In software development, generating non-duplicate IDs is a common requirement. Whether it is creating a unique identifier in the database or generating a unique session ID in the system, ensuring the uniqueness of the ID is crucial. Python provides a variety of ways to generate non-duplicate IDs. This article will introduce several common and practical methods, and will explain them in combination with code and cases.
1. Use UUID
UUID (Universally Unique Identifier) is a software construction standard and is adopted by the Distributed Computing Environment (DCE) of the Open Source Software Foundation (OSF). The purpose of UUID is to enable all elements in a distributed system to have unique identification information without being distributed through the central control end.
In Python, the UUID module can be used to generate a UUID. UUID version 1 is based on time and nodes (usually MAC addresses), and version 4 is based on random numbers. Since the UUID of version 4 does not depend on any external information, it is usually used to generate a unique identifier.
import uuid # Generate a UUID4 (UUID based on random numbers)unique_id = uuid.uuid4() print(unique_id)
The output will be a string similar to 550e8400-e29b-41d4-a716-446655440000. This UUID is unique globally and is therefore ideal as a non-duplicate ID.
2. Use hashlib to generate a unique ID
Although the UUID is already unique enough, in some cases you may want to generate a unique ID based on certain inputs (such as username, email, etc.). At this time, the hashlib library can be used to calculate the hash value of the input data and use it as a unique ID.
import hashlib
def generate_hash_id(input_string):
# Use SHA-256 hashing algorithm sha_signature = hashlib.sha256(input_string.encode()).hexdigest()
# Take the first 16 bits of the hash value as a unique ID (the length can be adjusted as needed) unique_id = sha_signature[:16]
return unique_id
# Exampleusername = "john_doe"
unique_id = generate_hash_id(username)
print(unique_id)
In this example, we generate a unique ID based on the username. Since the hash function's collision probability is very low (almost negligible for SHA-256), this ID is unique in most cases.
3. Use the database to increase the ID
If you are using a relational database (such as MySQL, PostgreSQL, etc.), you can use the database's self-increment ID function to generate non-duplicate IDs. When creating a table, you can specify an autoincrement field as the primary key.
CREATE TABLE users (
id INT AUTO_INCREMENT PRIMARY KEY,
username VARCHAR(255) NOT NULL,
email VARCHAR(255) NOT NULL
);
When inserting a new record, it is not necessary to explicitly specify the value of the ID field, and the database will automatically assign it a unique self-additive value.
In Python, you can use database connection libraries (such as pymysql, psycopg2, etc.) to execute SQL statements and obtain the self-increment ID.
import pymysql
# Connect to the databaseconnection = (host='localhost', user='root', password='password', db='test')
try:
with () as cursor:
# Insert a new record sql = "INSERT INTO users (username, email) VALUES (%s, %s)"
(sql, ("john_doe", "john_doe@"))
# Get the self-increasing ID ()
last_id =
print(f"Inserted ID: {last_id}")
finally:
()In this example, we insert a new record into the users table and obtain the self-increment ID automatically generated by the database.
4. Use Redis's INCR command
Redis is a high-performance key-value storage database that provides a variety of data types and rich operation commands. Among them, the INCR command is used to increment the value of the stored numeric key by 1. If the key does not exist, then initialize to 0 and add 1. This feature makes it very suitable for generating globally unique incremental IDs.
import redis
# Connect to Redis serverr = (host='localhost', port=6379, db=0)
# Generate a unique incremental IDunique_id = ("unique_id_key")
print(unique_id)
In this example, we connect to the Redis server and use the INCR command to generate a unique incremental ID. Each time the incr method is called, it increments the value of the key unique_id_key by 1 and returns the new value as a unique ID.
5. Use Snowflake Algorithm (Snowflake)
The Snowflake Algorithm is a distributed unique ID generation algorithm that is open sourced by Twitter. The ID it generates is a 64-bit integer that contains information such as timestamp, machine ID, data center ID, and serial number. Since this information is unique globally, the generated ID is also unique.
In Python, you can use third-party libraries such as python-snowflake to implement the snowflake algorithm.
pip install python-snowflake python from import Client # Configure the Snowflake Algorithm Clientclient = Client(1, 1) # worker_id and datacenter_id need to be configured according to actual situation # Generate a unique IDunique_id = client.get_guid() print(unique_id)
Note: In the above code, worker_id and datacenter_id are two important parameters in the snowflake algorithm, which are used to distinguish different machines or data centers. In practical applications, you need to configure these parameters according to the deployment environment. Meanwhile, the python-snowflake library may not be the latest or most popular implementation, so make sure to check its documentation and update logs before using it.
6. Summary
This article introduces several common methods for generating non-repetitive IDs in Python, including using UUID, hashlib to generate hash IDs, database self-increment IDs, Redis's INCR commands, and snowflake algorithms. Each method has its applicable scenarios and advantages and disadvantages. When choosing a specific method, please weigh your actual needs and environment.
This is the end of this article about the method of generating non-repetitive IDs in Python. For more related content on Python, please search for my previous articles or continue browsing the related articles below. I hope everyone will support me in the future!