vendor_report/README.md
2025-11-06 20:50:19 +04:00

544 lines
15 KiB
Markdown

# Vendor Report Generator
A Python tool that generates comprehensive vendor punchlist reports from Excel files. The tool processes Excel data, normalizes vendor information, calculates metrics, and generates both JSON and interactive HTML reports.
> **📘 For Taskboard Integration**: See [TASKBOARD_INTEGRATION_CONTEXT.md](./TASKBOARD_INTEGRATION_CONTEXT.md) for detailed context and integration possibilities.
## Features
- **Direct Excel Processing**: Reads Excel files directly using pandas
- **Data Normalization**: Automatically normalizes vendor names, statuses, and priorities
- **24-Hour Updates**: Tracks items added, closed, or changed to monitor status in the last 24 hours (based on Baltimore/Eastern timezone)
- **Priority Tracking**: Groups items by priority levels (Very High, High, Medium, Low)
- **Oldest Unaddressed Items**: Identifies and highlights the oldest 3 unaddressed items per vendor
- **Interactive HTML Reports**: Generates searchable, filterable HTML reports with tabs and filters
- **JSON Export**: Exports structured JSON data for further processing
- **SharePoint Integration**: Automatically download Excel files from SharePoint
- **Scheduled Generation**: Automatically generate reports on a schedule (interval or cron)
- **Web API**: REST API for on-demand report generation
## Requirements
- Python 3.8 or higher
- Dependencies listed in `requirements.txt`
## Installation
1. **Clone the repository**:
```bash
git clone https://gitea.lci.ge/ilia.gurielidze/vendor_report.git
cd vendor_report
```
2. **Create a virtual environment** (recommended):
```bash
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. **Install dependencies**:
```bash
pip install -r requirements.txt
```
## Setup
1. **Prepare your Excel files**:
- Place your Excel files (`.xlsx` or `.xls`) in the `reports/` directory
- Ensure your Excel files have the following columns (in order):
- Column 0: Punchlist Name
- Column 1: Vendor
- Column 2: Priority
- Column 3: Description
- Column 4: Date Identified
- Column 5: Status Updates
- Column 6: Issue Image
- Column 7: Status
- Column 8: Date Completed (optional)
2. **Create necessary directories** (if they don't exist):
```bash
mkdir -p reports output
```
## Usage
### Basic Usage
Generate a report from Excel files in the `reports/` directory:
```bash
python3 report_generator.py
```
This will:
- Process all Excel files in the `reports/` directory
- Generate a JSON report at `output/report.json`
- Generate an HTML report at `output/report.html`
- Save preprocessed data to `output/preprocessed_data.txt`
### Command-Line Options
```bash
python3 report_generator.py [OPTIONS]
```
**Options**:
- `--reports-dir DIR`: Directory containing Excel files (default: `reports`)
- `--output FILE`: Output JSON file path (default: `output/report.json`)
- `--verbose`: Print verbose output (default: True)
**Examples**:
```bash
# Use a custom reports directory
python3 report_generator.py --reports-dir /path/to/excel/files
# Specify custom output file
python3 report_generator.py --output /path/to/output/report.json
# Combine options
python3 report_generator.py --reports-dir my_reports --output my_output/report.json
```
### Programmatic Usage
You can also use the report generator in your own Python scripts:
```python
from report_generator import generate_report
# Generate report with default settings
report_data = generate_report()
# Or with custom settings
report_data = generate_report(
reports_dir="my_reports",
output_file="my_output/report.json",
verbose=True
)
# report_data is a dictionary containing the full report structure
print(f"Processed {len(report_data['vendors'])} vendors")
```
## Report Structure
### JSON Report Structure
The generated JSON report follows this structure:
```json
{
"report_generated_at": "2025-11-05T22:00:00",
"vendors": [
{
"vendor_name": "VendorName",
"total_items": 10,
"closed_count": 5,
"open_count": 3,
"monitor_count": 2,
"updates_24h": {
"added": [...],
"closed": [...],
"changed_to_monitor": [...]
},
"oldest_unaddressed": [...],
"very_high_priority_items": [...],
"high_priority_items": [...],
"closed_items": [...],
"monitor_items": [...],
"open_items": [...]
}
],
"summary": {
"total_vendors": 5,
"total_items": 50,
"total_closed": 25,
"total_open": 15,
"total_monitor": 10
}
}
```
### HTML Report Features
The HTML report includes:
- **Summary Cards**: Overview statistics at the top
- **Vendor Tabs**: Quick navigation between vendors
- **Status Tabs**: Filter by status (All, Yesterday's Updates, Oldest Unaddressed, Closed, Monitor, Open)
- **Search & Filters**:
- Search by item name or description
- Filter by vendor, status, or priority
- **Quick Filters**:
- Show only vendors with yesterday's updates
- Show only vendors with oldest unaddressed items
- Show all vendors
- **Interactive Elements**: Click tabs to switch views, use filters to narrow down results
## Data Processing Details
### Vendor Name Normalization
The tool automatically normalizes vendor names:
- Handles case variations (e.g., "autstand" → "Autstand")
- Preserves intentional capitalization (e.g., "AutStand" stays as-is)
- Normalizes combined vendors (e.g., "Autstand/Beumer")
- Handles vendors in parentheses (e.g., "MFO (Amazon)")
### Status Normalization
Statuses are normalized to:
- **Complete**: Items with status containing "complete" or "complette"
- **Monitor**: Items with status containing "monitor" or "montor"
- **Incomplete**: All other items (default)
### Priority Classification
Priorities are classified as:
- **Very High**: Priority contains "(1) Very High" or "Very High"
- **High**: Priority contains "(2) High" or "High" (but not "Very High")
- **Medium**: Priority contains "(3) Medium" or "Medium"
- **Low**: Priority contains "(4) Low" or "Low"
### 24-Hour Window Calculation
The tool uses **Baltimore/Eastern timezone (America/New_York)** for calculating 24-hour updates:
- Items are considered "added in last 24h" if their `date_identified` falls on yesterday's date
- Items are considered "closed in last 24h" if their `date_completed` falls on yesterday's date
- Items are considered "changed to monitor" if their status is Monitor and the date falls within the 24-hour window
## Output Files
After running the generator, you'll find:
- `output/report.json`: Structured JSON report data
- `output/report.html`: Interactive HTML report (open in browser)
- `output/preprocessed_data.txt`: Human-readable preprocessed data (for debugging)
## Project Structure
```
vendor_report/
├── report_generator.py # Main report generation script
├── data_preprocessor.py # Excel data preprocessing and normalization
├── html_generator.py # HTML report generation
├── models.py # Pydantic data models
├── excel_to_text.py # Utility for Excel to text conversion
├── sharepoint_downloader.py # SharePoint file downloader
├── scheduler.py # Scheduled report generation
├── api_server.py # REST API for on-demand reports
├── web_ui.py # Web UI for easy access
├── config.py # Configuration management
├── config.yaml.template # Configuration template
├── requirements.txt # Python dependencies
├── reports/ # Directory for input Excel files
├── output/ # Directory for generated reports
└── README.md # This file
```
## Troubleshooting
### No Excel files found
Ensure your Excel files are in the `reports/` directory and have `.xlsx` or `.xls` extensions.
### Date parsing errors
The tool supports common date formats:
- `MM/DD/YY` (e.g., `10/14/25`)
- `MM/DD/YYYY` (e.g., `10/14/2025`)
- `YYYY-MM-DD` (e.g., `2025-10-17`)
- `YYYY-MM-DD HH:MM:SS` (e.g., `2025-10-17 00:00:00`)
### Permission errors
If you encounter permission errors, ensure you have write access to the `output/` directory.
### Missing dependencies
If you get import errors, ensure all dependencies are installed:
```bash
pip install -r requirements.txt
```
## Timezone Notes
The tool uses **Baltimore/Eastern timezone (America/New_York)** for all date calculations. This ensures consistent 24-hour window calculations regardless of where the script is run. All dates are stored as timezone-aware datetime objects.
## SharePoint Integration
The application can automatically download Excel files from SharePoint before generating reports. This is useful when your source data is stored in SharePoint.
### Setup SharePoint Integration
1. **Create a configuration file**:
```bash
cp config.yaml.template config.yaml
```
2. **Edit `config.yaml`** and configure SharePoint settings:
```yaml
sharepoint:
enabled: true
site_url: "https://yourcompany.sharepoint.com/sites/YourSite"
folder_path: "/Shared Documents/Reports"
local_dir: "reports"
use_app_authentication: true # Recommended for automation
client_id: "your-azure-ad-client-id"
client_secret: "your-azure-ad-client-secret"
```
3. **Authentication Options**:
**Option A: App Authentication (Recommended)**
- Register an app in Azure AD
- Grant SharePoint permissions (Sites.Read.All or Sites.ReadWrite.All)
- Use `client_id` and `client_secret` in config
- Set `use_app_authentication: true`
**Option B: User Authentication**
- Use your SharePoint username and password
- Set `username` and `password` in config
- Set `use_app_authentication: false`
4. **Test SharePoint download**:
```bash
python sharepoint_downloader.py
```
### Manual SharePoint Download
Download files from SharePoint without generating a report:
```bash
python sharepoint_downloader.py
```
## Scheduled Report Generation
The application can automatically generate reports on a schedule, optionally downloading from SharePoint first.
### Setup Scheduling
1. **Edit `config.yaml`**:
```yaml
scheduler:
enabled: true
schedule_type: "interval" # or "cron"
interval_hours: 24 # Generate every 24 hours
# OR use cron expression:
# cron_expression: "0 8 * * *" # 8 AM daily
timezone: "America/New_York"
```
2. **Start the scheduler**:
```bash
python scheduler.py
```
The scheduler will run continuously and generate reports according to your schedule.
3. **Schedule Types**:
- **interval**: Generate report every N hours
- **cron**: Use cron expression for precise scheduling (e.g., "0 8 * * *" for 8 AM daily)
- **once**: Run once immediately (for testing)
### Running Scheduler as a Service
**Linux (systemd)**:
```bash
# Create service file: /etc/systemd/system/vendor-report-scheduler.service
[Unit]
Description=Vendor Report Scheduler
After=network.target
[Service]
Type=simple
User=your-user
WorkingDirectory=/path/to/vendor_report
ExecStart=/usr/bin/python3 /path/to/vendor_report/scheduler.py
Restart=always
[Install]
WantedBy=multi-user.target
# Enable and start
sudo systemctl enable vendor-report-scheduler
sudo systemctl start vendor-report-scheduler
```
**Windows (Task Scheduler)**:
- Create a scheduled task that runs `python scheduler.py` at startup or on a schedule
## Web UI & On-Demand Report Generation
The application includes both a **Web UI** and a **REST API** for generating reports on demand.
### Web UI (Recommended for Easy Access)
A simple, user-friendly web interface for generating reports without using the terminal.
1. **Start the Web UI server**:
```bash
python web_ui.py
```
2. **Open in browser**:
```
http://localhost:8080
```
3. **Features**:
- One-click report generation
- Download from SharePoint & generate (single button)
- View generated reports
- View service status
- View configuration
- No terminal knowledge required!
### REST API
The application also includes a REST API for integration with other systems or manual triggers.
### Setup API Server
1. **Edit `config.yaml`**:
```yaml
api:
enabled: true
host: "0.0.0.0"
port: 8080
api_key: "your-secret-api-key" # Optional, for authentication
```
2. **Start the Web UI** (recommended):
```bash
python web_ui.py
```
Then open `http://localhost:8080` in your browser.
**OR start the API server** (for programmatic access):
```bash
python api_server.py
```
3. **Generate report via API**:
```bash
# Without authentication
curl -X POST http://localhost:8080/api/generate \
-H "Content-Type: application/json" \
-d '{"download_from_sharepoint": true}'
# With API key authentication
curl -X POST http://localhost:8080/api/generate \
-H "Content-Type: application/json" \
-H "X-API-Key: your-secret-api-key" \
-d '{"download_from_sharepoint": true}'
```
### API Endpoints
- **POST `/api/generate`**: Generate report on demand
- Request body (optional):
```json
{
"download_from_sharepoint": true,
"reports_dir": "reports",
"output_file": "output/report.json"
}
```
- **GET `/api/status`**: Get service status and configuration
- **GET `/health`**: Health check endpoint
### Example: Integration with Webhook
You can trigger report generation from SharePoint webhooks, Power Automate, or any HTTP client:
```python
import requests
response = requests.post(
'http://your-server:8080/api/generate',
json={'download_from_sharepoint': True},
headers={'X-API-Key': 'your-api-key'}
)
print(response.json())
```
## Configuration
The application uses a YAML configuration file (`config.yaml`) for all settings. You can also use environment variables:
### Environment Variables
```bash
# SharePoint
export SHAREPOINT_ENABLED=true
export SHAREPOINT_SITE_URL="https://yourcompany.sharepoint.com/sites/YourSite"
export SHAREPOINT_FOLDER_PATH="/Shared Documents/Reports"
export SHAREPOINT_CLIENT_ID="your-client-id"
export SHAREPOINT_CLIENT_SECRET="your-client-secret"
export SHAREPOINT_USE_APP_AUTH=true
# Scheduler
export SCHEDULER_ENABLED=true
export SCHEDULER_INTERVAL_HOURS=24
# API
export API_ENABLED=true
export API_PORT=8080
export API_KEY="your-api-key"
```
## Complete Workflow Example
Here's a complete example setup for automated SharePoint → Report generation:
1. **Setup configuration** (`config.yaml`):
```yaml
sharepoint:
enabled: true
site_url: "https://company.sharepoint.com/sites/Reports"
folder_path: "/Shared Documents/Vendor Reports"
use_app_authentication: true
client_id: "your-client-id"
client_secret: "your-client-secret"
scheduler:
enabled: true
schedule_type: "cron"
cron_expression: "0 8 * * *" # 8 AM daily
timezone: "America/New_York"
report:
output_dir: "output"
reports_dir: "reports"
```
2. **Start scheduler**:
```bash
python scheduler.py
```
3. **The scheduler will**:
- Download latest Excel files from SharePoint at 8 AM daily
- Generate reports automatically
- Save to `output/report.json` and `output/report.html`
## License
[Add your license information here]
## Contributing
[Add contribution guidelines if applicable]
## Support
For issues or questions, please contact [your contact information or issue tracker URL].