Advanced Usage

Remarks on Storages

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.


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()
>>> == '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:

>>> == 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:
>>> == 'foo')
>>> # Use this instead:
>>>['country-code'] == 'foo')

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

>>> from tinydb import where
>>>'field') == 'value')

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

>>>['field'] == 'value')

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:
>>> # Regex:
>>> # Custom test:
>>> test_func = lambda s: s == 'John'
>>> # Custom test with parameters:
>>> def test_func(val, m, n):
>>>     return m <= val <= n
>>>, 0, 21))
>>>, 21, 99))

When a field contains a list, you also can use the following methods:

>>> # Using a query:
>>> # User is member of at least one admin group
>>> == 'admin'))
>>> # User is only member of admin groups
>>> == 'admin'))
>>> # Using a list of values:
>>> # User is member of at least one group which is 'admin' or 'user'
>>>['admin', 'user']))
>>> # User's groups are all either 'admin' or 'user'
>>>['admin', 'user']))

Query modifiers

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

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


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


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

Query().field.exists() Match any element where a field called field exists
Query().field.matches(regex) Match any element matching the regular expression
Query() Match any element with substring matching the regular expression
Query().field.test(func, *args) Matches any element for which the function returns True
Query().field.all(query | list) If given a query, matches all elements where all elements in the list field match the query. If given a list, matches all elements where all elements in the list field are a member of the given list
Query().field.any(query | list) If given a query, matches all elements where at least one element in the list field match the query. If given a list, matches all elements where at least one elements in the list field are a member of the given list
Logical operations on queries
~ query Match elements that don’t match the query
(query1) & (query2) Match elements that match both queries
(query1) | (query2) Match elements 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 element using db.insert(...). In case you want to insert multiple elements, 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

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

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

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

  • delete(key): delete a key from the element
  • increment(key): increment the value of a key
  • decrement(key): decrement the value of a key

Of course you also can write your own operations:

>>> def your_operation(your_arguments):
...     def transform(element):
...         # do something with the element
...         # ...
...     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 elements:

>>> len(db)

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

>>> try:
...     result = == 'John')[0]
... except IndexError:
...     pass

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

>>> db.get( == 'John')
{'name': 'John', 'age': 22}
>>> db.get( == 'Bobby')


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

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

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

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

>>> db.count( == 'John')


Let’s summarize the ways to handle data:

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

Using Element IDs

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

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

In addition you can get the ID of already inserted elements using element.eid:

>>> el = db.get( == 'John')
>>> el.eid

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}, eids=[1, 2])
>>> db.contains(eids=[1])
>>> db.remove(eids=[1, 2])
>>> db.get(eid=3)


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

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


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}]

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)


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

Storages & Middlewares

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)


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


Middlewares wrap around existing storages 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))


You can nest middlewares:

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


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

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 »