Free Django Model Generator

This tool helps you automatically generate Django model code from a JSON-formatted database schema, simplifying the initial setup of your Django models and saving development time. It's perfect for accelerating development workflows, minimizing manual coding errors, and ensuring consistency across your Django projects.

Simply paste your database schema in JSON format into the textarea provided and click "Generate Model". The tool will instantly provide you with the Django model code corresponding to your schema.

Yes, the tool supports generating models that include foreign key relationships. Ensure your JSON schema accurately represents these relationships for the best results. It, however, does not support many-to-many relationships as of now.

While there's no strict limit, very large schemas might impact the tool's performance. If you encounter any issues, try breaking your schema into smaller segments.

There are several ways to create a database schema in JSON format:

Many SQL database management systems come with tools that can export table definitions to various formats. These tools often have options to export schemas directly to JSON or to formats that can be easily converted to JSON (like SQL or CSV). For example, PostgreSQL has pg_dump with options to output in custom formats, which can then be processed into JSON.

SQL to JSON Converters:

Use online converters or command-line tools that take SQL CREATE TABLE statements and convert them to JSON. This requires exporting the schema as SQL statements first.

Custom Scripts:

Write a custom script in a language like Python that connects to the database, retrieves the schema information using queries (like INFORMATION_SCHEMA tables in SQL databases), and then formats that information as JSON. Python libraries such as psycopg2 for PostgreSQL or PyMySQL for MySQL can be used to connect to the database and execute schema retrieval commands.

                        
import psycopg2
import json

# Connect to your PostgreSQL database
conn = psycopg2.connect(dbname="your_dbname", user="your_user", password="your_password", host="your_host")
cur = conn.cursor()

# Query to get table structure (simplified)
cur.execute("""
SELECT table_name, column_name, data_type
FROM information_schema.columns
WHERE table_schema = 'public'
""")

schema = {}
for table_name, column_name, data_type in cur.fetchall():
    if table_name not in schema:
        schema[table_name] = []
    schema[table_name].append({"column_name": column_name, "data_type": data_type})

# Convert the schema dictionary to JSON
schema_json = json.dumps(schema, indent=4)

# Output or save the JSON
print(schema_json)

# Don't forget to close the connection
cur.close()
conn.close()