Python

Python's success is based on several key factors:

• simple and readable syntax
• rapid learning curve
• extremely rich ecosystem
• strong demand in the job market

Unlike other more complex languages, Python allows focusing on business logic rather than syntactic complexity. This makes it an accessible language, but also powerful enough for large-scale industrial projects.

Python's philosophy is summarized in the famous Zen of Python, which highlights essential principles such as:

• code readability
• simplicity over complexity
• explicit rather than implicit

Concretely, this translates into syntax close to natural language and a structure based on indentation, promoting clear, maintainable, and understandable code for everyone.

Python is a language that is:

• interpreted, facilitating development and debugging
• dynamically typed, with great flexibility
• strongly typed, limiting critical errors
• multi-paradigm, supporting imperative, object-oriented, and functional programming

It is also cross-platform, running on Windows, macOS, and Linux.

Python is today present in almost all digital sectors:

Web Development

Used on the server side with robust frameworks, Python enables creating performant and secure web applications.

Example: Mini API with Flask

from flask import Flask, jsonify

app = Flask(__name__)

@app.get("/health")
def health():
    return jsonify(status="ok")

if __name__ == "__main__":
    app.run(debug=True)

Data Science and Data Analysis

Python is the reference language for data manipulation, analysis, and visualization.

Example: Analyze a CSV with Pandas

import pandas as pd

df = pd.read_csv("jobs.csv")
print(df.head())
print(df["salary"].describe())

Artificial Intelligence and Machine Learning

The majority of AI projects use Python thanks to its specialized libraries.

Automation and Scripting

Python is highly appreciated for automating repetitive tasks, whether in system administration or DevOps.

Example: Rename files in bulk

from pathlib import Path

folder = Path("./candidates")
for file in folder.glob("*.txt"):
    file.rename(file.with_stem(file.stem.lower().replace(" ", "-")))

Cybersecurity

It is used for vulnerability analysis, audit scripts, and security tools.

Example: Check if a port is open (simple audit)

import socket

host = "example.com"
port = 443

with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
    s.settimeout(2)
    result = s.connect_ex((host, port))
print("open" if result == 0 else "closed")

Python is one of the most in-demand languages by recruiters. It is found in many job offers for positions such as:

• Python Developer
• Data Analyst
• Data Scientist
• Machine Learning Engineer
• Backend Developer
• DevOps Engineer

Its versatility makes it a strategic skill, both for startups and large companies.

On a tech job board like StackJobs, Python regularly ranks among the most sought-after skills.

Learning Python today represents a strategic choice for one's career. Whether in the context of a career change, a first job in tech, or skill development, Python offers many opportunities.

Thanks to its strong market demand, Python enables:

• improving employability
• accessing promising careers
• working in innovative sectors

It is a durable language, widely adopted by the industry, and will continue to play a central role in the years to come.

Python's philosophy is based on a set of principles summarized in the famous Zen of Python:

• Readability counts
• Simple is better than complex
• Explicit is better than implicit
• There should be one obvious way to do it

Concretely, this translates into clear syntax, close to natural language, and code structure based on indentation rather than braces.

Python is a language that is:

• Interpreted: code is executed line by line, which facilitates development and debugging
• Dynamically typed: variable types are determined at runtime
• Strongly typed: dangerous implicit conversions are limited
• Multi-paradigm: imperative, object-oriented, and functional programming

It is also cross-platform, running on Windows, macOS, and Linux.

Display a message

print("Hello  StackJobs!")

Variables and Types (Dynamic)

name = "Alice" #str
age = 28 #int
pi = 3.14159 #float
is_hiring = True #boolean

Conditions

score = 82
if score >= 80:
    print("Excellent")
elif score >= 50:
    print("Correct")
else:
    print("Needs improvement")

Loops

for i in range(3):
    print(i)

n = 3
while n > 0:
    n -= 1

Functions (with Type Annotations)

def greet(name: str) -> str:
    return f"Hello, {name}!"

print(greet("Nina"))

• PyPy: focused on performance thanks to JIT compilation
• Jython: integrated with the Java ecosystem
• IronPython: compatible with the .NET environment

These variants allow Python to adapt to different technical contexts.

One of Python's great strengths is its extremely rich standard library. It natively handles:

• Files and operating system
• Regular expressions
• Networks and web protocols
• Multithreading and multiprocessing

Code Examples: Standard Library

Read/Write a File

from pathlib import Path

path = Path("notes.txt")
path.write_text("Python + StackJobs = ", encoding="utf-8")
print(path.read_text(encoding="utf-8"))

Call an HTTP API (Standard Library)

import json
from urllib.request import urlopen

with urlopen("https://api.github.com") as resp:
    data = json.loads(resp.read().decode("utf-8"))
print(data["current_user_url"])  # example field

Regular Expressions

import re

text = "Contact: dev@stackjobs.ai"
pattern = r"[A-Za-z0-9_.-]+@[A-Za-z0-9_.-]+\.[A-Za-z]{2,}"
match = re.search(pattern, text)
print(match.group(0) if match else "No match")

To this is added an impressive ecosystem of third-party libraries available via PyPI, such as:

• Django and Flask for the web
• NumPy, Pandas, and Matplotlib for data
• TensorFlow and PyTorch for artificial intelligence
• Selenium and Requests for automation