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Python Introduction — Why Python?

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Fundamentals

Python is a high-level, dynamically typed, interpreted language famous for readable syntax and a massive ecosystem — the default choice for backend APIs, automation, data engineering, and AI.

Overview

Python was created by Guido van Rossum and released in 1991 with one guiding idea: code is read far more often than it is written. Python trades raw speed for developer speed — no semicolons, no type declarations required, indentation instead of braces — and backs it with the largest package ecosystem in the world (PyPI has 500K+ packages). In Indian tech hiring, Python appears everywhere: backend services (FastAPI, Django), data engineering (Spark, Airflow), AI/ML (PyTorch, LangChain), testing, and scripting. If Java is the language of large enterprise systems, Python is the language of getting things done fast — and most product companies now accept DSA interviews in Python.

Your First Python Program

No class, no main method, no compilation step. A Python file (.py) runs top to bottom through the interpreter. Compare "Hello World" in Java vs Python — this difference in ceremony is the whole philosophy.

Python — a complete program in 3 lines
# hello.py — this is a comment
print("Hello, AiCanCode!")

name = "Akshay"          # no type declaration
age = 24                 # int, inferred
print(name, "is", age)   # Hello-style printing

# Run it:
# $ python hello.py

Interpreted, Dynamically Typed — What That Means

Java compiles to bytecode ahead of time and checks types at compile time. Python (CPython) compiles to bytecode at runtime and checks types while running — a variable is just a name pointing to an object, and it can point to a different type later. This makes Python flexible and fast to write, but pushes type errors to runtime — which is why modern Python adds optional type hints (covered later).

Dynamic typing — names point to objects
x = 10          # x points to an int object
x = "ten"       # now x points to a str — perfectly legal
x = [1, 2, 3]   # now a list

# Type errors appear at RUNTIME, not compile time:
def add(a, b):
    return a + b

add(2, 3)        # 5
add("a", "b")    # "ab"  (str + str works)
add(2, "b")      # TypeError — only when this line RUNS

Key Points to Remember

  • 1Python is interpreted and dynamically typed — types live on objects, not variables
  • 2Indentation IS the syntax — blocks are defined by consistent spaces (use 4)
  • 3Batteries included: a huge standard library + PyPI ecosystem (pip install)
  • 4CPython is the reference implementation; "Python is slow" usually means CPython bytecode interpretation — real apps offload hot paths to C libraries (NumPy) or async I/O

Interview Questions

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Python is called an interpreted language — what actually happens when you run a .py file?

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2

How is dynamic typing different from static typing? What are the trade-offs?

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3

Is Python compiled or interpreted? Explain the role of .pyc files and bytecode.

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