1. Basic Syntax and Data Types
-
Variable Declaration: No need for
var
,let
, orconst
. Just name the variable.
x = 10 name = "Python"
-
Primitive Types:
-
int
(Integer) -
float
(Floating Point) -
str
(String) -
bool
(Boolean)
-
-
Data Structures:
- Lists (like arrays in JS):
numbers = [1, 2, 3] numbers.append(4)
- Tuples (immutable lists):
point = (10, 20)
- Dictionaries (like JS objects):
person = {"name": "Alice", "age": 30} person["name"] # Accessing value
- Sets (unique, unordered elements):
unique_numbers = {1, 2, 3, 2}
2. Control Structures
-
Conditionals:
if x > 5: print("Greater") elif x == 5: print("Equal") else: print("Lesser")
-
Loops:
- For Loop (works with iterable objects):
for num in [1, 2, 3]: print(num)
- While Loop:
i = 0 while i < 5: i += 1
3. Functions
-
Function definition and return syntax:
def greet(name): return f"Hello, {name}"
-
Lambda Functions (like JS arrow functions):
square = lambda x: x * x
4. List Comprehensions and Generators
-
List Comprehensions (efficient way to create lists):
squares = [x * x for x in range(10)]
-
Generators (yielding values one by one):
def generate_numbers(n): for i in range(n): yield i
5. Error Handling
-
Try/Except Blocks:
try: result = 10 / 0 except ZeroDivisionError: print("Cannot divide by zero")
6. Classes and OOP
-
Class Definition:
class Animal: def __init__(self, name): self.name = name def speak(self): return f"{self.name} makes a sound"
-
Inheritance:
class Dog(Animal): def speak(self): return f"{self.name} barks"
7. Common Built-In Functions
-
len()
,max()
,min()
,sum()
,sorted()
- Type conversions:
int()
,float()
,str()
,list()
,dict()
8. Working with Files
-
Reading and Writing:
with open("file.txt", "r") as file: data = file.read()
9. Important Libraries
- NumPy for numerical operations, Pandas for data manipulation, and Matplotlib for plotting.
10. Differences from JavaScript
- No need for semicolons.
- Indentation is mandatory for defining blocks.
- No
switch
statement (useif-elif
instead). -
None
is used instead ofnull
.
This summary should provide the essentials to begin coding in Python efficiently.
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