Modules and Packages in Python

import math

print(math.sqrt(49))        # 7.0  — square root
print(math.pi)              # 3.141592...
print(math.floor(4.9))      # 4    — always rounds down
print(math.ceil(4.1))       # 5    — always rounds up
print(math.pow(2, 8))       # 256.0
print(math.factorial(6))    # 720  — 6!
print(math.log(100, 10))    # 2.0  — log base 10
print(math.fabs(-9.5))      # 9.5  — absolute value as float
print(math.e)               # 2.718... — Euler's number

from math import sqrt, pi, factorial

# Use directly — no "math." prefix
print(sqrt(81))         # 9.0
print(pi)               # 3.14159...
print(factorial(5))     # 120

# Import multiple items
from math import floor, ceil, log
print(floor(9.9))       # 9
print(ceil(9.1))        # 10
print(log(1000, 10))    # 3.0

import math as m

print(m.sqrt(64))    # 8.0
print(m.pi)          # 3.14159...

from math import factorial as fact
print(fact(7))       # 5040

# These are standard industry aliases — every Python developer uses them:
# import numpy as np       ← data science / arrays
# import pandas as pd      ← data analysis / dataframes
# import matplotlib.pyplot as plt  ← charts and graphs
# import tensorflow as tf  ← deep learning

print("Aliases make long names shorter and code cleaner.")

import random

# Random integer — both endpoints included
print(random.randint(1, 10))

# Random float between 0.0 and 1.0
print(random.random())

# Random float between two specific values
print(random.uniform(5.0, 10.0))

# Pick one item at random from a list
colors = ["red", "green", "blue", "yellow", "purple"]
print(random.choice(colors))

# Pick multiple items — no repeats
print(random.sample(colors, 3))

# Shuffle a list in place (modifies the original)
cards = [1, 2, 3, 4, 5, 6, 7, 8]
random.shuffle(cards)
print("Shuffled:", cards)

# Set a seed for reproducible results (useful in testing)
random.seed(42)
print("Seeded:", random.randint(1, 100))    # always same value with same seed

from datetime import datetime, date, timedelta

# Current date and time
now = datetime.now()
print("Now      :", now)
print("Year     :", now.year)
print("Month    :", now.month)
print("Weekday  :", now.strftime("%A"))   # e.g. Monday

# Format a datetime as a readable string
print("Formatted:", now.strftime("%d %B %Y, %H:%M"))

# Today's date only (no time)
today = date.today()
print("Today    :", today)

# Create a specific date
launch = date(2024, 1, 15)
print("Launch   :", launch)

# Arithmetic — timedelta lets you add or subtract days
in_30_days = today + timedelta(days=30)
print("In 30 days:", in_30_days)

# Difference between two dates
days_since = (today - launch).days
print("Days since launch:", days_since)

import os

# Current working directory
print("CWD:", os.getcwd())

# List all files and folders in a directory
print("Contents:", os.listdir("."))

# Check if a file or folder exists
print("Exists:", os.path.exists("data.txt"))

# Build a file path that works on Windows, Mac, and Linux
path = os.path.join("reports", "sales", "q1.csv")
print("Path:", path)

# Extract filename and folder from a path
print("Filename:", os.path.basename(path))    # q1.csv
print("Folder  :", os.path.dirname(path))     # reports/sales

# Get the file extension
name, ext = os.path.splitext("report.xlsx")
print("Name:", name, "| Extension:", ext)

# Create a new directory (use exist_ok=True to avoid errors if it exists)
# os.makedirs("new_folder/sub", exist_ok=True)

# Get environment variables
home = os.environ.get("HOME", "Not set")
print("Home directory:", home)

import sys

# Python version
print("Version:", sys.version)
print("Version info:", sys.version_info)

# Platform
print("Platform:", sys.platform)   # 'linux', 'win32', 'darwin'

# The list of folders Python searches when you write import
print("First 3 search paths:")
for path in sys.path[:3]:
    print(" ", path)

# Memory size of a Python object in bytes
data = [i for i in range(1000)]
print("List size:", sys.getsizeof(data), "bytes")

# Exit the program — 0 = success, non-zero = error
# sys.exit(0)   ← uncomment to stop execution here

print("sys gives access to the interpreter itself.")

from collections import Counter, defaultdict, namedtuple

# Counter — count occurrences in one step
words = ["python", "is", "great", "python", "is", "python", "easy"]
count = Counter(words)
print("Word counts:", count)
print("Most common:", count.most_common(2))   # top 2

# defaultdict — like a dict but never raises KeyError for missing keys
scores = defaultdict(list)    # default value is an empty list
scores["Alice"].append(85)
scores["Alice"].append(92)
scores["Bob"].append(78)
print("Scores:", dict(scores))

# namedtuple — like a tuple but fields have names
Point = namedtuple("Point", ["x", "y"])
p = Point(3, 7)
print("Point:", p)
print("X:", p.x, "Y:", p.y)

Employee = namedtuple("Employee", ["name", "dept", "salary"])
emp = Employee("Priya", "Engineering", 90000)
print(emp.name, "in", emp.dept, "earns", emp.salary)

import itertools

# chain — combine multiple iterables into one sequence
combined = list(itertools.chain([1, 2, 3], [4, 5], [6]))
print("Chained:", combined)

# product — cartesian product (like nested loops)
sizes = ["S", "M", "L"]
colors = ["Red", "Blue"]
combos = list(itertools.product(sizes, colors))
print("Size-color combinations:", combos)

# permutations — all ordered arrangements
letters = list(itertools.permutations("ABC", 2))
print("2-char permutations of ABC:", letters)

# combinations — all unordered selections (no repeats)
team = list(itertools.combinations(["Alice", "Bob", "Carol", "Dan"], 2))
print("Possible pairs:", team)

# islice — take only the first N items from any iterator (memory-efficient)
evens = itertools.count(0, 2)   # infinite even numbers
first_5_evens = list(itertools.islice(evens, 5))
print("First 5 evens:", first_5_evens)

# === FILE: mytools.py ===
# Save this as mytools.py in the same folder as your main script

def greet(name):
    """Return a welcome message."""
    return f"Hello, {name}! Welcome to Dataplexa."

def calc_tax(price, rate=8):
    """Returns tax amount. Default rate is 8%."""
    return round(price * rate / 100, 2)

def is_even(n):
    """Returns True if n is even."""
    return n % 2 == 0

def word_count(text):
    """Returns a dict of word frequencies."""
    words = text.lower().split()
    counts = {}
    for w in words:
        counts[w] = counts.get(w, 0) + 1
    return counts

TAX_RATE = 8    # module-level constant

# === FILE: main.py ===
import mytools

print(mytools.greet("Arjun"))
print("Tax on Rs.500:", mytools.calc_tax(500))
print("Is 9 even?", mytools.is_even(9))
print("Tax rate:", mytools.TAX_RATE, "%")
freq = mytools.word_count("python is great and python is easy")
print("Word freq:", freq)

# Real-world project structure using packages:
#
#   myapp/
#   ├── __init__.py          ← makes myapp a package
#   ├── billing.py           ← invoice and payment functions
#   ├── users.py             ← user management functions
#   ├── reports/             ← sub-package for reports
#   │   ├── __init__.py
#   │   ├── sales.py
#   │   └── analytics.py
#   └── utils/
#       ├── __init__.py
#       └── helpers.py
#
# How you import from a package:
# import myapp.billing
# from myapp.billing import calc_invoice
# from myapp.reports.sales import monthly_report
#
# Real example — os is a package, path is a sub-module:
import os.path
print(os.path.join("data", "2025", "sales.csv"))
print(os.path.exists("/tmp"))

# datetime is also a package — datetime.datetime is a class inside it:
from datetime import datetime
print(datetime.now().strftime("%Y-%m-%d"))

# Run in your terminal (not inside Python):

# Install a package
# pip install requests          ← HTTP requests / web APIs
# pip install pandas            ← data analysis
# pip install numpy             ← numerical computing
# pip install flask             ← web framework
# pip install matplotlib        ← charts and graphs

# Install a specific version
# pip install requests==2.28.0

# Install multiple from a requirements file
# pip install -r requirements.txt

# See all installed packages
# pip list

# See details about one package
# pip show requests

# Uninstall a package
# pip uninstall requests

# Create a requirements.txt of everything in your environment
# pip freeze > requirements.txt

# After installing, import just like a built-in module:
# import requests
# import pandas as pd
# import numpy as np

print("pip installs packages from PyPI — the Python Package Index.")

import sys

# Python searches these locations in order:
# 1. The current script's directory
# 2. Directories in the PYTHONPATH environment variable
# 3. The Standard Library directories
# 4. Site-packages (where pip installs third-party packages)

print("Python searches these paths:")
for i, path in enumerate(sys.path, 1):
    print(f"  {i}. {path}")

# You can add a custom path at runtime:
# sys.path.append("/my/custom/modules")
# Now Python will also search that folder

# Find where a module is physically located on disk
import os
print("\nmath module location:", os.path.abspath(os.__file__))

def add(a, b):
    return a + b

def multiply(a, b):
    return a * b

def greet(name):
    return f"Hi, {name}!"

# This block ONLY runs when you execute this file directly:
#   python myfile.py
#
# It does NOT run when another file imports this module:
#   import myfile  ← __name__ is "myfile" here, not "__main__"

if __name__ == "__main__":
    print("Running as a standalone script")
    print("add(10, 20)     =", add(10, 20))
    print("multiply(3, 7)  =", multiply(3, 7))
    print("greet('Priya') =", greet("Priya"))