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---
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 |