Day 3: File Handling and Error Handling
Continuing from where we left off, today’s focus is on file handling and error management in Python. Understanding these concepts will help you manage data and handle unexpected scenarios gracefully. Let’s dive in!
File Handling in Python
Reading and Writing Files
1. Writing to a File
Use the open() function with mode 'w' (write) or 'a' (append) to save data to a file.
with open("user_log.txt", "w") as file: file.write("User logged in at 10:00 AM.\n")
2. Reading from a File
Use mode 'r' (read) to access data.
with open("user_log.txt", "r") as file: content = file.read() print(content)
Error Handling in Python
Using Try-Except for Error Handling
Error handling allows your program to respond to issues without crashing.
try: number = int(input("Enter a number: ")) print(f"The number you entered is {number}.") except ValueError: print("Invalid input! Please enter a valid number.")
Common Exceptions and How to Handle Them
- FileNotFoundError: Occurs when trying to read a non-existent file.
try: with open("missing_file.txt", "r") as file: content = file.read() except FileNotFoundError: print("The file does not exist.")
- ZeroDivisionError: Occurs when dividing by zero.
try: result = 10 / 0 except ZeroDivisionError: print("You cannot divide by zero!")
Project: User Input Logger
Build a small application that logs user inputs into a file.
try: with open("user_log.txt", "a") as file: while True: user_input = input("Enter something (type 'exit' to quit): ") if user_input.lower() == "exit": break file.write(user_input + "\n") except Exception as e: print(f"An error occurred: {e}")
Conclusion
Today, we covered:
- File handling: Reading and writing files.
- Error handling: Using try-except to manage exceptions gracefully.
- Practical project: Logging user inputs into a file for better understanding.
Practice these examples and try tweaking them for better insight. See you next time for more Python learning! ?
The above is the detailed content of Day File Handling and Error Handling. For more information, please follow other related articles on the PHP Chinese website!

Arraysarebetterforelement-wiseoperationsduetofasteraccessandoptimizedimplementations.1)Arrayshavecontiguousmemoryfordirectaccess,enhancingperformance.2)Listsareflexiblebutslowerduetopotentialdynamicresizing.3)Forlargedatasets,arrays,especiallywithlib

Mathematical operations of the entire array in NumPy can be efficiently implemented through vectorized operations. 1) Use simple operators such as addition (arr 2) to perform operations on arrays. 2) NumPy uses the underlying C language library, which improves the computing speed. 3) You can perform complex operations such as multiplication, division, and exponents. 4) Pay attention to broadcast operations to ensure that the array shape is compatible. 5) Using NumPy functions such as np.sum() can significantly improve performance.

In Python, there are two main methods for inserting elements into a list: 1) Using the insert(index, value) method, you can insert elements at the specified index, but inserting at the beginning of a large list is inefficient; 2) Using the append(value) method, add elements at the end of the list, which is highly efficient. For large lists, it is recommended to use append() or consider using deque or NumPy arrays to optimize performance.

TomakeaPythonscriptexecutableonbothUnixandWindows:1)Addashebangline(#!/usr/bin/envpython3)andusechmod xtomakeitexecutableonUnix.2)OnWindows,ensurePythonisinstalledandassociatedwith.pyfiles,oruseabatchfile(run.bat)torunthescript.

When encountering a "commandnotfound" error, the following points should be checked: 1. Confirm that the script exists and the path is correct; 2. Check file permissions and use chmod to add execution permissions if necessary; 3. Make sure the script interpreter is installed and in PATH; 4. Verify that the shebang line at the beginning of the script is correct. Doing so can effectively solve the script operation problem and ensure the coding process is smooth.

Arraysaregenerallymorememory-efficientthanlistsforstoringnumericaldataduetotheirfixed-sizenatureanddirectmemoryaccess.1)Arraysstoreelementsinacontiguousblock,reducingoverheadfrompointersormetadata.2)Lists,oftenimplementedasdynamicarraysorlinkedstruct

ToconvertaPythonlisttoanarray,usethearraymodule:1)Importthearraymodule,2)Createalist,3)Usearray(typecode,list)toconvertit,specifyingthetypecodelike'i'forintegers.Thisconversionoptimizesmemoryusageforhomogeneousdata,enhancingperformanceinnumericalcomp

Python lists can store different types of data. The example list contains integers, strings, floating point numbers, booleans, nested lists, and dictionaries. List flexibility is valuable in data processing and prototyping, but it needs to be used with caution to ensure the readability and maintainability of the code.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

WebStorm Mac version
Useful JavaScript development tools

Dreamweaver CS6
Visual web development tools

SublimeText3 Linux new version
SublimeText3 Linux latest version

SublimeText3 Mac version
God-level code editing software (SublimeText3)

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function
