Python
40 items tagged with "python"
Standards2
Python 3.12 (PEP 693)
Understanding and adhering to Python standards during software migrations is crucial for ensuring code clarity, compatibility, and maintainability. By following key guidelines such as PEP 8 compliance, implementing comprehensive testing, and utilizing effective tools, teams can mitigate risks and foster collaboration, ultimately ensuring a successful migration process.
Python PEP 8 (Style Guide)
Understanding migration standards in Python is crucial for ensuring seamless transitions from legacy systems. By adhering to these standards, teams can mitigate risks, maintain security, and enhance performance during migrations. Practical steps and tools can further support compliance, leading to successful project outcomes.
Tutorials7
How to deploy a Python function on Google Cloud Functions
Write and deploy an HTTP-triggered Python function on Google Cloud Functions (2nd gen) with the gcloud CLI.
How to run SQLAlchemy database migrations with Alembic
Generate, edit, and apply Alembic migrations for a Python SQLAlchemy project, including autogeneration and safe downgrades.
How to author a data pipeline DAG in Apache Airflow
Write an Airflow DAG with scheduled tasks and dependencies, run it locally, and monitor execution in the UI.
How to set up a Python project with Poetry and pytest
Create a reproducible Python project using Poetry for dependency management and pytest for testing.
How to write concurrent Python with asyncio
Use Python's asyncio to run I/O-bound work concurrently with coroutines, tasks, and gather, and know when to use threads instead.
How to test a FastAPI application with pytest and TestClient
Test a FastAPI app's endpoints using pytest and the built-in TestClient, with fixtures and dependency overrides.
Scan a Python Project for Upgrade Drift
Use Vibgrate CLI to scan a Python project for upgrade drift, read the DriftScore, and export JSON for further processing.
Blueprints2
Python 2 to Python 3 Modernization Blueprint
Migrate end-of-life Python 2 codebases to Python 3 with automated 2to3 fixes, string/bytes correctness, and dependency upgrades.
Django Monolith to Services Blueprint
Extract bounded capabilities from a large Django monolith into separate services with their own datastores and async messaging.
Migrations4
Django REST Framework to FastAPI Migration
Migrate DRF APIs to FastAPI with explicit schemas and new auth/middleware patterns
Flask to FastAPI Migration
Migrate Python APIs from Flask to FastAPI with async support and OpenAPI-first contracts
Python 2 to Python 3 Migration
Migrate Python 2 codebase to Python 3 with modern syntax
Python 3.8 to Python 3.12 Migration
Upgrade Python runtime and dependencies from 3.8 to 3.12 with test-driven validation
Products4
Stacks6
Django HTMX Stack
Django, HTMX, Alpine.js - Modern Python web stack
FastAPI + SQLAlchemy Stack
Async Python backend stack using FastAPI, SQLAlchemy, and PostgreSQL for high-performance, type-hinted REST and ML-serving APIs.
React + Django REST Framework
A React frontend consuming a Django REST Framework API, a productive Python full-stack for data-rich and ML-adjacent web applications.
FastAPI + HTMX
A modern Python stack pairing the async FastAPI framework with HTMX to build dynamic, server-rendered web apps with little custom JavaScript.
Prefect + Spark
A Python-native orchestration stack where Prefect schedules and monitors large-scale data processing jobs running on Apache Spark.
Ray Distributed ML
A unified compute stack using Ray to scale Python machine learning workloads from data processing through training to serving.
Comparisons10
Python vs JavaScript
Comparison of Python and JavaScript for backend and full-stack development
Python vs Go
Python prioritizes expressiveness and a vast data/AI ecosystem, while Go prioritizes raw performance, concurrency, and lean deployment for services.
Node.js vs Python
Two leading backend runtimes: Node.js offers event-driven, non-blocking I/O with JavaScript everywhere, while Python brings readability and a vast data ecosystem.
Python vs R
Two leading languages for data work: Python is a general-purpose language strong across the data and ML pipeline, while R is purpose-built for statistics and visualization.
Ruby vs Python
Two expressive, dynamic languages: Ruby is beloved for web development with Rails, while Python dominates data, ML, and general-purpose scripting.
CPython vs PyPy
Two Python implementations: CPython is the reference interpreter with full compatibility, while PyPy uses a JIT compiler for major speedups on long-running code.
Django vs FastAPI
Django is a batteries-included framework for full web apps; FastAPI is a modern, async, type-driven framework focused on high-performance APIs.
Django vs Flask
Django is a full-featured framework with conventions baked in; Flask is a minimal microframework you extend as needed.
FastAPI vs Flask
FastAPI is async-first with type-driven validation and auto docs; Flask is a mature, synchronous microframework with a vast extension ecosystem.
Rails vs Django
Rails and Django are both mature, batteries-included MVC frameworks; Rails uses Ruby and convention over configuration, Django uses Python.
FAQs2
What languages and ecosystems does Vibgrate support?
Vibgrate supports Node.js/TypeScript (package.json, npm/pnpm/yarn/bun lockfiles), .NET (*.csproj, *.sln, NuGet), Python (requirements.txt, pyproject.t...
How do I scan a Python project?
Run vg scan /path/to/python-project. Vibgrate detects requirements.txt, pyproject.toml, setup.py, and Pipfile. It analyzes Python version from .python...