Ralat Mengendalikan dan Melog masuk dalam Python

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Lepaskan: 2024-08-13 06:40:03
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Perisian penulisan ialah aktiviti yang jauh dari sempurna. Dari idea kepada pengeluaran, ralat boleh muncul, dan dalam beberapa kes, kegagalan boleh berlaku dengan sengaja. Inilah sebabnya mengapa memahami pengendalian ralat dan log masuk dalam bahasa pengaturcaraan utama anda adalah kemahiran kritikal untuk dikuasai.

Ralat boleh berlaku dan situasi boleh timbul, tetapi cara anda bertindak balas—dengan persediaan dan maklumat tentang ralat itu—akan membawa anda keluar daripada situasi itu secepat mungkin.

Dalam artikel ini, kita akan belajar tentang pengendalian ralat dan log masuk dalam Python. Kami terutamanya akan meneroka pengecualian dan cara menggunakan pakej pengelogan Python untuk menulis pelbagai jenis log.

Jika anda berminat dengan lebih banyak kandungan yang meliputi topik seperti ini, langgan surat berita saya untuk mendapatkan kemas kini tetap tentang pengaturcaraan perisian, seni bina dan cerapan berkaitan teknologi.

Pengecualian dalam Python

Seperti dalam banyak bahasa pengaturcaraan lain, Python mempunyai keupayaan untuk menimbulkan pengecualian apabila ralat berlaku. Dalam pengaturcaraan, pengecualian ialah peristiwa yang berlaku semasa pelaksanaan program, mengganggu aliran biasa arahan.

Dalam Python, pengecualian ialah ralat yang dikesan semasa pelaksanaan. Apabila pengecualian berlaku, Python berhenti menjalankan kod dan mencari blok kod khas (cuba/kecuali blok) untuk mengendalikan ralat.

Berikut ialah beberapa pengecualian biasa yang boleh berlaku dalam program Python:

  • ZeroDivisionError: Berlaku apabila cuba membahagikan nombor dengan sifar.

  • FileNotFoundError: Berlaku apabila cuba membuka fail yang tidak wujud.

  • ValueError: Berlaku apabila cuba menukar rentetan kepada integer apabila rentetan itu tidak mewakili nombor.

  • IndexError: Berlaku apabila cuba mendapatkan semula elemen daripada senarai dengan indeks yang tidak wujud.

Terdapat banyak lagi pengecualian, dan Python memberi anda keupayaan untuk mencipta pengecualian anda sendiri jika anda memerlukan tingkah laku tersuai. Ini adalah ciri yang akan kami terokai kemudian dalam artikel.

Untuk mengendalikan pengecualian Python, anda perlu menangkapnya. Menangkap pengecualian memerlukan sintaks mudah yang dikenali sebagai cuba/kecuali. Mari terokai ini.

Cuba/Kecuali

Blok cuba/kecuali digunakan untuk mengendalikan pengecualian. Kod yang mungkin menimbulkan pengecualian diletakkan dalam blok cuba, dan jika pengecualian berlaku, blok kecuali dilaksanakan. Berikut ialah sintaks try/except dalam blok kod:

try:
    # Code that might raise an exception
    pass
except ExceptionType as e:
    # Code to handle the exception
    pass
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Kod yang berpotensi gagal diletakkan di dalam blok percubaan. Jika isu timbul, pelaksanaan program akan memasuki blok kecuali.

Berikut ialah carta alir yang menggambarkan cara cuba/kecuali berfungsi:

Error Handling and Logging in Python

Mari lihat bagaimana kita boleh mengendalikan pembahagian dengan sifar dengan pendekatan ini:

# Handling division by zero
try:
    result = 10 / 0
except ZeroDivisionError:
    print("Error: Cannot divide by zero.")
# The code will continue its execution
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Terdapat juga blok tambahan dalam sintaks cuba/kecuali, seperti else dan akhirnya:

try:
    # Code that might raise an exception
    pass
except ExceptionType as e:
    # Code to handle the exception
    pass
else:
    # Code to run if no exception is raised
    pass
finally:
    # Code that always runs, regardless of whether an exception was raised or not
    pass
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Blok ini adalah pilihan tetapi berfungsi untuk tujuan tertentu:

  • Sekat lain (Pilihan): Mengandungi kod yang dijalankan jika tiada pengecualian dibangkitkan dalam blok cuba. Ia berguna untuk kod yang sepatutnya hanya dijalankan apabila blok cuba berjaya.

  • akhirnya Sekat (Pilihan): Mengandungi kod yang sentiasa dijalankan, tidak kira sama ada pengecualian dinaikkan atau tidak. Ini biasanya digunakan untuk tindakan pembersihan, seperti menutup fail atau melepaskan sumber.

Berikut ialah contoh di mana kami mengendalikan penutupan fail akhirnya sekiranya berlaku ralat:

try:
    # Open the file
    file = open('example.txt', 'r')

    # Read from the file
    content = file.read()

    # Print file content (this will only execute if no exceptions are raised)
    print(content)
except FileNotFoundError as e:
    # Handle the specific exception
    print(f"Error: {e}")
except Exception as e:
    # Handle any other exceptions
    print(f"An unexpected error occurred: {e}")
else:
    # Code that runs if no exception was raised in the try block
    print("File read successfully.")
finally:
    # Ensure the file is closed, regardless of whether an exception was raised
    try:
        file.close()
        print("File closed.")
    except:
        # Handle the case where file was never opened (e.g., if open() failed)
        print("File was not opened or already closed.")
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Penafian: Contoh di atas menunjukkan pengendalian fail menggunakan cuba/kecuali/akhirnya untuk memastikan fail ditutup dengan betul walaupun ralat berlaku. Walau bagaimanapun, pendekatan ini tidak sesuai untuk operasi fail setiap hari. Dalam amalan, adalah disyorkan untuk menggunakan pernyataan dengan untuk pengendalian fail dalam Python. Pernyataan with secara automatik mengurus pembukaan dan penutupan fail, memastikan fail ditutup dengan betul selepas suitenya selesai, walaupun pengecualian berlaku.

Beginilah cara cubaan/kecuali berfungsi. Sekarang, mungkin terdapat kekeliruan dengan if/else. Bilakah anda harus menggunakan try/except, dan bilakah anda harus menggunakan if/else?

Apakah perbezaan antara cuba/kecuali dan jika/lain? Gunakan if/else apabila anda ingin menyemak keadaan yang anda boleh ramalkan dan kendalikan sebelum ia menyebabkan ralat, dan gunakan try/except untuk menangkap dan mengurus pengecualian yang berlaku semasa pelaksanaan kod, terutamanya untuk ralat yang anda tidak dapat jangkakan dengan mudah.

Dalam kes di bawah, jika/lain tidak berfungsi dengan betul:

filename = 'non_existent_file.txt'

if filename:  # This only checks if filename is not empty, not if the file exists
    # The following line will raise an exception if the file doesn't exist
    content = open(filename, 'r').read()  # This will crash if the file does not exist
    if content:
        print("File content exists:")
        print(content)
    else:
        print("File is empty.")
else:
    print("Filename is invalid.")
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Berikut ialah penyelesaian yang lebih baik dengan cuba/kecuali:

filename = 'non_existent_file.txt'

try:
    content = open(filename, 'r').read()
    if content:
        print("File content exists:")
        print(content)
    else:
        print("File is empty.")
except FileNotFoundError:
    print("Error: File not found.")
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In the solution above, the code attempts to open and read a file, checking if its content exists and printing it if present. If the file does not exist, it catches the FileNotFoundError and prints an error message, preventing the program from crashing.

As mentioned earlier in the article, Python allows for custom exceptions. Let’s learn more about it.

Creating Custom Exceptions in Python

In Python, you can define your own exceptions to handle specific error conditions in a more granular way. Custom exceptions are particularly useful in complex applications, such as fintech, where you may need to enforce business rules or handle specific error cases uniquely.

For example, in a fintech application, you might have a scenario where a wallet’s balance is checked against certain criteria. You may want to raise an exception if a wallet’s balance is not sufficient or does not conform to specific rules. Here’s how you can create and use a custom exception for this purpose:

# Define a custom exception
class WalletBalanceError(Exception):
    def __init__(self, message):
        self.message = message
        super().__init__(self.message)

# Function that checks wallet balance
def check_wallet_balance(wallet_balance, required_balance):
    if wallet_balance < required_balance:
        # Raise the custom exception with a specific message
        raise WalletBalanceError(f"Insufficient balance: Wallet balance of {wallet_balance} is less than the required {required_balance}.")

# Example usage
try:
    # Example wallet balance and required balance
    wallet_balance = 50
    required_balance = 100

    # Check if the wallet balance is sufficient
    check_wallet_balance(wallet_balance, required_balance)
except WalletBalanceError as e:
    # Handle the custom exception
    print(f"Error: {e}")
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In this example, we define a custom exception WalletBalanceError to handle cases where a wallet’s balance does not meet the required criteria. The check_wallet_balance function raises this exception if the wallet’s balance is insufficient, providing a clear and specific error message.

Custom exceptions in Python help make the code more readable and maintainable by clearly defining specific error conditions and handling them in a structured manner.

Now that we know how to handle errors in Python, it’s time to understand what to do when these errors occur. There are many strategies, but keeping a log of these errors can help identify issues later and correct them. In the next section of this article, we will explore logging.

Logging in Python

Logging helps developers track errors, events, or any runtime information in an application or program. Logging is an important and crucial aspect of software engineering as it has the ability to record everything that goes right or wrong in a post-development application. Logging is one of the most important pillars of monitoring.

Python provides a built-in module that can be used for logging

purposes. To use this module, the first thing to do is to import it.

import logging
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Then, configure the logger using the basicConfig method. You need to pass parameters to it, such as the log level, the format of the message, and the output file to save the log.

import logging

# Set up the basic configuration for logging
logging.basicConfig(filename='app.log', level=logging.DEBUG,
                    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')

# Log messages of various severity levels
logging.debug('This is a debug message')
logging.info('This is an info message')
logging.warning('This is a warning message')
logging.error('This is an error message')
logging.critical('This is a critical message')
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In the example above, logs will be written to a file called app.log. The log message format includes the timestamp, logger name, log level, and the actual message.

Python logging has different log levels that indicate the severity of an event or message. These log levels allow you to categorize and filter messages based on their importance. Here’s a breakdown of the common log levels in Python:

Log Levels

  1. DEBUG: Detailed information, typically of interest only when diagnosing problems. Used for debugging purposes during development.

  2. INFO: Confirmation that things are working as expected. This is the level you would use for normal operations and informational messages.

  3. WARNING: An indication that something unexpected happened, or indicative of some problem in the near future (e.g., "disk space low"). The software is still working as expected.

  4. ERROR: Due to a more serious problem, the software has not been able to perform some function. An error indicates a significant issue that needs attention.

  5. CRITICAL: A very serious error, indicating that the program itself may be unable to continue running. Critical errors often represent severe problems that require immediate action.

The logging module allows you to control which messages are recorded by setting the logging level. Only messages that are equal to or more severe than the set level will be logged. The default level is WARNING, meaning only WARNING, ERROR, and CRITICAL messages are logged unless you change the logging configuration.

In the code example above, we set the logging level to DEBUG, which means all log messages (DEBUG, INFO, WARNING, ERROR, and CRITICAL) will be recorded in the app.log file.

You can also create custom loggers, which give you more control over how messages are logged. Custom loggers allow you to set up multiple loggers with different configurations, such as different log levels, formats, or output destinations. This is particularly useful in larger applications where you need to separate logs for different modules or components.

Here’s how you can create and use a custom logger:

import logging

# Create a custom logger
logger = logging.getLogger('my_custom_logger')

# Set the log level for the custom logger
logger.setLevel(logging.DEBUG)

# Create a file handler to write logs to a file
file_handler = logging.FileHandler('custom.log')

# Create a console handler to output logs to the console
console_handler = logging.StreamHandler()

# Set log levels for the handlers
file_handler.setLevel(logging.ERROR)
console_handler.setLevel(logging.DEBUG)

# Create a formatter for log messages
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')

# Add the formatter to the handlers
file_handler.setFormatter(formatter)
console_handler.setFormatter(formatter)

# Add the handlers to the logger
logger.addHandler(file_handler)
logger.addHandler(console_handler)

# Log messages using the custom logger
logger.debug('This is a debug message')
logger.info('This is an info message')
logger.warning('This is a warning message')
logger.error('This is an error message')
logger.critical('This is a critical message')
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In this example, we create a custom logger named my_custom_logger. This logger writes ERROR and more severe messages to a file called custom.log, while DEBUG and more severe messages are output to the console. By customizing the loggers, you can tailor the logging behavior to fit the specific needs of your application.

Real-world Example: Logging in a Web Application

In a web application, logging plays a critical role in monitoring and maintaining the system’s health. For example, in a Flask web application, you might use logging to track incoming requests, errors, and performance metrics.

Here’s a basic example of how you can use logging in a Flask application:

from flask import Flask, request
import logging

app = Flask(__name__)

# Set up the basic configuration for logging
logging.basicConfig(filename='webapp.log', level=logging.INFO,
                    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')

@app.route('/')
def index():
    app.logger.info('Index page accessed')
    return 'Welcome to the Flask Web Application!'

@app.route('/error')
def error():
    app.logger.error('Error page accessed')
    raise ValueError('This is a simulated error')

if __name__ == '__main__':
    app.run(debug=True)
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In this Flask application, we configure logging to write logs to a file named webapp.log. Each time the index page is accessed, an informational log message is recorded. If the error page is accessed, an error log message is recorded, and a simulated error is raised.

By implementing logging in your web application, you can gain insights into user activity, system errors, and performance issues. This information is invaluable for debugging, troubleshooting, and optimizing the application.

Conclusion

Error handling and logging are essential aspects of software development, ensuring that applications run smoothly and that any issues are quickly identified and resolved.

In this article, we explored exceptions in Python, including how to handle them using try/except, and the importance of logging for tracking errors and events. We also discussed how to create custom exceptions and custom loggers to suit specific application needs.

By mastering error handling and logging, you’ll be better equipped to build robust and maintainable software that can gracefully handle unexpected situations and provide valuable insights into its operation.

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