Python

Getting started:

1. Install ConfigCat SDK

pip install configcat-client

2. Import the package

import configcatclient

3. Create the ConfigCat client with your SDK Key

configcat_client = configcatclient.create_client('#YOUR-SDK-KEY#')

4. Get your setting value

isMyAwesomeFeatureEnabled = configcat_client.get_value('isMyAwesomeFeatureEnabled', False)if isMyAwesomeFeatureEnabled:    do_the_new_thing()else:    do_the_old_thing()

5. Stop ConfigCat client

You can safely shut down the client instance and release all associated resources on application exit.

configcat_client.stop()

Creating the ConfigCat Client

ConfigCat Client is responsible for:

• managing the communication between your application and ConfigCat servers.
• caching your setting values and feature flags.
• serving values quickly in a failsafe way.

create_client() returns a client with default options.

Properties	Description
sdk-key	REQUIRED. SDK Key to access your feature flags and configurations. Get it from ConfigCat Dashboard.
data_governance	Optional, defaults to DataGovernance.Global. Describes the location of your feature flag and setting data within the ConfigCat CDN. This parameter needs to be in sync with your Data Governance preferences. More about Data Governance. Available options: Global, EuOnly.

create_client_with_auto_poll(), create_client_with_lazy_load(), create_client_with_manual_poll()
Creating the client is different for each polling mode. See below for details.

caution

We strongly recommend you to use the ConfigCat Client as a Singleton object in your application. If you want to use multiple SDK Keys in the same application, create only one ConfigCat Client per SDK Key.

Anatomy of get_value()

Parameters	Description
key	REQUIRED. Setting-specific key. Set on ConfigCat Dashboard for each setting.
default_value	REQUIRED. This value will be returned in case of an error.
user	Optional, User Object. Essential when using Targeting. Read more about Targeting.

value = configcat_client.get_value(    'keyOfMySetting', # Setting Key    False, # Default value    User('435170f4-8a8b-4b67-a723-505ac7cdea92') # Optional User Object);

User Object

The User Object is essential if you'd like to use ConfigCat's Targeting feature.

user_object = User('435170f4-8a8b-4b67-a723-505ac7cdea92')   

user_object = User('john@example.com')   

Parameters	Description
identifier	REQUIRED. Unique identifier of a user in your application. Can be any value, even an email address.
email	Optional parameter for easier targeting rule definitions.
country	Optional parameter for easier targeting rule definitions.
custom	Optional dictionary for custom attributes of a user for advanced targeting rule definitions. e.g. User role, Subscription type.

user_object = User('435170f4-8a8b-4b67-a723-505ac7cdea92', 'john@example', 'United Kingdom',                {'SubscriptionType': 'Pro', 'UserRole': 'Admin'})

Polling Modes

The ConfigCat SDK supports 3 different polling mechanisms to acquire the setting values from ConfigCat. After latest setting values are downloaded, they are stored in the internal cache then all get_value() calls are served from there. With the following polling modes, you can customize the SDK to best fit to your application's lifecycle.

Auto polling (default)

The ConfigCat SDK downloads the latest values and stores them automatically every 60 seconds.

Use the poll_interval_seconds option parameter to change the polling interval.

configcatclient.create_client_with_auto_poll(    "#YOUR-SDK-KEY#", poll_interval_seconds=95);

Adding a callback to on_configuration_changed_callback option parameter will get you notified about changes.

def configuration_changed_callback(self):# Configuration changed.    pass
configcatclient.create_client_with_auto_poll("#YOUR-SDK-KEY#", on_configuration_changed_callback=configuration_changed_callback);

Available options:

Option Parameter	Description	Default
poll_interval_seconds	Polling interval.	60
on_configuration_changed_callback	Callback to get notified about changes.	-
max_init_wait_time_seconds	Maximum waiting time between the client initialization and the first config acquisition in secconds.	5
config_cache_class	Custom cache implementation.	None

caution

Auto polling mode utilizes its polling job in a threading.Thread object. If you are running your application behind an uWSGI web server, the auto polling mode may not work as expected, because the uWSGI web server disables Python's threading by default. Please enable threading or switch to another polling mode in this case.

Lazy loading

When calling get_value() the ConfigCat SDK downloads the latest setting values if they are not present or expired in the cache. In this case the get_value() will return the setting value after the cache is updated.

Use cache_time_to_live_seconds option parameter to set cache lifetime.

configcatclient.create_client_with_lazy_load(    "#YOUR-SDK-KEY#", cache_time_to_live_seconds=600);

Use a custom config_cache_class option parameter.

from configcatclient.interfaces import ConfigCacheclass InMemoryConfigCache(ConfigCache):    def __init__(self):        self._value = {}
    def get(self, key):        return self._value.get(key)
    def set(self, key, value):        self._value[key] = value
configcatclient.create_client_with_lazy_load("#YOUR-SDK-KEY#", config_cache_class=InMemoryConfigCache);

Available options:

Option Parameter	Description	Default
cache_time_to_live_seconds	Cache TTL.	60
config_cache_class	Custom cache implementation.	None

Manual polling

Manual polling gives you full control over when the config.json (with the setting values) is downloaded. ConfigCat SDK will not update them automatically. Calling force_refresh() is your application's responsibility.

configcat_client = configcatclient.create_client_with_manual_poll("#YOUR-SDK-KEY#");configcat_client.force_refresh();

Available options:

Option Parameter	Description	Default
config_cache_class	Custom cache implementation.	None

get_value() returns default_value if the cache is empty. Call force_refresh() to update the cache.

configcat_client = configcatclient.create_client_with_manual_poll('#YOUR-SDK-KEY#');value = configcat_client.get_value('key', 'my default value') # Returns "my default value"configcat_client.force_refresh();value = configcat_client.get_value('key', 'my default value') # Returns "value from server"

Logging

In the ConfigCat SDK there is a default logger writes logs to the standard output. The following example shows how to configure the Log Level of the default logger.

import logginglogging.basicConfig(level=logging.INFO)

Available log levels:

Level	Description
ERROR	Only error level events are logged.
WARN	Errors and Warnings are logged.
INFO	Errors, Warnings and feature flag evaluation is logged.
DEBUG	All of the above plus debug info is logged.

Info level logging helps to inspect the feature flag evaluation process:

INFO -- : Evaluating get_value('isPOCFeatureEnabled').INFO -- : Evaluating rule: [Email] [CONTAINS] [@something.com] => no matchINFO -- : Evaluating rule: [Email] [CONTAINS] [@example.com] => match, returning: true

get_all_keys()

You can query the keys from your configuration in the SDK with the get_all_keys() method.

configcat_client = configcatclient.create_client('#YOUR-SDK-KEY#')keys = configcat_client.get_all_keys()

Using ConfigCat behind a proxy

Provide your own network credentials (username/password), and proxy server settings (proxy server/port) by passing the proxy details to the creator method.

proxies = {'https': '127.0.0.1:8080'}proxy_auth = HTTPProxyAuth("user", "password")configcat_client = configcatclient.create_client_with_auto_poll('#YOUR-SDK-KEY#',                                                                proxies=proxies,                                                                proxy_auth=proxy_auth)

Sample Applications

• Sample Console App
• Django Web App

Look under the hood

• ConfigCat's Python SDK on GitHub
• ConfigCat's Python SDK in PyPI