Skip to main content

Lightweight query access-pattern declaration for ORMs

Project description

query-patterns

Declare query-access patterns in code and verify matching DB indexes. Supports SQLAlchemy and Django, both schema-based and database introspection modes.

Motivation

As projects grow, the number and variety of database queries increase. Over time, it becomes difficult to maintain a consistent set of query-access patterns across the codebase, and even harder to verify whether each pattern is backed by an appropriate database index. Relying on manual checks or memory often leads to:

  • Missing or outdated indexes that cause silent performance regressions
  • Inconsistent query patterns across teams or modules
  • Schema changes that unintentionally break previously optimized queries
  • Performance issues that surface only in production traffic

query-patterns addresses these problems by allowing you to declare expected query patterns in code and validate them against either your ORM schema or a running database instance — all via a simple CLI command.

What it does

  • Collects all @query_pattern declarations from your Python modules
  • Extracts index definitions from:
    • SQLAlchemy
      • ORM schema (MetaData)
      • Actual DB (Inspector)
    • Django
      • ORM schema (Model._meta.indexes)
      • Actual DB (connection.introspection)
  • Compares (table, columns) tuples
  • Can be integrated into CI to enforce index coverage

Install

pip install query-patterns

Declare a pattern

from query_patterns import query_pattern


# Declare query pattern using table/column names
class RepoA:
    @query_pattern(table="users", columns=["email"])
    def find(self, email): ...


# Declare query pattern using ORM models(works with both SQLAlchemy and Django models)
from models import User

class RepoB:
    @query_pattern(table=User, columns=[User.email])
    def find(self, email): ...

a. SQLAlchemy Command

# Reads indexes from MetaData
query-patterns sqlalchemy \
  --metadata myapp.db.metadata \
  --module myapp.repo
  
# Auto-discover modules
query-patterns sqlalchemy \
  --metadata myapp.db.metadata
  
# Reads actual indexes from the database
query-patterns sqlalchemy \
  --source db \
  --engine-url postgresql://user:pass@localhost/mydb \
  --module myapp.repo

b. Django Command

# Reads Model._meta.indexes from installed apps
query-patterns django \
  --settings config.settings \
  --module myapp.repo
  
# Auto-discover modules 
query-patterns django \
  --settings config.settings
  
# Reads actual DB indexes using Django introspection
query-patterns django \
  --source db \
  --settings config.settings \
  --module myapp.repo

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

query_patterns-0.1.7.tar.gz (10.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

query_patterns-0.1.7-py3-none-any.whl (11.4 kB view details)

Uploaded Python 3

File details

Details for the file query_patterns-0.1.7.tar.gz.

File metadata

  • Download URL: query_patterns-0.1.7.tar.gz
  • Upload date:
  • Size: 10.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.14

File hashes

Hashes for query_patterns-0.1.7.tar.gz
Algorithm Hash digest
SHA256 9037cf6bcaaddf6ee7ef69eefa64800a0fe3a03d66da79715c5048547fcb6905
MD5 beb612edf403eb59be8e019374872e03
BLAKE2b-256 59e04aa3505046ec45969de85aea1578573d0ae8d783147c9ab5cb6e47053e6f

See more details on using hashes here.

File details

Details for the file query_patterns-0.1.7-py3-none-any.whl.

File metadata

  • Download URL: query_patterns-0.1.7-py3-none-any.whl
  • Upload date:
  • Size: 11.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.14

File hashes

Hashes for query_patterns-0.1.7-py3-none-any.whl
Algorithm Hash digest
SHA256 009792c8258f5c9965b69c316e6b304f7945896fe76d6704827b91f8ea69e446
MD5 fa18356fce4e8cb8c7dcf2871a31b025
BLAKE2b-256 6952304e2b4f72b5b6f885bdbef24583c5a89336617df9c52b3282c4d8bec9ee

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page