logbrew-sdk 0.1.2

Public LogBrew Python SDK for building, validating, and flushing event batches.

logbrew-sdk

Public Python SDK for creating LogBrew event batches, validating them locally, and flushing them through a transport.

Install

python3 -m pip install logbrew-sdk

The package includes py.typed, public type aliases such as ReleaseAttributes, SpanAttributes, MetricAttributes, and TraceparentContext, and copyable examples for wiring LogBrew into your Python service. Keep the real key in your app configuration and use preview_json() when you want to inspect queued JSON before sending.

Example

import json
import sys

from logbrew_sdk import LogBrewClient, RecordingTransport

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="logbrew-python",
    sdk_version="0.1.0",
)

client.release(
    "evt_release_001",
    "2026-06-02T10:00:00Z",
    {
        "version": "1.2.3",
        "commit": "abc123def456",
        "notes": "Public release marker",
    },
)
client.environment(
    "evt_environment_001",
    "2026-06-02T10:00:01Z",
    {"name": "production", "region": "global"},
)
client.issue(
    "evt_issue_001",
    "2026-06-02T10:00:02Z",
    {
        "title": "Checkout timeout",
        "level": "error",
        "message": "Request timed out after retry budget",
    },
)
client.log(
    "evt_log_001",
    "2026-06-02T10:00:03Z",
    {"message": "worker started", "level": "info", "logger": "job-runner"},
)
client.span(
    "evt_span_001",
    "2026-06-02T10:00:04Z",
    {
        "name": "GET /health",
        "traceId": "trace_001",
        "spanId": "span_001",
        "status": "ok",
        "durationMs": 12.5,
    },
)
client.action(
    "evt_action_001",
    "2026-06-02T10:00:05Z",
    {"name": "deploy", "status": "success"},
)

print(client.preview_json())

transport = RecordingTransport.always_accept()
response = client.shutdown(transport)
print(
    json.dumps(
        {"ok": True, "status": response.status_code, "attempts": response.attempts, "events": 6}
    ),
    file=sys.stderr,
)

Use a clearly fake placeholder like LOGBREW_API_KEY in examples. Call flush() or shutdown() to send queued events through a transport, and use preview_json() when you want a stable local JSON preview before sending anything.

First Useful Telemetry

For a new Python service, capture a small set of signals that explain what changed, where the service ran, what the user or job attempted, which outbound dependency mattered, how long it took, and how the request links to a distributed trace:

import logging

from logbrew_sdk import (
    LogBrewClient,
    LogBrewLoggingHandler,
    RecordingTransport,
    create_network_milestone_attributes,
    create_product_action_attributes,
    span_attributes_from_traceparent,
)

traceparent = "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01"
trace_id = "4bf92f3577b34da6a3ce929d0e0e4736"
route_template = "/checkout/:cart_id"

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-api",
    sdk_version="1.4.0",
)
client.release(
    "evt_release_checkout_api",
    "2026-06-15T08:00:00Z",
    {"version": "1.4.0", "commit": "abc123def456"},
)
client.environment(
    "evt_environment_checkout_api",
    "2026-06-15T08:00:01Z",
    {"name": "production", "region": "us-east-1"},
)

logger = logging.getLogger("checkout-api")
logger.addHandler(LogBrewLoggingHandler(client, metadata={"service": "checkout-api"}))
logger.setLevel(logging.INFO)
logger.info("checkout request accepted", extra={"routeTemplate": route_template, "traceId": trace_id})

client.action(
    "evt_action_checkout_started",
    "2026-06-15T08:00:03Z",
    create_product_action_attributes(
        {
            "name": "checkout started",
            "status": "running",
            "sessionId": "sess_checkout_123",
            "traceId": trace_id,
            "routeTemplate": route_template,
            "funnel": "checkout",
            "step": "payment",
        }
    ),
)
client.action(
    "evt_network_payment_authorized",
    "2026-06-15T08:00:04Z",
    create_network_milestone_attributes(
        {
            "routeTemplate": "/payments/:payment_id",
            "method": "POST",
            "statusCode": 202,
            "durationMs": 43,
            "sessionId": "sess_checkout_123",
            "traceId": trace_id,
        }
    ),
)
client.metric(
    "evt_metric_checkout_duration",
    "2026-06-15T08:00:05Z",
    {
        "name": "checkout.duration",
        "kind": "histogram",
        "value": 128,
        "unit": "ms",
        "temporality": "delta",
        "metadata": {"routeTemplate": route_template, "traceId": trace_id},
    },
)
client.span(
    "evt_span_checkout_request",
    "2026-06-15T08:00:06Z",
    span_attributes_from_traceparent(
        traceparent,
        name="POST /checkout/:cart_id",
        span_id="b7ad6b7169203331",
        status="ok",
        duration_ms=17,
        metadata={"routeTemplate": route_template, "service": "checkout-api"},
    ),
)
client.shutdown(RecordingTransport.always_accept())

The packaged example prints a local JSON preview of this flow:

python -m logbrew_sdk.examples first-useful-telemetry

This path is intentionally app-owned. It uses Python's standard logging module, explicit W3C traceparent continuation, and explicit product, network, and metric helpers. It does not patch global HTTP clients, does not collect request or response bodies, does not capture arbitrary headers, and timeline helpers strip query strings and hashes from route templates.

Support Ticket Drafts

Use create_support_ticket_draft() when a user or agent explicitly asks to prepare a support ticket payload. The helper is local-only: it validates the planned public support-ticket fields, redacts diagnostics, and returns a dictionary. It does not send data, open a ticket, use account/session API credentials, or call backend support routes.

from logbrew_sdk import create_support_ticket_draft

draft = create_support_ticket_draft(
    source="sdk",
    category="sdk_install_failure",
    title="Python import fails after install",
    description="Wheel installs, but the app cannot import logbrew_sdk.",
    environment="production",
    runtime="python 3.13",
    framework="fastapi",
    sdk_package="logbrew-sdk",
    sdk_version="0.1.2",
    release="checkout-api@1.4.0",
    trace_id="4bf92f3577b34da6a3ce929d0e0e4736",
    diagnostics={
        "install_command": "python3 -m pip install logbrew-sdk",
        "endpoint": "https://api.example.com/v1/events?debug=true",
        "authorization": "Bearer hidden",
        "local_path": "/Users/example/service/app.py",
        "error": RuntimeError("private failure message"),
    },
)

The returned draft keeps only structured JSON-like diagnostics. Auth-like keys, cookies, tokens, URL origins, local paths, unsupported objects, and exception messages/stacks are redacted or omitted before the dictionary is returned.

Metrics

Use metric() for explicit, application-owned measurements. LogBrew validates the metric name, kind, value, unit, temporality, and optional metadata before queueing the event:

from logbrew_sdk import LogBrewClient

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="logbrew-python",
    sdk_version="0.1.0",
)

client.metric(
    "evt_metric_queue_depth",
    "2026-06-02T10:00:06Z",
    {
        "name": "queue.depth",
        "kind": "gauge",
        "value": 42,
        "unit": "{items}",
        "temporality": "instant",
        "metadata": {"service": "worker"},
    },
)

Supported metric kinds are counter, gauge, and histogram. Counters and histograms require delta or cumulative temporality and non-negative values; gauges require instant temporality and may be negative. Keep metadata low-cardinality and primitive. This SDK does not automatically collect runtime or framework metrics yet.

Trace Context

Use the W3C helpers when a Python service needs to interoperate with distributed tracing headers:

from logbrew_sdk import (
    create_logbrew_trace_context,
    create_traceparent_headers,
    parse_traceparent,
    span_attributes_from_trace_context,
    trace_metadata,
    use_logbrew_trace,
)

traceparent = "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01"
context = parse_traceparent(traceparent)
trace = create_logbrew_trace_context(traceparent, span_id="b7ad6b7169203331")
attributes = span_attributes_from_trace_context(
    trace,
    name="GET /health",
    status="ok",
    duration_ms=12.5,
    metadata={"service": "checkout"},
)
headers = create_traceparent_headers(
    trace_id=attributes["traceId"],
    span_id=attributes["spanId"],
    trace_flags="01",
)
with use_logbrew_trace(trace):
    metadata = trace_metadata()

parse_traceparent() validates W3C shape, rejects all-zero trace/span IDs, normalizes IDs to lowercase, and exposes the sampled flag. create_logbrew_trace_context() creates the request-local LogBrewTraceContext used to correlate request spans, app-owned logs, issues, actions, metrics, and outgoing milestones with one safe set of IDs. use_logbrew_trace() makes that context available through trace_metadata() and get_active_logbrew_trace() during framework handler work, including async work that keeps Python contextvars. create_traceparent_headers() returns an explicit outbound carrier with only traceparent for app-owned HTTP clients. FastAPI and Django integrations use these helpers automatically for valid inbound traceparent headers and start a fresh W3C-shaped local trace when the header is missing or malformed. The helpers do not patch HTTP clients or capture request payloads, headers, cookies, query strings, or the raw traceparent value.

Outbound HTTP Client Spans

Use urlopen_with_logbrew_span() when you want one dependency-free outbound HTTP client span around an app-owned urllib.request call:

from urllib.request import Request

from logbrew_sdk import LogBrewClient, urlopen_with_logbrew_span

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-api",
    sdk_version="1.0.0",
)

response = urlopen_with_logbrew_span(
    Request("https://api.example.com/payments/123?coupon=summer", method="GET"),
    client=client,
    event_id="evt_payment_lookup",
    timestamp="2026-06-19T08:00:00Z",
    route_template="/payments/:payment_id",
    metadata={"service": "checkout-api"},
)

The helper clones the caller request, writes exactly one normalized W3C traceparent, runs the opener under a child LogBrewTraceContext, queues one span with method, query-free route, status, duration, and primitive metadata, then returns the original response or re-raises the original HTTP/network error. Telemetry capture failures are reportable through on_capture_error and do not replace the app-owned HTTP result. It does not patch urllib, does not capture request or response payloads, does not store headers, cookies, query strings, fragments, baggage, tracestate, or raw propagation values.

For apps that use requests, use requests_request_with_logbrew_span() with your own requests.Session or request callable. LogBrew does not add requests as a dependency and does not monkeypatch the library:

import requests

from logbrew_sdk import LogBrewClient, requests_request_with_logbrew_span

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-api",
    sdk_version="1.0.0",
)
session = requests.Session()

response = requests_request_with_logbrew_span(
    "POST",
    "https://api.example.com/payments/123?coupon=summer",
    client=client,
    event_id="evt_payment_submit",
    timestamp="2026-06-19T08:00:03Z",
    session=session,
    timeout=3.5,
    headers={"x-caller": "checkout-api"},
    json={"amount": 42},
    route_template="/payments/:payment_id",
    metadata={"service": "checkout-api"},
)

The requests helper clones caller headers, replaces any caller-supplied traceparent with one normalized child header, runs the request under that child trace context, queues one sanitized dependency span, and returns the original requests.Response or re-raises the original exception. It records method, route template, status code, duration, sampled flag, and primitive metadata only. It does not capture payloads, response bodies, headers, cookies, full URLs, query strings, fragments, baggage, tracestate, or raw propagation values.

For apps that use httpx, use httpx_request_with_logbrew_span() for sync calls or async_httpx_request_with_logbrew_span() for async calls. LogBrew does not add httpx as a dependency and does not patch httpx.Client, httpx.AsyncClient, or transports:

import httpx

from logbrew_sdk import (
    LogBrewClient,
    async_httpx_request_with_logbrew_span,
    httpx_request_with_logbrew_span,
)

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-api",
    sdk_version="1.0.0",
)

with httpx.Client() as session:
    response = httpx_request_with_logbrew_span(
        "POST",
        "https://api.example.com/payments/123?coupon=summer",
        client=client,
        event_id="evt_payment_submit",
        timestamp="2026-06-19T09:00:00Z",
        session=session,
        timeout=3.5,
        headers={"x-caller": "checkout-api"},
        json={"amount": 42},
        route_template="/payments/:payment_id",
        metadata={"service": "checkout-api"},
    )

async def submit_payment(async_session: httpx.AsyncClient) -> httpx.Response:
    return await async_httpx_request_with_logbrew_span(
        "POST",
        "https://api.example.com/payments/123?coupon=summer",
        client=client,
        event_id="evt_payment_submit_async",
        timestamp="2026-06-19T09:00:01Z",
        session=async_session,
        timeout=3.5,
        route_template="/payments/:payment_id",
        metadata={"service": "checkout-api"},
    )

The httpx helpers follow the same privacy and failure behavior as the requests helper: cloned caller headers, exactly one normalized child traceparent, active child trace context during the call or awaited call, sanitized dependency span capture, original response/error preservation, and optional on_capture_error reporting for telemetry failures. They do not capture payloads, response bodies, headers, cookies, full URLs, query strings, fragments, baggage, tracestate, or raw propagation values.

Database Operation Spans

Use database_operation_with_logbrew_span() for sync database calls and async_database_operation_with_logbrew_span() for async calls when you want one app-owned DB span without installing or patching a database driver:

from logbrew_sdk import LogBrewClient, database_operation_with_logbrew_span

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-api",
    sdk_version="1.0.0",
)

result = database_operation_with_logbrew_span(
    "SELECT checkout_order",
    client=client,
    event_id="evt_checkout_db_query",
    timestamp="2026-06-19T10:30:00Z",
    operation=lambda: session.execute("SELECT * FROM checkout_order WHERE id = ?", [cart_id]),
    system="postgresql",
    db_name="checkout",
    statement_template="SELECT * FROM checkout_order WHERE id = ?",
    row_count_from_result=lambda rows: rows.rowcount,
    metadata={"service": "checkout-api"},
)

The helper activates a child LogBrewTraceContext while your callable runs, queues one span named from the DB system and operation, preserves the original result or exception, and reports telemetry capture failures through on_capture_error without replacing the database result. Metadata is intentionally bounded to primitive caller metadata, dbSystem, dbOperation, optional dbName, optional statementTemplate, optional non-negative rowCount, sampled state, and exception type. It does not monkeypatch SQLAlchemy or DB-API drivers, does not open support tickets, and does not capture SQL parameters, result rows, connection strings, network addresses, sensitive configuration values, payloads, baggage, tracestate, stack traces, or exception messages.

Cache Operation Spans

Use cache_operation_with_logbrew_span() for sync cache calls and async_cache_operation_with_logbrew_span() for async calls when you want one app-owned cache span without installing or patching Redis, memcached, Django cache, or Flask cache clients:

from logbrew_sdk import LogBrewClient, cache_operation_with_logbrew_span

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-api",
    sdk_version="1.0.0",
)

profile = cache_operation_with_logbrew_span(
    "GET profile",
    client=client,
    event_id="evt_checkout_profile_cache_get",
    timestamp="2026-06-19T11:15:00Z",
    operation=lambda: redis_client.get(profile_cache_key),
    system="redis",
    cache_name="profiles",
    cache_hit=True,
    item_count=1,
    metadata={"service": "checkout-api"},
)

The helper activates a child LogBrewTraceContext while your callable runs, queues one span named from the cache system and operation, preserves the original result or exception, and reports telemetry capture failures through on_capture_error without replacing the cache result. Metadata is intentionally bounded to primitive caller metadata, cacheSystem, cacheOperation, optional cacheName, optional hit state, optional non-negative item size/count, sampled state, and exception type. It drops key-like metadata fields and does not monkeypatch cache clients, open support tickets, capture cache keys, values, commands, payloads, headers, cookies, network addresses, baggage, tracestate, stack traces, or exception messages.

Queue Operation Spans

Use queue_operation_with_logbrew_span() for sync queue calls and async_queue_operation_with_logbrew_span() for async calls when you want one app-owned publish/process span without installing or patching Celery, RQ, Dramatiq, or broker clients:

from logbrew_sdk import LogBrewClient, queue_operation_with_logbrew_span

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-worker",
    sdk_version="1.0.0",
)

queued = queue_operation_with_logbrew_span(
    "publish checkout.email",
    client=client,
    event_id="evt_checkout_email_publish",
    timestamp="2026-06-19T13:00:00Z",
    operation=lambda: celery_task.apply_async(args=[order_id]),
    system="celery",
    operation_kind="publish",
    queue_name="email",
    task_name="checkout.email",
    message_count=1,
    metadata={"service": "checkout-worker"},
)

The helper activates a child LogBrewTraceContext while your callable runs, queues one span named from the queue system and operation, preserves the original result or exception, and reports telemetry capture failures through on_capture_error without replacing the queue result. Metadata is intentionally bounded to primitive caller metadata, queueSystem, queueOperation, optional operation kind, optional queue/task names, optional non-negative message count/attempt, sampled state, and exception type. It drops message-like metadata fields and does not monkeypatch queue frameworks, write broker metadata, open support tickets, capture job arguments, message bodies, headers, cookies, broker URLs, baggage, tracestate, stack traces, or exception messages.

For RQ jobs, use rq_operation_with_logbrew_span() when you want LogBrew to derive safe func_name and origin metadata from an app-owned job object without installing RQ as a LogBrew dependency or patching Queue/Worker globally:

from logbrew_sdk import LogBrewClient, rq_operation_with_logbrew_span

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-worker",
    sdk_version="1.0.0",
)

job = queue.create_job(checkout_email_task, args=[order_id])
queued = rq_operation_with_logbrew_span(
    client=client,
    event_id="evt_checkout_email_rq_publish",
    timestamp="2026-06-19T14:00:00Z",
    job=job,
    operation=lambda: queue.enqueue_job(job),
    operation_kind="publish",
    metadata={"service": "checkout-worker"},
)

The RQ helper records one rq queue span using explicit caller control. It reads only string-like job.func_name and job.origin by default, lets you override queue/task names, and still avoids job args, kwargs, descriptions, broker metadata writes, global worker patching, baggage, and tracestate.

For Celery tasks, use celery_operation_with_logbrew_span() when you want safe task and queue metadata without registering Celery signals, mutating task headers, or patching apply_async:

from logbrew_sdk import LogBrewClient, celery_operation_with_logbrew_span

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-worker",
    sdk_version="1.0.0",
)

queued = celery_operation_with_logbrew_span(
    client=client,
    event_id="evt_checkout_receipt_celery_publish",
    timestamp="2026-06-19T15:00:00Z",
    task=send_receipt_task,
    operation=lambda: send_receipt_task.apply_async(args=[order_id]),
    operation_kind="publish",
    queue_name="receipts",
    metadata={"service": "checkout-worker"},
)

The Celery helper reads only string-like task.name and an optional routing key from task.request.delivery_info, lets you override queue/task names, and still avoids task args, kwargs, request headers, broker URLs, signal registration, header mutation, baggage, and tracestate.

Agent-Readable Timelines

Use create_product_action_attributes() and create_network_milestone_attributes() when your service already knows important product steps or API milestones. The helpers create normal action event attributes with primitive metadata that AI assistants can analyze across sessions without visual replay, global HTTP patching, payload capture, or header capture.

from logbrew_sdk import (
    LogBrewClient,
    create_network_milestone_attributes,
    create_product_action_attributes,
)

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="checkout-api",
    sdk_version="1.0.0",
)

client.action(
    "evt_checkout_submit",
    "2026-06-02T10:00:05Z",
    create_product_action_attributes(
        {
            "name": "checkout.submit",
            "status": "running",
            "sessionId": "sess_123",
            "traceId": "4bf92f3577b34da6a3ce929d0e0e4736",
            "routeTemplate": "/checkout/:step",
            "funnel": "checkout",
            "step": "submit",
            "metadata": {"service": "checkout"},
        }
    ),
)
client.action(
    "evt_payment_api",
    "2026-06-02T10:00:06Z",
    create_network_milestone_attributes(
        {
            "routeTemplate": "/payments/:id",
            "method": "POST",
            "statusCode": 202,
            "durationMs": 94,
            "sessionId": "sess_123",
            "traceId": "4bf92f3577b34da6a3ce929d0e0e4736",
            "metadata": {"service": "checkout"},
        }
    ),
)

Timeline helpers keep only primitive metadata, strip query strings and hashes from route templates, normalize HTTP methods, infer failed network milestones from status codes 400 and above, and serialize through the existing action event type. Keep metadata low-cardinality, such as sessionId, traceId, routeTemplate, method, statusCode, durationMs, screen, funnel, and step.

The packaged agent-timeline example shows a two-event checkout timeline with explicit traceparent propagation and sanitized product/network metadata:

python -m logbrew_sdk.examples agent-timeline

HTTP Delivery

Use HttpTransport for real outbound delivery from server-side Python apps:

from logbrew_sdk import HttpTransport, LogBrewClient

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="logbrew-python",
    sdk_version="0.1.0",
)
transport = HttpTransport(
    endpoint="https://api.logbrew.com/v1/events",
    headers={"x-logbrew-source": "python-worker"},
)

client.log(
    "evt_worker_started",
    "2026-06-02T10:00:06Z",
    {"message": "worker started", "level": "info", "logger": "worker"},
)
client.flush(transport)

HttpTransport uses Python's standard-library HTTP stack, posts JSON, passes the SDK key through the authorization header, supports custom endpoint/header/timeout settings, and maps connection failures into retryable TransportError.network(...) failures so LogBrewClient.flush() can preserve queued events and retry.

Standard Logging

Use LogBrewLoggingHandler when an application already uses Python's standard logging module:

import logging

from logbrew_sdk import LogBrewClient, LogBrewLoggingHandler, RecordingTransport

client = LogBrewClient.create(
    api_key="LOGBREW_API_KEY",
    sdk_name="logbrew-python",
    sdk_version="0.1.0",
)
transport = RecordingTransport.always_accept()
handler = LogBrewLoggingHandler(
    client,
    transport,
    flush_on_emit=True,
    metadata={"service": "checkout"},
)

logger = logging.getLogger("checkout.worker")
logger.addHandler(handler)
logger.setLevel(logging.INFO)

logger.info("worker started", extra={"order_id": "ord_123"})

The handler does not change global logging configuration. It maps standard logging levels into canonical LogBrew severities (info, warning, error, critical), keeps the logger name, captures primitive extra={...} values as metadata, and records source file name, function, line, thread, and process names without sending the full source path by default. Python DEBUG records are captured as info and CRITICAL records as critical; the original Python level name and number remain available in metadata. Exception type and message are captured when exc_info is present; full exception text is opt-in with include_exception_text=True.