Skip to main content

Time Module in Python

 


Learning Sections         show

Time Module in Python

Introduction

The time module in Python provides various functions to handle time-related tasks. It allows you to work with time in different ways, such as fetching the current time, measuring execution time, and formatting time representations.

Basic Functions

Here are some basic functions provided by the time module:

  • time.time(): Returns the current time in seconds since the Epoch (January 1, 1970, 00:00:00 UTC).
  • time.sleep(secs): Suspends execution for the given number of seconds.
  • time.ctime([secs]): Converts a time expressed in seconds since the Epoch to a string representing local time.
  • time.localtime([secs]): Converts a time expressed in seconds since the Epoch to a struct_time in local time.
  • time.gmtime([secs]): Converts a time expressed in seconds since the Epoch to a struct_time in UTC.
Example Usage

Let's look at some examples to understand how these functions work.


import time

# Get the current time in seconds since the Epoch
current_time = time.time()
print("Current time:", current_time)

# Suspend execution for 2 seconds
time.sleep(2)

# Convert current time to a readable string
readable_time = time.ctime(current_time)
print("Readable time:", readable_time)

# Convert current time to struct_time in local time
local_time = time.localtime(current_time)
print("Local time:", local_time)

# Convert current time to struct_time in UTC
utc_time = time.gmtime(current_time)
print("UTC time:", utc_time)
Formatting Time

The time module also provides functions to format and parse time representations.

  • time.strftime(format, [t]): Converts a struct_time or tuple representing a time to a string as specified by the format argument.
  • time.strptime(string, format): Parses a string representing a time according to a format.
Example Usage of Formatting Functions

import time

# Format current local time as a string
formatted_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
print("Formatted time:", formatted_time)

# Parse a string to struct_time
time_string = "2024-05-27 10:30:00"
parsed_time = time.strptime(time_string, "%Y-%m-%d %H:%M:%S")
print("Parsed time:", parsed_time)
Measuring Execution Time

The time module can be used to measure the execution time of code snippets using time.time() or time.perf_counter() for higher precision.


import time

# Measure execution time using time.time()
start_time = time.time()
# Some code to measure
end_time = time.time()
execution_time = end_time - start_time
print("Execution time:", execution_time)

# Measure execution time using time.perf_counter()
start_perf_time = time.perf_counter()
# Some code to measure
end_perf_time = time.perf_counter()
perf_execution_time = end_perf_time - start_perf_time
print("Performance execution time:", perf_execution_time)
Labels:

Popular posts from this blog

Learn Python

  Learning Sections Introduction to Python Comment, escape sequence and print statement in Python Variables and Data Types in Python Typecasting in Python User input in Python String slicing and operations on string in Python String methods in Python If else conditional statements in Python Match case statement in Python For loops in Python While loops in Python Break and continue statement in Python Functions in Python Function Arguments in Python introduction to lists in Python List methods in Python Tuples in Python Operations on tuple in Python f strings in Python Docstrings in Python Recursion in Python Sets in Python Set methods in Python Dictionaries in Python for Loop with else in Python Exception Handling in Python Finally keyword in Python Raising custom errors in Python Short hand if else statements Enumerate Function in Python Virtual Environment in Python How import works in Python if __nam...
Read more

MultiProcessing in Python

  Learning Sections          show MultiProcessing in Python Multiprocessing in Python involves using the multiprocessing module to run multiple processes concurrently, taking advantage of multiple CPU cores. This module provides a higher level of concurrency than threading and is especially useful for CPU-bound tasks. Creating Processes You can create and start a new process by using the multiprocessing module: import multiprocessing def print_numbers (): for i in range ( 10 ): print ( i ) p1 = multiprocessing.Process ( target = print_numbers ) p1 . start () p1 . join () # Wait for the process to complete Using Process Pools The multiprocessing module provides a Pool class, which allows you to manage a pool of worker processes: from multiprocessing import Pool def square ( n ): return n * n with Pool ( 4 ) as pool : result = pool.map ( square , range (...
Read more

Match Case Statement in Python

  Learning Sections      show Match-Case Statements In Python 3.10 and later, the match-case statement was introduced as a way to perform pattern matching, similar to switch-case statements in other programming languages. It allows you to check the value of a variable against multiple patterns and execute corresponding blocks of code. Basic Match-Case Statement The match statement is followed by an expression and several case clauses. Each case specifies a pattern and an action to be taken if the pattern matches the value of the expression. # Basic match-case statement example command = "start" match command : case "start" : print ( "Starting..." ) case "stop" : print ( "Stopping..." ) case "pause" : print ( "Pausing..." ) case _: print ( "Unknown command" ) Matching Multiple Patterns Using the pipe sy...
Read more