Github Repository Setup the SDK
Install the SDK
Install the sdk using pip3:The Statsig SDK is not compatible with python 2. You must be on python 3.7+ to use the Statsig SDK.
Initialize the SDK
After installation, you will need to initialize the SDK using a Server Secret Key from the Statsig console.Do NOT embed your Server Secret Key in client-side applications, or expose it in any external-facing documents. However, if you accidentally expose it, you can create a new one in the Statsig console.
options that allows you to pass in a StatsigOptions to customize the SDK.from statsig import statsig statsig.initialize("server-secret-key") # or with StatsigOptions options = StatsigOptions(tier=StatsigEnvironmentTier.development) statsig.initialize("server-secret-key", options) # check if sdk is initialized initialized = statsig.is_initialized()
initialize will perform a network request. After initialize completes, virtually all SDK operations will be synchronous (See Evaluating Feature Gates in the Statsig SDK). The SDK will fetch updates from Statsig in the background, independently of your API calls. Working with the SDK
Checking a Feature Flag/Gate
Now that your SDK is initialized, let’s fetch a Feature Gate. Feature Gates can be used to create logic branches in code that can be rolled out to different users from the Statsig Console. Gates are always CLOSED or OFF (think return false;) by default. From this point on, all APIs will require you to specify the user (see Statsig user) associated with the request. For example, check a gate for a certain user like this: from statsig.statsig_user import StatsigUser ... statsig.check_gate(StatsigUser("user-id"), "gate-name")
Reading a Dynamic Config
Feature Gates can be very useful for simple on/off switches, with optional but advanced user targeting. However, if you want to be able send a different set of values (strings, numbers, and etc.) to your clients based on specific user attributes, e.g. country, Dynamic Configs can help you with that. The API is very similar to Feature Gates, but you get an entire json object you can configure on the server and you can fetch typed parameters from it. config = statsig.get_config(StatsigUser("user-id"), "config-name") config_json = config.get_value()
Getting a Layer/Experiment
Then we have Layers/Experiments, which you can use to run A/B/n experiments. We offer two APIs, but we recommend the use of layers to enable quicker iterations with parameter reuse. # Values via getLayer layer = statsig.get_layer(user, "user_promo_experiments") title = layer.get("title", "Welcome to Statsig!") discount = layer.get("discount", 0.1) # or, via getExperiment title_exp = statsig.get_experiment(user, "new_user_promo_title") price_exp = statsig.get_experiment(user, "new_user_promo_price") title = title_exp.get("title", "Welcome to Statsig!") discount = price_exp.get("discount", 0.1) ... price = msrp * (1 - discount)
gate = statsig.get_feature_gate(StatsigUser("user-id"), "gate-name") print(gate.name) # 'gate-name' print(gate.value) # True or False print(gate.rule_id) # rule ID that was evaluated print(gate.evaluation_details) # evaluation metadata
Logging an Event
Now that you have a Feature Gate or an Experiment set up, you may want to track some custom events and see how your new features or different experiment groups affect these events. This is super easy with Statsig - simply call the Log Event API and specify the user and event name to log; you additionally provide some value and/or an object of metadata to be logged together with the event: from statsig.statsig_user import StatsigUser from statsig.statsig_event import StatsigEvent statsig.log_event(StatsigEvent(StatsigUser("user-id"), "event-name"))
retry_queue_size, which allows you to adjust the memory allocated for handling retries. While service outages are rare, increasing the retry_queue_size can help minimize event loss by providing additional memory to buffer events during such occurrences. This option is generally not needed for typical use but offers added flexibility in exceptional situations. Statsig User
When calling APIs that require a user, you should pass as much information as possible in order to take advantage of advanced gate and config conditions (like country or OS/browser level checks), and correctly measure impact of your experiments on your metrics/events. At least one identifier, either userID or a Custom ID, is required to provide a consistent experience for a given user (as explained here). Besides userID, we also have email, ip, userAgent, country, locale and appVersion as top-level fields on StatsigUser. In addition, you can pass any key-value pairs in an object/dictionary to the custom field and be able to create targeting based on them. Note that while typing is lenient on the StatsigUser object to allow you to pass in numbers, strings, arrays, objects, and potentially even enums or classes, the evaluation operators will only be able to operate on primitive types - mostly strings and numbers. While we attempt to smartly cast custom field types to match the operator, we cannot guarantee evaluation results for other types. For example, setting an array as a custom field will only ever be compared as a string - there is no operator to match a value in that array. Private Attributes
Have sensitive user PII data that should not be logged? No problem, we have a solution for it! On the StatsigUser object we also have a field called privateAttributes, which is a simple object/dictionary that you can use to set private user attributes. Any attribute set in privateAttributes will only be used for evaluation/targeting, and removed from any logs before they are sent to Statsig server. For example, if you have feature gates that should only pass for users with emails ending in “@statsig.com”, but do not want to log your users’ email addresses to Statsig, you can simply add the key-value pair { email: "my_user@statsig.com" } to privateAttributes on the user and that’s it! Statsig Options
initialize() takes an optional parameter options in addition to the secret key that you can provide to customize the Statsig client. Here are the current options and we are always adding more to the list: Create a StatsigOptions class to pass in with the following available parameters: (unit of measure for time related options is seconds) tier
StatsigEnvironmentTier | str
default:"None"
Sets the environment tier (for gates to evaluate differently in development and production)You can set an environment tier with the StatsigEnvironmentTier enum or just as a str
Enforces a minimum timeout on network requests from the SDK
Sets the maximum timeout on download config specs and id lists network requests for initialization
How often the SDK updates rulesets from Statsig servers
How often the SDK updates idlists from Statsig servers
Disables all network requests. SDK returns default values and will not log events. Useful in combination with overrides to mock behavior for tests
a string that represents all rules for all feature gates, dynamic configs and experiments. It can be provided to bootstrap the Statsig server SDK at initialization in case your server runs into network issue or Statsig server is down temporarily.
rules_updated_callback
typing.Callable
default:"None"
a callback function that’s called whenever we have an update for the rules; it’s called with a logical timestamp and a JSON string (used as is for bootstrapValues mentioned above). Note that as of v0.6.0, this will be called from a background thread that the SDK uses to update config values.
The number of events to batch before flushing the queue to the network. Default 500.Note that events are also batched every minute by a background thread
A data store with custom storage behavior for config specs. Can be used to bootstrap Statsig server (takes priority over bootstrap_values).
proxy_configs
Optional[Dict[NetworkEndpoint, ProxyConfig]]
default:"None"
Configuration network for each endpoint, for example, download_config_spec, get_id_lists
fallback_to_statsig_api
Optional[bool]
default:"False"
Fallback to Statsig CDN for download config specs and get id lists if the overridden api failed.
initialize_sources
Optional[List[DataSource]]
default:"None"
List of sources SDK tries to get download_config_specs from when initialize. The list is ordered, SDK tries to get source from first element, and stops when getting dcs successfully
config_sync_sources
Optional[List[DataSource]]
default:"None"
List of sources SDK tries to get download_config_specs from when downloading. The list is ordered, SDK tries to get source from first element, and stops when getting dcs successfully
from statsig import statsig, StatsigEnvironmentTier, StatsigOptions options = StatsigOptions(None, StatsigEnvironmentTier.development) statsig.initialize("secret-key", options).wait()
set_environment_parameter function, but that takes in string values only: from statsig import statsig, StatsigEnvironmentTier, StatsigOptions options = StatsigOptions() options.set_environment_parameter("tier", StatsigEnvironmentTier.development.value) statsig.initialize("secret-key", options).wait()
Shutdown
To gracefully shutdown the SDK and ensure all events are flushed: Client SDK Bootstrapping
The Statsig server SDK can be used to generate the initialization values for a client SDK. This is useful for server-side rendering (SSR) or when you want to pre-fetch values for a client. values = statsig.get_client_initialize_response(user); # dict() | None # To apply local overrides, set include_local_overrides = True (python sdk v0.32.0+) values = statsig.get_client_initialize_response(user=user, include_local_overrides=True); # dict() | None
Local Overrides
You can override the values returned by the SDK for testing purposes. This can be useful for local development when you want to test specific scenarios. # Adding/Removing gate overrides statsig.override_gate("a_gate_name", true, "a_user_id") statsig.remove_gate_override("a_gate_name", "a_user_id") # Adding/Removing config overrides statsig.override_config("a_config_name", {"key": "value"}, "a_user_id") statsig.remove_config_override("a_config_name", "a_user_id") # Adding/Removing experiment overrides statsig.override_experiment("an_experiment_name", {"key": "value"}, "a_user_id") statsig.remove_experiment_override("an_experiment_name", "a_user_id") # Remove All Overrides statsig.remove_all_overrides() # You can also override with custom ids custom_id_user = StatsigUser("a_user_id", custom_ids={"statsigId": "a_statsig_id"}) statsig.override_gate("a_gate_name", true, "a_statsig_id") # Local overrides will prioritize override with userId, then look up the custom id to override. # To prevent clashing overrides, it is recommended to not use the same value for userId and customIds for different users.
Multi-Instance Usage
If you need to create multiple independent instances of the Statsig SDK (for example, to use different API keys or configurations), you can use the instance-based approach: sdk_instance = StatsigServer() sdk_instance.initialize(secret_key, options);
Forward Proxy Configuration
You can configure the SDK to use a forward proxy for network requests: Basic setup to stream download config spec from forward proxy: proxyAddress = "0.0.0.0:50051" // local address update to your address Statsig.initialize(secret_key, StatsigOptions(proxy_configs={ NetworkEndpoint.DOWNLOAD_CONFIG_SPECS: ProxyConfig(NetworkProtocol.GRPC_WEBSOCKET, proxyAddress)}))
push_worker_failover_threshold retries, the sdk will start polling from Statsig until reconnecting to the forward proxy. You can customize Streaming Failover Behavior. You can also define the sources/endpoints SDK poll from, SDK will try from source at index 0, and stops trying if get a response. statsigOptions = StatsigOptions( proxy_configs={ NetworkEndpoint.DOWNLOAD_CONFIG_SPECS: ProxyConfig( protocol=NetworkProtocol.GRPC_WEBSOCKET, proxy_address=address, push_worker_failover_threshold=1, # start polling from Statsig endpoint after 1 retry failed # 1st retry 5000 ms later, 2nd retry 2 * 5000ms = 10 seconds .... retry_backoff_multiplier=2, max_retry_attempt=8, retry_backoff_base_ms=5000 ) }, # Get from network first, which is forward proxy here, if fails, try datastore, if fails try poll from Statsig endpoint initialize_sources=[ DataSource.NETWORK, DataSource.DATASTORE, DataSource.STATSIG_NETWORK, ], )
FAQs
How can I mock Statsig for testing?
The python server SDK, starting in version 0.5.1+, supports a few features to make testing easier. First, there is a StatsigOption parameter called localMode. Setting localMode to true will cause the SDK to never hit the network, and only return default values. This is perfect for dummy environments or test environments that should not access the network. Next, there are the overrideGate and overrideConfig APIs on the global statsig interface, see Local Overrides These can be used to set a gate or config override for a specific user, or for all users (by not providing a specific user ID). We suggest you enable localMode and then override gates/configs/experiments to specific values to test the various code flows you are building. Can I generate the initialize response for a client SDK using the Python server SDK?
Yes. See Client Initialize Response. Reference
StatsigUser
@dataclass class StatsigUser: """An object of properties relating to the current user user_id or at least a custom ID is required: learn more https://docs.statsig.com/concepts/user#why-is-an-id-always-required-for-server-sdks Provide as many as possible to take advantage of advanced conditions in the statsig console A dictionary of additional fields can be provided under the custom field Set private_attributes for any user property you need for gate evaluation but prefer stripped from logs/metrics """ user_id: Optional[str] = None email: Optional[str] = None ip: Optional[str] = None user_agent: Optional[str] = None country: Optional[str] = None locale: Optional[str] = None app_version: Optional[str] = None custom: Optional[dict] = None # key: string, value: string private_attributes: Optional[dict] = None # key: string, value: string custom_ids: Optional[dict] = None # key: string, value: string
StatsigOptions
class StatsigOptions: """An object of properties for initializing the sdk with additional parameters""" def __init__( self, api: Optional[str] = None, api_for_download_config_specs: Optional[str] = None, api_for_get_id_lists: Optional[str] = None, api_for_log_event: Optional[str] = None, tier: Union[str, StatsigEnvironmentTier, None] = None, init_timeout: Optional[int] = None, timeout: Optional[int] = None, rulesets_sync_interval: int = DEFAULT_RULESET_SYNC_INTERVAL, idlists_sync_interval: int = DEFAULT_IDLIST_SYNC_INTERVAL, local_mode: bool = False, bootstrap_values: Optional[str] = None, rules_updated_callback: Optional[Callable] = None, event_queue_size: Optional[int] = DEFAULT_EVENT_QUEUE_SIZE, data_store: Optional[IDataStore] = None, idlists_thread_limit: int = DEFAULT_IDLISTS_THREAD_LIMIT, logging_interval: int = DEFAULT_LOGGING_INTERVAL, #deprecated disable_diagnostics: bool = False, custom_logger: Optional[OutputLogger] = None, enable_debug_logs = False, disable_all_logging = False, evaluation_callback: Optional[Callable[[Union[Layer, DynamicConfig, FeatureGate]], None]] = None, retry_queue_size: int = DEFAULT_RETRY_QUEUE_SIZE, proxy_configs: Optional[Dict[NetworkEndpoint, ProxyConfig]] = None, fallback_to_statsig_api: Optional[bool] = False, initialize_sources: Optional[List[DataSource]] = None, config_sync_sources: Optional[List[DataSource]] = None, ):
FeatureGate
class FeatureGate: def get_value(self): """Returns the underlying value of this FeatureGate""" def get_name(self): """Returns the name of this FeatureGate""" def get_evaluation_details(self): """Returns the evaluation detail of this FeatureGate"""
DynamicConfig
class DynamicConfig: def get(self, key, default=None): """Returns the value of the config at the given key or the provided default if the key is not found """ def get_typed(self, key, default=None): """Returns the value of the config at the given key iff the type matches the type of the provided default. Otherwise, returns the default value """ def get_value(self): """Returns the underlying value of this DynamicConfig""" def get_name(self): """Returns the name of this DynamicConfig""" def get_evaluation_details(self): """Returns the evaluation detail of this DynamicConfig"""
Layer
class Layer: def get(self, key, default=None): """Returns the value of the layer at the given key or the provided default if the key is not found """ def get_typed(self, key, default=None): """Returns the value of the layer at the given key iff the type matches the type of the provided default. Otherwise, returns the default value """ def get_name(self): """Returns the name of this Layer""" def get_values(self): """Returns all the values in this Layer but does not trigger an exposure log""" def get_evaluation_details(self): """Returns the evaluation detail of this Layer"""
EvaluationDetails
class EvaluationDetails: reason: EvaluationReason config_sync_time: int init_time: int server_time: int class EvaluationReason(str, Enum): network = "Network" local_override = "LocalOverride" unrecognized = "Unrecognized" uninitialized = "Uninitialized" bootstrap = "Bootstrap" data_adapter = "DataAdapter" unsupported = "Unsupported" error = "error"
DataStore
class IDataStore: def get(self, key: str) -> Optional[str]: return None def set(self, key: str, value: str): pass def shutdown(self): pass def should_be_used_for_querying_updates(self, key: str) -> bool: return False
ForwardProxy - ProxyConfig
class NetworkProtocol(Enum): HTTP = "http" GRPC = "grpc" GRPC_WEBSOCKET = "grpc_websocket" class NetworkEndpoint(Enum): LOG_EVENT = "log_event" DOWNLOAD_CONFIG_SPECS = "download_config_specs" GET_ID_LISTS = "get_id_lists" ALL = "all" class ProxyConfig: def __init__( self, protocol: NetworkProtocol, proxy_address: str, # Websocket worker failover config max_retry_attempt: Optional[int] = None, # default is 10 retry_backoff_multiplier: Optional[int] = None, # default is # default is 5 retry_backoff_base_ms: Optional[int] = None, # default is 10,000 ms # Push worker failback to polling threshold, fallback immediate set 0, # n means fallback after n retry failed push_worker_failover_threshold: Optional[int] = None, # default is 4, about 30 minutes ): self.proxy_address = proxy_address self.protocol = protocol self.max_retry_attempt = max_retry_attempt self.retry_backoff_multiplier = retry_backoff_multiplier self.retry_backoff_base_ms = retry_backoff_base_ms self.push_worker_failover_threshold = push_worker_failover_threshold
