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How To Write A Python Web Api With Flask

You should see JSON output for the three entries in our test catalog. Flask provides us with a jsonify function that allows us to convert lists and dictionaries to JSON format. In the route we created, our book entries are converted from a list of Python build simple restful api with python and flask part 1 dictionaries to JSON before being returned to a user. First, create a new folder on your computer that will serve as a project folder. This can be in your Desktop folder, but I recommend creating a dedicated projects folder for this and similar projects.

build simple restful api with python and flask part 1

In this post, I want to show you what I find to be helpful patterns for the development of RESTful Flask applications. Also, the client may make an OPTIONS HTTP request to the server to see if it may really make requests with other methods.

The server will add this information to the Database and then forget the action. That is next time I use a GET request to retrieve the Book; the server will not have any memory of the previous POST method action. If you’re looking to build a web app or API, Flask is a good option to consider. It’s powerful and robust, and the project documentation makes it easy to get started. Try it out, evaluate it, and see if it’s right for your project. Python is a high-level, object-oriented programming language known for its simple syntax. It is consistently among the top-rated programming languages for building RESTful APIs.


By the end of this tutorial, you will be able to build a REST API that can manage blog posts data with create, read, update, and delete functionality. When I started writing this post, I though it would end up being relatively straightforward.

Start the server, send a request to /posts endpoint, and you will get an empty array. Finally, we register our resource by using api.add_resource method and define the rouute endpoint.

How A Rest Api Is Created And Tested

Once you’ve picked a data format, the next step is to decide how you’ll respond to HTTP requests. All responses from your REST API should have a similar format and include the proper HTTP status code. Any data sent with a PUT request will completely replace the existing values of the todo. Once the API responds, you call response.json() to view the JSON. The 201 status code tells you that a new resource was created. This code calls requests.get() to send a GET request to /todos/1, which responds with the todo item with the ID 1.

build simple restful api with python and flask part 1

To install them, please refer to the virtualenv and pip documentation, though you probably have them on your system already. REST APIs have become a common way to establish an interface between web back-ends and front-ends, and between different web services.

Connecting Our Api To A Database

A bare-bones comparison made by Andriy Kornatskyy put it among the top three frameworks in terms of response time and throughput . At this point, our project does not have any real source code. A python package is a directory with a __init__.py file.

  • This route handles POST requests to /countries in Flask 1.
  • Any fixture defined in a conftest.py file can be used by all tests in the same directory or sub-directoy the conftest.py lives in.
  • For an extensively documented API, see the MediaWiki Action API, which provides documentation to users who pass partial queries to the API.
  • In this article, I’ll provide a walkthrough of how to build a RESTful API service using Bottle.
  • A PUT request would update the user information, maybe updating an email address.

Each entry in the array has the fields that we defined above for our tasks. Finally, let us also try the delete method to remove users from the file. Now, the server is not only limited to a database but can also be another machine that reads and writes data from a flat file or any other data store.

Coding The Flask Application

You can also view the response’s HTTP headers with response.headers. This dictionary contains metadata about the response, such as the Content-Type of the response. GET is one of the most common HTTP methods you’ll use when working with REST APIs. This method allows you to retrieve resources from a given API. GET is a read-only operation, so you shouldn’t use it to modify an existing resource. Now that you’ve got requests installed, you can start sending HTTP requests. To write code that interacts with REST APIs, most Python developers turn to requests to send HTTP requests.

  • This helper function uses a generator expression to select all the country IDs and then calls max() on them to get the largest value.
  • Besides uwsgi, one might want to set up a reverse proxy.
  • These indicate to the requester that we will serve the indicated requests.

That will print out possible Python errors on the web page helping us trace the errors. This line ask the application to import Flask module from flask package. Now, let’s add the remaining CRUD operations, update and delete. Here, we also have accept a GET request, but instead of querying all posts, we just fetch a single post with the given id.

I strongly prefer pytest for all my Python testing needs. Pytest leads to short, easy-to-read tests, and often lend themselves better to both reusability and extensibility. Before we dig into our API implementation we will implement our Marshmallow schemas. Marshmallow is an ORM/ODM/framework-agnostic library for https://remotemode.net/ converting complex datatypes, such as objects, to and from native Python datatypes. We will be using Marshmallow for the marshalling and unmarshalling of our data, as well as some very basic data validation. This file is our SQLite database containing a small amount of football stats data to test our API with.

Complete Guide On Rest Api With Python And Flask

We can start our project by initializing a new virtual environment with Python venv module. Then, create a new Python virtual environment and install the dependencies with Pip. Nothing irritates me more than using a JSON API which returns HTML when an error occurs, so I was keen to put in some reasonable error handling to avoid this happening. After validating the data, to_bson() is called on the Cocktail to convert it to a BSON-compatible dict, and this is directly passed to PyMongo’s insert_one method. There’s no way to get PyMongo to return the document that was just inserted in a single operation . In this API, that cocktail could be accessed by sending a GET request to the /cocktails/rye-whiskey-old-fashioned endpoint.

Second, install our we can install our dependencies via Pip by running this command. In the Rust version of this code, I was nudged to use a different approach.

  • We’ll discuss these elements in greater depth later in this tutorial.
  • After deleting the resource, the API sends back an empty JSON object indicating that the resource has been deleted.
  • We will use the latter to deserialize and serialize instances of Transaction from and to JSON objects.
  • We will soon create classes to represent incomes and expenses.
  • Ensure you have at least Python 3.9 installed before proceeding.
  • Simply put, REST is an architectural structure that uses HTTP methods to POST and GET data.

This tutorial will assume that the files related to this lesson will be stored in a folder called api inside a folder named projects in your home directory. Python has a number of web frameworks that can be used to create web apps and APIs.

In our restaurant example, the GET method is illustrated by asking the waiter for the menu, who will then provide it in response. Using your new Python REST API skills, you’ll be able to not only interact with web services but also build REST APIs for your applications. These tools open the door to a wide range of interesting, data-driven applications and services. The JSON in this request was missing a value for area, so FastAPI returned a response with the status code 422 Unprocessable Entity as well as details about the error.

build simple restful api with python and flask part 1

Models define how records can be manipulated or retrieved in the database. Now, let’s set up the configurations that would be required by our application. In this series, I’m going to take you through a very easy to learn path in creating RESTFUL API using Python and Flask micro-framework. This line define function that will be executed if we access route. After that you could set your project location and interpreter.

As always, Let’s take books as an example of the data in this tutorial. Of course if we do this we will need the client application to look for 403 errors as well. If we find the task then we just package it as JSON with jsonify and send it as a response, just like we did before for the entire collection. The response of this function is not text, we are now replying with JSON data, which Flask’s jsonify function generates for us from our data structure. There are a couple of Flask extensions that help with building RESTful services with Flask, but the task is so simple that in my opinion there is no need to use an extension. In this article I’m going to show you how easy it is to create a RESTful web service using Python and the Flask microframework. As you can see in this snippet, there are three methods to fetch, write and delete records from the CSV file.

Running the app in debug mode is a huge deal during development because this ensures that the app will be reloaded every time a change is made to the source code. Moreover, error reports are directly outputted to the console. This is syntactic sugar that let’s you start the app by running this script. For example, if this file is named main.py, you can simply run python main.py to start the app. Bottle carries quite an extensive list of server adapters that can be used this way.

Building Your Rest Api

If you’d like to use a database in your app, the Python Package Index has several interesting options, like SQLAlchemy, PyMongo, MongoEngine, CouchDB and Boto for DynamoDB. You only need the appropriate adapter to get it working with the database of your choice. Install on your system using the Python Package Index with pip install bottle. Install on your system using the system’s package manager. Debian Jessie packages the version 0.12 as python-bottle. The Bottle framework achieves its impressive performance in part thanks to its light weight. In fact the entire library is distributed as a one-file module.

Lastly, Flask also has extensive documentation that address everything that developers need to start. Our models class will inherit Model object from flask-sqlalchemy, Flask Sqlalchemy is a flask wrapper for Sqlalchemy. An ORM is a database sql abstraction that makes it easy to carry out sql operations on relational database. With ORM, instead of writing raw sql queries(e.g to retrieve all rows from our User’s table) we could do something like – model.query.all(). Here, we accept a GET request and make query to fetch all posts with Post model. Then, we take advantage of posts_schema to serialize the data from database and return it as a response to the client.

This means that it does not hold your hand as much as other frameworks, but it is also more flexible and can be adapted to fit into many different tech stacks. Finally, we are at the end of part 1 of this tutorial series. Now we are ready to explore the final segments of part 1, distributing and running the application. Let’s first create an instance directory at the root of our project. This directory will contain the actual configuration values for different environments. Note that, we should keep this directory out of git so that sensitive information don’t get exposed. Note that, this will also add flask-tutorial in requirements.txt file.

Static Files

I know from experience that APIs can develop in a sometimes random manner over time, making finding the code that supports the endpoints, and coordinating them, difficult at best. This displays the structure of the expected response, the content-type of that response, and the description text you entered about the endpoint in the swagger.yml file. This tells the app instance to read the file swagger.yml from the specification directory and configure the system to provide the Connexion functionality. All of this can happen when you create a configuration file your application can access. The Swagger site even provides an online configuration editor tool to help create and/or syntax check the configuration file you will create. This data could be represented in a database, saved in a file, or be accessible through some network protocol, but for us an in-memory data structure works fine. One of the purposes of an API is to decouple the data from the application that uses it, hiding the data implementation details.

These responses should include a description of what error occurred along with the appropriate status code. This response only includes the status code 204 No Content. This status code tells a user that the operation was successful, but no content was returned in the response. There’s no reason to send a copy of it back in the response. This POST request includes JSON for the new car in the request. It sets the Content-Type header to application/json so the API knows the content type of the request. This response contains a single JSON object with the car’s data.

Similar to Java packages and C# namespaces, modules in Python are files organized in directories that can be imported by other Python scripts. To create a module on a Python application, we just need to create a folder and add an empty file called __init__. We use UserModel.get_user_by_email(data.get(‘email’)) to filter the user’s table using the user email address and return an error message if the user does not exist. If the password matches, then we generate and return a token to the user. Now that we have our application ready, it’s time to add our tests. Let’s start by creating a tests/conftest.py file which will hold our shared pytest fixtures.