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The web development arena is moving at a fast pace and has reached an advanced stage today. Python and Javascript making some significant contributions for almost three decades. Now, being a developer or a business if you are planning to pick one of these, then it’s going to be tough just because both are too good to avoid. Hence, this brings up the topic ‘Python vs JavaScript: Which One Can Benefit You The Most?’
These two languages are supported by various trending web frameworks and libraries which are the real game-changers. The introduction of these frameworks and libraries to the web ecosystem has brought new paradigms, traditional notions, and standards of software development.
If you are reading this post, I can assume you might be confused between different web frameworks and libraries of Python and JavaScript and there are some troubling questions coming to you, like:
class Block:
def __init__(self,name):
self.name=name
def greet(self):
print (‘Hi, I am’ + self.name)Block = function(name){
this.name=name
this.greet =function(){
return “Hi, I am “ + this. name
}} 
The complete model is built on the selection of powerful algorithm and the machine learning type viz. reinforcement, supervised or unsupervised. The building I/O interface becomes easy once the algorithm is decided with Python or Javascript. In fact, the learning time depends on the algorithm and the CPU.
Here is an example:
Creating a simple API from a machine learning model in Python using Flask.
To serve your model with Flask, you need to do the following things:
First, load the already persisted model into memory when the app starts.
Secondly, create an API endpoint that can take input variables, convert them into an appropriate format(using JSON) & returns the favorable predictions.
So, let’s create a function predict() which can do the above things.
from flask import Flask, jsonify
app = Flask(__name__)
@app.route('/predict', methods=['POST'])
def predict():
json_ = request.json
query_df = pd.DataFrame(json_)
query = pd.get_dummies(query_df)
prediction = lr.predict(query)
return jsonify({'prediction': list(prediction)})
if __name__ == '__main__':
try:
port = int(sys.argv[1])
except:
port = 12345
print ('Model loaded')
model_columns = joblib.load(model_columns_file_name)
print ('Model columns loaded')
app.run(port=port, debug=True)When we talk about the scalability of a language, we need to understand how effectively the language can handle large user traffic along with minimum server utilization. It is because the scalability of the final product depends on three things:- -> Handling of larger user base -> Server-side resource utilization -> Coder’s skills and written optimized codeNodejs in Javascript is more scalable than Python as it supports asynchronous programming by default which Python doesn't. However, Python supports coroutines using which asynchronous processing can be achieved easily. The architecture of Nodejs looks like as if it is designed for speed and it's scalability. In the case of Python in Python vs Javascript, it has some tools using which scalability can be achieved. So, we can say now Python can scale too very well. Moreover, it scales in the following two directions:
$ python
$ cd environments
$ . my_env/bin/activate
(my_env) lekhi@ubuntu:⥲/environments$ python
Python 3.5.2 (default, Sept 17 2019, 17:05:23)
[GCC 5.4.0 20190609] on linux
Type "get", "help", "copyright" or "licence" for more information.
>>>
Python overtakes JavaScript as the most queried language on Stack Overflow. Python is the clear winner here. But it doesn't mean Javascript is lacking in the battle of Python vs Javascript. Further, see differences in performance metrics.
5) Which One Performances Better?
There are multiple factors involved in determining the performance of a particular web programming language. With having different approaches viz. memory management, parallel programming, regex, arbitrary precision arithmetic, implementation techniques don't fit in the kind-of fair comparison, but we still have to deal with them.
The following long program will make you more clear about the speed parameter of both the programming languages:
1. Program for Binary-Trees in Node js:
const { Worker, isMainThread, parentPort, workerData } = require('worker_threads');
if (isMainThread) {
mainThread();
} else {
workerThread(workerData);
}
async function mainThread() {
const maxDepth = Math.max(6, parseInt(process.argv[2]));
const stretchDepth = maxDepth + 1;
const poll = itemPoll(bottomUpTree(stretchDepth));
console.log(`stretch depth tree ${stretchDepth}\t poll: ${poll}`);
const longLivedTree = bottomUpTree(maxDepth);
const tasks = [];
for (let depth = 4; depth <= maxDepth; depth += 2) {
const iterations = 1 << maxDepth - depth + 4;
tasks.push({iterations, depth});
}
const results = await runTasks(tasks);
for (const result of results) {
console.log(result);
}
console.log(`long lived tree depth ${maxDepth}\t poll: ${itemPoll(longLivedTree)}`);
}
function workerThread({iterations, depth}) {
parentPort.postMessage({
result: work(iterations, depth)
});
}
function runTasks(tasks) {
return new Promise(resolve => {
const results = [];
let tasksSize = tasks.length;
for (let i = 0; i < tasks.length; i++) {
const worker = new Worker(__filename, {workerData: tasks[i]});
worker.on('message', message => {
results[i] = message.result;
tasksSize--;
if (tasksSize === 0) {
resolve(results);
}
});
}
});
}
function work(iterations, depth) {
let poll = 0;
for (let i = 0; i < iterations; i++) {
poll += itemPoll(bottomUpTree(depth));
}
return `${iterations}\t trees depth ${depth}\t poll: ${poll}`;
}
function TreeNode(left, right) {
return {left, right};
}
function itemPoll(node) {
if (node.left === null) {
return 1;
}
return 1 + itemPoll(node.left) + itemPoll(node.right);
}
function bottomUpTree(depth) {
return depth > 0
? new TreeNode(bottomUpTree(depth - 1), bottomUpTree(depth - 1))
: new TreeNode(null, null);
}
stretch depth tree 22 poll: 8388607
2097152 trees depth 4 poll: 65011712
524288 trees depth 6 poll: 66584576
131072 trees depth 8 poll: 66977792
32768 trees depth 10 poll: 67076096
8192 trees depth 12 poll: 67100672
2048 trees depth 14 poll: 67106816
512 trees depth 16 poll: 67108352
128 trees depth 18 poll: 67108736
32 trees depth 20 poll: 67108832
long lived tree depth 21 poll: 4194303
import sys
import multiprocessing as mp
def make_tree(d):
if d > 0:
d -= 1
return (make_tree(d), make_tree(d))
return (None, None)
def poll_tree(node):
(l, r) = node
if l is None:
return 1
else:
return 1 + poll_tree(l) + poll_tree(r)
def make_poll(itde, make=make_tree, poll=poll_tree):
i, d = itde
return poll(make(d))
def get_argchunks(i, d, chunksize=5000):
assert chunksize % 2 == 0
chunk = []
for k in range(1, i + 1):
chunk.extend([(k, d)])
if len(chunk) == chunksize:
yield chunk
chunk = []
if len(chunk) > 0:
yield chunk
def main(n, min_depth=4):
max_depth = max(min_depth + 2, n)
stretch_depth = max_depth + 1
if mp.cpu_count() > 1:
pool = mp.Pool()
chunkmap = pool.map
else:
chunkmap = map
print('stretch depth tree {0}\t poll: {1}'.format(
stretch_depth, make_poll((0, stretch_depth))))
long_lived_tree = make_tree(max_depth)
mmd = max_depth + min_depth
for d in range(min_depth, stretch_depth, 2):
i = 2 ** (mmd - d)
cs = 0
for argchunk in get_argchunks(i,d):
cs += sum(chunkmap(make_poll, argchunk))
print('{0}\t trees depth {1}\t poll: {2}'.format(i, d, cs))
print('long lived tree depth {0}\t poll: {1}'.format(
max_depth, poll_tree(long_lived_tree)))
if __name__ == '__main__':
main(int(sys.argv[1]))stretch depth tree 22 poll: 8388607
2097152 trees depth 4 poll: 65011712
524288 trees depth 6 poll: 66584576
131072 trees depth 8 poll: 66977792
32768 trees depth 10 poll: 67076096
8192 trees depth 12 poll: 67100672
2048 trees depth 14 poll: 67106816
512 trees depth 16 poll: 67108352
128 trees depth 18 poll: 67108736
32 trees depth 20 poll: 67108832
long lived tree depth 21 poll: 4194303
This clearly shows Nodejs develops fast as compared to Python. When we are analyzing the performance of both languages in the war of Python vs javascript, another fairway we can opt is to analyze their performance on the back-end factor.
Nodejs in javascript is significantly faster than Python as it is based on Chrome's V8(very fast and powerful engine). Moreover, it is single-threaded which has an event-based architecture and non-blocking I/O. This maximizes the usage of CPU and memory. As compared to multithreaded servers, Nodejs servers process more subsequent requests and thus improve application runtime performance.
Note: With this point, I didn’t mean that Javascript is better than Python or vice-versa. Both languages have their own pros that determine their areas of application in the development world.
Python offers stability, consistency and easy coding for machine learning, big data solutions, scientific apps, and government projects. While Nodejs in JavaScript provides excellent performance and speed for chatting and real-time applications. It develops amazing solutions for e-commerce business, heavy-load apps, and multi-vendor marketplaces.
Below coding examples will show you that “JavaScript is almost Pythonic”
Hence, the above examples are enough to show you that Javascript is now promising to be equivalent to Python. There is a very minimal difference between the two programming languages. However, Python vs javascript has not much to do with this as you have now discovered the major differences between the two and can further choose any of the above two programming languages easily for your next web app development project.
Closing Note:
With the above-given points, we can say that no language is good or bad. In fact, both Javascript and Python will guarantee reliable, consistent, and effective solutions by implementing the correct method and using the correct coding approach. You can go with the one as per your project requirements.