Python - Working Code Sample for Datetime and Time Modules

Working Code Sample for Datetime and Time Modules in Python

The Python standard library offers robust support for handling dates, times, and time intervals through two primary modules: datetime and time. These modules provide essential functionality for dealing with real-world problems involving scheduling, logging, time measurement, delays, and more. In this document, we will explore extensive code examples for both modules, demonstrating their individual capabilities as well as their interoperability in various contexts.

Introduction to datetime and time Modules

Importing Required Modules

import datetime
import time

The datetime module includes classes like datetime, date, time, timedelta, and timezone. The time module provides low-level functions to interact with the system time, sleep, and measure durations.

Working with datetime Module

Getting Current Date and Time

from datetime import datetime

current_time = datetime.now()
print("Current date and time:", current_time)

Creating Specific datetime Object

custom_dt = datetime(2024, 12, 25, 10, 30, 45)
print("Custom datetime:", custom_dt)

Accessing Individual Components

print("Year:", custom_dt.year)
print("Month:", custom_dt.month)
print("Day:", custom_dt.day)
print("Hour:", custom_dt.hour)
print("Minute:", custom_dt.minute)
print("Second:", custom_dt.second)

Formatting datetime Objects

formatted = current_time.strftime('%Y-%m-%d %H:%M:%S')
print("Formatted datetime:", formatted)

Parsing Strings into datetime Objects

dt_str = '2025-06-27 15:45:00'
parsed_dt = datetime.strptime(dt_str, '%Y-%m-%d %H:%M:%S')
print("Parsed datetime:", parsed_dt)

Comparing datetime Objects

dt1 = datetime(2025, 6, 27)
dt2 = datetime(2025, 6, 30)

print("Is dt1 before dt2?", dt1 < dt2)

Adding/Subtracting Time with timedelta

from datetime import timedelta

now = datetime.now()
future = now + timedelta(days=10)
past = now - timedelta(days=5)

print("10 days in the future:", future)
print("5 days in the past:", past)

Calculating the Difference Between Dates

start_date = datetime(2025, 6, 1)
end_date = datetime(2025, 6, 27)
diff = end_date - start_date
print("Days difference:", diff.days)

Replacing DateTime Components

replaced = current_time.replace(hour=20, minute=0)
print("Replaced datetime:", replaced)

Weekday and ISO Calendar

print("Weekday (0=Monday):", current_time.weekday())
print("ISO Weekday (1=Monday):", current_time.isoweekday())
print("ISO Calendar:", current_time.isocalendar())

Using ISO Format

print("ISO Format:", current_time.isoformat())

Working with date Class

Creating and Accessing date

from datetime import date

today = date.today()
print("Today:", today)

specific_date = date(2023, 5, 15)
print("Specific Date:", specific_date)

Comparing Dates

print("Is today > specific_date?", today > specific_date)

Getting Min and Max date

print("Minimum date:", date.min)
print("Maximum date:", date.max)

Working with time Class

Creating a time Object

from datetime import time

t = time(14, 30, 45)
print("Time:", t)

Accessing Time Components

print("Hour:", t.hour)
print("Minute:", t.minute)
print("Second:", t.second)
print("Microsecond:", t.microsecond)

Working with time Module

Getting Current Time in Seconds Since Epoch

epoch_time = time.time()
print("Time since epoch:", epoch_time)

Converting Epoch to Local Time

local_time = time.localtime(epoch_time)
print("Local time struct:", local_time)

Formatting time with asctime

print("Readable format:", time.asctime(local_time))

Using strftime in time Module

formatted_time = time.strftime('%Y-%m-%d %H:%M:%S', local_time)
print("Formatted:", formatted_time)

Using sleep for Delay

print("Sleeping for 2 seconds...")
time.sleep(2)
print("Awake now.")

Measuring Execution Time with perf_counter

start = time.perf_counter()
for _ in range(1000000):
    pass
end = time.perf_counter()
print("Time taken:", end - start)

Datetime and Timezone Handling

Using timezone from datetime Module

from datetime import timezone, timedelta

utc_dt = datetime.now(timezone.utc)
print("UTC Time:", utc_dt)

ist = timezone(timedelta(hours=5, minutes=30))
ist_time = utc_dt.astimezone(ist)
print("IST Time:", ist_time)

Using pytz for Timezone Handling

import pytz

utc = pytz.utc
india = pytz.timezone("Asia/Kolkata")
now_utc = datetime.now(utc)
now_india = now_utc.astimezone(india)

print("UTC Time:", now_utc)
print("India Time:", now_india)

Real World Examples

Example 1: Countdown Timer

future_event = datetime(2025, 12, 31, 23, 59, 59)
now = datetime.now()
remaining = future_event - now
print("Time left:", remaining)

Example 2: Age Calculator

dob = date(1990, 7, 1)
today = date.today()
age = today.year - dob.year - ((today.month, today.day) < (dob.month, dob.day))
print("Age:", age)

Example 3: Log Timestamps

def log_event(message):
    timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
    print(f"[{timestamp}] {message}")

log_event("Program started")
time.sleep(1)
log_event("Operation completed")

Example 4: Business Days Calculator

def business_days(start_date, end_date):
    day_count = 0
    while start_date <= end_date:
        if start_date.weekday() < 5:
            day_count += 1
        start_date += timedelta(days=1)
    return day_count

start = date(2025, 6, 1)
end = date(2025, 6, 30)
print("Business days:", business_days(start, end))

Example 5: Scheduler with Delays

def scheduler():
    print("Task will run in 5 seconds...")
    time.sleep(5)
    print("Task executed at:", datetime.now())

scheduler()

Working with UTC and Conversion

utc_now = datetime.utcnow()
print("UTC now:", utc_now)

local_dt = utc_now.replace(tzinfo=timezone.utc).astimezone()
print("Local time:", local_dt)

Creating List of Dates

start = date(2025, 1, 1)
date_list = [start + timedelta(days=i) for i in range(10)]
for d in date_list:
    print(d)

The Python datetime and time modules offer versatile tools to handle nearly every time-related programming need. From simple tasks like delays and timestamp logging to complex date arithmetic and timezone-aware datetime manipulation, these libraries cover a broad spectrum. This tutorial presented comprehensive, real-world working code examples to help you understand and apply both modules effectively in your projects.

Mastering these modules is particularly useful in domains such as data science (timestamps in data), backend development (logging and session expiration), DevOps (scheduling), and more. You can now confidently format, calculate, convert, and control time in Python applications of all sizes.