Integrating Python with databases that require JDBC drivers, such as Informix, can be a challenge. Unlike databases with native Python connectors, JDBC-based connections often require complex configurations and a deep understanding of JVM, JDBC drivers, and connection libraries.

This is where wbjdbc comes in — a library designed to simplify this process, abstracting complexities and making the connection fast and efficient.

With the release of its new version, wbjdbc introduces features that make developers' lives even easier. Let's explore these new features and understand how they can positively impact your workflow.

🚀 Key Improvements in the New Version (v1.1.3)

✅ Automatic JVM Initialization

One of the biggest challenges when using JDBC in Python is the need to manually configure the JVM. Now, wbjdbc automatically detects and initializes the JVM, eliminating the need for manual adjustments in the development environment.

✅ Enhanced Support for Informix and MongoDB

The new version expands its compatibility, allowing connections not only with Informix but also with MongoDB. This broadens the range of applications and reduces the need for specific configurations for each database.

✅ Dependency and JDBC Driver Management

Now, the library takes care of pre-compiling dependencies, ensuring that the correct JDBC drivers are used without requiring developers to manually download or configure .jar files.

✅ Simplified Connection with Informix

wbjdbc now allows a more intuitive connection setup, reducing complexity in defining necessary parameters. The new format facilitates connection initialization with Informix databases in a direct and efficient way.

Example of a Connection to Informix 

from wbjdbc import connect_to_db

# Connection parameters
conn = connect_to_db(
    db_type=1,  # Accepts both strings and numbers to define the database type
    host="my-server",
    database="my_database",
    user="my_user",
    password="my_password",
    port=1526,
    server="my_informix_server"
)

# Checking the connection
if conn:
    print("✅ Connection successfully established!")
else:
    print("❌ Failed to connect to the database.")

Supported parameters:

  • db_type: Database type. Accepts numbers or strings:
    • 1 or "informix-sqli" (Informix)
    • 2 or "mysql" (MySQL)
    • 3 or "postgresql" (PostgreSQL)
  • host: Database server address.
  • database: Database name.
  • user: Username.
  • password: Access password.
  • port: Optional port (default varies by database type).
  • server: Server name for Informix databases.
  • extra_jars: List of additional JAR files if needed.
  • java_home: Alternative JAVA_HOME path (optional).
  • debug: Enables detailed debug logs in the console.
  • return: Active connection via JDBC or None if the connection fails.

✅ New fetchdh() Function: Structured Data Retrieval

Traditionally, executing SQL queries in Python using JDBC libraries returns data in lists of tuples, requiring developers to manually convert the results into a more readable format.

To solve this, wbjdbc introduces the fetchdh() function, which returns results as dictionaries, where keys correspond to column names.

Before (using fetchall()): 

cursor.execute("SELECT id, name, age FROM customers")
data = cursor.fetchall()
print(data)
# Output: [(1, 'John', 30), (2, 'Mary', 25)]

Now, with fetchdh(): 

cursor.execute("SELECT id, name, age FROM customers")
data = cursor.fetchdh()
print(data)
# Output: [{'id': 1, 'name': 'John', 'age': 30}, {'id': 2, 'name': 'Mary', 'age': 25}]

This approach simplifies data handling in Python, making the code cleaner and more intuitive.

🎯 Practical Applications

  • Ideal for legacy systems using Informix needing Python access without major rewrites.
  • Supports MongoDB for NoSQL storage via JDBC.
  • Saves setup time and reduces technical friction in data integration pipelines.

📌 Conclusion

The new version of wbjdbc removes technical barriers and reduces the time needed to configure JDBC connections in Python. Whether accessing Informix, MongoDB, or PostgreSQL, the library simplifies the process and enhances the developer experience.

If you work with data integration and want to test these new features, visit the official PyPI page:

PyPI - wbjdbc

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