or run

npx @tessl/cli init

Version

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Overview

Evals

Files

docs

command-line-tools.md configuration.md dogstatsd-client.md error-handling.md http-api-client.md index.md threadstats.md

tile.json

tessl/pypi-datadog

The Datadog Python library provides tools for interacting with Datadog's monitoring platform through HTTP API client functionality, DogStatsD metrics client, and command-line tools.

Workspace: tessl
Visibility: Public
Created: 3 months ago
Last updated: 3 months ago
Describes: pkg:pypi/datadog@0.52.x

To install, run

npx @tessl/cli install tessl/pypi-datadog@0.52.0

Datadog

The Datadog Python Library is a comprehensive collection of tools for interacting with Datadog's monitoring and analytics platform. It provides HTTP API client functionality for managing Datadog resources, DogStatsD client capabilities for efficient real-time metrics aggregation, thread-safe metrics collection, and command-line tools for DevOps workflows.

Package Information

Package Name: datadog
Package Type: pypi
Language: Python
Installation: pip install datadog
Version: 0.52.1

Core Imports

import datadog

For API functionality:

from datadog import initialize, api

For metrics collection:

from datadog import DogStatsd, statsd, ThreadStats

For command-line tools:

from datadog.dogshell import main

Basic Usage

from datadog import initialize, api

# Configure the library with your credentials
options = {
    "api_key": "<YOUR_API_KEY>",
    "app_key": "<YOUR_APP_KEY>",
}

initialize(**options)

# Submit an event
title = "Application deployment successful"
text = "Version 1.2.3 deployed to production"
tags = ["version:1.2.3", "environment:production"]

api.Event.create(title=title, text=text, tags=tags)

# Submit metrics using DogStatsD
from datadog import statsd

statsd.increment('web.requests', tags=['endpoint:api'])
statsd.gauge('system.cpu.usage', 75.5, tags=['host:web01'])
statsd.timing('db.query.duration', 245, tags=['table:users'])

Architecture

The Datadog Python Library is organized into several key modules:

datadog.api: REST API client providing full access to Datadog's HTTP API endpoints
datadog.dogstatsd: StatsD client for efficient real-time metrics submission to DogStatsD
datadog.threadstats: Thread-safe alternative for metrics collection without performance impact
datadog.dogshell: Command-line interface tools wrapping the API functionality
datadog.util: Shared utilities for hostname resolution, formatting, and compatibility

The library supports multiple transport protocols (UDP, UDS), includes automatic telemetry injection, comprehensive error handling, and both high-level abstractions and low-level control over Datadog's platform.

Capabilities

Library Configuration

Core initialization and configuration for API authentication, StatsD connection settings, and global library behavior.

def initialize(
    api_key=None,
    app_key=None,
    host_name=None,
    api_host=None,
    statsd_host=None,
    statsd_port=None,
    statsd_disable_aggregation=True,
    statsd_disable_buffering=True,
    statsd_aggregation_flush_interval=0.3,
    statsd_use_default_route=False,
    statsd_socket_path=None,
    statsd_namespace=None,
    statsd_max_samples_per_context=0,
    statsd_constant_tags=None,
    return_raw_response=False,
    hostname_from_config=True,
    cardinality=None,
    **kwargs
):
    """
    Initialize and configure Datadog API and StatsD modules.
    
    Parameters:
    - api_key (str): Datadog API key
    - app_key (str): Datadog application key  
    - host_name (str): Specific hostname override
    - api_host (str): Datadog API endpoint URL
    - statsd_host (str): Host of DogStatsD server
    - statsd_port (int): Port of DogStatsD server
    - statsd_disable_aggregation (bool): Disable client-side aggregation (default: True)
    - statsd_disable_buffering (bool): Disable metric buffering (default: True)
    - statsd_aggregation_flush_interval (float): Aggregation flush interval in seconds (default: 0.3)
    - statsd_use_default_route (bool): Auto-detect StatsD host from default route (default: False)
    - statsd_socket_path (str): Path to DogStatsD UNIX socket
    - statsd_namespace (str): Prefix for all metric names
    - statsd_max_samples_per_context (int): Max samples per metric context (default: 0)
    - statsd_constant_tags (list): Tags applied to all metrics
    - return_raw_response (bool): Return raw HTTP response objects (default: False)
    - hostname_from_config (bool): Get hostname from Datadog agent config (default: True)
    - cardinality (str): Global cardinality level ('none', 'low', 'orchestrator', 'high')
    - **kwargs: Additional configuration options
    """

Configuration

HTTP API Client

Complete REST API client providing access to all Datadog HTTP endpoints for managing events, metrics, monitors, dashboards, infrastructure, integrations, users, and more.

# Event management
api.Event.create(title, text, **kwargs)
api.Event.query(**kwargs)
api.Event.get(event_id)

# Metrics querying and submission  
api.Metric.query(**kwargs)
api.Metric.send(**kwargs)
api.Metric.list()

# Monitor management
api.Monitor.create(type, query, **kwargs) 
api.Monitor.get_all(**kwargs)
api.Monitor.get(monitor_id)
api.Monitor.update(monitor_id, **kwargs)
api.Monitor.delete(monitor_id)
api.Monitor.mute_all()
api.Monitor.unmute_all()
api.Monitor.search(**kwargs)

HTTP API Client

DogStatsD Metrics Client

High-performance StatsD client for submitting metrics, events, and service checks to DogStatsD with support for buffering, aggregation, and multiple transport protocols.

class DogStatsd:
    def gauge(self, metric, value, tags=None, sample_rate=None, cardinality=None): ...
    def gauge_with_timestamp(self, metric, value, timestamp, tags=None, sample_rate=None, cardinality=None): ...
    def increment(self, metric, value=1, tags=None, sample_rate=None, cardinality=None): ...  
    def decrement(self, metric, value=1, tags=None, sample_rate=None, cardinality=None): ...
    def count(self, metric, value, tags=None, sample_rate=None, cardinality=None): ...
    def histogram(self, metric, value, tags=None, sample_rate=None, cardinality=None): ...
    def distribution(self, metric, value, tags=None, sample_rate=None, cardinality=None): ...
    def timing(self, metric, value, tags=None, sample_rate=None, cardinality=None): ...
    def set(self, metric, value, tags=None, sample_rate=None, cardinality=None): ...
    def event(self, title, text, **kwargs): ...
    def service_check(self, check_name, status, **kwargs): ...

# Default instance
statsd = DogStatsd()

DogStatsD Client

ThreadStats Metrics Collection

Thread-safe metrics collection system that aggregates metrics in background threads without hindering application performance, ideal for high-throughput applications.

class ThreadStats:
    def start(self): ...
    def stop(self): ...
    def gauge(self, metric, value, tags=None, sample_rate=1): ...
    def increment(self, metric, value=1, tags=None, sample_rate=1): ...
    def histogram(self, metric, value, tags=None, sample_rate=1): ...
    def timing(self, metric, value, tags=None, sample_rate=1): ...
    def timer(self): ...  # Context manager
    def timed(self): ...  # Decorator
    def flush(self): ...

ThreadStats

Command-Line Tools

Comprehensive command-line interface providing access to all Datadog functionality through shell commands, supporting automation, scripting, and DevOps workflows.

def main():
    """Main entry point for dogshell CLI commands."""

# Available commands via console scripts:
# - dogshell: Main CLI command
# - dog: Legacy CLI command (deprecated)  
# - dogwrap: Command wrapper for metrics
# - dogshellwrap: Shell wrapper for metrics

Command-Line Tools

Error Handling

Comprehensive exception hierarchy for handling API errors, network issues, authentication problems, and client-side errors with appropriate retry and recovery strategies.

class DatadogException(Exception): ...
class ApiError(DatadogException): ...
class ClientError(DatadogException): ...
class HttpTimeout(ClientError): ...
class HttpBackoff(ClientError): ... 
class HTTPError(ClientError): ...
class ProxyError(ClientError): ...
class ApiNotInitialized(ApiError): ...

Error Handling

Constants

Service Check Status

OK = 0
WARNING = 1  
CRITICAL = 2
UNKNOWN = 3

Cardinality Levels

CARDINALITY_NONE = "none"
CARDINALITY_LOW = "low" 
CARDINALITY_ORCHESTRATOR = "orchestrator"
CARDINALITY_HIGH = "high"

Types

# Metric value types
MetricValue = Union[int, float]

# Tag format
Tag = str  # Format: "key:value" or "key"
Tags = List[Tag]

# Timestamp format  
Timestamp = Union[int, float]  # Unix timestamp

# Service check status
ServiceCheckStatus = Literal[0, 1, 2, 3]  # OK, WARNING, CRITICAL, UNKNOWN

# Monitor types (constants from MonitorType class)
QUERY_ALERT = "query alert"
COMPOSITE = "composite" 
SERVICE_CHECK = "service check"
PROCESS_ALERT = "process alert"
LOG_ALERT = "log alert"
METRIC_ALERT = "metric alert"
RUM_ALERT = "rum alert" 
EVENT_ALERT = "event alert"
SYNTHETICS_ALERT = "synthetics alert"
TRACE_ANALYTICS = "trace-analytics alert"

Version

Tile

Files

tessl/pypi-datadog

To install, run

index.md.css-3qkkll{font-size:var(--chakra-font-sizes-sm);font-weight:var(--chakra-font-weights-normal);color:var(--chakra-colors-gray-300);}docs/

Datadog

Package Information

Core Imports

Basic Usage

Architecture

Capabilities

Library Configuration

HTTP API Client

DogStatsD Metrics Client

ThreadStats Metrics Collection

Command-Line Tools

Error Handling

Constants

Service Check Status

Cardinality Levels

Types

index.mddocs/