Advanced Usage

Remarks on Storage

Before we dive deeper into the usage of TinyDB, we should stop for a moment and discuss how TinyDB stores data.

To convert your data to a format that is writable to disk TinyDB uses the Python JSON module by default. It’s great when only simple data types are involved but it cannot handle more complex data types like custom classes. On Python 2 it also converts strings to Unicode strings upon reading (described here).

If that causes problems, you can write your own storage, that uses a more powerful (but also slower) library like pickle or PyYAML.

Alternative JSON library

As already mentioned, the default storage relies upon Python’s JSON module. To improve performance, you can install ujson , an extremely fast JSON implementation. TinyDB will auto-detect and use it if possible.

Queries

With that out of the way, let’s start with TinyDB’s rich set of queries. There are two main ways to construct queries. The first one resembles the syntax of popular ORM tools:

>>> from tinydb import Query
>>> User = Query()
>>> db.search(User.name == 'John')

As you can see, we first create a new Query object and then use it to specify which fields to check. Searching for nested fields is just as easy:

>>> db.search(User.birthday.year == 1990)

Not all fields can be accessed this way if the field name is not a valid Python identifier. In this case, you can switch to array indexing notation:

>>> # This would be invalid Python syntax:
>>> db.search(User.country-code == 'foo')
>>> # Use this instead:
>>> db.search(User['country-code'] == 'foo')

The second, traditional way of constructing queries is as follows:

>>> from tinydb import where
>>> db.search(where('field') == 'value')

Using where('field') is a shorthand for the following code:

>>> db.search(Query()['field'] == 'value')

Accessing nested fields with this syntax can be achieved like this:

>>> db.search(where('birthday').year == 1900)
>>> db.search(where('birthday')['year'] == 1900)

Advanced queries

In the Getting Started you’ve learned about the basic comparisons (==, <, >, ...). In addition to these TinyDB supports the following queries:

>>> # Existence of a field:
>>> db.search(User.name.exists())
>>> # Regex:
>>> # Full item has to match the regex:
>>> db.search(User.name.matches('[aZ]*'))
>>> # Any part of the item has to match the regex:
>>> db.search(User.name.search('b+'))
>>> # Custom test:
>>> test_func = lambda s: s == 'John'
>>> db.search(User.name.test(test_func))
>>> # Custom test with parameters:
>>> def test_func(val, m, n):
>>>     return m <= val <= n
>>> db.search(User.age.test(test_func, 0, 21))
>>> db.search(User.age.test(test_func, 21, 99))

When a field contains a list, you also can use the any and all methods. There are two ways to use them: with lists of values and with nested queries. Let’s start with the first one. Assuming we have a user object with a groups list like this:

>>> db.insert({'name': 'user1', 'groups': ['user']})
>>> db.insert({'name': 'user2', 'groups': ['admin', 'user']})
>>> db.insert({'name': 'user3', 'groups': ['sudo', 'user']})

Now we can use the following queries:

>>> # User's groups include at least one value from ['admin', 'sudo']
>>> db.search(User.groups.any(['admin', 'sudo']))
[{'name': 'user2', 'groups': ['admin', 'user']},
 {'name': 'user3', 'groups': ['sudo', 'user']}]
>>>
>>> # User's groups include all values from ['admin', 'user']
>>> db.search(User.groups.all(['admin', 'user']))
[{'name': 'user2', 'groups': ['admin', 'user']}]

In some cases you may want to have more complex any/all queries. This is where nested queries come in as helpful. Let’s set up a table like this:

>>> Group = Query()
>>> Permission = Query()
>>> groups = db.table('groups')
>>> groups.insert({'name': 'user', 'permissions': [{'type': 'read'}]})
>>> groups.insert({'name': 'sudo', 'permissions': [{'type': 'read'}, {'type': 'sudo'}]})
>>> groups.insert({'name': 'admin', 'permissions': [{'type': 'read'}, {'type': 'write'}, {'type': 'sudo'}]})

Now let’s search this table using nested any/all queries:

>>> # Group has a permission with type 'read'
>>> groups.search(Group.permissions.any(Permission.type == 'read'))
[{'name': 'user', 'permissions': [{'type': 'read'}]},
 {'name': 'sudo', 'permissions': [{'type': 'read'}, {'type': 'sudo'}]},
 {'name': 'admin', 'permissions': [{'type': 'read'}, {'type': 'write'}, {'type': 'sudo'}]}]
>>> # Group has ONLY permission 'read'
>>> groups.search(Group.permissions.all(Permission.type == 'read'))
[{'name': 'user', 'permissions': [{'type': 'read'}]}]

As you can see, any tests if there is at least one document matching the query while all ensures all documents match the query.

Query modifiers

TinyDB also allows you to use logical operations to modify and combine queries:

>>> # Negate a query:
>>> db.search(~ User.name == 'John')
>>> # Logical AND:
>>> db.search((User.name == 'John') & (User.age <= 30))
>>> # Logical OR:
>>> db.search((User.name == 'John') | (User.name == 'Bob'))

Note

When using & or |, make sure you wrap the conditions on both sides with parentheses or Python will mess up the comparison.

Recap

Let’s review the query operations we’ve learned:

Queries
Query().field.exists() Match any document where a field called field exists
Query().field.matches(regex) Match any document with the whole field matching the regular expression
Query().field.search(regex) Match any document with a substring of the field matching the regular expression
Query().field.test(func, *args) Matches any document for which the function returns True
Query().field.all(query | list) If given a query, matches all documents where all documents in the list field match the query. If given a list, matches all documents where all documents in the list field are a member of the given list
Query().field.any(query | list) If given a query, matches all documents where at least one document in the list field match the query. If given a list, matches all documents where at least one documents in the list field are a member of the given list
Logical operations on queries
~ query Match documents that don’t match the query
(query1) & (query2) Match documents that match both queries
(query1) | (query2) Match documents that match at least one of the queries

Handling Data

Next, let’s look at some more ways to insert, update and retrieve data from your database.

Inserting data

As already described you can insert an document using db.insert(...). In case you want to insert multiple documents, you can use db.insert_multiple(...):

>>> db.insert_multiple([{'name': 'John', 'age': 22}, {'name': 'John', 'age': 37}])
>>> db.insert_multiple({'int': 1, 'value': i} for i in range(2))

Updating data

Sometimes you want to update all documents in your database. In this case, you can leave out the query argument:

>>> db.update({'foo': 'bar'})

When passing a dict to db.update(fields, query), it only allows you to update an document by adding or overwriting its values. But sometimes you may need to e.g. remove one field or increment its value. In that case you can pass a function instead of fields:

>>> from tinydb.operations import delete
>>> db.update(delete('key1'), User.name == 'John')

This will remove the key key1 from all matching documents. TinyDB comes with these operations:

  • delete(key): delete a key from the document
  • increment(key): increment the value of a key
  • decrement(key): decrement the value of a key
  • add(key, value): add value to the value of a key (also works for strings)
  • subtract(key, value): subtract value from the value of a key
  • set(key, value): set key to value

Of course you also can write your own operations:

>>> def your_operation(yodocumentur_arguments):
...     def transform(doc):
...         # do something with the document
...         # ...
...     return transform
...
>>> db.update(your_operation(arguments), query)

Retrieving data

There are several ways to retrieve data from your database. For instance you can get the number of stored documents:

>>> len(db)
3

Then of course you can use db.search(...) as described in the Getting Started section. But sometimes you want to get only one matching document. Instead of using

>>> try:
...     result = db.search(User.name == 'John')[0]
... except IndexError:
...     pass

you can use db.get(...):

>>> db.get(User.name == 'John')
{'name': 'John', 'age': 22}
>>> db.get(User.name == 'Bobby')
None

Caution

If multiple documents match the query, probably a random one of them will be returned!

Often you don’t want to search for documents but only know whether they are stored in the database. In this case db.contains(...) is your friend:

>>> db.contains(User.name == 'John')

In a similar manner you can look up the number of documents matching a query:

>>> db.count(User.name == 'John')
2

Recap

Let’s summarize the ways to handle data:

Inserting data
db.insert_multiple(...) Insert multiple documents
Updating data
db.update(operation, ...) Update all matching documents with a special operation
Retrieving data
len(db) Get the number of documents in the database
db.get(query) Get one document matching the query
db.contains(query) Check if the database contains a matching document
db.count(query) Get the number of matching documents

Using Document IDs

Internally TinyDB associates an ID with every document you insert. It’s returned after inserting an document:

>>> db.insert({'name': 'John', 'age': 22})
3
>>> db.insert_multiple([{...}, {...}, {...}])
[4, 5, 6]

In addition you can get the ID of already inserted documents using document.doc_id. This works both with get and all:

>>> el = db.get(User.name == 'John')
>>> el.doc_id
3
>>> el = db.all()[0]
>>> el.doc_id
12

Different TinyDB methods also work with IDs, namely: update, remove, contains and get. The first two also return a list of affected IDs.

>>> db.update({'value': 2}, doc_ids=[1, 2])
>>> db.contains(doc_ids=[1])
True
>>> db.remove(doc_ids=[1, 2])
>>> db.get(doc_id=3)
{...}

Recap

Let’s sum up the way TinyDB supports working with IDs:

Getting an document’s ID
db.insert(...) Returns the inserted document’s ID
db.insert_multiple(...) Returns the inserted documents’ ID
document.doc_id Get the ID of an document fetched from the db
Working with IDs
db.get(doc_id=...) Get the document with the given ID
db.contains(doc_ids=[...]) Check if the db contains documents with one of the given IDs
db.update({...}, doc_ids=[...]) Update all documents with the given IDs
db.remove(doc_ids=[...]) Remove all documents with the given IDs

Tables

TinyDB supports working with multiple tables. They behave just the same as the TinyDB class. To create and use a table, use db.table(name).

>>> table = db.table('table_name')
>>> table.insert({'value': True})
>>> table.all()
[{'value': True}]
>>> for row in table:
>>>     print(row)
{'value': True}

To remove a table from a database, use:

>>> db.purge_table('table_name')

If on the other hand you want to remove all tables, use the counterpart:

>>> db.purge_tables()

Finally, you can get a list with the names of all tables in your database:

>>> db.tables()
{'_default', 'table_name'}

Default Table

TinyDB uses a table named _default as the default table. All operations on the database object (like db.insert(...)) operate on this table. The name of this table can be modified by either passing default_table to the TinyDB constructor or by setting the DEFAULT_TABLE class variable to modify the default table name for all instances:

>>> #1: for a single instance only
>>> TinyDB(storage=SomeStorage, default_table='my-default')
>>> #2: for all instances
>>> TinyDB.DEFAULT_TABLE = 'my-default'

Query Caching

TinyDB caches query result for performance. You can optimize the query cache size by passing the cache_size to the table(...) function:

>>> table = db.table('table_name', cache_size=30)

Hint

You can set cache_size to None to make the cache unlimited in size.

Storage & Middleware

Storage Types

TinyDB comes with two storage types: JSON and in-memory. By default TinyDB stores its data in JSON files so you have to specify the path where to store it:

>>> from tinydb import TinyDB, where
>>> db = TinyDB('path/to/db.json')

To use the in-memory storage, use:

>>> from tinydb.storages import MemoryStorage
>>> db = TinyDB(storage=MemoryStorage)

Hint

All arguments except for the storage argument are forwarded to the underlying storage. For the JSON storage you can use this to pass additional keyword arguments to Python’s json.dump(...) method.

To modify the default storage for all TinyDB instances, set the DEFAULT_STORAGE class variable:

>>> TinyDB.DEFAULT_STORAGE = MemoryStorage

Middleware

Middleware wraps around existing storage allowing you to customize their behaviour.

>>> from tinydb.storages import JSONStorage
>>> from tinydb.middlewares import CachingMiddleware
>>> db = TinyDB('/path/to/db.json', storage=CachingMiddleware(JSONStorage))

Hint

You can nest middleware:

>>> db = TinyDB('/path/to/db.json', storage=FirstMiddleware(SecondMiddleware(JSONStorage)))

CachingMiddleware

The CachingMiddleware improves speed by reducing disk I/O. It caches all read operations and writes data to disk after a configured number of write operations.

To make sure that all data is safely written when closing the table, use one of these ways:

# Using a context manager:
with database as db:
    # Your operations
# Using the close function
db.close()

What’s next

Congratulations, you’ve made through the user guide! Now go and build something awesome or dive deeper into TinyDB with these resources:

« Getting Started | How to Extend TinyDB »