# Management

`Document` subclasses utilizing the `Collection` trait (which `Queryable` inherits) gain class-level *active record* behaviours. Additionally, `Collection` inherits `Identified` as well, providing an automatically generated ObjectId field named `id` which maps to the stored `_id` key. There is a fairly substantial number of [collection metadata and calculated properties](https://github.com/marrow/mongo/tree/c047b93da447084919dd02c068a5548c59d1c8fe/guide/reference/trait/collection.md#metadata) available.

Before much can be done, it will be necessary to get a reference to a MongoDB connection or database object. Begin by importing the client object from the `pymongo` package.

```python
from pymongo import MongoClient
```

Then, open a connection to a MongoDB server, here, running locally. We can save some space by defining the database to utilize at the same time, and requesting a handle to the default database back without needing to refer to it by name a second time.

```python
client = MongoClient('mongodb://localhost/test')
db = client.get_database()
```

Binding our `Account` class to a database will look up the collection name to use from the `__collection__` attribute. Alternatively you could bind directly to a specific collection. Either way, binding will automatically apply the metadata options for data access and validation and enable the `get_collection` method to provide you the correct, configured object.

```python
Account.bind(db)
```

Two class methods are provided for collection management requiring awareness of our metadata: `create_collection` and `create_indexes`. Creating the collection will create any declared indexes automatically by default. For other collection-level management operations it is recommended to utilize `get_collection` and issue calls to the PyMongo API directly.

```python
Account.create_collection()
```

With the class bound you can now more easily interact with your documents in the collection.


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