Integration Between `wborm` and `wbjdbc`¶

Why Use `wborm` Together with `wbjdbc`?¶

1. Native and Direct Integration¶

wborm was designed to work directly with the connection created by wbjdbc, without needing to adapt cursors, drivers, or perform additional mappings.

from wbjdbc import connect_to_db
from my_model import Cliente

conn = connect_to_db(...)
Cliente._connection = conn
clientes = Cliente.filter(idade=25).all()

2. Full Focus on JDBC and Informix Ecosystem¶

wbjdbc solves a core problem: connecting Python to legacy databases via JDBC, like Informix, which usually requires Java.
wborm handles the next step: querying and manipulating those data through an ORM, without writing raw SQL all the time.

Together, they create a natural flow:

JDBC → wbjdbc → connection → wborm → model/table

3. Safety and Abstraction Without Losing Control¶

wbjdbc manages JVM, classpath, .jar files, authentication, etc.
wborm abstracts SQL reading and writing safely: requires confirm=True, validates fields, enforces WHERE on deletes, etc.
Neither tries to hide too much of what’s going on.

You gain productivity without losing SQL clarity.

4. Perfect for ETL, BI, and Data Transformation Workflows¶

With wbjdbc, you can already run JDBC queries from Python. But with wborm, you can:

Map tables as classes
Use .filter() and .select() without worrying about raw SQL strings
Integrate directly with Pandas or Spark

Example using DataFrame:

from wborm.core import Model
import pandas as pd

df = pd.DataFrame([c.to_dict() for c in Cliente.all()])

5. Compatibility with Informix Advanced Features¶

wborm respects Informix-specific behavior such as:

SKIP and FIRST immediately after SELECT
Transaction-level locks (BEGIN WORK / COMMIT WORK)
Prevents updates or deletes without proper WHERE clauses

Things that generic ORMs often handle poorly for Informix-like databases.

Comparison Table¶

Feature	wbjdbc	wborm
JVM Initialization	✅	❌
Loads `.jar` and drivers	✅	❌
Creates JDBC connection	✅	❌
Executes SQL	✅ (`cursor.execute`)	✅ (`.raw_sql()` or `.filter()`)
ORM with validation and models	❌	✅
Automatic model generation	❌	✅ (`generate_model`)

Conclusion¶

If you work with Informix, DB2, Oracle, or any other JDBC-compatible database — the wbjdbc + wborm combo offers:

Reliable and automated Java-based connection
Lightweight and powerful ORM with validation and safety
Seamless usage with Pandas, Spark, and any Python tool

Harness the power of JDBC with the simplicity of Python!

Integration Between wborm and wbjdbc¶

Why Use wborm Together with wbjdbc?¶