kinto-client 3.0.0

Kinto client

Kinto is a service that allows to store and synchronize arbitrary data, attached to a user account. Its primary interface is HTTP.

kinto-client is a Python library that eases the interactions with a Kinto server instance. A project with related goals is also available for JavaScript.

Installation

Use pip:

$ pip install kinto-client

Usage

Note

Operations are always performed directly on the server, and no synchronisation features are implemented yet.

• The first version of this API doesn’t cache any access nor provide any refresh mechanism. If you want to be sure you have the latest data available, issue another call.

Here is an overview of what the API provides:

from kinto_client import Client

client = Client(server_url="http://localhost:8888/v1",
                auth=('alexis', 'p4ssw0rd'))

records = client.get_records(bucket='default', collection='todos')
for i, record in enumerate(records['data']):
    record['title'] = 'Todo #%d' %i

for record in records:
    client.update_record(record)

Creating a client

The passed auth parameter is a requests authentication policy, allowing authenticating using whatever scheme fits you best.

By default, Kinto supports Firefox Accounts and Basic authentication policies.

from kinto_client import Client
credentials = ('alexis', 'p4ssw0rd')

client = Client(server_url='http://localhost:8888/v1',
                auth=credentials)

It is also possible to pass the bucket and the collection to the client at creation time, so that this value will be used by default.

client = Client(bucket="payments", collection="receipts", auth=auth)

Handling buckets

All operations are rooted in a bucket. It makes little sense for one application to handle multiple buckets at once (but it is possible). If no specific bucket name is provided, the “default” bucket is used.

from kinto_client import Client
credentials = ('alexis', 'p4ssw0rd')

client = Client(server_url='http://localhost:8888/v1',
                auth=credentials)
client.create_bucket('payments')
client.get_bucket('payments')

# It is also possible to manipulate bucket permissions (see later)
client.update_bucket('payments', permissions={})

Collections

A collection is where records are stored.

client.create_collection('receipts', bucket='payments')

# Or get an existing one.
client.get_collection('receipts', bucket='payments')

# To delete an existing collection.
client.delete_collection('receipts', bucket='payments')

Records

Records can be retrieved from and saved to collections.

A record is a dict with the “permissions” and “data” keys.

# You can pass a python dictionary to create the record
# bucket='default' can be omitted since it's the default value

client.create_record(data={'id': 1234, status: 'done', title: 'Todo #1'},
                     collection='todos', bucket='default')

# Retrieve all records.
record = client.get_records(collection='todos', bucket='default')

# Retrieve a specific record and update it.
record = client.get_record('89881454-e4e9-4ef0-99a9-404d95900352',
                           collection='todos', bucket='default')
client.update_record(record, collection='todos', bucket='default')

# Update multiple records at once.
client.update_records(records, collection='todos')

# It is also possible to delete records.
client.delete_record(id='89881454-e4e9-4ef0-99a9-404d95900352',
                     collection='todos')

Permissions

By default, authors will get read and write access to the manipulated objects. It is possible to change this behavior by passing a dict to the permissions parameter.

client.create_record(
    data={'foo': 'bar'},
    permissions={'read': ['group:groupid']},
    collection='todos')

Note

Every creation or modification operation on a distant object can be given a permissions parameter.

Buckets, collections and records have permissions which can be edited. For instance to give access to “leplatrem” to a specific record, you would do:

record = client.get_record(1234, collection='todos', bucket='alexis')
record['permissions']['write'].append('leplatrem')
client.update_record(record)

# During creation, it is possible to pass the permissions dict.
client.create_record(data={'foo': 'bar'}, permissions={})

Get or create

In some cases, you might want to create a bucket, collection or record only if it doesn’t exist already. To do so, you can pass the if_not_exists=True to the create_* methods:

client.create_bucket('bucket', if_not_exists=True)

Overwriting existing objects

Most of the methods take a safe argument, which defaults to True. If set to True and a last_modified field is present in the passed data, then a check will be added to the requests to ensure the record wasn’t modified on the server side in the meantime.

Batching operations

Rather than issuing a request for each and every operation, it is possible to batch the requests. The client will then issue as little requests as possible.

Currently, batching operations only supports write operations, so it is not possible to do the retrieval of information inside a batch.

It is possible to do batch requests using a Python context manager (with):

with client.batch() as batch:
    for idx in range(0,100):
        batch.update_record(data={'id': idx})

A batch object shares the same methods as another client.

Retry on error

When the server is throttled (under heavy load or maintenance) it can return error responses.

The client can hence retry to send the same request until it succeeds. To enable this, specify the number of retries on the client:

client = Client(server_url='http://localhost:8888/v1',
                auth=credentials,
                retry=10)

The Kinto protocol lets the server define the duration in seconds between retries. It is possible (but not recommended) to force this value in the clients:

client = Client(server_url='http://localhost:8888/v1',
                auth=credentials,
                retry=10,
                retry_after=5)

Run tests

In one terminal, run a Kinto server:

$ make runkinto

In another, run the tests against it:

$ make tests