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Django ORM connector for Google BigQuery

Project description

Django BigQuery Connector

A Django database backend for Google BigQuery, enabling Django ORM queries against BigQuery datasets.

Features

  • Use Django ORM to query BigQuery tables seamlessly
  • Read-only operations support
  • Supports most Django ORM query methods and filters
  • GIS operations support (minimal)
  • Django admin integration

Installation

pip install django-bigquery-connector

Configuration

Add the following to your Django settings:

DATABASES = {
    'default': {
        # Your regular database for models, auth, etc.
        'ENGINE': 'django.db.backends.sqlite3',
        'NAME': BASE_DIR / 'db.sqlite3',
    },
    'bigquery': {
        'ENGINE': 'django_bq',
        'PROJECT': 'your-gcp-project-id',
        'CREDENTIALS': None,  # Uses default credentials, or provide a credentials object
        'LOCATION': 'us-central1',  # Optional: BigQuery location
    }
}

# Optional: Set a default BigQuery dataset for all queries
BIGQUERY_DATASET = 'your_dataset_name'

Authentication

You can provide credentials in three ways:

  1. Set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path of your service account JSON file:

    export GOOGLE_APPLICATION_CREDENTIALS="/path/to/your/service-account-file.json"
    
  2. Pass a credentials object in the settings:

    from google.oauth2 import service_account
    credentials = service_account.Credentials.from_service_account_file(
        '/path/to/your/service-account-file.json',
    )
    
    DATABASES = {
        'bigquery': {
            'ENGINE': 'django_bq',
            'PROJECT': 'your-gcp-project-id',
            'CREDENTIALS': credentials,
        }
    }
    
  3. Use Application Default Credentials (ADC) by setting CREDENTIALS to None.

Usage Examples

Direct SQL Queries

from django.db import connections

# Using the BigQuery connection
with connections['bigquery'].cursor() as cursor:
    cursor.execute("SELECT * FROM `your-project.dataset.table` LIMIT 10")
    results = cursor.fetchall()
    for row in results:
        print(row)

Using Django Models

  1. Define models with BigQuery tables:
from django.db import models

class Customer(models.Model):
    id = models.IntegerField(primary_key=True)
    name = models.CharField(max_length=100)
    email = models.EmailField()
    
    class Meta:
        managed = False  # Important: we don't want Django to create/modify tables
        db_table = 'customers'  # Your BigQuery table name
  1. Query using Django ORM:
# Get all records
customers = Customer.objects.using('bigquery').all()

# Filter records
active_customers = Customer.objects.using('bigquery').filter(
    status='active',
    registration_date__gte='2023-01-01'
)

# Aggregate functions
from django.db.models import Count, Avg
customer_stats = Customer.objects.using('bigquery').values('country').annotate(
    count=Count('id'),
    avg_purchases=Avg('purchase_count')
)

Limitations

  • Read-only operations only (no INSERT, UPDATE, DELETE)
  • Regular expression operations need improvements
  • Some Django ORM features may not be fully supported
  • Complex JOIN operations may not work as expected

Contributing

Contributions are welcome! See CONTRIBUTING.md for guidelines.

License

MIT License - See LICENSE file for details.

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