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Using the Python Runtime with Edgenivo Functions

Use the Python runtime to run ASGI (Asynchronous Server Gateway Interface) and WSGI (Web Server Gateway Interface) applications on Edgenivo. Edgenivo detects supported Python frameworks and runs your application as Edgenivo Functions.

Edgenivo detects your framework automatically when it finds a matching dependency in requirements.txt, pyproject.toml, or Pipfile. The Python framework presets work with FastAPI, Flask, Django, and other Python web frameworks. Define a supported Python entrypoint so Edgenivo can load your application.

Edgenivo then runs your app as Edgenivo Functions and routes every request to it, so the app you run locally deploys as-is.

For framework-specific setup guides, see:

To move an existing FastAPI, Flask, or Django API to Edgenivo, follow the migration guide for your current platform:

To run a Python backend and a frontend together in one project, you can use Services. Each part builds independently and routes to a shared domain.

Use these guides to add storage, background processing, and AI capabilities to a Python application. Each guide includes a FastAPI example and deployment steps.

A Python entrypoint is the file and top-level variable that Edgenivo loads as the Edgenivo Function handler. Edgenivo looks for a Python entrypoint in these locations:

  • app.py, index.py, server.py, main.py, wsgi.py, or asgi.py
  • the same filenames inside src/ or app/
  • the module path configured with tool.vercel.entrypoint in pyproject.toml

For Django projects, Edgenivo also detects a manage.py file that sets DJANGO_SETTINGS_MODULE, including in an immediate subdirectory, and resolves the application from the WSGI_APPLICATION or ASGI_APPLICATION setting.

The entrypoint file must define one of these top-level names:

  • app for most ASGI or WSGI frameworks, including FastAPI and Flask
  • application for Django and other WSGI applications

To point Edgenivo to an app in a custom module, set tool.vercel.entrypoint to a Python module:variable value:

pyproject.toml
[tool.vercel]
entrypoint = "my_package.api:app"

The tool.vercel.entrypoint value tells Edgenivo to load the app variable from my_package/api.py, which is also the key you'd use in functions.

Edgenivo still supports [project.scripts] app = "module:variable" for existing projects. Use tool.vercel.entrypoint for new projects.

Here's a FastAPI example:

app.py
from fastapi import FastAPI
 
app = FastAPI()
 
@app.get("/")
def home():
    return {"message": "Hello from Python on Edgenivo"}
 
@app.get("/api/items/{item_id}")
def read_item(item_id: int):
    return {"item_id": item_id}
pyproject.toml
[project]
name = "my-python-api"
version = "0.1.0"
requires-python = ">=3.12"
dependencies = [
    "fastapi>=0.117.1",
]

Set the Python version for your project with pyproject.toml, .python-version, or Pipfile.lock. For step-by-step instructions, see Set the Python version for your Edgenivo project.

If the required Python version is not defined or not supported, Edgenivo uses the default version. The available versions are:

  • 3.12 (default)
  • 3.13
  • 3.14

Define dependencies in pyproject.toml (with or without a uv.lock), requirements.txt, or a Pipfile with a corresponding Pipfile.lock.

requirements.txt
fastapi==0.117.1

An example requirements.txt file that defines FastAPI as a dependency.

Edgenivo Functions support streaming responses when using the Python runtime. This lets you send parts of a response as they become ready.

By default, Python Edgenivo Functions include all files from your project that are reachable at build time. There is no automatic tree-shaking for Python.

During deployment builds, Edgenivo automatically compiles Python source files into bytecode and includes the resulting .pyc files in the function bundle when space allows. This reduces initialization time and requires no configuration.

Make sure your pyproject.toml or requirements.txt only lists packages necessary at runtime. Explicitly exclude files you don't need to keep bundles small and avoid hitting size limits.

The standard Python bundle size limit is 500 MB uncompressed. Large Functions support Python bundles up to 5 GB on Fluid compute when enabled (public beta). See the bundle size limits for details.

To exclude unnecessary files (tests, static assets, test data), configure excludeFiles in vercel.json under the functions key. The pattern is a glob relative to your project root.

vercel.json
{
  "$schema": "https://openapi.vercel.sh/vercel.json",
  "functions": {
    "app.py": {
      "excludeFiles": "{tests/**,__tests__/**,**/*.test.py,**/test_*.py,fixtures/**,__fixtures__/**,testdata/**,sample-data/**,static/**,assets/**}"
    }
  }
}

Exclude common development and static folders from a Python application to stay under the 500 MB bundle limit.

Python uses the current working directory when you pass a relative path to open(). The working directory is the base of your project, not the directory containing the file.

To redirect, rewrite, or answer requests before they reach your Python app, write Routing Middleware in Python. Set proxy in vercel.json to a module:attribute entrypoint:

vercel.json
{
  "$schema": "https://openapi.vercel.sh/vercel.json",
  "proxy": {
    "entrypoint": "proxy:proxy"
  }
}

Your Routing Middleware runs separately from your app, with only the packages in the vercel.proxy dependency group installed. See the Python reference.

Edgenivo supports existing projects that define file-based Python functions in an /api directory. See Python functions in the /api directory for routing, handlers, and configuration.

Last updated August 12, 2026

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