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Description:

kintoclient 5.0.0

Note
kinto-client have been renamed kinto-http.
We encourage you to switch to the new kinto-http project to keep getting updates.

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)

Getting server information
You can use the server_info method to get the server information:
.. code-block:: python

from kinto_client import Client
client = Client(server_url=’http://localhost:8888/v1’)
info = client.server_info()
assert ‘schema’ in info[‘capabilities’], “Server doesn’t support schema validation.”

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={})

# Or delete a bucket and everything under.
client.delete_bucket('payment')

# Or even every writable buckets.
client.delete_buckets()

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')

# Or every collections in a bucket.
client.delete_collections(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 a record.
client.delete_record(id='89881454-e4e9-4ef0-99a9-404d95900352',
collection='todos')

# Or every records of a collection.
client.delete_records(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 if_match 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)

Generating endpoint paths
You may want to generate some endpoint paths, you can use the
get_endpoint utility to do so:
client = Client(server_url='http://localhost:8888/v1',
auth=('token', 'your-token'),
bucket="payments",
collection="receipts")
print(client.get_endpoint("record",
id="c6894b2c-1856-11e6-9415-3c970ede22b0"))

# '/buckets/payments/collections/receipts/records/c6894b2c-1856-11e6-9415-3c970ede22b0'

Command-line scripts
In order to have common arguments and options for scripts, some utilities are provided
to ease configuration and initialization of client from command-line arguments.
import argparse
import logging

from kinto_client import cli_utils

logger = logging.getLogger(__name__)

if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Download records")
cli_utils.set_parser_server_options(parser)

args = parser.parse_args()

cli_utils.setup_logger(logger, args)

logger.debug("Instantiate Kinto client.")
client = cli_utils.create_client_from_args(args)

logger.info("Fetch records.")
records = client.get_records()
logger.warn("%s records." % len(records))
The script now accepts basic options:
$ python example.py --help

usage: example.py [-h] [-s SERVER] [-a AUTH] [-b BUCKET] [-c COLLECTION] [-v]
[-q] [-D]

Download records

optional arguments:
-h, --help show this help message and exit
-s SERVER, --server SERVER
The location of the remote server (with prefix)
-a AUTH, --auth AUTH BasicAuth token:my-secret
-b BUCKET, --bucket BUCKET
Bucket name.
-c COLLECTION, --collection COLLECTION
Collection name.
-v, --verbose Show all messages.
-q, --quiet Show only critical errors.
-D, --debug Show all messages, including debug messages.

Run tests
In one terminal, run a Kinto server:
$ make runkinto
In another, run the tests against it:
$ make tests