Schematic Ruby SDK

Installation and Setup

Install the Ruby gem:

gem install schematichq

Or add it to your Gemfile:

gem "schematichq"

Then run:

bundle install

Issue an API key for the appropriate environment using the Schematic app. Be sure to capture the secret key when you issue the API key; you'll only see this key once, and this is what you'll use with schematic-ruby.
Using this secret key, initialize a client in your application:

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(api_key: api_key)

# interactions with the client

client.close

By default, the client will do some local caching for flag checks. If you would like to change this behavior, you can do so using an initialization option to specify the max size of the cache (in terms of number of records) and the max age of the cache (in seconds):

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
cache_size = 100
cache_ttl = 1.0 # in seconds
client = Schematic::SchematicClient.new(
  api_key: api_key,
  cache_providers: [
    Schematic::LocalCache.new(max_size: cache_size, ttl: cache_ttl)
  ]
)

# interactions with the client

client.close

You can also disable local caching entirely with an initialization option; bear in mind that, in this case, every flag check will result in a network request:

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(
  api_key: api_key,
  cache_providers: []
)

# interactions with the client

client.close

You may want to specify default flag values for your application, which will be used if there is a service interruption or if the client is running in offline mode (see below). You can do this using an initialization option:

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(
  api_key: api_key,
  flag_defaults: {
    "some-flag-key" => true
  }
)

# interactions with the client

client.close

Custom Logging

You can provide your own logger implementation to control how the Schematic client logs messages. The logger must implement the Schematic::Logger module with error, warn, info, and debug methods:

require "schematichq"

class CustomLogger
  include Schematic::Logger

  def error(message, *args)
    # Your custom error logging logic
  end

  def warn(message, *args)
    # Your custom warning logging logic
  end

  def info(message, *args)
    # Your custom info logging logic
  end

  def debug(message, *args)
    # Your custom debug logging logic
  end
end

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(
  api_key: api_key,
  logger: CustomLogger.new
)

# interactions with the client

client.close

You can also adjust the log level of the built-in console logger via the log_level option:

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(
  api_key: api_key,
  log_level: :debug
)

If no logger is provided, the client will use a default console logger at the :warn level that outputs to stderr. The log_level option only applies to this built-in logger; when you supply your own logger, its level is left untouched.

Usage Examples

A number of these examples use keys to identify companies and users. Learn more about keys here.

Sending identify events

Create or update users and companies using identify events.

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(api_key: api_key)

client.identify({
  company: {
    keys: { "id" => "your-company-id" },
    name: "Acme, Inc.",
    traits: { "city" => "Atlanta" }
  },
  keys: {
    "email" => "wcoyote@acme.net",
    "user_id" => "your-user-id"
  },
  name: "Wile E. Coyote",
  traits: {
    "enemy" => "Bugs Bunny",
    "login_count" => 24,
    "is_staff" => false
  }
})

client.close

This call is non-blocking and there is no response to check.

Sending track events

Track activity in your application using track events; these events can later be used to produce metrics for targeting.

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(api_key: api_key)

client.track({
  event: "some-action",
  company: { "id" => "your-company-id" },
  user: {
    "email" => "wcoyote@acme.net",
    "user_id" => "your-user-id"
  }
})

client.close

This call is non-blocking and there is no response to check.

If you want to record large numbers of the same event at once, or perhaps measure usage in terms of a unit like tokens or memory, you can optionally specify a quantity for your event:

client.track({
  event: "query-tokens",
  company: { "id" => "your-company-id" },
  user: {
    "email" => "wcoyote@acme.net",
    "user_id" => "your-user-id"
  },
  quantity: 1500
})

Event options

Both track and identify accept an options: keyword for optional event metadata. Only fields you set are sent.

client.track(
  { event: "query-tokens", company: { "id" => "your-company-id" }, quantity: 1500 },
  options: {
    # Dedupe key. Duplicate events with the same key are dropped
    # server-side for 24 hours.
    idempotency_key: "evt_2026_05_21_query_tokens",
    # Timestamp the event occurred (Time or ISO 8601 String). Required
    # when trusted_client_clock is true.
    sent_at: Time.now.utc,
    # Use sent_at as the effective event time instead of server receipt
    # time. Requires a secret API key and sent_at.
    trusted_client_clock: true,
    # Import historical data without affecting billing. Requires a secret
    # API key and trusted_client_clock.
    backfill: false
  }
)

client.identify(
  { keys: { "user_id" => "your-user-id" }, name: "Wile E. Coyote" },
  # identify only supports idempotency_key.
  options: { idempotency_key: "ident_your-user-id" }
)

Creating and updating companies

Although it is faster to create companies and users via identify events, if you need to handle a response, you can use the companies API to upsert companies. Because you use your own identifiers to identify companies, rather than a Schematic company ID, creating and updating companies are both done via the same upsert operation:

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(api_key: api_key)

response = client.companies.upsert_company(
  keys: { "id" => "your-company-id" },
  name: "Acme Widgets, Inc.",
  traits: {
    "city" => "Atlanta",
    "high_score" => 25,
    "is_active" => true
  }
)
puts response.data

client.close

You can define any number of company keys; these are used to address the company in the future, for example by updating the company's traits or checking a flag for the company.

You can also define any number of company traits; these can then be used as targeting parameters.

Creating and updating users

Similarly, you can upsert users using the Schematic API, as an alternative to using identify events. Because you use your own identifiers to identify users, rather than a Schematic user ID, creating and updating users are both done via the same upsert operation:

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(api_key: api_key)

response = client.companies.upsert_user(
  keys: {
    "email" => "wcoyote@acme.net",
    "user_id" => "your-user-id"
  },
  company: { "id" => "your-company-id" },
  name: "Wile E. Coyote",
  traits: {
    "city" => "Atlanta",
    "login_count" => 24,
    "is_staff" => false
  }
)
puts response.data

client.close

You can define any number of user keys; these are used to address the user in the future, for example by updating the user's traits or checking a flag for the user.

You can also define any number of user traits; these can then be used as targeting parameters.

Checking flags

When checking a flag, you'll provide keys for a company and/or keys for a user. You can also provide no keys at all, in which case you'll get the default value for the flag.

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(api_key: api_key)

is_flag_on = client.check_flag(
  "some-flag-key",
  company: { "id" => "your-company-id" },
  user: {
    "email" => "wcoyote@acme.net",
    "user_id" => "your-user-id"
  }
)

if is_flag_on
  # Flag is on
else
  # Flag is off
end

client.close

Checking flags with entitlement details

If you need more detail about how a flag check was resolved, including any entitlement associated with the check, use check_flag_with_entitlement. This returns a response object with the flag value, the reason for the evaluation result, and entitlement details such as usage, allocation, and credit balances when applicable.

require "schematichq"

api_key = ENV["SCHEMATIC_API_KEY"]
client = Schematic::SchematicClient.new(api_key: api_key)

resp = client.check_flag_with_entitlement(
  "some-flag-key",
  company: { "id" => "your-company-id" },
  user: {
    "email" => "wcoyote@acme.net",
    "user_id" => "your-user-id"
  }
)

puts "Flag: #{resp.flag_key}, Value: #{resp.value}, Reason: #{resp.reason}"

if resp.entitlement
  puts "Feature allocation: #{resp.feature_allocation}"
  puts "Feature usage: #{resp.feature_usage}"
end

client.close

Credit Leases and Reservations

For features metered by credit burndown (e.g. inference tokens), check reserves credits for the work about to run and track_with_reservation settles the reservation with actual usage. The SDK gates in one of two modes:

Client mode acquires a lease, a tranche of credits held against the company's balance, and carves a per-request reservation out of it locally, so a check needs no API call. It requires DataStream (or Replicator Mode) and, across multiple processes, a shared Redis so every instance gates against the same lease.
Server mode makes one check-and-reserve API call per check. No lease, no Redis, no local state.

credit_leases[:mode] defaults to :auto: client when DataStream is enabled, server otherwise. Client mode suits high-throughput gating; server mode suits low-volume checks and operations that run for seconds.

Durations are in milliseconds, as in the other Schematic SDKs.

Setup

The redis gem is not a dependency; pass a client you already have.

require "redis"
require "schematichq"

redis_client = Redis.new(url: "redis://localhost:6379")

client = Schematic::SchematicClient.new(
  api_key: ENV["SCHEMATIC_API_KEY"],
  use_data_stream: true,
  datastream_options: {
    redis_client: redis_client # also backs lease and reservation state
  },
  credit_leases: {
    default_lease_size: 10_000,           # credits requested per lease
    default_lease_duration: 5 * 60 * 1000, # lease lifetime (ms)
    default_reservation_ttl: 60 * 1000     # how long a reservation is held if no track settles it (ms)
  }
)

Set credit_leases[:redis_client] to keep lease state in a different Redis than the DataStream cache.

Server mode needs only a TTL:

client = Schematic::SchematicClient.new(
  api_key: ENV["SCHEMATIC_API_KEY"],
  credit_leases: {
    default_reservation_ttl: 60 * 1000 # how long the server holds the credits if no track settles them (ms, max 24 hours)
  }
)

Only mode and default_reservation_ttl apply in server mode; the SDK warns at startup if a client-only option is set.

Checking and tracking

# Reserve up to max_tokens for this operation.
result = client.check(
  "inference",
  company: { "id" => "your-company-id" },
  usage: max_tokens,                  # upper bound for this operation
  event_subtype: "inference_tokens"   # the metered event
)
raise "credit balance exceeded" unless result.allowed?

inference = run_inference(...)

# Report actual usage; the unused slice of the reservation is refunded.
if result.reservation
  client.track_with_reservation(result.reservation, inference.tokens_used)
else
  client.track({
    event: "inference_tokens",
    company: { "id" => "your-company-id" },
    quantity: inference.tokens_used
  })
end

A check can allow without reserving credits (the feature is not credit-metered, usage is 0, or the check failed open), and that usage still has to be tracked.

Without credit_leases configured, or without a usage, check falls through to a plain flag check with no reservation. usage is still sent as a preflight, locally or to the API, so the verdict accounts for what the call is about to spend. Preflighted verdicts are not cached.

usage may be fractional. A client-mode reservation is sized in whole event units, ceil(usage) x consumption_rate, and a settle debits the lease by ceil(actual) x consumption_rate, so the local ledger moves by exactly what the track event bills. The reservation still records the fractional quantity the caller declared. Everything on the wire rounds up with the debit: the track event's quantity, a server-mode reservation, and the preflight quantity, whether it goes to the API or the local engine.

result.entitlement is a symbol-keyed hash with the field names of Schematic::Types::FeatureEntitlement, the same in both modes.

An unsettled reservation expires after default_reservation_ttl and its credits return to the lease. A late settle still bills the usage (the track event carries a deterministic idempotency key, so it never double-bills) but does not re-debit the local lease, so set default_reservation_ttl above the longest expected gap between check and track_with_reservation.

Pre-warming

Pre-warm leases when the user is identified, so a session's first check does not wait on a lease acquire:

client.identify(
  {
    keys: { "user_id" => "your-user-id" },
    company: { keys: { "id" => "your-company-id" } }
  },
  prewarm: ["credit-type-id"] # credit type IDs to acquire leases for
)

Or call client.prewarm(credit_type_ids, company:) directly. Both are no-ops in server mode.

Pre-warming resolves the company the way the server does: it looks the keys up first, whatever they are named, and only when nothing matches does it read a value carrying Schematic's comp_ prefix as the company id.

Failure behavior

A check that cannot be gated (API unreachable, Redis down, lease exhausted) fails closed by default. Override per check:

result = client.check(
  "inference",
  company: { "id" => "your-company-id" },
  usage: max_tokens,
  event_subtype: "inference_tokens",
  on_acquire_failure: :fail_open
)

In server mode, a check that times out after the server has already reserved leaves those credits reserved until the TTL expires, so keep default_reservation_ttl short there.

In client mode, :fail_open still evaluates the flag's rules with the credit balance assumed sufficient, so plan targeting and all non-credit conditions apply and only the credit gate is bypassed. In server mode it returns the flag's default value, which is false unless you pass default_value or configure a flag_defaults entry.

default_value also applies when a check falls back to a plain flag check and that check fails. Pass a boolean or a callable.

check accepts timeout_ms, which bounds each attempt of the API calls the check makes (retries still apply) and how long it waits on a lease acquire or extend already in flight.

Configuration options

Option	Type	Default	Description
`mode`	`:client`, `:server`, `:auto`	`:auto`	Where credits are reserved; `:auto` picks client when DataStream is enabled, server otherwise
`default_reservation_ttl`	`Integer`	60000 (60 seconds)	How long an unsettled reservation is held (ms)
`default_lease_duration`	`Integer`	300000 (5 minutes)	(client mode) Lease lifetime (ms)
`default_lease_size`	`Numeric`	10000	(client mode) Credits requested per lease acquire or extend
`low_water_mark`	`Float`	0.25	(client mode) Extend in the background when the lease balance dips below this fraction
`sweep_interval_ms`	`Integer`	1000	(client mode) Sweep interval for expired reservations (ms)
`prewarm_resolve_timeout_ms`	`Integer`	5000	(client mode) How long `prewarm` waits for a freshly identified company to surface (ms); 0 resolves from the DataStream cache only
`redis_client`	Redis client	`datastream_options[:redis_client]`	(client mode) Redis client for lease and reservation state
`redis_key_prefix`	`String`	`datastream_options[:redis_key_prefix]`	(client mode) Key prefix for lease and reservation keys
`overrides`	`Hash`	none	(client mode) Per-credit-type overrides of the above, keyed by credit type ID

Other API operations

The Schematic API supports many operations beyond these, accessible via the API modules on the client: accounts, billing, companies, credits, entitlements, events, features, and plans.

Webhook Verification

Schematic can send webhooks to notify your application of events. To ensure the security of these webhooks, Schematic signs each request using HMAC-SHA256. The SDK provides utility functions to verify these signatures.

Verifying Webhook Signatures

When your application receives a webhook request from Schematic, you should verify its signature to ensure it's authentic:

require "schematichq"

webhook_secret = "your-webhook-secret" # Get this from the Schematic app

# Verify a signature directly
Schematic::Webhooks.verify_signature(payload, signature, timestamp, webhook_secret)
# Raises Schematic::Webhooks::InvalidSignatureError if the signature is invalid
# Raises Schematic::Webhooks::MissingSignatureError if the signature is missing
# Raises Schematic::Webhooks::MissingTimestampError if the timestamp is missing

Computing Signatures

You can compute a hex-encoded signature for a given payload:

hex_sig = Schematic::Webhooks.compute_hex_signature(body, timestamp, secret)

Rack / Rails Integration

The SDK can verify webhook signatures from Rack-compatible request objects (including Rails controllers):

# In a Rails controller
class WebhooksController < ApplicationController
  skip_before_action :verify_authenticity_token

  def create
    webhook_secret = ENV["SCHEMATIC_WEBHOOK_SECRET"]

    begin
      Schematic::Webhooks.verify_webhook_request(request, webhook_secret)

      # Signature is valid, process the webhook
      payload = JSON.parse(request.raw_post)
      # ... handle the event ...

      head :ok
    rescue Schematic::Webhooks::WebhookSignatureError => e
      render json: { error: e.message }, status: :bad_request
    end
  end
end

For a Sinatra application:

require "sinatra"
require "schematichq"

post "/webhooks/schematic" do
  webhook_secret = ENV["SCHEMATIC_WEBHOOK_SECRET"]

  begin
    Schematic::Webhooks.verify_webhook_request(request, webhook_secret)

    payload = JSON.parse(request.body.read)
    request.body.rewind
    # ... handle the event ...

    status 200
    json status: "ok"
  rescue Schematic::Webhooks::WebhookSignatureError => e
    status 400
    json error: e.message
  end
end

Webhook Test Server

The SDK includes a standalone webhook test server for local development:

ruby scripts/webhook_test_server.rb <webhook_secret>
# or
SCHEMATIC_WEBHOOK_SECRET=your-secret ruby scripts/webhook_test_server.rb

This starts a WEBrick server on port 8080 (configurable via PORT env var) that listens for POST requests at /webhook, verifies signatures, and prints the payload.

Context Signatures

A browser SDK uses a publishable key, which anyone can read from your page, so on its own it can't prove which company or user it's acting for. When an environment requires context signatures, the API only accepts a publishable-key request whose company and user your backend has signed with the environment's secret API key. The browser SDK asks your backend for the signature through its getContextSignature option and sends it in the X-Schematic-Context-Sig header.

Signing a context

Sign the logged-in user's own company and user, read from your session. Don't sign whatever company or user the browser asks for, or anyone could get a signature for another company.

require "schematichq"

# In a Rails controller
def schematic_signature
  signature = Schematic::ContextSignature.sign(
    ENV.fetch("SCHEMATIC_SECRET_KEY"),
    company: { "id" => current_user.company_id },
    user: { "id" => current_user.id.to_s }
  )

  render json: { signature: signature }
end

The company and user keys must match the context you give the browser SDK exactly, or the API rejects the signature. Values must be strings. A signature is valid for 10 minutes by default; set a different lifetime, up to an hour, with lifetime_seconds:, and the start time with issued_at:. The browser SDK reuses a signature until shortly before it expires, then asks for a new one. sign raises Schematic::ContextSignature::ContextSignatureError when the secret is missing, the lifetime is out of range, or a key's value isn't a string.

DataStream

DataStream enables local flag evaluation by maintaining a WebSocket connection to Schematic and caching flag rules, company, and user data locally. Flag checks are evaluated using a local WASM rules engine, significantly reducing latency and network calls.

Setup

require "schematichq"

client = Schematic::SchematicClient.new(
  api_key: ENV["SCHEMATIC_API_KEY"],
  use_data_stream: true
)

# Flag checks are now evaluated locally
is_flag_on = client.check_flag(
  "some-flag-key",
  company: { "id" => "your-company-id" }
)

client.close

Configuration Options

You can customize DataStream behavior via the datastream_options hash:

Option	Type	Default	Description
`cache_ttl`	`Integer`	86400 (24 hours)	Cache TTL in seconds
`replicator_mode`	`Boolean`	`false`	Enable replicator mode (see below)
`replicator_health_url`	`String`	`http://localhost:8090/ready`	URL to poll for replicator health
`replicator_health_interval`	`Integer`	30	Health check interval in seconds
`max_frame_size`	`Integer`	20971520 (20 MB)	Maximum size, in bytes, of a single incoming WebSocket frame

require "schematichq"

client = Schematic::SchematicClient.new(
  api_key: ENV["SCHEMATIC_API_KEY"],
  use_data_stream: true,
  datastream_options: {
    cache_ttl: 3600 # 1 hour
  }
)

Frame size limit

DataStream sends the full flag set as a single WebSocket frame on connect. If that frame exceeds the limit, the SDK cannot decode it and logs an error naming the limit; raise max_frame_size to accept a larger payload.

client = Schematic::SchematicClient.new(
  api_key: ENV["SCHEMATIC_API_KEY"],
  use_data_stream: true,
  datastream_options: {
    max_frame_size: 64 * 1024 * 1024 # 64 MB
  }
)

The underlying websocket gem stores this limit in a module-level global (WebSocket.max_frame_size), so it has no per-connection setting. The SDK leaves that global alone unless you pass max_frame_size, and when you do it only ever raises the limit, never lowers it, so it cannot shrink the ceiling for other WebSocket users in the same process.

Replicator Mode

When running the schematic-datastream-replicator service, you can configure the Schematic client to operate in Replicator Mode. In this mode, the client reads from a shared cache populated by the external replicator rather than establishing its own WebSocket connection.

Setup

require "schematichq"

client = Schematic::SchematicClient.new(
  api_key: ENV["SCHEMATIC_API_KEY"],
  use_data_stream: true,
  datastream_options: {
    replicator_mode: true,
    replicator_health_url: "http://localhost:8090/ready",
    replicator_health_interval: 30
  }
)

# Flag checks use the shared cache
is_flag_on = client.check_flag(
  "some-flag-key",
  company: { "id" => "your-company-id" }
)

client.close

When running in Replicator Mode, the client will:

Skip establishing WebSocket connections
Periodically check if the replicator service is ready
Use cached data populated by the external replicator service
Fall back to direct API calls if the replicator is not available

Testing

Offline Mode

In development or testing environments, you may want to avoid making network requests to the Schematic API. You can run Schematic in offline mode by specifying the offline option; in this case, it does not matter what API key you specify:

require "schematichq"

client = Schematic::SchematicClient.new(offline: true)

client.close

You can also enable offline mode by not providing an API key:

require "schematichq"

client = Schematic::SchematicClient.new
# Logs a warning and automatically enables offline mode

client.close

Offline mode works well with flag defaults:

require "schematichq"

client = Schematic::SchematicClient.new(
  offline: true,
  flag_defaults: { "some-flag-key" => true }
)

# interactions with the client

client.close

In an automated testing context, you may also want to use offline mode and specify single flag responses for test cases:

require "schematichq"

# In your test setup
client = Schematic::SchematicClient.new(offline: true)
client.set_flag_default("some-flag-key", true)

# test code that expects the flag to be on
assert client.check_flag("some-flag-key")

client.close

Errors

Failed API calls will raise errors that can be rescued from granularly:

require "schematichq"

client = Schematic::SchematicClient.new(api_key: ENV["SCHEMATIC_API_KEY"])

begin
  result = client.accounts.create_api_key(name: "name")
rescue Schematic::Errors::TimeoutError
  puts "API didn't respond before our timeout elapsed"
rescue Schematic::Errors::ServiceUnavailableError
  puts "API returned status 503, is probably overloaded, try again later"
rescue Schematic::Errors::ServerError
  puts "API returned some other 5xx status, this is probably a bug"
rescue Schematic::Errors::ResponseError => e
  puts "API returned an unexpected status other than 5xx: #{e.code} #{e.message}"
rescue Schematic::Errors::ApiError => e
  puts "Some other error occurred when calling the API: #{e.message}"
end

Note that check_flag and check_flag_with_entitlement never raise exceptions -- errors are logged and default values are returned.

Advanced

Retries

The SDK is instrumented with automatic retries. A request will be retried as long as the request is deemed retryable and the number of retry attempts has not grown larger than the configured retry limit (default: 2).

A request is deemed retryable when any of the following HTTP status codes is returned:

408 (Timeout)
429 (Too Many Requests)
5XX (Internal Server Errors)

Use the max_retries option to configure this behavior:

require "schematichq"

client = Schematic::SchematicClient.new(
  api_key: ENV["SCHEMATIC_API_KEY"],
  max_retries: 3 # Configure max retries (default is 2)
)

Timeouts

The SDK defaults to a 60 second timeout. Use the timeout option to configure this behavior:

response = client.accounts.create_api_key(
  name: "name",
  timeout: 30 # 30 second timeout
)

Reference

A full reference for the underlying API library is available here.

Contributing

While we value open-source contributions to this SDK, this library is generated programmatically. Additions made directly to this library would have to be moved over to our generation code, otherwise they would be overwritten upon the next generated release. Feel free to open a PR as a proof of concept, but know that we will not be able to merge it as-is. We suggest opening an issue first to discuss with us!

On the other hand, contributions to the README are always very welcome!

Name		Name	Last commit message	Last commit date
.claude		.claude
.fern		.fern
.github		.github
conformance		conformance
lib		lib
scripts		scripts
test		test
testapp		testapp
.fernignore		.fernignore
.gitattributes		.gitattributes
.gitignore		.gitignore
.rubocop.yml		.rubocop.yml
CLAUDE.md		CLAUDE.md
CONTRIBUTING.md		CONTRIBUTING.md
Gemfile		Gemfile
Gemfile.custom		Gemfile.custom
LICENSE		LICENSE
README.md		README.md
Rakefile		Rakefile
WASM_VERSION		WASM_VERSION
custom.gemspec.rb		custom.gemspec.rb
reference.md		reference.md
schematic.gemspec		schematic.gemspec

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Schematic Ruby SDK

Installation and Setup

Custom Logging

Usage Examples

Sending identify events

Sending track events

Event options

Creating and updating companies

Creating and updating users

Checking flags

Checking flags with entitlement details

Credit Leases and Reservations

Setup

Checking and tracking

Pre-warming

Failure behavior

Configuration options

Other API operations

Webhook Verification

Verifying Webhook Signatures

Computing Signatures

Rack / Rails Integration

Webhook Test Server

Context Signatures

Signing a context

DataStream

Setup

Configuration Options

Frame size limit

Replicator Mode

Setup

Testing

Offline Mode

Errors

Advanced

Retries

Timeouts

Reference

Contributing

About

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