{"id":8499,"library":"pymongo-schema","title":"PyMongo Schema","description":"PyMongo Schema is a Python library designed to analyze MongoDB collections and databases, inferring their underlying schema structure. It helps users understand the document shapes within their MongoDB instances. As of version 0.4.2, it provides tools for generating schema definitions but does not enforce them. The project has a low release cadence, indicating stability but also less frequent updates.","status":"active","version":"0.4.2","language":"en","source_language":"en","source_url":"https://github.com/pajachiet/pymongo-schema","tags":["mongodb","schema","validation","pymongo","data-analysis"],"install":[{"cmd":"pip install pymongo-schema","lang":"bash","label":"Install PyMongo Schema"}],"dependencies":[{"reason":"Required to connect to MongoDB and interact with collections/databases.","package":"pymongo","optional":false}],"imports":[{"symbol":"Schema","correct":"from pymongo_schema import Schema"},{"symbol":"DBSchema","correct":"from pymongo_schema.db import DBSchema"}],"quickstart":{"code":"import os\nimport pymongo\nfrom pymongo_schema import Schema\nfrom pymongo_schema.db import DBSchema\n\n# Ensure MongoDB is running on localhost:27017\n# For authentication, use os.environ.get('MONGO_USER') etc.\nMONGO_URI = os.environ.get('MONGO_URI', 'mongodb://localhost:27017/')\nDB_NAME = 'pymongo_schema_test_db'\nCOLLECTION_NAME = 'my_test_collection'\n\ntry:\n    client = pymongo.MongoClient(MONGO_URI)\n    db = client[DB_NAME]\n    collection = db[COLLECTION_NAME]\n\n    # Insert some dummy data for schema inference\n    collection.insert_many([\n        {\"name\": \"Alice\", \"age\": 30, \"city\": \"New York\"},\n        {\"name\": \"Bob\", \"age\": 25, \"hobbies\": [\"reading\", \"coding\"]},\n        {\"name\": \"Charlie\", \"age\": 35, \"city\": \"London\", \"is_active\": True},\n        {\"name\": \"David\", \"country\": \"Canada\", \"age\": 40}\n    ])\n\n    print(f\"--- Schema for collection '{COLLECTION_NAME}' ---\")\n    collection_schema = Schema(collection)\n    schema_result = collection_schema.create_schema()\n    # print(schema_result) # Uncomment to see full schema\n    print(f\"Keys in collection schema: {list(schema_result.keys())}\")\n    print(f\"Name type: {schema_result.get('name', {}).get('type')}\")\n\n    print(f\"\\n--- Schema for database '{DB_NAME}' ---\")\n    db_schema = DBSchema(db)\n    db_schema_result = db_schema.create_schema()\n    # print(db_schema_result) # Uncomment to see full DB schema\n    print(f\"Collections in DB schema: {list(db_schema_result.keys())}\")\n\nexcept pymongo.errors.ConnectionFailure as e:\n    print(f\"Error: Could not connect to MongoDB at {MONGO_URI}. Please ensure MongoDB is running. Details: {e}\")\nexcept Exception as e:\n    print(f\"An unexpected error occurred: {e}\")\nfinally:\n    # Clean up the test database\n    if 'client' in locals() and client:\n        if DB_NAME in client.list_database_names():\n            client.drop_database(DB_NAME)\n            print(f\"\\nCleaned up database '{DB_NAME}'.\")\n        client.close()\n","lang":"python","description":"This quickstart demonstrates how to connect to a MongoDB instance, insert sample data into a temporary collection, and then use `pymongo_schema.Schema` to infer the schema of a single collection and `pymongo_schema.db.DBSchema` to infer the schema of an entire database. It includes basic error handling for MongoDB connection issues and cleans up the temporary database."},"warnings":[{"fix":"If you need schema validation, consider MongoDB's built-in schema validation features or other libraries that provide real-time validation.","message":"PyMongo Schema infers and describes the schema of your data; it does NOT validate or enforce schema rules at runtime. It's a reporting tool, not a validation engine.","severity":"gotcha","affected_versions":"All versions"},{"fix":"For performance-critical applications, consider running schema generation during off-peak hours or on a read-replica. You might also want to sample a subset of documents manually before passing them to the schema analyzer if precise schema is not strictly required.","message":"Generating a schema for very large collections or databases can be memory-intensive and slow, as it may need to sample or process a significant portion of the documents.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Ensure you are passing the correct PyMongo object type to the constructor: `Schema(my_collection)` or `DBSchema(my_database)`.","message":"There's a distinction between `pymongo_schema.Schema` and `pymongo_schema.db.DBSchema`. `Schema` expects a `pymongo.collection.Collection` object, while `DBSchema` expects a `pymongo.database.Database` object.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Test `pymongo-schema` against your specific `pymongo` and MongoDB versions. If you encounter issues with newer versions, you might need to pin `pymongo` to an older compatible version or consider alternative schema analysis tools.","message":"The library's development activity is low. While stable, it may not immediately support very recent `pymongo` versions or new MongoDB features, potentially leading to compatibility issues in the future.","severity":"gotcha","affected_versions":"0.4.x and potentially future versions"}],"env_vars":null,"last_verified":"2026-04-16T00:00:00.000Z","next_check":"2026-07-15T00:00:00.000Z","problems":[{"fix":"Run `pip install pymongo-schema` to install the library.","cause":"The 'pymongo-schema' library has not been installed in your Python environment.","error":"ModuleNotFoundError: No module named 'pymongo_schema'"},{"fix":"Pass a valid collection object: `schema = Schema(my_collection)`.","cause":"You are trying to instantiate `pymongo_schema.Schema` without passing a `pymongo.collection.Collection` object.","error":"TypeError: __init__ missing 1 required positional argument: 'collection'"},{"fix":"Pass a valid database object: `db_schema = DBSchema(my_database)`.","cause":"You are trying to instantiate `pymongo_schema.db.DBSchema` without passing a `pymongo.database.Database` object.","error":"TypeError: __init__ missing 1 required positional argument: 'db'"},{"fix":"Ensure your MongoDB server is running and accessible from where you're running your Python script. Verify the connection URI, host, and port. If authentication is required, include credentials in your `pymongo.MongoClient` URI or parameters.","cause":"The Python client could not establish a connection to your MongoDB server. This often means MongoDB is not running, is running on a different port/host, or has network restrictions.","error":"pymongo.errors.ConnectionFailure: Cannot connect to database"}]}