FastAPI Latest Version, Python Requirements & Setup (2026 Guide)

Looking for the FastAPI latest version? Here is the current FastAPI release, supported Python versions, and the recommended installation command.

What is the latest FastAPI version in 2026?

The latest FastAPI version at the time of this update is 0.136.1. If you are checking compatibility, debugging a dependency issue, or creating a new project, always confirm the current release before pinning packages in production.

FastAPI latest version vs stable version vs PyPI version

For most developers, “latest FastAPI version” means the newest release listed on PyPI. “Stable version” usually means the release your team has tested with your Python runtime, Pydantic models, Starlette dependency, deployment setup, and application code.

For local experiments, using the latest version is usually fine. For production, pin the version you have tested instead of installing an unpinned latest release every time your app is deployed.

How to check your installed FastAPI version

If FastAPI is already installed in your project, check the installed version from the same virtual environment where your app runs.

Check with pip

pip show fastapi

Check from Python

python -c "import fastapi; print(fastapi.__version__)"

Check available package versions

pip index versions fastapi

If your terminal shows a different version than expected, confirm that the correct virtual environment is active before reinstalling packages.

What Python version does FastAPI require?

The current FastAPI release requires Python 3.10 or higher. If you are using an older runtime such as Python 3.8 or Python 3.9, you should not expect the latest FastAPI package to install cleanly.

If you are starting fresh, keep your Python version modern and your dependency file explicit. That reduces version mismatch issues in local development, CI pipelines, and production deployments. For teams planning a larger backend, Python web development decisions should include runtime versioning, dependency management, and deployment readiness from the beginning.

What Python version is recommended for FastAPI?

For most new FastAPI projects in 2026, Python 3.12 or 3.13 is the safest practical choice. It gives you a modern runtime, strong package support, and avoids the confusion that often appears in older Python environments.

If you are migrating an older codebase, validate your Pydantic, Starlette, database drivers, async libraries, and deployment stack before changing Python versions. That step is especially important if your project still carries older dependencies or compatibility shortcuts.

What should a basic FastAPI requirements.txt include?

A simple FastAPI project does not need a huge dependency file. For most setups, you only need FastAPI itself and the standard runtime extras needed for local development and serving the app.

Minimal requirements.txt for a new FastAPI project

# requirements.txt
fastapi[standard]==0.136.1

If you prefer installing from the command line, use:

pip install "fastapi[standard]"

This is the better default for most developers because it includes the recommended standard extras and the server tooling needed to run a FastAPI app without manually piecing things together.

Example requirements.txt for common FastAPI projects

The right requirements.txt file depends on what your API actually does. Start small, then add dependencies only when your project needs them.

Example: FastAPI with Uvicorn and environment variables

# requirements.txt
fastapi[standard]==0.136.1
python-dotenv

Example: FastAPI with external API calls

# requirements.txt
fastapi[standard]==0.136.1
httpx
python-dotenv

Example: FastAPI with database support

# requirements.txt
fastapi[standard]==0.136.1
sqlalchemy
asyncpg
python-dotenv

FastAPI Dependency Compatibility 2026

FastAPI relies on several core dependencies behind the scenes, most importantly Pydantic for data validation and Starlette for the ASGI web framework layer. If these packages use incompatible versions, developers may encounter installation errors, runtime exceptions, or dependency conflicts when installing packages.

The table below gives a practical compatibility reference for modern FastAPI setups. Before upgrading a production application, always check your installed package metadata, lock file, and test environment.

Common FastAPI dependency roles

Example requirements.txt with compatible versions

# Example FastAPI dependency setup
fastapi[standard]==0.136.1
python-dotenv
httpx

For most projects, the simplest and safest approach is installing the recommended bundle:

pip install "fastapi[standard]"

This installs FastAPI along with commonly used standard runtime dependencies. If your team needs tighter dependency control, pin exact tested versions before moving to production.

FastAPI installation and setup

The fastest clean setup is to create a virtual environment, activate it, install FastAPI, and start a local development server.

Copy-paste setup

python -m venv .venv
source .venv/bin/activate   # macOS / Linux
.venv\Scripts\activate      # Windows

pip install "fastapi[standard]"

Minimal FastAPI app

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def home():
    return {"message": "FastAPI is running"}

Run locally

uvicorn main:app --reload

Important: use --reload only for local development. It is helpful while coding, but it is not meant for production use.

FastAPI project structure

A clean project structure makes FastAPI easier to scale, test, and maintain. Even if your first endpoint is tiny, it is better to start with a structure that will still make sense after 20 or 50 routes.

fastapi_app/
├── app/
│   ├── main.py
│   ├── routers/
│   ├── schemas/
│   ├── services/
│   └── core/
├── tests/
├── requirements.txt
└── .env

This structure keeps route handling, validation, business logic, and shared configuration separate. It also makes the project easier to understand when more developers start contributing.

For production APIs or SaaS backends, FastAPI development services usually need to cover clean architecture, maintainable modules, and deployment-ready backend systems, not just the first endpoint.

Example router setup

from fastapi import APIRouter

router = APIRouter(prefix="/users", tags=["Users"])

@router.get("/")
async def get_users():
    return [{"name": "John"}, {"name": "Sara"}]

Example main.py

from fastapi import FastAPI
from app.routers import users

app = FastAPI(title="FastAPI Example")
app.include_router(users.router)

FastAPI Version History & Latest Release

FastAPI releases frequent updates that improve Python compatibility, dependency stability, developer experience, and framework behavior. If you are upgrading an older project, checking the release line before pinning dependencies can save a lot of debugging time.

Common version and dependency issues

Many FastAPI setup problems are not really FastAPI problems. They are usually environment or dependency mismatches.

1. FastAPI does not install on an older Python version

If your runtime is below the currently supported Python version, the latest FastAPI package may not install. Check your Python version first before debugging anything else.

python --version

2. ModuleNotFoundError: No module named 'fastapi'

This usually means FastAPI was installed in a different environment than the one running your app. Activate your virtual environment and check the installed package again.

pip show fastapi

3. No matching distribution found for fastapi

This can happen when your Python version is too old, pip is outdated, or your environment is resolving packages from the wrong index. Start by checking Python and pip versions.

python --version
pip --version

4. Dependency conflicts after upgrading

When projects evolve over time, dependency mismatches can appear between FastAPI and the rest of the stack. The safest fix is usually to verify Python version, clean the environment, and reinstall from a controlled dependency file.

5. Reload mode used in production

--reload is useful in development, but it increases resource usage and is not appropriate for production deployments.

FastAPI Best Practices for Production 2026

Once a FastAPI project moves beyond local development, a few production basics make a major difference in stability, maintainability, and deployment safety.

• Use a modern Python runtime such as Python 3.12 or 3.13.
• Pin dependency versions in requirements.txt for shared development and production.
• Avoid using --reload outside local development.
• Keep routing, schemas, and business logic separated as the codebase grows.
• Validate dependency compatibility before upgrading FastAPI, Pydantic, or Starlette.
• Keep environment variables out of application code.
• Add health checks, structured logging, and staging validation before production release.

If your API is already live or expected to handle real traffic, also review common FastAPI production issues under load.

FastAPI deployment basics

Once your app works locally, deployment is straightforward. The goal is to keep the runtime predictable, avoid local-only assumptions, and run FastAPI behind a production-ready process.

Simple Docker example

FROM python:3.12
WORKDIR /app

COPY requirements.txt .
RUN pip install -r requirements.txt

COPY . .
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

That is enough to containerize a basic FastAPI application. As the project grows, you can add environment management, health checks, structured logging, and deployment automation.

For a deeper production setup, read our FastAPI deployment guide.

FastAPI Quick Checklist

• Check the latest FastAPI version before starting a new project
• Keep Python current and consistent across environments
• Use virtual environments for every project
• Use fastapi[standard] for most new setups
• Pin dependencies for shared development and production
• Keep routing, schemas, and business logic separated
• Use development reload only locally
• Verify version compatibility before upgrading packages
• Test upgrades in staging before production

When a basic FastAPI setup becomes a production architecture decision

A small FastAPI project can start with a few files and a simple requirements.txt. That is fine. But once the API supports a SaaS product, internal platform, AI workflow, customer-facing dashboard, or multi-service backend, setup decisions become architecture decisions.

At that point, teams usually need to think beyond the first install command. Runtime versioning, dependency pinning, background jobs, auth, database migrations, observability, deployment automation, and scaling strategy all start to matter.

If your team is using FastAPI for AI-backed APIs, this guide on building AI workflows with FastAPI and LangGraph may be a useful next step.

For larger backend builds, you can also review our backend and SaaS case studies to see how production software decisions connect with real delivery outcomes.

Conclusion

If you came here to answer one practical question, here is the short version: the latest FastAPI release is 0.136.1, the current release line requires Python 3.10+, and the cleanest setup for new work is to use a virtual environment and install with pip install "fastapi[standard]".

That gives you a solid foundation for local development, cleaner dependency handling, and a more predictable deployment path later.

Quick Recap

• Latest FastAPI version: 0.136.1
• Current minimum Python version: 3.10+
• Recommended Python version for most new production projects: 3.12 or 3.13
• Recommended install command: pip install "fastapi[standard]"
• Use --reload for local development only
• Pin tested dependency versions before production deployment

Related FastAPI Guides:

• FastAPI guide
• FastAPI deployment guide
• FastAPI production issues under load