nullscope 0.1.0

Zero-cost telemetry for Python. No-op when disabled, rich context when enabled.

Nullscope

Zero-cost telemetry for Python. No-op when disabled, rich context when enabled.

Why Nullscope?

Most telemetry libraries have runtime cost even when you don't need them. Nullscope is different:

• Disabled: Returns a singleton no-op object. No allocations, no timing calls, no overhead.
• Enabled: Full-featured timing and metrics with automatic scope hierarchy.

This makes Nullscope ideal for libraries (users can enable telemetry if they want) and applications where you want zero production overhead but rich debugging capability.

from nullscope import TelemetryContext

# When NULLSCOPE_ENABLED != "1", this is literally just returning a cached object
telemetry = TelemetryContext()

with telemetry("database.query"):  # No-op when disabled
    results = db.execute(query)

What Nullscope Is Not

• A distributed tracing system. No trace propagation, no span IDs, no context injection for cross-service correlation. If you need that, use OpenTelemetry directly. Nullscope can feed OTel, but it doesn't replace it.

• A metrics aggregation layer. Nullscope reports raw events to reporters. It doesn't compute percentiles, histograms, or roll up data. That's the reporter's job (or the backend's).

• Auto-instrumentation. Nullscope won't patch your HTTP client or database driver. You instrument what you want, explicitly.

• A logging framework. Scopes are for timing and metrics, not structured log events. (Though a reporter could emit logs.)

Installation

pip install nullscope

With OpenTelemetry support:

pip install nullscope[otel]

Quick Start

import os
os.environ["NULLSCOPE_ENABLED"] = "1"  # Enable telemetry

from nullscope import TelemetryContext, SimpleReporter

# Create a reporter to see output
reporter = SimpleReporter()
telemetry = TelemetryContext(reporter)

# Time operations with automatic hierarchy
with telemetry("request"):
    with telemetry("auth"):
        validate_token()

    with telemetry("handler"):
        process_data()

# See what was collected
reporter.print_report()

Output:

=== Nullscope Report ===

--- Timings ---
request:
  auth                           | Calls: 1    | Avg: 0.0012s | Total: 0.0012s
  handler                        | Calls: 1    | Avg: 0.0234s | Total: 0.0234s

Configuration

Environment Variable	Description
NULLSCOPE_ENABLED=1	Enable telemetry (default: disabled)

Note: environment flags are read at import time. In tests, reload nullscope after changing env vars.

API

TelemetryContext

from nullscope import TelemetryContext

telemetry = TelemetryContext()  # Uses default SimpleReporter when enabled
telemetry = TelemetryContext(my_reporter)  # Custom reporter
telemetry = TelemetryContext(reporter1, reporter2)  # Multiple reporters

Scopes (Timing)

with telemetry("operation"):
    do_work()

# With metadata
with telemetry("http.request", method="GET", path="/api/users"):
    handle_request()

Metrics

telemetry.count("cache.hit")  # Increment counter
telemetry.count("items.processed", 5)  # Increment by N
telemetry.gauge("queue.depth", len(queue))  # Point-in-time value
telemetry.metric("custom", value, metric_type="counter")  # Generic

Check Status

if telemetry.is_enabled:
    # Do expensive debug logging
    pass

OpenTelemetry Adapter

Export to OpenTelemetry backends:

from nullscope import TelemetryContext
from nullscope.adapters.opentelemetry import OTelReporter

# Configure OTel SDK first (providers, exporters, etc.)
# Then use Nullscope with OTel reporter
telemetry = TelemetryContext(OTelReporter(service_name="my-service"))

The adapter emits:

• Timings → Histogram (seconds) + synthetic Span when wall-clock bounds are present
• Counters → Counter
• Gauges → Histogram (sampled values, since Python OTel sync gauge support is limited)

Documentation

• Design - Architecture and implementation details
• Examples - Real-world usage patterns
• Comparison - When to use Nullscope vs alternatives
• Roadmap - Version milestones and planned features

License

MIT