API Documentation

class UnQLite([filename=':mem:'[, flags=UNQLITE_OPEN_CREATE[, open_database=True]])

The UnQLite object provides a pythonic interface for interacting with UnQLite databases. UnQLite is a lightweight, embedded NoSQL database and JSON document store.

  • filename (str) – The path to the database file.
  • flags (int) – How the database file should be opened.
  • open_database (bool) – When set to True, the database will be opened automatically when the class is instantiated. If set to False you will need to manually call open().


UnQLite supports in-memory databases, which can be created by passing in ':mem:' as the database file. This is the default behavior if no database file is specified.

Example usage:

>>> db = UnQLite()  # Create an in-memory database.
>>> db['foo'] = 'bar'  # Use as a key/value store.
>>> print db['foo']

>>> for i in range(4):
...     db['k%s' % i] = str(i)

>>> 'k3' in db
>>> 'k4' in db
>>> del db['k3']

>>> db.append('k2', 'XXXX')
>>> db['k2']

>>> with db.cursor() as cursor:
...     for key, value in cursor:
...         print key, '=>', value
foo => bar
k0 => 0
k1 => 1
k2 => 2XXXX

>>> script = """
...     db_create('users');
...     db_store('users', $list_of_users);
...     $users_from_db = db_fetch_all('users');
... """

>>> list_of_users = [
...     {'username': 'Huey', 'age': 3},
...     {'username': 'Mickey', 'age': 5}
... ]

>>> with db.vm(script) as vm:
...     vm['list_of_users'] = list_of_users
...     vm.execute()
...     users_from_db = vm['users_from_db']

>>> users_from_db  # UnQLite assigns items in a collection an ID.
[{'username': 'Huey', 'age': 3, '__id': 0},
 {'username': 'Mickey', 'age': 5, '__id': 1}]

Open the database. This method should only be called if the database was manually closed, or if the database was instantiated with open_database=False.

Valid flags:


Detailed descriptions of these flags can be found in the unqlite_open docs.


Close the database.


If you are using a file-based database, by default any uncommitted changes will be committed when the database is closed. If you wish to discard uncommitted changes, you can use disable_autocommit().


Use the database as a context manager, opening the connection and closing it at the end of the wrapped block:

with UnQLite('my_db.udb') as db:
    db['foo'] = 'bar'

# When the context manager exits, the database is closed.

When the database is closed, prevent any uncommitted writes from being saved.


This method only affects file-based databases.

store(key, value)

Store a value in the given key.

  • key (str) – Identifier used for storing data.
  • value (str) – A value to store in UnQLite.


db = UnQLite()
db.store('some key', 'some value')
db.store('another key', 'another value')

You can also use the dictionary-style db[key] = value to store a value:

db['some key'] = 'some value'

Retrieve the value stored at the given key. If no value exists in the given key, a KeyError will be raised.

Parameters:key (str) – Identifier to retrieve
Returns:The data stored at the given key
Raises:KeyError if the given key does not exist.


db = UnQLite()
db.store('some key', 'some value')
value = db.fetch('some key')

You can also use the dictionary-style value = db[key] lookup to retrieve a value:

value = db['some key']

Remove the key and its associated value from the database.

Parameters:key (str) – The key to remove from the database.
Raises:KeyError if the given key does not exist.


def clear_cache():

You can also use the python del keyword combined with a dictionary lookup:

def clear_cache():
    del db['cached-data']
append(key, value)

Append the given value to the data stored in the key. If no data exists, the operation is equivalent to store().

  • key (str) – The identifier of the value to append to.
  • value – The value to append.

Return whether the given key exists in the database.

Parameters:key (str) –
Returns:A boolean value indicating whether the given key exists in the database.


def get_expensive_data():
    if not db.exists('cached-data'):
        db.set('cached-data', calculate_expensive_data())
    return db.get('cached-data')

You can also use the python in keyword to determine whether a key exists:

def get_expensive_data():
    if 'cached-data' not in db:
        db['cached-data'] = calculate_expensive_data()
    return db['cached-data']

Begin a transaction.


Roll back the current transaction.


Commit the current transaction.


Create a context manager for performing multiple operations in a transaction.


Transactions occur at the disk-level and have no effect on in-memory databases.


# Transfer $100 in a transaction.
with db.transaction():
    db['from_acct'] = db['from_account'] - 100
    db['to_acct'] = db['to_acct'] + 100

# Make changes and then roll them back.
with db.transaction():
    db['foo'] = 'bar'
    db.rollback()  # Whoops, do not commit these changes.

Function decorator that will cause the wrapped function to have all statements wrapped in a transaction. If the function returns without an exception, the transaction is committed. If an exception occurs in the function, the transaction is rolled back.


>>> @db.commit_on_success
... def save_value(key, value, exc=False):
...     db[key] = value
...     if exc:
...         raise Exception('uh-oh')
>>> save_value('k3', 'v3')
>>> save_value('k3', 'vx', True)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "unqlite/core.py", line 312, in wrapper
    return fn()
  File "<stdin>", line 5, in save_value
Exception: uh-oh
>>> db['k3']
Returns:a Cursor instance.

Create a cursor for traversing database records.

Parameters:code (str) – a Jx9 script.
Returns:a VM instance with the compiled script.

Compile the given Jx9 script and return an initialized VM instance.


script = "$users = db_fetch_all('users');"
with db.vm(script) as vm:
    users = vm['users']
Parameters:name (str) – The name of the collection.

Factory method for instantiating a Collection for working with a collection of JSON objects.


Users = db.collection('users')

# Fetch all records in the collection.
all_users = Users.all()

# Create a new record.
Users.store({'name': 'Charlie', 'activities': ['reading', 'programming']})

See the Collection docs for more examples.

Returns:A generator that successively yields the keys in the database.
Returns:A generator that successively yields the values in the database.
Returns:A generator that successively yields tuples containing the keys and values in the database.
Parameters:data (dict) – Dictionary of data to store in the database. If any keys in data already exist, the values will be overwritten.

UnQLite databases can be iterated over. The iterator is a Cursor, and will yield 2-tuples of keys and values:

db = UnQLite('my_db.udb')
for (key, value) in db:
    print key, '=>', value
range(start_key, end_key[, include_end_key=True])

Iterate over a range of key/value pairs in the database.

for key, value in db.range('d.20140101', 'd.20140201', False):
    calculate_daily_aggregate(key, value)

Return the number of records in the database.


This method calculates the lengthy by iterating and counting every record. At the time of writing, there is no C API for calculating the size of the database.


Delete all records in the database.


This method works by iterating through all the records and deleting them one-by-one. At the time of writing there is no API for bulk deletes. If you are worried about speed, simply delete the database file and re-open it.

Parameters:nbytes (int) – number of bytes to generate
Returns:a string consisting of random lower-case letters (a-z).
Returns:a random positive integer
Returns:The UnQLite library version.
class Transaction(unqlite)
Parameters:unqlite (UnQLite) – An UnQLite instance.

Context-manager for executing wrapped blocks in a transaction. Rather than instantiating this object directly, it is recommended that you use UnQLite.transaction().


with db.transaction():
    db['from_acct'] = db['from_acct'] + 100
    db['to_acct'] = db['to_acct'] - 100

To roll back changes inside a transaction, call UnQLite.rollback():

with db.transaction():
    db['from_acct'] = db['from_acct'] + 100
    db['to_acct'] = db['to_acct'] - 100
    if int(db['to_acct']) < 0:
        db.rollback()  # Not enough funds!
class Cursor(unqlite)
Parameters:unqlite (UnQLite) – An UnQLite instance.

Create a cursor. Cursors should generally be used as context managers.

Rather than instantiating this class directly, it is preferable to call the factory method UnQLite.cursor().

for i in range(4):
    db['k%d' % i] = str(i)

# Cursor support iteration, which returns key/value pairs.
with db.cursor() as cursor:
    all_items = [(key, value) for key, value in cursor]

    # You can seek to a record, then iterate to retrieve a portion
    # of results.
    k2, k3 = [key for key, _ in cursor]

# Previous cursor was closed automatically, open a new one.
with db.cursor() as cursor:
    cursor.seek('k1')  # Jump to the 2nd record, k1
    assert cursor.key() == 'k1'  # Use the key()/value() methods.
    assert cursor.value() == '1'

    cursor.delete()  # Delete k1/v1
    cursor.first()  # Cursor now points to k0/0
    cursor.next()  # Cursor jumps to k2/2 since k1/1 is deleted.
    assert cursor.key() == 'k2'

    keys = [key for key, value in cursor]  # Cursor iterates from k2->k3
    assert keys == ['k2', 'k3']

Reset the cursor, which also resets the pointer to the first record.


Advance the cursor to the given key using the comparison method described in the flags.

A detailed description of alternate flags and their usage can be found in the unqlite_kv_cursor docs.


with db.cursor() as cursor:
    while cursor.is_valid():
        data_for_day = cursor.value()
        # do something with data for day
        if cursor.key() == 'item.20140201':

Place cursor at the first record.


Place cursor at the last record.


Move the cursor to the next record.

Raises:StopIteration if you have gone past the last record.

Move the cursor to the previous record.

Raises:StopIteration if you have gone past the first record.
Return type:bool

Indicate whether this cursor is pointing to a valid record.


Iterate over the keys in the database, returning 2-tuples of key/value.


Iteration will begin wherever the cursor is currently pointing, rather than starting at the first record.


Return the key of the current record.


Return the value of the current record.


Delete the record currently pointed to by the cursor.


The delete() method is a little weird in that it only seems to work if you explicitly call seek() beforehand.

fetch_until(stop_key[, include_stop_key=True])
  • stop_key (str) – The key at which the cursor should stop iterating.
  • include_stop_key (bool) – Whether the stop key/value pair should be returned.

Yield successive key/value pairs until the stop_key is reached. By default the stop_key and associated value will be returned, but this behavior can be controlled using the include_stop_key flag.

class VM(unqlite, code)
  • unqlite (UnQLite) – An UnQLite instance.
  • code (str) – A Jx9 script.

Python wrapper around an UnQLite virtual machine. The VM is the primary means of executing Jx9 scripts and interacting with the JSON document store.

VM instances should not be instantiated directly, but created by calling UnQLite.vm().


For information on Jx9 scripting, see the Jx9 docs.

Example of passing values into a Jx9 script prior to execution, then extracting values afterwards:

script = """
    $collection = 'users';
    db_store($collection, $values);
    $users = db_fetch_all($collection);

# We can pass all sorts of interesting data in to our script.
values = [
    {'username': 'huey', 'color': 'white'},
    {'username': 'mickey', 'color': 'black'},

with db.vm(script) as vm:
    # Set the value of the `values` variable in the Jx9 script:
    vm['values'] = values

    # Execute the script, which creates the collection and stores
    # the two records.

    # After execution, we can extract the value of the `users` variable.
    users = vm['users']

    # Jx9 document store assigns a unique 0-based id to each record
    # in a collection. The extracted variable `users` will now equal:
    print users == [
        {'username': 'huey', 'color': 'white', '__id': 0},
        {'username': 'mickey', 'color': 'black', '__id': 1},
    ]  # prints `True`

When using the VM outside of a context-manager, the following steps should be followed:

  1. instantiate VM with a Jx9 script.
  2. call VM.compile() to compile the script.
  3. optional: set one or more values to pass to the Jx9 script using VM.set_value() or VM.set_values().
  4. call VM.execute() to execute the script.
  5. optional: read one or more values back from the VM context, for example a return value for a function call, using VM.get_value().
  6. call VM.reset() and return to step 4 if you intend to re-execute the script, or call VM.close() to free the VM and associated resources.

Execute the compiled Jx9 script.


Release the VM, deallocating associated memory.


When using the VM as a context manager, this is handled automatically.


Typically the VM should be used as a context manager. The context manager API handles compiling the Jx9 code and releasing the data-structures afterwards.

with db.vm(jx9_script) as vm:
set_value(name, value)
  • name (str) – A variable name
  • value – Value to pass in to the scope of the Jx9 script, which should be either a string, int, float, bool, list, dict, or None (basically a valid JSON type).

Set the value of a Jx9 variable. You can also use dictionary-style assignment to set the value.

Parameters:mapping (dict) – Dictionary of name to value to pass in to the Jx9 script. This method is short-hand for making multiple calls to set_value().

Set multiple Jx9 variables.

Parameters:name (str) – A variable name

Retrieve the value of a variable after the execution of a Jx9 script. You can also use dictionary-style lookup to retrieve the value.

Parameters:code (str) – A Jx9 script.

Compile the Jx9 script and initialize the VM.


It is not necessary to call this method yourself, as it is called automatically when the VM is used as a context manager.


This does not execute the code. To execute the code, you must also call VM.execute().

class Collection(unqlite, name)
  • unqlite – a UnQLite instance
  • name (str) – the name of the collection

Perform common operations on a JSON document collection.


Rather than instantiating this class directly, use the factory method UnQLite.collection().

Basic operations:

>>> users = db.collection('users')
>>> users.create()  # Create the collection if it does not exist.
>>> users.exists()

>>> users.store([
...     {'name': 'Charlie', 'color': 'green'},
...     {'name': 'Huey', 'color': 'white'},
...     {'name': 'Mickey', 'color': 'black'}])
>>> users.store({'name': 'Leslie', 'color': 'also green'})

>>> users.fetch(0)  # Fetch the first record (user "__id" = 0).
{'__id': 0, 'color': 'green', 'name': 'Charlie'}

>>> users.delete(0)  # Delete the first record (user "__id" = 0).
>>> users.delete(users.last_record_id())  # Delete the last record.

>>> users.update(1, {'color': 'white', 'name': 'Baby Huey'})

>>> users.all()
[{'__id': 1, 'color': 'white', 'name': 'Baby Huey'},
 {'__id': 2, 'color': 'black', 'name': 'Mickey'}]

>>> for user in users:
...     print(user)
{'__id': 1, 'color': 'white', 'name': 'Baby Huey'}
{'__id': 2, 'color': 'black', 'name': 'Mickey'}

>>> users.filter(lambda obj: obj['name'].startswith('B'))
[{'__id': 1, 'color': 'white', 'name': 'Baby Huey'}]
Returns:list containing all records in the collection.

As of 0.9.0, it is also possible to iterate the collection using a Python iterable. See iterator().

Returns:CollectionIterator for iterating over the records in the collection.
>>> reg = db.collection('register')
>>> reg.create()
>>> reg.store([{'key': 'k0'}, {'key': 'k1'}, {'key': 'k2'}])

>>> it = reg.iterator()
>>> for row in it:
...     print(row)
{'__id': 0, 'key': 'k0'}
{'__id': 1, 'key': 'k1'}
{'__id': 2, 'key': 'k2'}

>>> list(it)  # We can re-use the iterator.
[{'__id': 0, 'key': 'k0'},
 {'__id': 1, 'key': 'k1'},
 {'__id': 2, 'key': 'k2'}]

>>> for row in reg:  # Iterating over collection is fine, too.
...     print(row)
{'__id': 0, 'key': 'k0'}
{'__id': 1, 'key': 'k1'}
{'__id': 2, 'key': 'k2'}

Filter the list of records using the provided function (or lambda). Your filter function should accept a single parameter, which will be the record, and return a boolean value indicating whether the record should be returned.

Parameters:filter_fn – callable that accepts record and returns boolean.
Returns:list of matching records.


>>> users.filter(lambda user: user['is_admin'] == True)
[{'__id': 0, 'username': 'Huey', 'is_admin': True},
 {'__id': 3, 'username': 'Zaizee', 'is_admin': True},
 {'__id': 4, 'username': 'Charlie', 'is_admin': True}]

Create the collection if it does not exist.

Returns:true on success, false if collection already exists.

Drop the collection, deleting all records.

Returns:true on success, false if collection does not exist.
Returns:boolean value indicating whether the collection exists.
Returns:the timestamp the collection was created (if exists) or None.
set_schema([_schema=None[, **kwargs]])

Set the schema metadata associated with the collection. The schema is not enforced by the database engine, and is for metadata purposes.

  • _schema (dict) – a mapping of field-name to data-type, or
  • kwargs – key/value mapping of field to data-type.

true on success, false on failure.


Get the schema metadata associated with the collection.

Returns:mapping of field-name to data-type on success, or None.
Returns:The integer ID of the last record stored in the collection.
Returns:The integer ID of the record pointed to by the active cursor.

Reset the collection cursor to point to the first record in the collection.


Return the number of records in the collection.


Return a CollectionIterator for iterating over the records in the collection.


Return the record with the given id.

>>> users = db.collection('users')
>>> users.fetch(0)  # Fetch the first record in collection (id=0).
{'name': 'Charlie', 'color': 'green', '__id': 0}

>>> users[1]  # You can also use dictionary-style lookup.
{'name': 'Huey', 'color': 'white', '__id': 1}

You can also use the dictionary API:

>>> users[0]
{'name': 'Charlie', 'color': 'green', '__id': 0}
store(record[, return_id=True])
  • record – Either a dictionary (single-record), or a list of dictionaries.
  • return_id (bool) – Return the ID of the newly-created object.

New object’s ID, or a boolean indicating if the record was stored successfully.

Store the record(s) in the collection.

>>> users = db.collection('users')
>>> users.store({'name': 'Charlie', 'color': 'green'})
>>> users.store([
...     {'name': 'Huey', 'color': 'white'},
...     {'name': 'Mickey', 'color': 'black'}])
update(record_id, record)
  • record_id – The ID of the record to update.
  • record – A dictionary of data to update the given record ID.

Boolean value indicating if the update was successful.

Update the data stored for the given record_id. The data is completely replaced, rather than being appended to.

>>> users = db.collection('users')
>>> users.store({'name': 'Charlie'})
>>> users.update(users.last_record_id(), {'name': 'Chuck'})
>>> users.fetch(users.last_record_id())
{'__id': 0, 'name': 'Chuck'}

You can also use dictionary-style assignment using the record ID:

>>> users[0] = {'name': 'Charles'}  # Can also use item assignment by id.
>>> users[0]
{'__id': 0, 'name': 'Charles'}
Parameters:record_id – The database-provided ID of the record to delete.
Returns:Boolean indicating if the record was deleted successfully.

Delete the record with the given id.

>>> data = db.collection('data')
>>> data.create()
>>> data.store({'foo': 'bar'})
>>> data.delete(data.last_record_id())
>>> data.all()

You can also use the dictionary API:

>>> del users[1]  # Delete user object with `__id=1`.

Fetch the record pointed to by the collection cursor.

This method does not work as intended as the VM is reset for each script execution.
class CollectionIterator(Collection)

Python iterator that returns rows from a collection. This class should not be instantiated directly, but via Collection.iterator() or implicitly by iterating directly over a Collection.