Migrating from old API

Why a new API?

With the introduction of Workflows, ftrack is capable of supporting a greater diversity of industries. We’re enabling teams to closely align the system with their existing practices and naming conventions, resulting in a tool that feels more natural and intuitive. The old API was locked to specific workflows, making it impractical to support this new feature naturally.

We also wanted this new flexibility to extend to developers, so we set about redesigning the API to fully leverage the power in the system. And while we had the wrenches out, we figured why not go that extra mile and build in some of the features that we see developers having to continually implement in-house across different companies - features such as caching and support for custom pipeline extensions. In essence, we decided to build the API that, as pipeline developers, we had always wanted from our production tracking and asset management systems. We think we succeeded, and we hope you agree.


Before, you used to download the API package from your ftrack instance. With each release of the new API we make it available on PyPi, and installing is super simple:

pip install ftrack-python-api

Before installing, it is always good to check the latest Release Notes to see which version of the ftrack server is required.

See also



An API needs to be approachable, so we built the new API to feel intuitive and familiar. We bundle all the core functionality into one place – a session – with consistent methods for interacting with entities in the system:

import ftrack_api
session = ftrack_api.Session()

The session is responsible for loading plugins and communicating with the ftrack server and allows you to use multiple simultaneous sessions. You will no longer need to explicitly call ftrack.setup() to load plugins.

The core methods are straightforward:

create a new entity, like a new version.
fetch entities from the server using a powerful query language.
delete existing entities.
commit all changes in one efficient call.


The new API batches create, update and delete operations by default for efficiency. To synchronise local changes with the server you need to call Session.commit().

In addition all entities in the API now act like simple Python dictionaries, with some additional helper methods where appropriate. If you know a little Python (or even if you don’t) getting up to speed should be a breeze:

>>> print user.keys()
['first_name', 'last_name', 'email', ...]
>>> print user['email']
>>> user['email'] = 'new@example.com'

And of course, relationships between entities are reflected in a natural way as well:

new_timelog = session.create('Timelog', {...})

See also


The new API also makes use of caching in order to provide more efficient retrieval of data by reducing the number of calls to the remote server.

See also


Open source and standard code style

The new API is open source software and developed in public at Bitbucket. We welcome you to join us in the development and create pull requests there.

In the new API, we also follow the standard code style for Python, PEP-8. This means that you will now find that methods and variables are written using snake_case instead of camelCase, amongst other things.

Package name

The new package is named ftrack_api. By using a new package name, we enable you to use the old API and the new side-by-side in the same process.

Old API:

import ftrack

New API:

import ftrack_api

Specifying your credentials

The old API used three environment variables to authenticate with your ftrack instance. While these continue to work as before, you now also have the option to specify them when initializing the session:

>>> import ftrack_api
>>> session = ftrack_api.Session(
...     server_url='http://mycompany.ftrackapp.com',
...     api_key='7545384e-a653-11e1-a82c-f22c11dd25eq',
...     api_user='martin'
... )

In the examples below, will assume that you have imported the package and created a session.

Querying objects

The old API relied on predefined methods for querying objects and constructors which enabled you to get an entity by it’s id or name.

Old API:

project = ftrack.getProject('dev_tutorial')
task = ftrack.Task('8923b7b3-4bf0-11e5-8811-3c0754289fd3')
user = ftrack.User('jane')

New API:

project = session.query('Project where name is "dev_tutorial"').one()
task = session.get('Task', '8923b7b3-4bf0-11e5-8811-3c0754289fd3')
user = session.query('User where username is "jane"').one()

While the new API can be a bit more verbose for simple queries, it is much more powerful and allows you to filter on any field and preload related data:

tasks = session.query(
    'select name, parent.name from Task '
    'where project.full_name is "My Project" '
    'and status.type.short is "DONE" '
    'and not timelogs any ()'

The above fetches all tasks for “My Project” that are done but have no timelogs. It also pre-fetches related information about the tasks parent – all in one efficient query.

See also


Creating objects

In the old API, you create objects using specialized methods, such as ftrack.createProject(), Project.createSequence() and Task.createShot().

In the new API, you can create any object using Session.create(). In addition, there are a few helper methods to reduce the amount of boilerplate necessary to create certain objects. Don’t forget to call Session.commit() once you have issued your create statements to commit your changes.

As an example, let’s look at populating a project with a few entities.

Old API:

project = ftrack.getProject('migration_test')

# Get default task type and status from project schema
taskType = project.getTaskTypes()[0]
taskStatus = project.getTaskStatuses(taskType)[0]

sequence = project.createSequence('001')

# Create five shots with one task each
for shot_number in xrange(10, 60, 10):
    shot = sequence.createShot(
        'Task name',

New API:

project = session.query('Project where name is "migration_test"').one()

# Get default task type and status from project schema
project_schema = project['project_schema']
default_shot_status = project_schema.get_statuses('Shot')[0]
default_task_type = project_schema.get_types('Task')[0]
default_task_status = project_schema.get_statuses(
    'Task', default_task_type['id']

# Create sequence
sequence = session.create('Sequence', {
    'name': '001',
    'parent': project

# Create five shots with one task each
for shot_number in xrange(10, 60, 10):
    shot = session.create('Shot', {
        'name': '{0:03d}'.format(shot_number),
        'parent': sequence,
        'status': default_shot_status
    session.create('Task', {
        'name': 'Task name',
        'parent': shot,
        'status': default_task_status,
        'type': default_task_type

# Commit all changes to the server.

If you test the example above, one thing you might notice is that the new API is much more efficient. Thanks to the transaction-based architecture in the new API only a single call to the server is required to create all the objects.

Updating objects

Updating objects in the new API works in a similar way to the old API. Instead of using the set() method on objects, you simply set the key of the entity to the new value, and call Session.commit() to persist the changes to the database.

The following example adjusts the duration and comment of a timelog for a user using the old and new API, respectively.

Old API:

import ftrack

user = ftrack.User('john')
user.set('email', 'john@example.com')

New API:

import ftrack_api
session = ftrack_api.Session()

user = session.query('User where username is "john"').one()
user['email'] = 'john@example.com'

Date and datetime attributes

In the old API, date and datetime attributes where represented using a standard datetime object. In the new API we have opted to use the arrow library instead. Datetime attributes are represented in the server timezone, but with the timezone information stripped.

Old API:

>>> import datetime

>>> task_old_api = ftrack.Task(task_id)
>>> task_old_api.get('startdate')
datetime.datetime(2015, 9, 2, 0, 0)

>>> # Updating a datetime attribute
>>> task_old_api.set('startdate', datetime.date.today())

New API:

>>> import arrow

>>> task_new_api = session.get('Task', task_id)
>>> task_new_api['start_date']
<Arrow [2015-09-02T00:00:00+00:00]>

>>> # In the new API, utilize the arrow library when updating a datetime.
>>> task_new_api['start_date'] = arrow.utcnow().floor('day')
>>> session.commit()

Custom attributes

In the old API, custom attributes could be retrieved from an entity by using the methods get() and set(), like standard attributes. In the new API, custom attributes can be written and read from entities using the custom_attributes property, which provides a dictionary-like interface.

Old API:

>>> task_old_api = ftrack.Task(task_id)
>>> task_old_api.get('my_custom_attribute')

>>> task_old_api.set('my_custom_attribute', 'My new value')

New API:

>>> task_new_api = session.get('Task', task_id)
>>> task_new_api['custom_attributes']['my_custom_attribute']

>>> task_new_api['custom_attributes']['my_custom_attribute'] = 'My new value'

For more information on working with custom attributes and existing limitations, please see:

Using both APIs side-by-side

With so many powerful new features and the necessary support for more flexible workflows, we chose early on to not limit the new API design by necessitating backwards compatibility. However, we also didn’t want to force teams using the existing API to make a costly all-or-nothing switchover. As such, we have made the new API capable of coexisting in the same process as the old API:

import ftrack
import ftrack_api

In addition, the old API will continue to be supported for some time, but do note that it will not support the new Workflows and will not have new features back ported to it.

In the first example, we obtain a task reference using the old API and then use the new API to assign a user to it:

import ftrack
import ftrack_api

# Create session for new API, authenticating using envvars.
session = ftrack_api.Session()

# Obtain task id using old API
shot = ftrack.getShot(['migration_test', '001', '010'])
task = shot.getTasks()[0]
task_id = task.getId()

user = session.query(
    'User where username is "{0}"'.format(session.api_user)
session.create('Appointment', {
    'resource': user,
    'context_id': task_id,
    'type': 'assignment'

The second example fetches a version using the new API and uploads and sets a thumbnail using the old API:

import arrow
import ftrack

# fetch a version published today
version = session.query(
    'AssetVersion where date >= "{0}"'.format(

# Create a thumbnail using the old api.
thumbnail_path = '/path/to/thumbnail.jpg'
version_old_api = ftrack.AssetVersion(version['id'])
thumbnail = version_old_api.createThumbnail(thumbnail_path)

# Also set the same thumbnail on the task linked to the version.
task_old_api = ftrack.Task(version['task_id'])


It is now possible to set thumbnails using the new API as well, for more info see Working with thumbnails.

Plugin registration

To make event and location plugin register functions work with both old and new API the function should be updated to validate the input arguments. For old plugins the register method should validate that the first input is of type ftrack.Registry, and for the new API it should be of type ftrack_api.session.Session.

If the input parameter is not validated, a plugin might be mistakenly registered twice, since both the new and old API will look for plugins the same directories.

Example: publishing a new version

In the following example, we look at migrating a script which publishes a new version with two components.

Old API:

# Query a shot and a task to create the asset against.
shot = ftrack.getShot(['dev_tutorial', '001', '010'])
task = shot.getTasks()[0]

# Create new asset.
asset = shot.createAsset(name='forest', assetType='geo')

# Create a new version for the asset.
version = asset.createVersion(
    comment='Added more leaves.',

# Get the calculated version number.
print version.getVersion()

# Add some components.
previewPath = '/path/to/forest_preview.mov'
previewComponent = version.createComponent(path=previewPath)

modelPath = '/path/to/forest_mode.ma'
modelComponent = version.createComponent(name='model', path=modelPath)

# Publish.

# Add thumbnail to version.
thumbnail = version.createThumbnail('/path/to/forest_thumbnail.jpg')

# Set thumbnail on other objects without duplicating it.

New API:

# Query a shot and a task to create the asset against.
shot = session.query(
    'Shot where project.name is "dev_tutorial" '
    'and parent.name is "001" and name is "010"'
task = shot['children'][0]

# Create new asset.
asset_type = session.query('AssetType where short is "geo"').first()
asset = session.create('Asset', {
    'parent': shot,
    'name': 'forest',
    'type': asset_type

# Create a new version for the asset.
status = session.query('Status where name is "Pending"').one()
version = session.create('AssetVersion', {
    'asset': asset,
    'status': status,
    'comment': 'Added more leaves.',
    'task': task

# In the new API, the version number is not set until we persist the changes
print 'Version number before commit: {0}'.format(version['version'])
print 'Version number after commit: {0}'.format(version['version'])

# Add some components.
preview_path = '/path/to/forest_preview.mov'
preview_component = version.create_component(preview_path, location='auto')

model_path = '/path/to/forest_mode.ma'
model_component = version.create_component(model_path, {
    'name': 'model'
}, location='auto')

# Publish. Newly created version defaults to being published in the new api,
# but if set to false you can update it by setting the key on the version.
version['is_published'] = True

# Persist the changes

# Add thumbnail to version.
thumbnail = version.create_thumbnail(

# Set thumbnail on other objects without duplicating it.
task['thumbnail'] = thumbnail

Workarounds for missing convenience methods

Query object by path

In the old API, there existed a convenience methods to get an object by referencing the path (i.e object and parent names).

Old API:

shot = ftrack.getShot(['dev_tutorial', '001', '010'])

New API:

shot = session.query(
    'Shot where project.name is "dev_tutorial" '
    'and parent.name is "001" and name is "010"'

Retrieving an object’s parents

To retrieve a list of an object’s parents, you could call the method getParents() in the old API. Currently, it is not possible to fetch this in a single call using the new API, so you will have to traverse the ancestors one-by-one and fetch each object’s parent.

Old API:

parents = task.getParents()

New API:

parents = []
for item in task['link'][:-1]:
    parents.append(session.get(item['type'], item['id']))

Note that link includes the task itself so [:-1] is used to only retreive the parents. To learn more about the link attribute, see Using link attributes example.

Limitations in the current version of the API

The new API is still quite young and in active development and there are a few limitations currently to keep in mind when using it.

Missing schemas

The following entities are as of the time of writing not currently available in the new API. Let us know if you depend on any of them.

  • Booking
  • Calendar and Calendar Type
  • Dependency
  • Manager and Manager Type
  • Phase
  • Role
  • Task template
  • Temp data

Action base class

There is currently no helper class for creating actions using the new API. We will add one in the near future.

In the meantime, it is still possible to create actions without the base class by listening and responding to the ftrack.action.discover and ftrack.action.launch events.

Legacy location

The ftrack legacy disk locations utilizing the InternalResourceIdentifierTransformer has been deprecated.