semvec/pypi-packages huggingface dataset:
probecheck 0.1.0
A modern, advanced testing framework for probing and validating complex systems.
License: MIT
Requires Python: <4.0,>=3.10

# Testrium

<div style="display: flex; align-items: center;">
  <img src="https://github.com/letalboy/Spectrum/assets/63066865/cf9c60e7-9eba-474c-8cc1-b246e661fd5c" alt="Testrium Logo" width="200" height="200" style="margin-right: 20px;">
  <div>
    <p>Testrium is a versatile library designed to test and analyze systems. It provides tools for data processing, monitoring, and ensuring system integrity, making it an essential part of your development workflow.</p>
  </div>
</div>

## Key Features

- **Better Organization of Tests**: Streamline your testing process with improved test management and categorization.
- **Easy Testing of Async or Parallelized Dependent Tests**: Simplify the testing of asynchronous or parallel workflows with built-in support.
- **Historic Performance Comparison and Evaluation**: Track and compare test performance over time for better insights.
- **Custom Behavior Through Callback Systems**: Customize test behaviors using flexible callback mechanisms.
- **Manipulation of Test Flows**: Gain control over test execution flows to suit various testing scenarios.
- **Highly Configurable and Expandable**: Tailor Testrium to your specific needs with extensive configuration options.

## Installation

Testrium can be installed using [Poetry](https://python-poetry.org/) or [pip](https://pip.pypa.io/en/stable/). 

### Using Poetry

```bash
poetry add testrium
```
mongoDB-python-connector 0.0.1
A python package for connecting with database.
License: MIT
Requires Python: >=3.7

### Description

This code defines a class `mongo_operation` that provides methods for interacting with a MongoDB database. The class allows you to create a MongoDB client, create collections, and insert data in bulk. It supports both single records and lists of records, as well as CSV and Excel file formats.

### How to Use

To use this class as a package on PyPI, you can follow these steps:

1. **Install the Package**:
   ```bash
   pip install mongodb_connect
   ```

2. **Import the Class**:
   ```python
   from mongodb_connect import mongo_crud
   ```

3. **Create an Instance of the Class**:
   ```python
   mongo = mongo_operation(client_url='mongodb://localhost:27017/', database_name='mydatabase', collection_name='mycollection')
   ```

4. **Use the Methods**:
   ```python
   # Insert a single record
   mongo.insert_record({'name': 'John', 'age': 30})

   # Insert multiple records
   records = [{'name': 'Jane', 'age': 25}, {'name': 'Bob', 'age': 40}]
   mongo.insert_record(records)

   # Bulk insert data from a CSV file
   mongo.bulk_insert('data.csv')

   # Bulk insert data from an Excel file
   mongo.bulk_insert('data.xlsx')
   ```