Welcome to the next pikoTutorial!
In the previous article, we learned how to use Python for symmetric data encryption. The final example is about converting a user-supplied password directly into an encryption key. While it works, it's not a recommended practice. Today you will learn the recommended method, the key derivation function.
Key derivation function
Below you can find an extended example of how to use the PBKDF2HMAC key derivation function in Python:
# 导入Base64编码的实用程序 import base64 # 导入Fernet from cryptography.fernet import Fernet from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC from cryptography.hazmat.primitives import hashes # 导入getpass用于安全输入读取 from getpass import getpass # 读取纯文本密码 plain_text_password: str = getpass(prompt='密码:') # 将密码转换为字节 password_bytes = plain_text_password.encode('utf-8') # 演示的一些salt值,在实践中使用安全的随机值 salt = b'\x00' * 16 # 使用PBKDF2HMAC从密码派生安全密钥 kdf = PBKDF2HMAC( algorithm=hashes.SHA256(), length=32, salt=salt, iterations=100000 ) # 使用Base64编码派生的密钥 key = base64.urlsafe_b64encode(kdf.derive(password_bytes)) # 使用派生的密钥创建一个Fernet实例 fernet = Fernet(key) # 要加密的数据 data = b'一些秘密数据' # 加密数据 encrypted_data = fernet.encrypt(data) # 解密数据 decrypted_data = fernet.decrypt(encrypted_data) # 打印解密后的数据 print(f"解密文本:{decrypted_data.decode()}")
Not only are keys created this way more secure, but they no longer require plain text passwords to be exactly 32 bytes long.
Note for beginners: Remember that salt is necessary to decrypt data!
The above is the detailed content of Key derivation function with Python. For more information, please follow other related articles on the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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