---
title: Mip Csv Analyser
emoji: 🚀
colorFrom: yellow
colorTo: gray
sdk: streamlit
sdk_version: 1.28.1
app_file: app.py
pinned: false
---

# Batch Run Analyzer

A comprehensive Streamlit application for analyzing batch run results from CSV or XLSX files, visualizing pass/fail statistics, and comparing runs across different environments.

## Features

- Support for both CSV and XLSX file formats
- Multiple analysis modes:
  - **Multi**: Analyze multiple files from different environments
  - **Compare**: Compare two files to identify differences in scenario outcomes
  - **Weekly**: Generate weekly trend reports
  - **Multi-Env Compare**: Compare scenarios across multiple environments
- Detailed statistics on passing and failing scenarios
- Visual charts for failure counts by functional area
- Interactive filtering by functional area and status
- Time spent analysis per functional area
- Error Message analysis

## Setup and Installation

1. Clone this repository:
   ```
   git clone <repository-url>
   cd batch-run-csv-analyser
   ```

2. Install the required dependencies:
   ```
   pip install -r requirements.txt
   ```

3. Run the application:
   ```
   streamlit run app.py
   ```

## File Format Support

### CSV Format (Legacy)
The application still supports the original CSV format with the following columns:
- Functional area
- Scenario Name
- Start datetime
- End datetime
- Status
- Error Message

### XLSX Format (New)
The application now supports XLSX files with step-level data:
- Feature Name
- Scenario Name
- Step
- Result
- Time Stamp
- Duration (ms)
- Error Message

The application will automatically detect the file format based on the file extension and process it accordingly.

## Usage

1. Start the application with `streamlit run app.py`
2. Use the sidebar to select the desired analysis mode
3. Upload the necessary files based on the selected mode
4. Follow the on-screen instructions for filtering and analysis

## Analysis Modes

### Multi Mode
Upload files from multiple environments for individual analysis. View statistics, filter by functional area, and see charts of failing scenarios.

### Compare Mode
Upload two files to compare scenario statuses between them. The application will identify:
- Consistent failures (failed in both files)
- New failures (passed in the older file, failed in the newer)
- New passes (failed in the older file, passed in the newer)

### Weekly Mode
Upload files from multiple dates to see trend reports. Filter by environment and functional area, and view detailed statistics for each day.

### Multi-Env Compare Mode
Compare scenarios across multiple environments to identify inconsistencies in test coverage.

## Notes

- Filename format is important for date extraction in Weekly mode. The application will try to extract dates using various patterns like `name_YYYYMMDD_HHMMSS`, `name_YYYYMMDD`, or any 8-digit sequence resembling a date.
- For XLSX files, all steps within a scenario are aggregated to determine the overall scenario status.

## Troubleshooting

If you encounter issues:
1. Ensure the file format follows the expected structure
2. Check the logs for specific error messages
3. Try processing smaller files first to verify functionality

# Jira Integration for Test Analysis

This application provides a Streamlit interface for analyzing test results and creating Jira tasks for failed scenarios.

## Setup

1. Clone the repository
2. Install dependencies:
```bash
pip install -r requirements.txt
```

3. Create a `.env` file in the root directory with the following variables:
```env
JIRA_SERVER=your_jira_server_url
GROQ_API_KEY=your_groq_api_key
```

## Environment Variables

- `JIRA_SERVER`: Your Jira server URL (e.g., https://jira.yourdomain.com)
- `GROQ_API_KEY`: Your Groq API key for AI functionality

## Running the Application

```bash
streamlit run jira_integration.py
```

## Features

- Jira authentication and session management
- Test scenario analysis
- Automated Jira task creation
- Sprint statistics tracking
- Functional area mapping
- Customer field mapping

## Deployment

This application is designed to be deployed on Huggingface Spaces. When deploying:

1. Add the environment variables in the Huggingface Spaces settings
2. Ensure all dependencies are listed in requirements.txt
3. The application will automatically use the environment variables from Huggingface Spaces

## Security Notes

- Never commit the `.env` file to version control
- Keep your Jira credentials secure
- Use environment variables for all sensitive information