semvec/pypi-packages huggingface dataset:
otrs-somconnexio 0.8.0
Python package for Somconnexio data syncing in OTRS

# Python 2.7/3.8 module to manage the SomConnexio's ERP integration with OTRS

This library manages all the business logic between the Som Connexio's systems and the ticketing tool OTRS.

## [Processes](https://gitlab.com/coopdevs/otrs-somconnexio/-/wikis/processes/README)

## OTRS Configuration

Configure the web services in OTRS:

#### Ticket Connector (Provider)

* Usage:
It exposes the Ticket, Article and DynamicFields object and allows to get, create, update and remove tickets. We use the PyOTRS to interact with it. Look in the [PyOTRS](https://gitlab.com/rhab/PyOTRS/-/blob/master/README.rst) docs for more info.

* Configuration:
Use the template provided by the PyOTRS client: https://gitlab.com/rhab/PyOTRS/-/blob/master/webservices_templates/GenericTicketConnectorREST.yml

#### CustomerUser Connector (Provider)

* Usage:
It's a RPCConnector. It interacts with the OTRS objects directly calling the class methods.

* Configuration:
You need admin permissions to manage it.
Contact with your OTRS provider.

#### MMCaller Connector (Requester)

* Usage:
It calls MMProxy when an event is raised.

* Configuration:
https://gitlab.com/coopdevs/somconnexio-documentation/-/blob/master/integracions/masmovil.md#webservice-dotrs

## Environment configuration

### OTRSClient

The client to interact with OTRS. You need to define the next environment variables to use the client:

```
OTRS_URL=       # Baseurl of the OTRS instance
OTRS_USER=      # Creadencials of user with write acces to OTRS
OTRS_PASSW=
```

## Python version

We are using [Pyenv](https://github.com/pyenv/pyenv) to fix the Python version and the virtualenv to test the package.

You need:

* Intall and configure [`pyenv`](https://github.com/pyenv/pyenv)
* Install and configure [`pyenv-virtualenvwrapper`](https://github.com/pyenv/pyenv-virtualenvwrapper)
* Intall locally the version of python needed:

```
$ pyenv install 3.8.2
```

* Create the virtualenv to use:

```
$ pyenv virtualenv 3.8.2 otrs_somconnexio
```


## Python packages requirements

Install the Python packages in the virtual environment:

```
$ pyenv exec pip install -r requirements.txt
```

## Run tests

To run the test you can run:

```
$ tox
```

Also you can run only the tests running:

```
$ pytest .
```

and if you want the coverage info:

```
$ pytest --cov .
```

If running the tests with tox, they will be tested with both python3.8 and python2.7. This is because OTRS-SomConnexio works with an ERP which uses python2, as well as with other packages that use python3.

## Release process

Release and publish the package to PyPi:

- Update the VERSION var in setup.py matching the version you specified in the CHANGELOG.
- Open a merge request with these changes for the team to approve.
- Merge it, add a git tag on the Deployments > Releases section and push it.
- Once the pipeline has successfully passed, approve the publish step.
Topsis-Pulkit-102303800 1.0.9
TOPSIS CLI tool for Multi-Criteria Decision Making (MCDM) with CSV and Excel support
Requires Python: >=3.6

# Topsis-Pulkit-102303800

A command-line Python implementation of the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** algorithm used in **Multi-Criteria Decision Making (MCDM)**.

![Python](https://img.shields.io/badge/Python-3.6+-blue.svg)
![License](https://img.shields.io/badge/License-MIT-green.svg)
![PyPI](https://img.shields.io/pypi/v/Topsis-Pulkit-102303800)

---

## ðŸ“Œ Features

- Supports **CSV** and **Excel (.xlsx)** input files  
- Implements full TOPSIS ranking method  
- Validates user input and handles common errors  
- Produces decision scores and ranks  
- Lightweight and easy-to-use CLI tool  

---

## ðŸ§® About TOPSIS

TOPSIS ranks alternatives based on their distance from the **ideal best** and **ideal worst** solutions.

---

## usage

topsis <inputfile> <weights> <impacts> <outputfile>


---

## ðŸš€ Installation

```bash
pip install Topsis-Pulkit-102303800

---

##Author

Pulkit Goyal
topsis-nitin-102303918 0.1.0
TOPSIS CLI Tool
Requires Python: >=3.8

# Topsis-Nitin-102303918

A command-line Python implementation of the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** algorithm used in **Multi-Criteria Decision Making (MCDM)**.

---

## Features

- Supports **CSV** and **Excel (.xlsx)** input files  
- Implements full TOPSIS ranking method  
- Validates user input and handles common errors  
- Produces decision scores and ranks  
- Lightweight and easy-to-use CLI tool  

---

## About TOPSIS

TOPSIS is a popular decision-making technique that ranks alternatives based on their distance from the **ideal best** and **ideal worst** solutions.

---

## Installation
pip install topsis-nitin-102303918

---

## Usage

topsis <inputfile> <weights> <impacts> <outputfile>

EXAMPLE: 
topsis data.xlsx "1,1,1,1" "+,+,+,+" result.csv

---

## Input Rules

1. First column → Alternative names
2. Remaining columns → Numeric criteria only
3. Minimum 3 columns required
4. Number of weights must equal number of criteria
5. Number of impacts must equal number of criteria
6. Impacts must be:
    + → Benefit criterion
    - → Cost criterion

---

## Output

The output file contains:
    Original dataset
    Topsis Score
    Rank
**Higher score indicates a better alternative.**

---

## Dependencies

Automatically installed with the package:
pandas
numpy
openpyxl

## Author

**Nitin Malhotra**
ducklake-delta-exporter 0.3.0
A utility to export DuckLake database metadata to Delta Lake transaction logs.
Requires Python: >=3.8

# DuckLake Delta Exporter

A Python package for exporting DuckLake snapshots as Delta Lake checkpoint files, enabling compatibility with Delta Lake readers, support local path, s3 and gcs, for onelake use mounted storage as azure storage is not supported

this is just a fun project, please vote for a proper support in duckdb https://github.com/duckdb/duckdb-delta/issues/218

## Repository

https://github.com/djouallah/ducklake_delta_exporter

## Installation

```bash
pip install ducklake-delta-exporter
```

## Usage

```python
from ducklake_delta_exporter import generate_latest_delta_log

# Export all tables from a DuckLake database
generate_latest_delta_log("/path/to/ducklake.db")

# Specify a custom data root directory
generate_latest_delta_log("/path/to/ducklake.db", data_root="/custom/data/path")
```

## What it does

This package converts DuckLake table snapshots into Delta Lake format by:

1. **Reading DuckLake metadata** - Extracts table schemas, file paths, and snapshot information
2. **Creating Delta checkpoint files** - Generates `.checkpoint.parquet` files with Delta Lake metadata
3. **Writing JSON transaction logs** - Creates minimal `.json` log files for Spark compatibility
4. **Mapping data types** - Converts DuckDB types to Spark SQL equivalents

## Features

- ✅ **Spark Compatible** - Generated Delta files can be read by Spark and other Delta Lake tools
- ✅ **Type Mapping** - Automatic conversion between DuckDB and Spark data types
- ✅ **Batch Processing** - Exports all tables in a DuckLake database
- ✅ **Error Handling** - Graceful handling of missing snapshots and other issues
- ✅ **Progress Reporting** - Clear feedback on export progress and results

## Requirements

- Python 3.8+
- DuckDB

## File Structure

After running the exporter, your Delta tables will have the following structure:

```
your_table/
├── data_file_1.parquet
├── data_file_2.parquet
└── _delta_log/
    ├── 00000000000000000000.json
    ├── 00000000000000000000.checkpoint.parquet
    └── _last_checkpoint
```

## Type Mapping

The exporter automatically maps DuckDB types to Spark SQL types:

| DuckDB Type | Spark Type |
|-------------|------------|
| INTEGER     | integer    |
| BIGINT      | long       |
| FLOAT       | double     |
| DOUBLE      | double     |
| DECIMAL     | decimal(10,0) |
| BOOLEAN     | boolean    |
| TIMESTAMP   | timestamp  |
| DATE        | date       |
| VARCHAR     | string     |
| Others      | string     |

## Error Handling

The exporter handles various error conditions:

- **Missing snapshots** - Skips tables with no data
- **Existing checkpoints** - Avoids overwriting existing files
- **Schema changes** - Uses the latest schema for each table
- **File system errors** - Reports and continues with other tables

## License

MIT License - see LICENSE file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.