

![GitHub repo size](https://img.shields.io/github/repo-size/delpinos/delpinos-api-flask-python?style=for-the-badge)
![GitHub language count](https://img.shields.io/github/languages/count/delpinos/delpinos-api-flask-python?style=for-the-badge)
![GitHub forks](https://img.shields.io/github/forks/delpinos/delpinos-api-flask-python?style=for-the-badge)
![GitHub open issues](https://img.shields.io/github/issues-raw/delpinos/delpinos-api-flask-python?style=for-the-badge)
![GitHub open pull requests](https://img.shields.io/github/issues-pr-raw/delpinos/delpinos-api-flask-python?style=for-the-badge)


> Base codes for creating python modules
delpinos-core 0.0.3
Base codes - Delpinos Framework
Requires Python: >=3.10
Keywords: delpinos,framework,core

# Delpinos Core - Python

![GitHub repo size](https://img.shields.io/github/repo-size/delpinos/delpinos-core-python?style=for-the-badge)
![GitHub language count](https://img.shields.io/github/languages/count/delpinos/delpinos-core-python?style=for-the-badge)
![GitHub forks](https://img.shields.io/github/forks/delpinos/delpinos-core-python?style=for-the-badge)
![GitHub open issues](https://img.shields.io/github/issues-raw/delpinos/delpinos-core-python?style=for-the-badge)
![GitHub open pull requests](https://img.shields.io/github/issues-pr-raw/delpinos/delpinos-core-python?style=for-the-badge)


> Base codes for creating python modules
housing-library-5500 0.2
Sample code for coding practice
Requires Python: >=3.11
Keywords: housing,data training

#This Submission consists of soulutions for Tamlep-Assignment-2.1

# Median housing value prediction

The housing data can be downloaded from https://raw.githubusercontent.com/ageron/handson-ml/master/. The script has codes to download the data. We have modelled the median house value on given housing data. 

The following techniques have been used: 

 - Linear regression
 - Decision Tree
 - Random Forest

## Steps performed
 - We prepare and clean the data. We check and impute for missing values.
 - Features are generated and the variables are checked for correlation.
 - Multiple sampling techinuqies are evaluated. The data set is split into train and test.
 - All the above said modelling techniques are tried and evaluated. The final metric used to evaluate is mean squared error.

## To excute the script
Steps to reproduce:
1. ``` unzip dist/housing_library_5500-0.1-py3-none-any.whl -d wheel_contents```
2. ``` cd wheel_contents```
3. ``` python3 house_price_prediction/score.py ```

## To activate the environment
```conda activate <environment-name>```

## To export the environment
```conda env export > environment.yml```

## To import the environment
``` conda env create -f environment.yml```

## LICENSE

This project is licensed under the MIT license -  see the (LICENSE) file for details