semvec/pypi-packages huggingface dataset:
ent1ctosqlite 0.1.1
A tool for converting 1C:Enterprise configurations to SQLite database
Requires Python: >=3.7

# ent1ctosqlite

Version 0.1.1

A tool for converting 1C:Enterprise configuration files extracted from the configurator using the "Upload to files" command into a SQLite database

## Installation

pip install ent1ctosqlite

## Usage

ent1ctosqlite path/to/config.zip

### Command Line Arguments

- `zip_path` - path to the configuration export zip archive
- `-o, --output` - path to the extraction directory (default: temp)
- `-d, --database` - path to the SQLite database file (default: vcv_parser.db)
- `--log-file` - save log to file
- `--debug` - enable debug mode
- `--check-db` - check database integrity

## Development

1. Clone the repository
2. Create a virtual environment
3. Install development dependencies
4. Run tests

git clone https://github.com/yourusername/ent1ctosqlite.git

cd ent1ctosqlite

python -m venv venv

source venv/bin/activate # On Windows: venv\Scripts\activate

pip install -e ".[dev]"

pytest

## Contributing

1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request

## License

MIT

## Authors

- Your Name (@yourusername)

## Acknowledgments

- Thanks to all contributors
- Inspired by the need for better 1C:Enterprise configuration analysis tools
keev 0.1.2
A minimal yet ultrafast ASGI framework
Requires Python: >=3.8

# Keev

A lightweight ASGI web framework for Python that focuses on simplicity and performance.

## Features

- FastAPI-like route decorators
- Built-in request validation using Pydantic
- Automatic OpenAPI docs (Swagger UI & ReDoc)
- SQLAlchemy integration
- Static file serving
- Middleware support
- Plugin system
- Colored logging

## Installation

```bash
pip install keev
```

## Quick Start

```python
from keev import Application, Router, JSONResponse
from pydantic import BaseModel

app = Application()
router = Router()

class Item(BaseModel):
    name: str
    price: float

@router.get("/")
async def read_root():
    return JSONResponse({"message": "Hello World"})

@router.post("/items")
async def create_item(item: Item):
    return JSONResponse(item.model_dump(), status_code=201)

app.router = router

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)
```

## Running the Example

1. Clone the repository:
```bash
git clone https://github.com/yourusername/keev.git
cd keev
```

2. Create and activate a virtual environment:
```bash
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
```

3. Install dependencies:
```bash
pip install -r requirements.txt
```

4. Run the example app:
```bash
python example.py
```

The server will start at http://localhost:8000. Visit:
- http://localhost:8000/ - API root
- http://localhost:8000/docs - Swagger UI documentation
- http://localhost:8000/redoc - ReDoc documentation

## Development

### Running Tests

```bash
pytest tests/
```

### Running Benchmarks

```bash
python benchmark.py
```

## Project Status

This is a hobby project created for learning purposes. While functional, it's not recommended for production use.

## License

MIT
database-reporting-utils 0.1.3
Collection of Python utils for executing queries and generating report files.
Requires Python: >=3.6
Keywords: database_reporting_utils

========================
Database Reporting Utils
========================
Collection of Python utils for executing queries and generating report files.

Exported Scripts
----------------

* run-queries

Usage
-----

Install the package
-------------------

.. code-block:: shell

    pip install database-report-utils

Create the .env file
--------------------

.. code-block:: bash

    DB_SERVER = localhost
    DB_DATABASE = mydatabase
    DB_USERNAME = root
    DB_PASSWORD = root
    DB_DRIVER = ODBC Driver 17 for SQL Server

Create the queries file
-----------------------

my_queries.sql

.. code-block:: sql

    SELECT COUNT(*) 
    FROM table1
    WHERE column1 = "condition-1";

    SELECT COUNT(*) 
    FROM table2
    WHERE column2 = "condition-2";

Execute queries and generate report
-----------------------------------

.. code-block:: shell

    run-queries --infile my_queries.sql


=======
History
=======

0.1.0 (2025-02-08)
------------------

* First release on PyPI.
readwrite 0.10.1
readwrite - Quickly read/write file in common formats
Requires Python: >=3
Keywords: package development template

Quickly read and write file based on their extension.

[![PyTest](https://github.com/crunchdao/readwrite/actions/workflows/pytest.yml/badge.svg)](https://github.com/crunchdao/readwrite/actions/workflows/pytest.yml)

- [Install](#install)
- [CLI Usage](#cli-usage)
- [Code Usage](#code-usage)
- [Supported Extensions](#supported-extensions)

## Install

```
python3 -m pip install --upgrade readwrite
```

## CLI Usage

```bash
readf [FILE-PATHS...]
```

or

```bash
readfile <EXTENSION> [EXTENSION-SPECIFIC-OPTIONS] [FILE-PATHS...]
```

## Code Usage

```python
import readwrite as rw

# will use pandas.read_csv(...)
df = rw.read("data.csv")

# will use pandas.to_parquet(...)
rw.write(df, "data.parquet")
```

## Supported Extensions

| Handler | Extensions | Backend | Read | Write |
| --- | --- | --- |:---:|:---:|
| [Binary](./readwrite/handlers/binary.py) | `bin` | [Python's `bytes`](https://docs.python.org/3/library/stdtypes.html#bytes) | :heavy_check_mark: | :heavy_check_mark: |
| [Csv](./readwrite/handlers/csv.py) | `csv` | [`pandas`](https://pandas.pydata.org/) | :heavy_check_mark: | :heavy_check_mark: |
| [Excel](./readwrite/handlers/excel.py) | `xlsx` | [`pandas`](https://pandas.pydata.org/) | :heavy_check_mark: | :heavy_check_mark: |
| [H5ad](./readwrite/handlers/h5ad.py) | `h5ad` | [`scanpy`](https://scanpy.readthedocs.io/en/stable/) | :heavy_check_mark: | :x: |
| [Joblib](./readwrite/handlers/joblib.py) | `joblib` | [`joblib`](https://joblib.readthedocs.io/) | :heavy_check_mark: | :heavy_check_mark: |
| [Json](./readwrite/handlers/json.py) | `json` | [Python's `json`](https://docs.python.org/3/library/json.html) | :heavy_check_mark: | :heavy_check_mark: |
| [Parquet](./readwrite/handlers/parquet.py) | `parquet` | [`pandas`](https://pandas.pydata.org/) | :heavy_check_mark: | :heavy_check_mark: |
| [Pickle](./readwrite/handlers/pickle.py) | `pkl`, `pickle` | [Python's `pickle`](https://docs.python.org/3/library/pickle.html) or [`pandas`](https://pandas.pydata.org/) | :heavy_check_mark: | :heavy_check_mark: |
| [Toml](./readwrite/handlers/toml.py) | `toml` | [`toml`](https://pypi.org/project/toml/) | :heavy_check_mark: | :heavy_check_mark: |
| [Tar](./readwrite/handlers/tar.py) | `tar` | [Python's `tarfile`](https://docs.python.org/3/library/tarfile.html) | :heavy_check_mark: | :x: |
| [Text](./readwrite/handlers/text.py) | `txt` | [Python's `str`](https://docs.python.org/3/library/stdtypes.html#str) | :heavy_check_mark: | :heavy_check_mark: |
| [Yaml](./readwrite/handlers/yaml.py) | `yml`, `yaml` | [`PyYAML`](https://pyyaml.org/) | :heavy_check_mark: | :heavy_check_mark: |
| [Zarr](./readwrite/handlers/zarr.py) | `zarr` | [`SpatialData`](https://spatialdata.scverse.org/en/stable/) | :heavy_check_mark: | :x: |
| [Zip](./readwrite/handlers/zip.py) | `zip` | [Python's `zipfile`](https://docs.python.org/3/library/zipfile.html) | :heavy_check_mark: | :x: |