Brooke  Giles

Brooke Giles

1585830840

How to Create an REST API with Rust and PostgreSQL

There are quite a few frameworks that make it easy to create a REST API by reducing the number of boilerplates. I personally prefer Rust because it is simple, strongly typed, extremely fast, and safer than almost any language out there.

In this tutorial, we’ll demonstrate how to write simple endpoints, handle errors, maintain a connection to the database, persist data to Postgres DB, and, eventually, handle the request-response cycle.

I chose the Actix web 2.0 framework because it’s one of the most popular, has great documentation, and uses patterns similar to TypeScript Express in Node.js. Other popular alternatives include Rocket and Tower. Our persistence layer will consist of Postgres with Diesel as the ORM and query builder.

Before we dive into coding, let’s take establish what we’ll be building and some fundamental requirements and assumptions. We’ll create all the CRUD API endpoints for employee management applications. This will be a bare-bones project designed to demonstrate all the fundamental building blocks for writing APIs in Rust.

Setup and important concepts

First, let’s go over how to set up a basic Rust project, folder structures, dependencies, etc. If you’re coming from a Node.js background. you’ll already be familiar with npm as the package management and registry. The equivalent in Rust is called cargo.

When you initiate a Node project with npm init, you get a package.json. This is where all your dependencies live. It can be updated with new dependencies from the npm registry.

Unfortunately, as of the time of writing, cargo does not have a way to update dependencies automatically. You need to manually write out the name and version of the dependency in the Cargo.toml, which is the equivalent of package.json.
Below is a comparison between a bare-bones Node project with npm and a Rust project with Cargo.

Comparison Between Node with npm and Rust With Cargo

Getting started

If you don’t have Rust installed, follow the installation guide. Otherwise, create a new project.

cargo new emply

Basically, we asked rust cargo — just like we would with node’s npm — to scaffold a new project called emply.

Let’s set up a very basic route handler to ensure that everything works before moving forward.

First, navigate to the emply directory and add the dependencies inside Cargo.toml. Since we’ll be using Actix, add it’s dependencies by pasting the following under dependencies inside Cargo.toml.

Inside main.rs, which is the entry point for the application, pull in the actix crate. Per the Actix documentation, you’ll end up with code like this:

use actix_web::{web, App, HttpRequest, HttpServer, Responder};
async fn welcome(request: HttpRequest) -> impl Responder {
    let name = request.match_info().get("name").unwrap_or("World");
    format!("Hello {}!", &name)
}
#[actix_rt::main]
async fn main() -> std::io::Result<()> {
    HttpServer::new(|| {
        App::new()
            .route("/", web::get().to(welcome))
            .route("/{name}", web::get().to(welcome))
    })
    .bind("127.0.0.1:8000")?
    .run()
    .await
}

Here we brought the actix crate into scope within main.rs. The async function accepts the request parameter and returns “Welcome” if there is no request parameter. This is what we did with get("name").unwrap_or("World") from request.match_info. Now if you open postman and navigate to localhost:8000, you should see the text “Hello World.” Similarly, localhost:8000/Ola John will return “Welcome Ola John” where “Ola John” is a request parameter.

Watching for change

Try changing the name param in the request, and you’ll find that the response doesn’t change. That’s because, by default, you need to rebuild the code every time.

In Node, you’d fix this problem by watching for changes with nodemon. In Rust, you’d use cargo-watch to watch for changes and automatically rebuild your code after there is a change.

It’s also important to keep the connection open while your code recompiles. Imagine a situation in which a request is sent to your API during compilation, and the REST client just breaks off without any useful information. To ensure that the connection remains open and that we can respond to a request as soon as recompilation is complete, we’ll introduce the systemfd crate by running the following.

cargo install systemfd cargo-watch

Now run the code in watch mode so you don’t have to kill and restart the server after every modification.

systemfd --no-pid -s http::PORT -- cargo watch -x run

Creating the API endpoints

Now that you have the initial setup running and can confirm the modest server is up, you can proceed to create real API endpoints. Since your API will be communicating over HTTPS via JSON, you’ll need the ability to serialize and deserialize the JSON objects from and to the server.

For this, you’ll need to add another dependency called Serde. Since you’re running cargo-watch, you don’t need to rebuild; Cargo recompiles automagically.

[dependencies]
[dependencies]
actix-web = "2.0"
actix-rt = "1.0"
listenfd = "0.3"
serde = "1.0"
serde_json = "1.0"

First, define a model for the employees. In the src folder, create a directory named employees. Create a model.rs file and add the model as a struct.

// src/user/model.rs
use serde::{Deserialize, Serialize};
#[derive(Deserialize, Serialize)]
pub struct Employee {
    pub id: i32,
    pub first_name: String,
    pub last_name: String,
    pub department: String,
    pub salary: i32,
    pub age: i32,
}

Here we imported the serde crate’s Serialize and Deserialize annotations, respectively, which are responsible for converting our model from and to JSON. This is similar to what you’d do with body-parser in Node.

Creating routes for our API

Next, you’ll need to persist your data and respond to clients’ CRUD requests when they hit your endpoints. At first, you can respond with hardcoded data to make sure things work, then add persistence with postgres.

Create a route.rs file inside the employees directory.

use crate::note::Note;
use actix_web::{delete, get, post, put, web, HttpResponse, Responder};
use serde_json::json;
#[get("/employees")]
async fn find_all() -> impl Responder {
    HttpResponse::Ok().json(vec![
        Employee {
            id: 1,
            first_name : "Ola".to_string(),
            last_name: "John Ajiboye".to_string(),
           department: "Engineering".to_string(),
           salary: 4500,
           age: 23
        },
       Emoloyee {
             id: 2,
            first_name : "James".to_string(),
            last_name: "Bond".to_string(),
           department: "Accounting".to_string(),
           salary: 3500,
           age: 43
        },
    ])
}
#[get("/employees/{id}")]
async fn find() -> impl Responder {
    HttpResponse::Ok().json(Employee {
       id: 2,
            first_name : "James".to_string(),
            last_name: "Bond".to_string(),
           department: "Accounting".to_string(),
           salary: 3500,
           age: 43
    })
}
pub fn init_routes(config: &mut web::ServiceConfig) {
    config.service(find_all);
    config.service(find);
}

Here we simply created endpoints for \employees and \employees{id}. As of now, you’ll always get the same data back from these endpoints because you hardcoded the data without any persistence.

Your next task is to connect to a real database and expose the model as a crate to other programs within your application outside the employees directory. For this, you’ll need to create a mod.rs file.

// src/employees/mod.rs
mod model;
mod routes;
pub use model::*;
pub use routes::init_routes;

Here we imported the model and routes. Then, with the pub keyword, we made them public outside of the employees folder. It’s important to note that we exposed everything within the model by using * in line 4. We only made the init_routes public from the routes crate.

Now, bind your routes inside main.rs and bring the employees crate into scope with mod employees. Nothing has changed except that you’re replacing your dummy endpoints with a more dynamic mapping, which happens within route.rs. This is what we have in line 9:

App::new().configure(employees::init_routes)

Data persistence with Postgres

If you test all the endpoints with any of the HTTP verbs, it should work. However, you’re only returning hardcoded dummy data. A bunch of API endpoints without the ability to persist data is not really interesting.

Our next task is to persist clients’ data into a database, giving them the ability to retrieve, modify, and delete that data.

For this project, we’ll use postgres. To make queries and interactions with Postgres easier, we’ll use Diesel as our ORM and query builder. Diesel, which claims to be “the most productive way to interact with databases in Rust because of its safe and composable abstractions over queries,” has two major dependencies that you’ll need to have installed before you can use its CLI: openssl and the postgres library itself.

After you install those dependencies, install the Diesel CLI.

install diesel_cli --no-default-features --features postgres

The --features postgres postgres flag indicates to Diesel that you are only interested in using the postgres ORM.

You’ll also need to add Diesel to your list of dependencies.

[dependencies]
diesel = { version = "1.0.0", features = ["postgres"] }

Now that you have your dependencies updated, it’s time to set up Diesel in your project. It’s important to specify the database URL.

diesel setup
diesel migration generate create_employees

With these commands, Diesel will create a migration folder. You should have another folder inside the migration folder that contains up.sql and down.sql. up.sql creates a schema for the employees, while down.sql reverts everything done by up.sql or just drops the whole table.

Creating the employees schema and data table

Inside src/migrations/~/up.sql, create a table named employees to hold data for your notes.

// up.sql

sql
CREATE TABLE "employees"
(
id SERIAL PRIMARY KEY,
firstname VARCHAR NOT NULL,
lastname VARCHAR NOT NULL,
department VARCHAR NOT NULL,
salary INT NOT NULL,
age INT NOT NULL,
)

Now that you’ve created the employees migration, it’s time to run it with the Diesel CLI. This should create a schema file that will be used to build SQL queries. Run diesel migration to create the schema.

diesel migration run

If you run the above command, you’ll get an error asking for a database URL. For this, you’ll need to add a .env to handle your environment variables.

DATABASEURL=postgres://postgres:password@localhost/employeesrest_api

This will tell Diesel the location of your database. In the root of the project, create a .env file. By default, the schema is created inside src/schema.rs.

Database connection

Now it’s time to create a database connection for data persistence. Create db.rs. Upon connecting the database, you can now connect your CRUD operations to it. Update the model to reflect this.

js
use crate::db;
use crate::error_handler::CustomError;
use crate::schema::employees;
use diesel::prelude::*;
use serde::{Deserialize, Serialize};
#[derive(Serialize, Deserialize, AsChangeset, Insertable)]
#[table_name = "employees"]
pub struct Employee {
    pub first_name: String,
    pub last_name: String,
    pub department: String,
    pub salary: i32,
    pub age: i32,
}
#[derive(Serialize, Deserialize, Queryable, Insertable)]
#[table_name = "employees"]
pub struct Employees {
    pub id: i32,
    pub first_name: String,
    pub last_name: String,
    pub department: String,
    pub salary: i32,
    pub age: i32,
}
impl Employees {
    pub fn find_all() -> Result<Vec, CustomError> {
        let conn = db::connection()?;
        let employees = employees::table.load::(&conn)?;
        Ok(employees)
    }
    pub fn find(id: i32) -> Result<Self, CustomError> {
        let conn = db::connection()?;
        let employee = employees::table.filter(employees::id.eq(id)).first(&conn)?;
        Ok(employee)
    }
    pub fn create(employee: Employee) -> Result<Self, CustomError> {
        let conn = db::connection()?;
        let employee = Employee::from(employee);
        let employee = diesel::insert_into(employees::table)
            .values(employee)
            .get_result(&conn)?;
        Ok(employee)
    }
    pub fn update(id: i32, employee: Employee) -> Result<Self, CustomError> {
        let conn = db::connection()?;
        let employee = diesel::update(employees::table)
            .filter(employees::id.eq(id))
            .set(employee)
            .get_result(&conn)?;
        Ok(employee)
    }
    pub fn delete(id: i32) -> Result<usize, CustomError> {
        let conn = db::connection()?;
        let res = diesel::delete(employees::table.filter(employees::id.eq(id))).execute(&conn)?;
        Ok(res)
    }
}
impl Employee {
    fn from(employee: Employee) -> Employee {
        Employee {
            first_name: employee.first_name,
            last_name: employee.last_name,
            department: employee.department,
            salary: employee.salary,
            age: employee.age,
        }
    }
}

Let’s examine what’s happening in model.rs. We added an Employee struct as an Insertable, which is used to INSERT into the database. You’ll notice that this does not have an id property since this is automatically generated.

We also implemented this as a trait. In find_all, for instance, like all other methods, we connected the database with let conn = db::connection()?;.

The next line —

let employees = employees::table.load::(&conn)?;

— is equivalent to saying, “Connect to postgres and execute the below SQL.”

sql
SELECT * FROM employees

The above line is equivalent to:

rs
employees::table.load

We then stored the response as a JSON under employees. The expected response is an enum of type pub enum Result<T, E> — that is, result or error. We return an Option with the employee JSON. The logic is similar to all the other methods, which correspond to one HTTP verb.

You also need to replace the hardcoded route with routes operating on your postgres database.

js
use crate::employees::{Employee, Employees};
use crate::error_handler::CustomError;
use actix_web::{delete, get, post, put, web, HttpResponse};
use serde_json::json;
#[get("/employees")]
async fn find_all() -> Result<HttpResponse, CustomError> {
    let employees = Employees::find_all()?;
    Ok(HttpResponse::Ok().json(employees))
}
#[get("/employees/{id}")]
async fn find(id: web::Path) -> Result<HttpResponse, CustomError> {
    let employee = Employees::find(id.into_inner())?;
    Ok(HttpResponse::Ok().json(employee))
}
#[post("/employees")]
async fn create(employee: web::Json) -> Result<HttpResponse, CustomError> {
    let employee = Employees::create(employee.into_inner())?;
    Ok(HttpResponse::Ok().json(employee))
}
#[put("/employees/{id}")]
async fn update(
    id: web::Path,
    employee: web::Json,
) -> Result<HttpResponse, CustomError> {
    let employee = Employees::update(id.into_inner(), employee.into_inner())?;
    Ok(HttpResponse::Ok().json(employee))
}
#[delete("/employees/{id}")]
async fn delete(id: web::Path) -> Result<HttpResponse, CustomError> {
    let deleted_employee = Employees::delete(id.into_inner())?;
    Ok(HttpResponse::Ok().json(json!({ "deleted": deleted_employee })))
}
pub fn init_routes(config: &mut web::ServiceConfig) {
    config.service(find_all);
    config.service(find);
    config.service(create);
    config.service(update);
    config.service(delete);
}

Now it’s time to put everything together. You now have a dbconnection, an error handler, models, and the route handler. Import these crates inside main.rs. lazy_static has been implemented for pooling the database. Now update the main.rs to tie all this together.

Let’s test that everything works as expected. If you run the cargo watch command we went over earlier, you should be able to create, read, update, and delete (CRUD) an employee from the database through your API endpoints.

CRUD Operations in an API Built With Rust and Postgres
See the full code referenced in this tutorial on GitHub.

Conclusion

You should now understand how to create API endpoints and handle a simple request response cycle in Rust using Actix. We covered how to build endpoints to handle the fundamental CRUD operations, manage data persistence with Diesel as the postgres ORM, and handle and respond to errors with an error handler.

What I really like about building APIs with Rust is that it enforces good practices by engaging you to think critically about your code. If your code compiles, it is virtually guaranteed to do what it is intended to do.

For a deeper dive, refer to the finished GitHub repo.

Originally published by Olasunkanmi John Ajiboye at https://blog.logrocket.com

#rust #postgresql #rest #api #web-development

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How to Create an REST API with Rust and PostgreSQL
Easter  Deckow

Easter Deckow

1655630160

PyTumblr: A Python Tumblr API v2 Client

PyTumblr

Installation

Install via pip:

$ pip install pytumblr

Install from source:

$ git clone https://github.com/tumblr/pytumblr.git
$ cd pytumblr
$ python setup.py install

Usage

Create a client

A pytumblr.TumblrRestClient is the object you'll make all of your calls to the Tumblr API through. Creating one is this easy:

client = pytumblr.TumblrRestClient(
    '<consumer_key>',
    '<consumer_secret>',
    '<oauth_token>',
    '<oauth_secret>',
)

client.info() # Grabs the current user information

Two easy ways to get your credentials to are:

  1. The built-in interactive_console.py tool (if you already have a consumer key & secret)
  2. The Tumblr API console at https://api.tumblr.com/console
  3. Get sample login code at https://api.tumblr.com/console/calls/user/info

Supported Methods

User Methods

client.info() # get information about the authenticating user
client.dashboard() # get the dashboard for the authenticating user
client.likes() # get the likes for the authenticating user
client.following() # get the blogs followed by the authenticating user

client.follow('codingjester.tumblr.com') # follow a blog
client.unfollow('codingjester.tumblr.com') # unfollow a blog

client.like(id, reblogkey) # like a post
client.unlike(id, reblogkey) # unlike a post

Blog Methods

client.blog_info(blogName) # get information about a blog
client.posts(blogName, **params) # get posts for a blog
client.avatar(blogName) # get the avatar for a blog
client.blog_likes(blogName) # get the likes on a blog
client.followers(blogName) # get the followers of a blog
client.blog_following(blogName) # get the publicly exposed blogs that [blogName] follows
client.queue(blogName) # get the queue for a given blog
client.submission(blogName) # get the submissions for a given blog

Post Methods

Creating posts

PyTumblr lets you create all of the various types that Tumblr supports. When using these types there are a few defaults that are able to be used with any post type.

The default supported types are described below.

  • state - a string, the state of the post. Supported types are published, draft, queue, private
  • tags - a list, a list of strings that you want tagged on the post. eg: ["testing", "magic", "1"]
  • tweet - a string, the string of the customized tweet you want. eg: "Man I love my mega awesome post!"
  • date - a string, the customized GMT that you want
  • format - a string, the format that your post is in. Support types are html or markdown
  • slug - a string, the slug for the url of the post you want

We'll show examples throughout of these default examples while showcasing all the specific post types.

Creating a photo post

Creating a photo post supports a bunch of different options plus the described default options * caption - a string, the user supplied caption * link - a string, the "click-through" url for the photo * source - a string, the url for the photo you want to use (use this or the data parameter) * data - a list or string, a list of filepaths or a single file path for multipart file upload

#Creates a photo post using a source URL
client.create_photo(blogName, state="published", tags=["testing", "ok"],
                    source="https://68.media.tumblr.com/b965fbb2e501610a29d80ffb6fb3e1ad/tumblr_n55vdeTse11rn1906o1_500.jpg")

#Creates a photo post using a local filepath
client.create_photo(blogName, state="queue", tags=["testing", "ok"],
                    tweet="Woah this is an incredible sweet post [URL]",
                    data="/Users/johnb/path/to/my/image.jpg")

#Creates a photoset post using several local filepaths
client.create_photo(blogName, state="draft", tags=["jb is cool"], format="markdown",
                    data=["/Users/johnb/path/to/my/image.jpg", "/Users/johnb/Pictures/kittens.jpg"],
                    caption="## Mega sweet kittens")

Creating a text post

Creating a text post supports the same options as default and just a two other parameters * title - a string, the optional title for the post. Supports markdown or html * body - a string, the body of the of the post. Supports markdown or html

#Creating a text post
client.create_text(blogName, state="published", slug="testing-text-posts", title="Testing", body="testing1 2 3 4")

Creating a quote post

Creating a quote post supports the same options as default and two other parameter * quote - a string, the full text of the qote. Supports markdown or html * source - a string, the cited source. HTML supported

#Creating a quote post
client.create_quote(blogName, state="queue", quote="I am the Walrus", source="Ringo")

Creating a link post

  • title - a string, the title of post that you want. Supports HTML entities.
  • url - a string, the url that you want to create a link post for.
  • description - a string, the desciption of the link that you have
#Create a link post
client.create_link(blogName, title="I like to search things, you should too.", url="https://duckduckgo.com",
                   description="Search is pretty cool when a duck does it.")

Creating a chat post

Creating a chat post supports the same options as default and two other parameters * title - a string, the title of the chat post * conversation - a string, the text of the conversation/chat, with diablog labels (no html)

#Create a chat post
chat = """John: Testing can be fun!
Renee: Testing is tedious and so are you.
John: Aw.
"""
client.create_chat(blogName, title="Renee just doesn't understand.", conversation=chat, tags=["renee", "testing"])

Creating an audio post

Creating an audio post allows for all default options and a has 3 other parameters. The only thing to keep in mind while dealing with audio posts is to make sure that you use the external_url parameter or data. You cannot use both at the same time. * caption - a string, the caption for your post * external_url - a string, the url of the site that hosts the audio file * data - a string, the filepath of the audio file you want to upload to Tumblr

#Creating an audio file
client.create_audio(blogName, caption="Rock out.", data="/Users/johnb/Music/my/new/sweet/album.mp3")

#lets use soundcloud!
client.create_audio(blogName, caption="Mega rock out.", external_url="https://soundcloud.com/skrillex/sets/recess")

Creating a video post

Creating a video post allows for all default options and has three other options. Like the other post types, it has some restrictions. You cannot use the embed and data parameters at the same time. * caption - a string, the caption for your post * embed - a string, the HTML embed code for the video * data - a string, the path of the file you want to upload

#Creating an upload from YouTube
client.create_video(blogName, caption="Jon Snow. Mega ridiculous sword.",
                    embed="http://www.youtube.com/watch?v=40pUYLacrj4")

#Creating a video post from local file
client.create_video(blogName, caption="testing", data="/Users/johnb/testing/ok/blah.mov")

Editing a post

Updating a post requires you knowing what type a post you're updating. You'll be able to supply to the post any of the options given above for updates.

client.edit_post(blogName, id=post_id, type="text", title="Updated")
client.edit_post(blogName, id=post_id, type="photo", data="/Users/johnb/mega/awesome.jpg")

Reblogging a Post

Reblogging a post just requires knowing the post id and the reblog key, which is supplied in the JSON of any post object.

client.reblog(blogName, id=125356, reblog_key="reblog_key")

Deleting a post

Deleting just requires that you own the post and have the post id

client.delete_post(blogName, 123456) # Deletes your post :(

A note on tags: When passing tags, as params, please pass them as a list (not a comma-separated string):

client.create_text(blogName, tags=['hello', 'world'], ...)

Getting notes for a post

In order to get the notes for a post, you need to have the post id and the blog that it is on.

data = client.notes(blogName, id='123456')

The results include a timestamp you can use to make future calls.

data = client.notes(blogName, id='123456', before_timestamp=data["_links"]["next"]["query_params"]["before_timestamp"])

Tagged Methods

# get posts with a given tag
client.tagged(tag, **params)

Using the interactive console

This client comes with a nice interactive console to run you through the OAuth process, grab your tokens (and store them for future use).

You'll need pyyaml installed to run it, but then it's just:

$ python interactive-console.py

and away you go! Tokens are stored in ~/.tumblr and are also shared by other Tumblr API clients like the Ruby client.

Running tests

The tests (and coverage reports) are run with nose, like this:

python setup.py test

Author: tumblr
Source Code: https://github.com/tumblr/pytumblr
License: Apache-2.0 license

#python #api 

Wilford  Pagac

Wilford Pagac

1594289280

What is REST API? An Overview | Liquid Web

What is REST?

The REST acronym is defined as a “REpresentational State Transfer” and is designed to take advantage of existing HTTP protocols when used for Web APIs. It is very flexible in that it is not tied to resources or methods and has the ability to handle different calls and data formats. Because REST API is not constrained to an XML format like SOAP, it can return multiple other formats depending on what is needed. If a service adheres to this style, it is considered a “RESTful” application. REST allows components to access and manage functions within another application.

REST was initially defined in a dissertation by Roy Fielding’s twenty years ago. He proposed these standards as an alternative to SOAP (The Simple Object Access Protocol is a simple standard for accessing objects and exchanging structured messages within a distributed computing environment). REST (or RESTful) defines the general rules used to regulate the interactions between web apps utilizing the HTTP protocol for CRUD (create, retrieve, update, delete) operations.

What is an API?

An API (or Application Programming Interface) provides a method of interaction between two systems.

What is a RESTful API?

A RESTful API (or application program interface) uses HTTP requests to GET, PUT, POST, and DELETE data following the REST standards. This allows two pieces of software to communicate with each other. In essence, REST API is a set of remote calls using standard methods to return data in a specific format.

The systems that interact in this manner can be very different. Each app may use a unique programming language, operating system, database, etc. So, how do we create a system that can easily communicate and understand other apps?? This is where the Rest API is used as an interaction system.

When using a RESTful API, we should determine in advance what resources we want to expose to the outside world. Typically, the RESTful API service is implemented, keeping the following ideas in mind:

  • Format: There should be no restrictions on the data exchange format
  • Implementation: REST is based entirely on HTTP
  • Service Definition: Because REST is very flexible, API can be modified to ensure the application understands the request/response format.
  • The RESTful API focuses on resources and how efficiently you perform operations with it using HTTP.

The features of the REST API design style state:

  • Each entity must have a unique identifier.
  • Standard methods should be used to read and modify data.
  • It should provide support for different types of resources.
  • The interactions should be stateless.

For REST to fit this model, we must adhere to the following rules:

  • Client-Server Architecture: The interface is separate from the server-side data repository. This affords flexibility and the development of components independently of each other.
  • Detachment: The client connections are not stored on the server between requests.
  • Cacheability: It must be explicitly stated whether the client can store responses.
  • Multi-level: The API should work whether it interacts directly with a server or through an additional layer, like a load balancer.

#tutorials #api #application #application programming interface #crud #http #json #programming #protocols #representational state transfer #rest #rest api #rest api graphql #rest api json #rest api xml #restful #soap #xml #yaml

An API-First Approach For Designing Restful APIs | Hacker Noon

I’ve been working with Restful APIs for some time now and one thing that I love to do is to talk about APIs.

So, today I will show you how to build an API using the API-First approach and Design First with OpenAPI Specification.

First thing first, if you don’t know what’s an API-First approach means, it would be nice you stop reading this and check the blog post that I wrote to the Farfetchs blog where I explain everything that you need to know to start an API using API-First.

Preparing the ground

Before you get your hands dirty, let’s prepare the ground and understand the use case that will be developed.

Tools

If you desire to reproduce the examples that will be shown here, you will need some of those items below.

  • NodeJS
  • OpenAPI Specification
  • Text Editor (I’ll use VSCode)
  • Command Line

Use Case

To keep easy to understand, let’s use the Todo List App, it is a very common concept beyond the software development community.

#api #rest-api #openai #api-first-development #api-design #apis #restful-apis #restful-api

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Unilevel MLM Wordpress Rest API FrontEnd | UMW Rest API Woocommerce

Unilevel MLM Wordpress Rest API FrontEnd | UMW Rest API Woocommerce Price USA, Philippines : Our API’s handle the Unilevel MLM woo-commerce end user all functionalities like customer login/register. You can request any type of information which is listed below, our API will provide you managed results for your all frontend needs, which will be useful for your applications like Mobile App etc.
Business to Customer REST API for Unilevel MLM Woo-Commerce will empower your Woo-commerce site with the most powerful Unilevel MLM Woo-Commerce REST API, you will be able to get and send data to your marketplace from other mobile apps or websites using HTTP Rest API request.
Our plugin is used JWT authentication for the authorization process.

REST API Unilevel MLM Woo-commerce plugin contains following APIs.
User Login Rest API
User Register Rest API
User Join Rest API
Get User info Rest API
Get Affiliate URL Rest API 
Get Downlines list Rest API
Get Bank Details Rest API
Save Bank Details Rest API
Get Genealogy JSON Rest API
Get Total Earning Rest API
Get Current Balance Rest API
Get Payout Details Rest API
Get Payout List Rest API
Get Commissions List Rest API
Withdrawal Request Rest API
Get Withdrawal List Rest API

If you want to know more information and any queries regarding Unilevel MLM Rest API Woocommerce WordPress Plugin, you can contact our experts through 
Skype: jks0586, 
Mail: letscmsdev@gmail.com,
Website: www.letscms.com, www.mlmtrees.com,
Call/WhatsApp/WeChat: +91-9717478599.  

more information : https://www.mlmtrees.com/product/unilevel-mlm-woocommerce-rest-api-addon

Visit Documentation : https://letscms.com/documents/umw_apis/umw-apis-addon-documentation.html

#Unilevel_MLM_WooCommerce_Rest_API's_Addon #umw_mlm_rest_api #rest_api_woocommerce_unilevel #rest_api_in_woocommerce #rest_api_woocommerce #rest_api_woocommerce_documentation #rest_api_woocommerce_php #api_rest_de_woocommerce #woocommerce_rest_api_in_android #woocommerce_rest_api_in_wordpress #Rest_API_Woocommerce_unilevel_mlm #wp_rest_api_woocommerce

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Opencart REST API extensions - V3.x | Rest API Integration, Affiliate

Opencart REST API extensions - V3.x | Rest API Integration : OpenCart APIs is fully integrated with the OpenCart REST API. This is interact with your OpenCart site by sending and receiving data as JSON (JavaScript Object Notation) objects. Using the OpenCart REST API you can register the customers and purchasing the products and it provides data access to the content of OpenCart users like which is publicly accessible via the REST API. This APIs also provide the E-commerce Mobile Apps.

Opencart REST API 
OCRESTAPI Module allows the customer purchasing product from the website it just like E-commerce APIs its also available mobile version APIs.

Opencart Rest APIs List 
Customer Registration GET APIs.
Customer Registration POST APIs.
Customer Login GET APIs.
Customer Login POST APIs.
Checkout Confirm GET APIs.
Checkout Confirm POST APIs.


If you want to know Opencart REST API Any information, you can contact us at -
Skype: jks0586,
Email: letscmsdev@gmail.com,
Website: www.letscms.com, www.mlmtrees.com
Call/WhatsApp/WeChat: +91–9717478599.

Download : https://www.opencart.com/index.php?route=marketplace/extension/info&extension_id=43174&filter_search=ocrest%20api
View Documentation : https://www.letscms.com/documents/api/opencart-rest-api.html
More Information : https://www.letscms.com/blog/Rest-API-Opencart
VEDIO : https://vimeo.com/682154292  

#opencart_api_for_android #Opencart_rest_admin_api #opencart_rest_api #Rest_API_Integration #oc_rest_api #rest_api_ecommerce #rest_api_mobile #rest_api_opencart #rest_api_github #rest_api_documentation #opencart_rest_admin_api #rest_api_for_opencart_mobile_app #opencart_shopping_cart_rest_api #opencart_json_api