Data Export

Overview

CoroNet provides seamless data export functionality, allowing users to download the complete vehicle registration database as a CSV file. This enables data analysis in spreadsheet applications, integration with third-party systems, and backup creation.

Export Endpoint

The export functionality is implemented through a single, straightforward endpoint:

@app.route("/descargar")
def descargar():
    ensure_csv()
    return send_file(DATA_PATH, as_attachment=True, download_name="registros.csv")

Implementation details:

Route: /descargar (Spanish for “download”) (app.py:154)
Method: GET request
File validation: Calls ensure_csv() to guarantee file exists (app.py:155)
Response: Streams the CSV file directly to the browser (app.py:156)
Download name: File is saved as registros.csv on the user’s device

The export endpoint uses Flask’s send_file() function with as_attachment=True, which triggers a browser download dialog instead of displaying the file inline.

CSV File Structure

The exported CSV follows a consistent seven-column format:

id,fecha_hora,matricula,propietario,tipo_vehiculo,observacion,imagen
1,2024-03-15 14:30:22,ABC123,Juan Pérez,Automóvil,Vehículo oficial,matricula_20240315_143022.jpg
2,2024-03-15 14:35:10,XYZ789,María García,Camioneta,Visitante,matricula_20240315_143510.jpg
3,2024-03-15 15:20:45,DEF456,Carlos López,Motocicleta,,matricula_20240315_152045.jpg

Column Specifications

id - Unique Identifier

Type: String (numeric)
Format: Auto-incremented integer starting at 1
Purpose: Unique identifier for each registration
Usage: Can be used for record lookup, deletion, or updates

fecha_hora - Timestamp

Type: String (datetime)
Format: YYYY-MM-DD HH:MM:SS (ISO-like format)
Example: 2024-03-15 14:30:22
Purpose: Records exact date and time of vehicle entry
Usage: Chronological sorting, time-based filtering, audit trails

matricula - License Plate

Type: String (alphanumeric)
Format: Uppercase, alphanumeric + hyphens only, max 10 characters
Example: ABC-123, XYZ789
Source: Automatically detected via GPT-4o or Tesseract OCR
Special value: NO_DETECTADA when detection fails
Normalization: Spaces removed, uppercase conversion applied (app.py:74-75)

propietario - Vehicle Owner

Type: String (free text)
Format: User-provided, supports UTF-8 characters
Example: Juan Pérez, María García
Purpose: Identifies the vehicle owner or driver
Usage: Owner lookup, access control, contact information

tipo_vehiculo - Vehicle Type

Type: String (free text)
Format: User-provided category
Examples: Automóvil, Camioneta, Motocicleta, Camión
Purpose: Categorizes vehicles for reporting and analysis
Usage: Vehicle type statistics, parking allocation, access rules

observacion - Notes/Observations

Type: String (free text, optional)
Format: User-provided notes
Examples: Vehículo oficial, Visitante, Entrega de paquetes
Purpose: Additional context or special conditions
Usage: Security notes, visitor tracking, special permissions

imagen - Image Filename

Type: String (filename)
Format: matricula_YYYYMMDD_HHMMSS.jpg
Example: matricula_20240315_143022.jpg
Purpose: References the uploaded vehicle image
Location: Physical file stored in uploads/ directory
Usage: Visual verification, evidence, manual plate verification

How the Export Works

Step-by-Step Process

User Interaction
Server Processing
File Transfer

User clicks the download/export button in the web interface
Browser sends GET request to /descargar
Server processes request and initiates file download
Browser saves registros.csv to the user’s download folder

Flask receives request at /descargar endpoint (app.py:154)
ensure_csv() validates that the CSV file exists (app.py:155)
send_file() streams the file contents to the client (app.py:156)
as_attachment=True triggers download instead of display
download_name parameter sets the filename to registros.csv

File Validation

Before export, the system ensures data integrity:

def ensure_csv():
    if not os.path.exists(DATA_PATH):
        with open(DATA_PATH, "w", newline="", encoding="utf-8") as f:
            csv.writer(f).writerow(CSV_HEADER)

This guarantees that:

The CSV file exists (creates it if missing)
The file has proper headers
Export never fails due to missing file
Empty database exports as header-only CSV

If no registrations exist, the exported CSV will contain only the header row. This is valid CSV format and can be imported into spreadsheet applications.

Use Cases

Data Analysis

The exported CSV can be imported into analysis tools: Excel/Google Sheets:

Create pivot tables for vehicle type distribution
Generate charts showing entries by date/time
Calculate peak traffic hours
Identify frequent visitors by license plate

Python/Pandas:

import pandas as pd

# Load exported data
df = pd.read_csv('registros.csv')

# Convert timestamps
df['fecha_hora'] = pd.to_datetime(df['fecha_hora'])

# Analyze entries by hour
hourly = df.groupby(df['fecha_hora'].dt.hour).size()

# Find most common vehicle types
type_counts = df['tipo_vehiculo'].value_counts()

# Detect repeated plates
repeated = df['matricula'].value_counts()[df['matricula'].value_counts() > 1]

Backup and Archive

Regular CSV exports provide a simple backup mechanism. The file includes all registration metadata but not the actual images (which remain in uploads/).

Backup strategy:

Schedule regular exports (daily/weekly)
Store CSV files with dated filenames
Copy uploads/ directory for complete backup
Archive old records to reduce active database size

Integration with External Systems

The CSV format enables integration with:

Access control systems: Import plates into gate controllers
Billing systems: Calculate parking fees based on entry times
Security databases: Cross-reference with authorized vehicle lists
Reporting tools: Generate compliance and audit reports
Database systems: Bulk import into PostgreSQL, MySQL, etc.

Example: Import to PostgreSQL

CREATE TABLE registros (
    id SERIAL PRIMARY KEY,
    fecha_hora TIMESTAMP,
    matricula VARCHAR(10),
    propietario VARCHAR(255),
    tipo_vehiculo VARCHAR(100),
    observacion TEXT,
    imagen VARCHAR(255)
);

COPY registros(id, fecha_hora, matricula, propietario, tipo_vehiculo, observacion, imagen)
FROM '/path/to/registros.csv'
DELIMITER ','
CSV HEADER;

Technical Implementation

Flask send_file() Function

CoroNet uses Flask’s built-in send_file() for optimal file delivery:

return send_file(
    DATA_PATH,              # Path to the CSV file
    as_attachment=True,     # Trigger download dialog
    download_name="registros.csv"  # Custom filename
)

Key advantages:

Streaming: Large files are streamed without loading into memory
Automatic headers: Sets correct Content-Type and Content-Disposition
Cross-browser support: Works with all modern browsers
Error handling: Handles missing files gracefully

Content-Type Header

Flask automatically sets the appropriate MIME type:

Content-Type: text/csv
Content-Disposition: attachment; filename="registros.csv"

This ensures browsers:

Recognize the file as CSV
Trigger download instead of display
Use the correct filename

Character Encoding

The CSV file uses UTF-8 encoding throughout:

# Writing (creation/update)
with open(DATA_PATH, "w", newline="", encoding="utf-8") as f:
    writer = csv.DictWriter(f, fieldnames=CSV_HEADER)
    writer.writeheader()
    writer.writerows(rows)

This ensures:

International characters (Spanish accents, etc.) are preserved
Compatibility with modern spreadsheet applications
Data integrity during import/export cycles

UTF-8 vs. Latin-1 Encoding

Why UTF-8?

Supports all Unicode characters (accents, emojis, Asian characters)
Standard encoding for modern applications
Compatible with Excel, Google Sheets, LibreOffice

Potential issues with Excel:

Older Excel versions may not auto-detect UTF-8
Solution: Import via “Data > From Text/CSV” instead of double-clicking
Or save as UTF-8 with BOM for better Excel compatibility

Export Limitations

Images Not Included

The CSV export contains only metadata about registrations:

✅ License plate numbers
✅ Owner names
✅ Vehicle types
✅ Timestamps
✅ Image filenames
❌ Actual image data

The physical image files remain in the uploads/ directory. To create a complete backup, you must:

Export the CSV using /descargar
Copy the entire uploads/ directory separately
Maintain the directory structure for image references to work

File Size Considerations

The CSV file size grows linearly with the number of registrations (approximately 100-200 bytes per record). A database with 10,000 entries would produce a ~1-2 MB CSV file.

Performance characteristics:

Small datasets (< 1,000 records): Instant download
Medium datasets (1,000-10,000 records): Few seconds
Large datasets (> 10,000 records): May take 10-30 seconds
Very large datasets (> 100,000 records): Consider pagination or database migration

No Incremental Export

The current implementation exports the entire database every time:

def descargar():
    ensure_csv()
    return send_file(DATA_PATH, as_attachment=True, download_name="registros.csv")

There is no built-in support for:

Date range filtering
Exporting only new records since last export
Partial exports by vehicle type or owner

Workaround for filtered exports: You could implement custom export endpoints:

@app.route("/descargar/rango")
def descargar_rango():
    fecha_inicio = request.args.get('inicio')
    fecha_fin = request.args.get('fin')
    
    rows = read_csv()
    filtered = [
        r for r in rows 
        if fecha_inicio <= r['fecha_hora'] <= fecha_fin
    ]
    
    # Write to temporary file and send
    temp_path = os.path.join(BASE_DIR, "temp_export.csv")
    write_csv_to_path(filtered, temp_path)
    return send_file(temp_path, as_attachment=True, download_name="registros_filtrado.csv")

Security Considerations

Authentication Required

The current implementation does not include authentication. The /descargar endpoint is publicly accessible. For production deployments, add authentication using Flask-Login or similar.

Recommended security additions:

from flask_login import login_required

@app.route("/descargar")
@login_required
def descargar():
    ensure_csv()
    return send_file(DATA_PATH, as_attachment=True, download_name="registros.csv")

Data Privacy

The exported CSV contains personally identifiable information (PII):

Vehicle owner names
License plate numbers
Entry timestamps

Ensure compliance with data protection regulations (GDPR, CCPA) by:

Restricting export access to authorized personnel
Encrypting exported files for transmission
Implementing audit logging for export operations
Providing data retention policies

Future Enhancements

Potential improvements to the export system:

Multiple formats: Add JSON, Excel, PDF export options
Filtered exports: Date ranges, vehicle types, owner names
Scheduled exports: Automatic daily/weekly exports via email
Compressed archives: ZIP files containing CSV + all images
API endpoint: RESTful API for programmatic data access
Pagination: Export in chunks for very large datasets
Custom column selection: Allow users to choose which fields to export

Get Started

Core Features

Configuration

User Guide

Overview

Export Endpoint

CSV File Structure

Column Specifications

How the Export Works

Step-by-Step Process

File Validation

Use Cases

Data Analysis

Backup and Archive

Integration with External Systems

Technical Implementation

Flask send_file() Function

Content-Type Header

Character Encoding

Export Limitations

Images Not Included

File Size Considerations

No Incremental Export

Security Considerations

Authentication Required

Data Privacy

Future Enhancements

Build docs developers (and LLMs) love

Get Started

Core Features

Configuration

User Guide

​Overview

​Export Endpoint

​CSV File Structure

​Column Specifications

​How the Export Works

​Step-by-Step Process

​File Validation

​Use Cases

​Data Analysis

​Backup and Archive

​Integration with External Systems

​Technical Implementation

​Flask send_file() Function

​Content-Type Header

​Character Encoding

​Export Limitations

​Images Not Included

​File Size Considerations

​No Incremental Export

​Security Considerations

​Authentication Required

​Data Privacy

​Future Enhancements

Build docs developers (and LLMs) love

Overview

Export Endpoint

CSV File Structure

Column Specifications

How the Export Works

Step-by-Step Process

File Validation

Use Cases

Data Analysis

Backup and Archive

Integration with External Systems

Technical Implementation

Flask send_file() Function

Content-Type Header

Character Encoding

Export Limitations

Images Not Included

File Size Considerations

No Incremental Export

Security Considerations

Authentication Required

Data Privacy

Future Enhancements