Why Python?

For newbies and beginners, the Python language is relatively simple to learn and use. Python is one of the most accessible programming languages available since it has a simple syntax and is not very over the top in technical terms, allowing natural language to take precedence. Python scripts can easily be developed, and executed significantly quicker than other programming languages due to the ease of understanding and use. Here, we will try to review some of the best python http clients in 2022.

One of the biggest factors in Python’s success as a programming language, is its simple syntax, which allows it to be read and understood even by inexperienced programmers. As Python belongs to the group of interpreted languages, it can be readily experimented just by merely modifying the code base, making it even more popular among all types of developers.

Another advantage of Python’s adaptability, is that it can be efficiently utilised in a wide range of technical environments, including mobile apps, desktop apps, web development, hardware programming, and so on. Because of Python’s wide range of applications, it’s adaptability is second to none!

Furthermore, Machine Learning, Big Data, and Artificial Intelligence are powered by Python which makes its prowess in the programming world, second to none!

Best Python HTTP Clients:

 

·      Requests:

To put aptly, Requests is a, quite simple, yet elegant Python library which has been specifically built and designed for humans.

According to PePy, the Requests package is quite popular in the Python world, with over 110 million downloads per month. The main urllib.request documentation also recommends it as a “higher level HTTP client interface.” Working with requests is relatively straightforward, which is why the vast majority of Python developers choose it as their HTTP client of choice. It’s managed by the Python Software Foundation and is a dependency of several other Python libraries, including gRPC and pandas. It also has a whopping over 45k stars on Github(!)

This is how we can easily post data through Requests Library:

import requests

data = {“name”: “Obi-Wan Kenobi“, …}

r = requests.post(‘https://httpbin.org/post’, json=data)

print(r.json())

Among the best python http clients, it’s easy to understand why Requests is so successful – the design is really amazing! Of all the examples presented thus far, this one is the most basic and requires the least amount of code. HTTP verbs (GET, POST) are included as methods in Requests, and we’ve even been able to convert directly to JSON without having to develop our own decode function. Since a developer, this means it’s really easy to work with and comprehend, as we only need to make two method calls to acquire the data we need from our API.

We also didn’t have to worry about encrypting our data dictionary or defining the right data type in the request headers for our POST. Request takes care of everything for us. It’s also simple to change our POST function to submit form data instead of json by just substituting ‘data’ for the ‘json’ option. Sessions, request hooks, and configurable retry algorithms are just a few of the complex capabilities available in Requests. Sessions enable statefulness by allowing cookies to be maintained across requests from a single session instance, whereas urllib3 does not.

Sample Code:

#!/user/bin/python3

import requests

#GET Request
r = requests.get(‘https://api.github.com/events’)

#POST Request
r = requests.post(‘http://httpbin.org/post’, data = {‘key’:’value’})

·      urllib3:

Urllib3 is a Python HTTP client that is both efficient and user-friendly. Urllib3 is already used by a big section of the Python environment, and you should as well. Urllib3 adds a number of important capabilities that aren’t available in the Python standard libraries.

The urllib3 package is a different HTTP client package that builds on the urllib package, which is a bit confusing. It adds capabilities like connection pooling, TLS verification, and thread safety that were previously unavailable. As a result, programmes that make multiple calls, such as web scraping, would run better since they will reuse connections to hosts rather than initiating new ones. It receives over 150 million downloads every month, which goes on to show the popularity of the library.

Here’s the command to install urllib3 library:

Command: pip install urllib3

To make a request using urllib3, we call it as:

Import urllib3

import json

http = urllib3.PoolManager()

r = http.request(‘GET’, ‘https://swapi.dev/api/starships/9/’)

print(json.loads(r.data.decode(‘utf-8’)))

We had to convert this to JSON ourselves, like we did with the standard library, because urllib3 requires us to do it manually.

The example above, uses the Poolmanager object to handle connection pooling and thread safety, with the request needing an HTTP verb as a string argument. This is an optional step that offers urllib3 a lot of its extra capabilities. Pools will be cached, allowing subsequent requests to the same server to use the same http connection instance. This indicates that if we want to make a lot of requests to the same server, we can increase the maximum number of HTTP connections.

As many other Python libraries depend heavily on urllib3, it’s highly likely that we will continue to see it, for years to come.

Sample Code:

from requests.packages import urllib3

http = urllib3.PoolManager()
r = http.request(‘GET’, ‘http://yeahhub.com’)

print “r.status: “, r.status
print “r.data”, r.data

·      Grequests:

GRequests adds Gevent, a “co-routine based Python networking module,” to requests, enabling asynchronous requests. It’s an older library that didn’t utilise Python’s standard “asyncio” module when it was initially released in 2012. Individual requests can be made in the same way that requests are made, but we can also use the Gevent module to make a bunch of requests. An example of a code of a request using Grequests library is as follows:

import grequests

reqs = []

for ship_id in range(0, 50):

    reqs.append(grequests.get(f’https://swapi.dev/api/starships/{ship_id}/’))

for r in grequests.map(reqs):

    print(r.json On its Github website, GRequests’ documentation is poor, and it even

On its Github website, GRequests’ documentation is limited, and it even recommends other libraries over itself. With only 165 lines of code, it doesn’t provide any additional functionality over the Requests Library. It has seen six releases in its nine years, so it’s definitely only worth exploring if you find async programming very perplexing.

The command to install the Grequests library is as follows:

Command: pip install grequests

·       AIOHTTP:

Another one among the best python HTTP clients, is AIOHTTP. For asyncio and Python, AIOHTTP is an asynchronous HTTP client/server. AIOHTTP is a package that includes both a client and a server framework, making it a good fit for an API that makes requests from other places. It has 11k ratings on Github and is the foundation for a variety of third-party libraries.

This is how we can make a POST request through AIOHTTP python client:

import aiohttp

import asyncio

data = {“name”: “Hamza Masood”, …}

async def main():

    async with aiohttp.ClientSession() as session:

        async with session.post(‘https://httpbin.org/post’, json=data) as response:

            print(await response.json())

loop = asyncio.get_event_loop()

loop.run_until_complete(main())

In comparison to requests, the AIOHTTP documentation provides a solid understanding of why all this extra code is required. If you’re unfamiliar with asynchronous programming principles, it will take some time to grasp them, but the end result is that you may make several requests at once without having to wait for each one to return a response one by one.

Here we will take a look at the sample code for looking up data of the first, say, 50 Starships from the Star wars API.

Sample Code:

import aiohttp

import asyncio

import time

async def get_starship(ship_id: int):

    async with aiohttp.ClientSession() as session:

        async with session.get(f’https://swapi.dev/api/starships/{ship_id}/’) as response:

            print(await response.json())

async def main():

    tasks = []

    for ship_id in range(1, 50):

        tasks.append(get_starship(ship_id))

    await asyncio.gather(*tasks)

asyncio.run(main())

 ·      HTTPX:

HTTPX is the newest package on our list (it was originally published in 2015) with a v1 released in 2021. It provides a “broadly requests-compatible API,” is the only example here that supports HTTP2, and also provides async APIs. HTTPX Syntax is quite similar to that of Requests Python HTTP Client.

Here, we can take a look at code for POST:

import httpx

data = {“name”:  “ Hamza Masood””, …}

r = httpx.post(‘https://httpbin.org/post’, json=data)

print(r.json())

As we can see in the code above, the resemblance between Requests Python HTTP Client and HTTPX Python HTTP Client, is striking to say the least. We just modified the name of our module and didn’t have to deal with any JSON conversion this time. You’ll also see that, despite the async APIs, we can write synchronous code with it. By utilising the http. AsyncClient and requests style http verb syntax against it, we can generate asynchronous versions of our examples.

This eliminates the need for our user to wait for responses to requests that take a long time to respond. If you have a high number of requests to make at the same time and want to conserve CPU cycles, it’s absolutely worth investigating. HTTPX appears to be a decent substitute if you’re trying to rework programmes based on requests to something asynchronous.

Here is some sample code for the HTTPX Python HTTP Client same as in the POST example above.

Sample Code:

import httpx

import asyncio

    async def get_starship(ship_id: int):

    async with httpx.AsyncClient() as client:

      r = await client.get(f’https://swapi.dev/api/starships/{ship_id}/’)

      print(r.json())

…