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How to Deploy FastAPI on Render: Free Tutorial

Added: 2026-08-07

Deep Dive

Basic Python programming and familiarity with the FastAPI framework, including defining routes and running a local development server.

Python FastAPI Tutorial (Part 1): Getting Started - Web App + REST API

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FastAPI uses decorators to define routes, similar to Flask. Create routes using @app.get with the desired path, then define a function that returns data. FastAPI automatically converts dictionaries to JSON. Run the application using 'fastapi dev main.py' for development mode with auto-reload, or 'fastapi run' for production. The development mode automatically restarts the server when code changes are detected, providing immediate feedback. This simple structure allows quick setup of functional web endpoints.

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To run FastAPI, install FastAPI and Uvicorn (ASGI server) using pip. Create a FastAPI application instance using FastAPI(). Use decorators like @app.get() to define routes that respond to HTTP requests. The @app.get() decorator specifies the HTTP method and URL path. Functions decorated with @app.get() are executed when GET requests are made to the specified URL. The return value of these functions becomes the API response. Run the server using uvicorn main:app --reload for development.

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FastAPI Series | Tutorial 01 (Getting Started)

FastAPI Series | Tutorial 01 (Getting Started)

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FastAPI is a modern Python web framework gaining popularity with over 18,000 GitHub stars. It is characterized as fast, robust, lightweight, and simple. Before starting, set up a virtual environment using virtualenv to isolate dependencies. Install FastAPI and Uvicorn (an ASGI server) via pip. Create a FastAPI app instance using 'from fastapi import FastAPI' and 'app = FastAPI()'. Define routes using decorators like 'app.get('/')" with async functions that return dictionaries (automatically converted to JSON). Run the server with 'uvicorn main:app --reload' for auto-reload during development.

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Python FastAPI Tutorial: Build a REST API in 15 Minutes

Python FastAPI Tutorial: Build a REST API in 15 Minutes

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FastAPI is a modern Python web framework for building APIs, offering ease of learning, fast development, and async performance by default. To get started, install FastAPI and Uvicorn via pip, then create a main.py file importing FastAPI and initializing an app instance. Define routes using decorators like @app.get('/') for GET requests and @app.post('/items') for POST requests. Routes map URLs to functions that process requests and return responses. The server runs with 'uvicorn main:app --reload', enabling automatic reloading during development. This foundational setup enables rapid API prototyping with minimal boilerplate code.

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FASTAPI with Python from Scratch | Crash Course | Beginner to Pro 2026

FASTAPI with Python from Scratch | Crash Course | Beginner to Pro 2026

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To install FastAPI, use pip install fastapi. Create a main.py file and import FastAPI, then initialize an app instance. Run the application using uvicorn main:app --reload, which starts the development server on port 8000 by default. The --reload flag enables auto-reloading when code changes. Access the API documentation at http://localhost:8000/docs to interactively test endpoints.

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Deep Dive

Fundamental Git and GitHub workflows, such as staging, committing, and pushing code to a remote repository.

Tutorial Git e Github #01

Tutorial Git e Github #01

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The fundamental Git workflow consists of three main steps: (1) 'git add' - adds files to the staging area, preparing them for commit; (2) 'git commit' - saves the staged changes with a descriptive message; (3) 'git push' - sends the committed changes to the remote repository. The staging area is a temporary holding zone where changes are organized before becoming permanent. Commit messages should be concise and clearly indicate what was changed. Pushing synchronizes your local work with the remote repository, making changes visible to others.

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Using Git & GitHub in VSCode: Stage, Commit, and Push

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This tutorial covers the fundamental Git workflow in Visual Studio Code: initializing a local repository, tracking changes through the Source Control panel, staging specific modifications before committing them with descriptive messages, and pushing updates to a remote GitHub repository. The key concepts include understanding that Git tracks changes locally while GitHub hosts repositories remotely, using the add-commit-push-pull cycle for version control, and leveraging staging to selectively choose which changes to include in each commit.

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How To Stage, Commit, & Push From VS Code To Git & GitHub - Tutorial

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This section teaches the complete workflow for managing code changes. Git continuously monitors your project folder and detects changes when files are created, modified, or deleted. Staging acts as a holding area where you select exactly which changes to include in the next commit. A commit is a permanent snapshot of the project at a specific moment, captured with a descriptive message. The tutorial demonstrates creating a file, writing code, staging changes by clicking the plus icon, committing with a message like 'initial commit - added intro.py', and then publishing to GitHub by clicking 'Publish Branch' and authorizing the connection.

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The core Git workflow consists of three essential steps: staging changes with 'git add' to select which modifications go into the next snapshot, committing staged changes with 'git commit -m "message"' to create a permanent snapshot with descriptive context, and pushing commits to a remote repository with 'git push <remote-name> <branch-name>'. This workflow ensures that every change is intentionally recorded and synchronized across all copies of the repository.

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Demystifying Git for Beginners | Learn Git | Using the Git Bash CLI

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The Git workflow involves three main steps: staging, committing, and pushing. First, use 'git status' to check your repository state. Then stage files using 'git add <filename>' to make them available for the next commit. Commit changes using 'git commit -m <message>' with meaningful messages explaining why changes were made. Finally, push changes to the remote repository using 'git push origin master'. Remote repositories (like those on GitHub) serve as central hubs where team members can access and collaborate on the codebase.

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Deep Dive

An understanding of HTTP request methods (such as GET and POST) and how multipart/form-data works for handling file uploads.

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File uploads in HTTP POST requests require multipart form data encoding, where the browser sends file bytes alongside form fields separated by boundary markers; servers must read the Content-Length header to know how many bytes to read, then parse the body by finding boundary markers (with trailing -- for the last boundary) to separate headers from file content, while carefully avoiding converting file bytes to strings to prevent data corruption.

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1. Веб-разработка. Введение, сетевые протоколы | Технострим

1. Веб-разработка. Введение, сетевые протоколы | Технострим

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Multipart/form-data encoding allows uploading multiple files in a single request. Boundary strings separate different parts, each describing one file with headers and content. This enables photo galleries, document uploads, and complex form submissions.

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Mastering libcurl (2/2) with Daniel Stenberg

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POST data transmission uses CURLOPT_POSTFIELDS (string), CURLOPT_READFUNCTION (streaming), or CURLOPT_MIMEPOST (multipart/form-data). The MIME API creates structured multipart requests with named parts, filenames, and content types. This is essential for file uploads and complex form submissions.

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HTTP протокол на пальцах

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HTTP is a simple text-based protocol for web communication. Requests include method (GET/POST), HTTP version, host header, and path. Responses include status line with version and code, headers, and body. The protocol uses two line breaks (CRLF) to separate headers from body. Telnet can manually test HTTP by connecting to port 80. GET requests include query parameters in the URL path. POST requests include a body with data, requiring Content-Type and Content-Length headers. Content-Type tells the server what format the data is in (application/json, application/x-www-form-urlencoded, multipart/form-data). Content-Length specifies exact bytes to expect. Binary files use specific types like image/png, audio/mp3. File uploads use multipart/form-data with boundary strings. The Content-Type header acts as a contract between client and server.

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When uploading files via HTTP POST, files must be sent as multipart/form-data encoded requests. In Axios, this is achieved by creating a FormData object, appending the file using formData.append('fieldName', file), and sending it in the request body. The Content-Type header must be set to 'multipart/form-data'.

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Deep Dive

Python dependency management, specifically how to generate and use a 'requirements.txt' file for third-party packages.

PIP: criando e usando um arquivo requirements.txt para instalar pacotes.

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This tutorial explains how to manage Python packages using PIP and requirements.txt files. The process involves creating a virtual environment with 'python -m venv', activating it, installing packages with 'pip install package_name', and generating a requirements.txt file using 'pip freeze > requirements.txt' to list all installed packages and their versions. This file can then be shared with others who can recreate the same environment by running 'pip install -r requirements.txt'. The virtual environment folder should be added to .gitignore to prevent it from being committed to version control.

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PIP Freeze- Creating Packages(Requirements.txt) For The Application

PIP Freeze- Creating Packages(Requirements.txt) For The Application

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The pip freeze command generates a requirements.txt file containing all installed Python packages and their versions in the current environment, enabling easy replication of project dependencies across different environments or team members.

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Python Virtual Environments - Full Tutorial for Beginners

Python Virtual Environments - Full Tutorial for Beginners

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Use pip (Python's package installer) to manage packages within virtual environments. Run 'pip list' to view installed packages in the current environment. Installing packages like 'requests' with 'pip install requests' adds them only to the active environment, keeping them isolated from the global Python installation. To share dependencies, generate a requirements.txt file using 'pip freeze > requirements.txt', which captures all installed packages and their versions. To recreate an environment, create a new virtual environment, activate it, then run 'pip install -r requirements.txt' to install all dependencies from the file. This workflow ensures consistent environments across development, testing, and production.

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python pip install requirements txt

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This tutorial explains how to manage Python project dependencies using pip and a requirements.txt file, which is a plain text file listing all project dependencies with optional version numbers; the pip install command reads this file to automatically install all required packages and their dependencies, while pip install --upgrade updates all packages to their latest compatible versions, ensuring reproducibility across different development environments.

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Requirements txt como funciona e por que usar? [Obrigatório]

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A requirements.txt file is a text file that lists all Python libraries and their specific versions used in a project, ensuring all developers working on the project use identical library versions to prevent compatibility issues. To create this file, developers use the 'pip freeze' command in their terminal, which generates a list of all installed libraries with their versions. To install these dependencies on another machine, developers use the 'pip install -r requirements.txt' command, which reads the file and installs all listed libraries with their specified versions. This file is typically included in project repositories like GitHub so that anyone cloning the project can easily set up the same environment.

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API Demo

Project Setup

Deploy Config

Live Test

API Demo

0:00

Playing Section

1
Shows two endpoints: form for display and extract for PDF text extraction.
2
Runs the FastAPI server locally and demonstrates the Swagger UI.

API Demo

Project Setup

Deploy Config

Live Test

API Demo

0:00

Playing Section

1
Shows two endpoints: form for display and extract for PDF text extraction.
2
Runs the FastAPI server locally and demonstrates the Swagger UI.

1.7K views188:10@kumaresankpOriginal Release: 2025-08-24

To deploy a FastAPI application on Render.com for free, you need to create a requirements.txt file listing all dependencies (such as uvicorn, fastapi, and python-multipart), push your project files to a GitHub repository, connect your GitHub account to Render.com, select 'web service' as the project type, configure the start command as 'uvicorn main:app --host 0.0.0.0 --port $PORT', and deploy the project; Render.com will automatically clone the repository, install dependencies, and make your API accessible via a public URL.

[00:00:00]In this video, we're going to see how to deploy a fast AP and render.com. As you can see, I have a fast API project here and we're going to see how to deploy this fast AP project to the render.com.

[00:00:09]First, let me show you the demo for this fast AP project is support. You can see that I have two endpoints. The first one is the form endpoint and second is the extract endpoint. What this extract endpoint will do is it will take a PDF as a input and then it will extract the content and it will just return it. So, let me start this flask API server now.

[00:00:27]So to start the flask API u and the name of the file is main and the app and we're going to start it as reload. So you consider the first API has been started. Let me click on this URL. Consider and the home page it displays hello world and if you go to the do now so let me go to the doc route as you can see it gives us the swagger UI and you consider we have two endpoints the endpoints you are interested is the exact endpoint and in this set point and if you click on try now consider it takes a file as input so let me click on try it out and you consider here we need to select the file the file that I'm going to upload is this PDF file let me show you the PDF now you consider this PDF as a sample content that endpoint will take this PDF as a input and then it will return the contents from this PDF. Basically, it will extract the text from this PDF. So, let me select this PDF now and I'm going to execute now. You consider currently you don't have the content, right? And when I click on execute, it will return us the text from the PDF. You consider it give us the text from the PDF.

[00:01:29]Basically, it will extract all the text present in that PDF. So, this is the project that we're going to deploy to the render.com. Just go to the new tab and type panda.com because this is the website and make sure you log in using your GitHub account or any account. And before we continue here, we need to do one more thing. We need to create a file called the requirements.x file. So inside that file, we will put all our dependencies. So let me create that file now. Requirements.x file. Make sure you type the requirements filling correctly.

[00:01:59]And inside this text file, we have to put all the dependencies that we need.

[00:02:04]The first one is u as usual and pu pdf and fast api and we need the python multipart. So if you are having file upload then you need to put this library python multipart. So these are the four libraries. So and once you have done all of these then what you have to do is you have to upload all of the source file to the github and I have done this. So let me clear the screen and if you go to my browser you consider I have already pushed all my project files to this repository here and consider in this repository I have the requirements.ext file as well as the main.py file as well and consider this the main py file and if you go to my requirements file I have four bonuses here. So let's go to the render.com now. So in the render.com click on dashboard. So if you don't have your account then what you can do is so you can just uh create a new account using your GitHub account. So let me show you how to do that. If you click on let me sign out.

[00:02:59]You consider you have four options.

[00:03:01]GitHub. So make sure you select the GitHub and it will automatically login using your GitHub credentials. Once you have logged in the dashboard and to add a new project just click on add a new and make sure you select the web service because we are interested in the web service right. So select the web service and you consider either you can connect your GitHub account directly to this render here. So you can consider I have connected my GitHub account here or you can use the public repository. So I'm going to choose the public repository now and for the URL let me go to my GitHub and so let's go to the repository now and let me click on code and copy the repository URL and paste the URL here. So and click on connect and it will basically fetch all information from the repository and you can see this is the name. Let me change the name to PDF extract. So this is our project name and if you scroll down you consider it will automatically select the branch. So this is the branch that we have. If you have multiple branch so make sure you select the appropriate branch and leave the root directory as source and make sure you type the requirements.x file filling color three consider inside the requirements.x file we have the dependencies and the start command is very important. So we're going to start using the uon. So uon and here you have to take the file name. So let me go to my github. Now we consider in the github in the main py file I have the app. So main py that is main inside the main I have this app. So inside the main I have the app and so let me type app and you have to provide the for the URL also for equal to I'm going to type 0.0.0 and the port. So you also have to include the port number as well. The port will be automatically selected. So dollar symbol port. So make sure you type this. I will provide the link of this command in the description as well.

[00:04:47]and select the instance type. I'm going to select the free type now. So let me select the free type and you can see that this is the free type and if you have environment variables you can add your environment variables here also.

[00:04:58]And that's it. I think we have configured everything. We can click on deploy now. So deploy web service and you consider the vendor.com will do everything for you. You don't have to do anything. Just relax and you consider it's cloning the repository and it will install all the required dependencies from the requirements while you consider it starts downloading the library for us. Just give you a few minutes. It will take some time. You consider now the libraries has been installed successfully and is uploading the build for us.

[00:05:33]Consider uploading build and the build has been successful and it starts deploying. Just give you a few minutes.

[00:05:38]So once it is deployed the URL that we're going to open up is the URL that you can see at the top. You consider this the URL that I mentioned. So using this URL you can access all your endpoints. So before that let's make sure our deployment is successful and you can see our service is live. You will get a message like this your service is live and available at the primary URL. So either you can click this URL or you can click the URL at the top. So let me go to the top. Now you consider available primary URL and the status is also okay. So let me go up now and click on this URL and you can see that our homepage is successfully displayed. Hello world. So let me go to the docs now. So let's go to the docs now.

[00:06:27]And you can see that we got this swagger UI as well and we also got the URL as well. So this is our URL. So let's say so let me try this sack endpoint and I'm going to upload a PDF now. So let me upload this PDF and click on execute and you can see it successfully the content from the PDF. Now we have successfully deploy the fast API project on our render.com. You can also test this out locally as well. So what you can do is so let me remove this. So this is our endpoint and what you can do is let me copy this endpoint and if you go to the SR manually consider the method not phone because you have to use the post request. This only accept the post request but since the browser will automatically send the get request to try this out programmatically consider have this code here and you have to paste the URL here the URL is so let's go to the render.com one more time and to copy the URL consider this the URL and paste the URL here this is our URL and in the next line what I have done is I have open a PDF file consider I have opened this PF file and I have passed this PDF file to the URL that we have here consider this method only as the post request and I have sent the post request to the URL along with the files.

[00:07:42]So let's try to run this now. And one more thing is that we have copy and paste the URL here. The endpoint that we going to use is the SAR endpoint and let's save this and let's try to run this now and press enter and you can see that we got the contents from the PDF. So yeah, this is how you deploy a fast API project and render.com for free. You don't have to pay anything. We are deploying this project for free.

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