How to Migrate Redux to the Context API

In the following documentation, we are going to, from the ground up, refactor a Redux shopping cart product’s data into the Context Provider pattern.

• Video
• Source code

This guide’s primary focus will be on comparing and contrasting Redux vs. the Context API.

The refactor aims to provide a guided example, as well as deepen our understanding of state management in React, implementing various efficient scalable patterns.

Process Overview

The shopping cart application will be pulled from the official Redux GitHub repository to maintain a standard example environment.

We will trace the Flux-like pattern of Redux in the shopping cart app, and by focusing on the product data, implement a successful state management refactor by leveraging React Hooks and the Context API.

Guide Outline

• Clone Redux.
• Scalable state management analysis.
• Tracing shopping cart product data.
• Reducers and Actions.
• Thunk and logger: middleware vs. dispatch.
• Implement Context Provider pattern.
• HOCs, HOFs, and Redux Connect().
• Leveraging React Hooks and useContext.
• setTimeout() vs. promises.
• Final Context Provider pattern refactor.

Alright. So, let’s grab some coffee and get this show on the road.

Please note that a basic level requirement of Node and React is beneficial for getting started and for general concept comprehension.

Clone Redux

First off, go to the Redux GitHub repository.

Redux Github Repo

Clone the source project by copying the SSH link and running git clonein the command prompt.

git clone git@github.com:reduxjs/redux.git

Copy the Shopping Cart folder which can be found in the folder directory: examples/shopping-cart and paste it somewhere where you can conveniently access it throughout this guide.

Now, using the terminal (Mac) command prompt, go cd shopping-cart into the shopping-cart folder directory and install all required node modules simply by running npm install.

Open the code source into your text editor and then launch the local development server by running npm start. We should now see the shopping cart application up and running in the browser.

Open up the DevTools Console (Chrome) to verify this and also note Redux Logger is activated and working.

Excellent. Now, let’s take a quick yet savory sip of coffee before proceeding.

Application Structure and API Emulation

Simply by viewing the shopping cart’s display in the browser, we can ascertain two main sections: the products section and the cart section.

• The products section contains a list of products available to purchase including the title, price, and quantity. As well, there is an add to cart button to individually select products for the cart.
• When we click on the iPad 4 Mini add to cart button, we see that the cart sectiongets updated, including the total price. If we scroll down to the Logger in the DevTools and check on the previous state vs. the next state, the products inventory is updated and reflected accordingly.

Next State Logger

But where are we receiving our product’s item data to begin with?

Good question. In the Redux shopping cart project’s API folder, we see a products.json file with a list of items and a shop.jsfile, grabbing and exporting the array from products.json.

The shop.js getProducts object’s property has an additional setTimeout function set to 100 milliseconds to simulate an Async-esque operation of fetching the shopping cart items from a real-world API scenario.

const TIMEOUT = 100

export default { getProducts: (cb, timeout) => setTimeout(() => cb(_products), timeout || TIMEOUT),

buyProducts: (payload, cb, timeout) => setTimeout(() => cb(), timeout || TIMEOUT)}

If we change the TIMEOUT const numerical value to 2000 (two seconds) and go back to the browser and refresh, we’ll notice the initial products render will now take two full seconds before displaying: const TIMEOUT = 2000.

Having now located and assessed our API data structure and retrieval setup, let’s fully trace the state retrieval management process of the products data in Redux.

Products: Actions, Reducers, and Thunk Middleware

If we go into the actions folder, the index.jscontains the following code:

import shop from '../api/shop'

import * as types from '../constants/ActionTypes'

const receiveProducts = products => ({

type: types.RECEIVE_PRODUCTS,

products})

export const getAllProducts = () => dispatch => {

shop.getProducts(products => {

dispatch(receiveProducts(products))

})}

The receiveProducts establishes the type types.RECEIVE_PRODUCTS and a payload of products.

This type is set up as const in the ActionTypes file. It’s then passed to a switch statement in two reducers, visibleIds and byIds, located in the reducer folder in products.js.

Maintaining focus on the actions, also notice a getAllProducts function which returns a dispatch function that grabs the products.json from the shop and sends the data payload of products into our receiveProducts action.

Back in the main index.jsfile located in our src folder, if we remove our Thunk middleware: const middleware = [ ];, we receive the following error:

Since the action performs an emulated real-life API fetch, set to a setTimeout(), we need to implement Thunk to correctly process and handle the async action.

Have a contemplative sip or two of coffee and return Thunk back to the middleware: const middleware = [thunk].

We’ve now managed to complete a full assessment of the product’s data API display: How and where we’re receiving the data and managing it in our application.

With this assessment, let’s proceed by setting up the architecture for the Context Provider pattern.

Context Provider Pattern Setup

Back in the project’s src folder, create a new folder called providers and file inside of the folder named products.provider.js.

In the products provider file, we’re going to set up a products provider pre-test demonstration with the following code:

import React,{createContext, useState} from 'react'

export const ProductsContext = createContext({
    test: ''
})

const ProductsProvider = ({children}) => {
    const [test] = useState('the products provider has been successfully connected :)')
    return (
        <ProductsContext.Provider value={{test}}>
            {children}
        </ProductsContext.Provider>
    )
}

export default ProductsProvider

The code above first brings in createContext to access the React Context API and the useState Hook. Then, we set our context to the constProductsContext where we initialize an object that takes the property of test which we set to an empty string.

After that, we create the ProductsProviderfunction which takes the object of children props as its parameter, passing the props of children through the Context.Provider.

Within, we initialize the state of test to a string: const [test] = useState(‘the products provider has been successfully connected :)’).

ProductsProvider then explicitly returns the ProductsContext to the Provider with a value of the object test passing in the state with the property of children.

Alright, let’s stop for a second. Might sound like a bit of mouthful, but it’s actually quite simple, except that it takes a bit of following in terms of how things are hooked up.

If you’re having trouble following, go back and take each step one at a time, slowly. Just make sure you follow the traces and it will make much more sense, otherwise, if you’ve managed to follow along up to this part, kudos and let’s keep moving!

The products Context is made aware of an empty string of test in which we initialize state by setting up a const test in the product’s Provider, also taking a string.

We can then set the state of test to the object property of test by setting the ProductsContext.Provider value={{test}} to an object receiving test.

Finally, pass the children over as a wrapper.

To enable the Provider to be wrapped around the component/container of our choosing, let’s simply go into the index.js filein thesrc folder, import the Provider, and wrap it around our application granting it access to the children.

import React from 'react'
import { render } from 'react-dom'
import { createStore, applyMiddleware } from 'redux'
import { Provider } from 'react-redux'
import { createLogger } from 'redux-logger'
import thunk from 'redux-thunk'
import reducer from './reducers'
import { getAllProducts } from './actions'
import App from './containers/App'
import ProductsProvider from './provider/products.provider'

const middleware = [thunk];
if (process.env.NODE_ENV !== 'production') {
  middleware.push(createLogger());
}

const store = createStore(
  reducer,
  applyMiddleware(...middleware)
)

store.dispatch(getAllProducts())

render(
  <ProductsProvider>
  <Provider store={store}>
    <App />
  </Provider>
  </ProductsProvider>,
  document.getElementById('root')
)

Note that the ProductsProvider wraps over the Redux store Provider illustrating it at the utmost top of our application’s state management tree.

Context Provider Pattern Test

Time to drink some more coffee and test if our new Context Provider is effectively working.

Go into the containers folder in productsContainer.js.We can now bring in the useContext Hook and destructure our test from the ProductsContext into our products container to see if it works.

import React,{useContext} from 'react'
import PropTypes from 'prop-types'
import { connect } from 'react-redux'
import { addToCart } from '../actions'
import { getVisibleProducts } from '../reducers/products'
import ProductItem from '../components/ProductItem'
import ProductsList from '../components/ProductsList'
import {ProductsContext} from '../provider/products.provider'

const ProductsContainer = ({ products, addToCart }) => {
  const {test} = useContext(ProductsContext)
  console.log(test)
return (
  <ProductsList title="Products">
    {products.map(product =>
      <ProductItem
        key={product.id}
        product={product}
        onAddToCartClicked={() => addToCart(product.id)} />
    )}
  </ProductsList>
)
    }
ProductsContainer.propTypes = {
  products: PropTypes.arrayOf(PropTypes.shape({
    id: PropTypes.number.isRequired,
    title: PropTypes.string.isRequired,
    price: PropTypes.number.isRequired,
    inventory: PropTypes.number.isRequired
  })).isRequired,
  addToCart: PropTypes.func.isRequired
}

const mapStateToProps = state => ({
  products: getVisibleProducts(state.products)
})

export default connect(
  mapStateToProps,
  { addToCart }
)(ProductsContainer)

Our productsContainer.jsshould now be updated to the code above. Upon browser refresh, DevTools now displays the test log successfully.

Very nice. Our Context Provider pattern for our product’s display is now fully connected and ready for implementation.

Let’s head back to our products.provider.js file and completely refactor the product’s data into our Context API setup.

Migrate Products Data to Context Provider

We’ll now update the products.provider.jscode. First, we’ll import the shop from our shop.js.

We’ll establish a new property in our context object for the products’ data and set it to an empty array. We’ll then import the useEffect Hook as well from React and create a products’ state also set to an empty array.

Then, we’ll leverage the useEffect Hook to render our product’s data by setting the hook to async to await grabbing the product’s data from our shop and setting the response to our products state.

We’ll leave an empty array in our useEffect so that the mounting life-cycle executes once, by default.

Finally, we’ll bring the product’s state into the Context Provider’s value object.

import React,{createContext, useState, useEffect} from 'react'
import shop from '../api/shop'

export const ProductsContext = createContext({
    test: '',
    products: []
})

const ProductsProvider = ({children}) => {
    const [test] = useState('the products provider has been successfully connected :)')
    const [products, setProducts] = useState([])
    useEffect(async ()=> {
        const response = await shop.getProducts(products => products)
        setProducts(response)
},[])
    return (
        <ProductsContext.Provider value={{test, products}}>
            {children}
        </ProductsContext.Provider>
    )
}

export default ProductsProvider

Final Implementation and Async vs. Promises

Saving the newly updated code, let’s refill our coffee cups and head back to the productsContainer.js file.

Let’s update our products’ data to be called from our Products Provider instead of our Redux Provider by destructuring products off the ProductsContext and removing products destructured props from the ProductsContainer, as shown below.

import React,{useContext} from 'react'
import PropTypes from 'prop-types'
import { connect } from 'react-redux'
import { addToCart } from '../actions'
import { getVisibleProducts } from '../reducers/products'
import ProductItem from '../components/ProductItem'
import ProductsList from '../components/ProductsList'
import {ProductsContext} from '../provider/products.provider'

const ProductsContainer = ({  addToCart }) => {
  const {test, products} = useContext(ProductsContext)
  console.log(test)
return (
  <ProductsList title="Products">
    {products.map(product =>
      <ProductItem
        key={product.id}
        product={product}
        onAddToCartClicked={() => addToCart(product.id)} />
    )}
  </ProductsList>
)
    }
ProductsContainer.propTypes = {
  products: PropTypes.arrayOf(PropTypes.shape({
    id: PropTypes.number.isRequired,
    title: PropTypes.string.isRequired,
    price: PropTypes.number.isRequired,
    inventory: PropTypes.number.isRequired
  })).isRequired,
  addToCart: PropTypes.func.isRequired
}

const mapStateToProps = state => ({
  products: getVisibleProducts(state.products)
})

export default connect(
  mapStateToProps,
  { addToCart }
)(ProductsContainer)

After saving everything, we will now run into the following error.

No need to panic, this is expected behavior. Since setTimeout does not return a promise, async await will not execute accordingly to prevent JavaScript from running until the setTimeout interval value is completed.

To maintain the coded simulation effect of this API, let’s go back to the shop.jsfile and promisify the code.

Let’s create an async anonymous function and wrap a new Promise around the getProduct data retrieval property.

* Mocking client-server processing */

import _products from './products.json'

const TIMEOUT = 100

export default {

getProducts: async ()=> new Promise((cb, timeout) => setTimeout(() => cb(_products), timeout || TIMEOUT)),

buyProducts: (payload, cb, timeout) => setTimeout(() => cb(), timeout || TIMEOUT)
}

With the new promise patch modification, getProducts will now return a promise for our async useEffect to retrieve.

Saving this latest update, our product’s shopping cart data will once again successfully be displayed upon mounting.

Congratulations. We have now migrated our initial product’s data display from Redux into the newly instated Context Provider pattern.

Take a congratulatory sip or three of coffee and let’s do some final code clean-up and review.

Final Refactor and Conclusion

Back in our productsContainer.js file, we can delete our mapStateToProps const and remove it from our connect since our products’ data retrieval is no longer being managed by Redux.

export default connect(null,{ addToCart })(ProductsContainer)

Our application will continue to work as is it did before, demonstrating a successful refactor.

Just like Connect() is a higher-order component that wrapped around our productsContainer component to pass over the data state to props, our ProductsProvider now acts in its place.

The Products Context passes the children props of the products data state as the Products Provider wraps around the main application in our index.jsby being placed at the top of the app tree.

Although both implementations are effective, this guide in no way favors one over the other as an ultimate go-to.

It simply depends on each application and these are the decisions we need to think about carefully and make to achieve the most effective state management path for our applications.

This guide has purely been intended to simulate a refactor process and analysis of working with Context and Redux as a basic starting point.

If you’d like an additional exercise idea, you can go ahead and find something else in the Redux shopping cart example to refactor.

If you have any questions or comments, please feel free to leave them below. You can also check out the full source code or video tutorial in the links at the top of this post.

Thank you for checking this out and I hope you found some of this helpful!

#React #Redux #React Hook #JavaScript #Programming

What is GEEK

Buddha Community

Top 10 API Security Threats Every API Team Should Know

As more and more data is exposed via APIs either as API-first companies or for the explosion of single page apps/JAMStack, API security can no longer be an afterthought. The hard part about APIs is that it provides direct access to large amounts of data while bypassing browser precautions. Instead of worrying about SQL injection and XSS issues, you should be concerned about the bad actor who was able to paginate through all your customer records and their data.

Typical prevention mechanisms like Captchas and browser fingerprinting won’t work since APIs by design need to handle a very large number of API accesses even by a single customer. So where do you start? The first thing is to put yourself in the shoes of a hacker and then instrument your APIs to detect and block common attacks along with unknown unknowns for zero-day exploits. Some of these are on the OWASP Security API list, but not all.

Insecure pagination and resource limits

Most APIs provide access to resources that are lists of entities such as /users or /widgets. A client such as a browser would typically filter and paginate through this list to limit the number items returned to a client like so:

First Call: GET /items?skip=0&take=10 
Second Call: GET /items?skip=10&take=10

However, if that entity has any PII or other information, then a hacker could scrape that endpoint to get a dump of all entities in your database. This could be most dangerous if those entities accidently exposed PII or other sensitive information, but could also be dangerous in providing competitors or others with adoption and usage stats for your business or provide scammers with a way to get large email lists. See how Venmo data was scraped

A naive protection mechanism would be to check the take count and throw an error if greater than 100 or 1000. The problem with this is two-fold:

1. For data APIs, legitimate customers may need to fetch and sync a large number of records such as via cron jobs. Artificially small pagination limits can force your API to be very chatty decreasing overall throughput. Max limits are to ensure memory and scalability requirements are met (and prevent certain DDoS attacks), not to guarantee security.
2. This offers zero protection to a hacker that writes a simple script that sleeps a random delay between repeated accesses.

skip = 0
while True:    response = requests.post('https://api.acmeinc.com/widgets?take=10&skip=' + skip),                      headers={'Authorization': 'Bearer' + ' ' + sys.argv[1]})    print("Fetched 10 items")    sleep(randint(100,1000))    skip += 10

How to secure against pagination attacks

To secure against pagination attacks, you should track how many items of a single resource are accessed within a certain time period for each user or API key rather than just at the request level. By tracking API resource access at the user level, you can block a user or API key once they hit a threshold such as “touched 1,000,000 items in a one hour period”. This is dependent on your API use case and can even be dependent on their subscription with you. Like a Captcha, this can slow down the speed that a hacker can exploit your API, like a Captcha if they have to create a new user account manually to create a new API key.

Insecure API key generation

Most APIs are protected by some sort of API key or JWT (JSON Web Token). This provides a natural way to track and protect your API as API security tools can detect abnormal API behavior and block access to an API key automatically. However, hackers will want to outsmart these mechanisms by generating and using a large pool of API keys from a large number of users just like a web hacker would use a large pool of IP addresses to circumvent DDoS protection.

How to secure against API key pools

The easiest way to secure against these types of attacks is by requiring a human to sign up for your service and generate API keys. Bot traffic can be prevented with things like Captcha and 2-Factor Authentication. Unless there is a legitimate business case, new users who sign up for your service should not have the ability to generate API keys programmatically. Instead, only trusted customers should have the ability to generate API keys programmatically. Go one step further and ensure any anomaly detection for abnormal behavior is done at the user and account level, not just for each API key.

Accidental key exposure

APIs are used in a way that increases the probability credentials are leaked:

1. APIs are expected to be accessed over indefinite time periods, which increases the probability that a hacker obtains a valid API key that’s not expired. You save that API key in a server environment variable and forget about it. This is a drastic contrast to a user logging into an interactive website where the session expires after a short duration.
2. The consumer of an API has direct access to the credentials such as when debugging via Postman or CURL. It only takes a single developer to accidently copy/pastes the CURL command containing the API key into a public forum like in GitHub Issues or Stack Overflow.
3. API keys are usually bearer tokens without requiring any other identifying information. APIs cannot leverage things like one-time use tokens or 2-factor authentication.

If a key is exposed due to user error, one may think you as the API provider has any blame. However, security is all about reducing surface area and risk. Treat your customer data as if it’s your own and help them by adding guards that prevent accidental key exposure.

How to prevent accidental key exposure

The easiest way to prevent key exposure is by leveraging two tokens rather than one. A refresh token is stored as an environment variable and can only be used to generate short lived access tokens. Unlike the refresh token, these short lived tokens can access the resources, but are time limited such as in hours or days.

The customer will store the refresh token with other API keys. Then your SDK will generate access tokens on SDK init or when the last access token expires. If a CURL command gets pasted into a GitHub issue, then a hacker would need to use it within hours reducing the attack vector (unless it was the actual refresh token which is low probability)

Exposure to DDoS attacks

APIs open up entirely new business models where customers can access your API platform programmatically. However, this can make DDoS protection tricky. Most DDoS protection is designed to absorb and reject a large number of requests from bad actors during DDoS attacks but still need to let the good ones through. This requires fingerprinting the HTTP requests to check against what looks like bot traffic. This is much harder for API products as all traffic looks like bot traffic and is not coming from a browser where things like cookies are present.

Stopping DDoS attacks

The magical part about APIs is almost every access requires an API Key. If a request doesn’t have an API key, you can automatically reject it which is lightweight on your servers (Ensure authentication is short circuited very early before later middleware like request JSON parsing). So then how do you handle authenticated requests? The easiest is to leverage rate limit counters for each API key such as to handle X requests per minute and reject those above the threshold with a 429 HTTP response. There are a variety of algorithms to do this such as leaky bucket and fixed window counters.

Incorrect server security

APIs are no different than web servers when it comes to good server hygiene. Data can be leaked due to misconfigured SSL certificate or allowing non-HTTPS traffic. For modern applications, there is very little reason to accept non-HTTPS requests, but a customer could mistakenly issue a non HTTP request from their application or CURL exposing the API key. APIs do not have the protection of a browser so things like HSTS or redirect to HTTPS offer no protection.

How to ensure proper SSL

Test your SSL implementation over at Qualys SSL Test or similar tool. You should also block all non-HTTP requests which can be done within your load balancer. You should also remove any HTTP headers scrub any error messages that leak implementation details. If your API is used only by your own apps or can only be accessed server-side, then review Authoritative guide to Cross-Origin Resource Sharing for REST APIs

Incorrect caching headers

APIs provide access to dynamic data that’s scoped to each API key. Any caching implementation should have the ability to scope to an API key to prevent cross-pollution. Even if you don’t cache anything in your infrastructure, you could expose your customers to security holes. If a customer with a proxy server was using multiple API keys such as one for development and one for production, then they could see cross-pollinated data.

#api management #api security #api best practices #api providers #security analytics #api management policies #api access tokens #api access #api security risks #api access keys

Public ASX100 APIs: The Essential List

We’ve conducted some initial research into the public APIs of the ASX100 because we regularly have conversations about what others are doing with their APIs and what best practices look like. Being able to point to good local examples and explain what is happening in Australia is a key part of this conversation.

Method

The method used for this initial research was to obtain a list of the ASX100 (as of 18 September 2020). Then work through each company looking at the following:

1. Whether the company had a public API: this was found by googling “[company name] API” and “[company name] API developer” and “[company name] developer portal”. Sometimes the company’s website was navigated or searched.
2. Some data points about the API were noted, such as the URL of the portal/documentation and the method they used to publish the API (portal, documentation, web page).
3. Observations were recorded that piqued the interest of the researchers (you will find these below).
4. Other notes were made to support future research.
5. You will find a summary of the data in the infographic below.

Data

With regards to how the APIs are shared:

• Documentation is where just the Swagger/OpenAPI docs are hosted somewhere. e.g. https://api.linkgroup.com/member/docs/index
• Portal is where an interactive portal has been developed. e.g. https://dev.telstra.com/
• The web page is where the company has a single page that isn’t interactive explaining their Public APIs. e.g. https://www.bendigoadelaide.com.au/banking-products-api.asp

#api #api-development #api-analytics #apis #api-integration #api-testing #api-security #api-gateway

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

What Are Good Traits That Make Great API Product Managers

As more companies realize the benefits of an API-first mindset and treating their APIs as products, there is a growing need for good API product management practices to make a company’s API strategy a reality. However, API product management is a relatively new field with little established knowledge on what is API product management and what a PM should be doing to ensure their API platform is successful.

Many of the current practices of API product management have carried over from other products and platforms like web and mobile, but API products have their own unique set of challenges due to the way they are marketed and used by customers. While it would be rare for a consumer mobile app to have detailed developer docs and a developer relations team, you’ll find these items common among API product-focused companies. A second unique challenge is that APIs are very developer-centric and many times API PMs are engineers themselves. Yet, this can cause an API or developer program to lose empathy for what their customers actually want if good processes are not in place. Just because you’re an engineer, don’t assume your customers will want the same features and use cases that you want.

This guide lays out what is API product management and some of the things you should be doing to be a good product manager.

#api #analytics #apis #product management #api best practices #api platform #api adoption #product managers #api product #api metrics

54% of Developers Cite Lack of Documentation as the Top Obstacle to Consuming APIs

Recently, I worked with my team at Postman to field the 2020 State of the API survey and report. We’re insanely grateful to the folks who participated—more than 13,500 developers and other professionals took the survey, helping make this the largest and most comprehensive survey in the industry. (Seriously folks, thank you!) Curious what we learned? Here are a few insights in areas that you might find interesting:

API Reliability

Whether internal, external, or partner, APIs are perceived as reliable—more than half of respondents stated that APIs do not break, stop working, or materially change specification often enough to matter. Respondents choosing the “not often enough to matter” option here came in at 55.8% for internal APIs, 60.4% for external APIs, and 61.2% for partner APIs.

Obstacles to Producing APIs

When asked about the biggest obstacles to producing APIs, lack of time is by far the leading obstacle, with 52.3% of respondents listing it. Lack of knowledge (36.4%) and people (35.1%) were the next highest.

#api #rest-api #apis #api-first-development #api-report #api-documentation #api-reliability #hackernoon-top-story