Python Tutorial
Django PostgreSQL
SQLite is fine for learning. PostgreSQL is the usual production database. Install the adapter and change DATABASES.
Install and Settings
Use psycopg (v3) or psycopg2.
pip install psycopg[binary]
# settings.py
DATABASES = {
"default": {
"ENGINE": "django.db.backends.postgresql",
"NAME": "mysitedb",
"USER": "myuser",
"PASSWORD": "secret",
"HOST": "localhost",
"PORT": "5432",
}
}Migrate
Create the database in PostgreSQL first, then run migrations.
python manage.py migrate📘 Real-World Deep Dive
Knowing <strong>Django Postgresql (Django)</strong> well is what turns Django from a curiosity into a daily tool — you'll reach for it in nearly every real project.
Real-Life Scenario
An end-to-end usage of Django Postgresql that you'd actually see in a data pipeline or analytics notebook.
Real-Life Example
# settings.py
DATABASES = {
"default": {
"ENGINE": "django.db.backends.postgresql",
"NAME": os.environ["PGDATABASE"],
"USER": os.environ["PGUSER"],
"PASSWORD": os.environ["PGPASSWORD"],
"HOST": os.environ.get("PGHOST", "localhost"),
"PORT": os.environ.get("PGPORT", "5432"),
}
}Expected Output
(no output)Common mistakes
- Forgetting to call
.save()on a model instance after mutation silently persists nothing. - Reading every row with
Model.objects.all()on a 1 M-row table OOMs the worker — use.iterator()for streaming. - Queries inside loops produce N+1 problems — pull related rows with
select_related/prefetch_related. - Treating Django Postgresql as a black box without reading the docs — the API has subtle defaults that bite when you scale.
🚀 Performance & Best Practices
- Add database indexes (
db_index=TrueorMeta.indexes) on columns used infilter. - Use
cache_pageon read-heavy views and setCONN_MAX_AGEto keep DB connections warm. - Generate migrations with
python manage.py makemigrations --dry-run --verbosity 3and review before committing. - When working with Django, prefer vectorised / batched operations over Python loops.
🧪 Try It Yourself
- Reproduce the snippet on a representative slice of your own data.
- Profile the snippet with
cProfileortimeitand find the single biggest improvement. - Generalise the snippet into a small, reusable function you can drop into future projects.