Datadog Python API Client

The datadog_api_client.v1.api package is organized into specialized submodules, each corresponding to a specific functional area of the Datadog API. Developers should import the specific submodule required for their task to access relevant API endpoints.

Key functional areas include:

• Integrations: Manage connections with cloud providers and tools like aws_integration_api, azure_integration_api, gcp_integration_api, slack_integration_api, and pager_duty_integration_api.
• Observability & Monitoring: Access metrics, logs, monitors, service level objectives (SLOs), and synthetics via metrics_api, logs_api, monitors_api, service_level_objectives_api, and synthetics_api.
• Infrastructure: Manage hosts, service checks, and IP ranges using hosts_api, service_checks_api, and ip_ranges_api.
• Dashboards & Visualization: Interact with dashboards and notebook features via dashboards_api, dashboard_lists_api, and notebooks_api.
• Security & Governance: Manage security monitoring, users, and organizations through security_monitoring_api, users_api, and organizations_api.

The datadog_api_client.v1.model package contains various data models used for Synthetics operations. Key modules include:

• synthetics_test_uptime: Models for uptime testing.
• synthetics_timing: Models for timing-related synthetics data.
• synthetics_trigger_body: Payload models for triggering synthetics tests.
• synthetics_trigger_ci_test_location: Models for CI test locations.
• synthetics_trigger_ci_test_run_result: Models for CI test run results.
• synthetics_trigger_ci_tests_response: Response models for CI test triggers.
• synthetics_trigger_test: Models for triggering specific tests.
• synthetics_update_test_pause_status_payload: Payload for updating the pause status of a test.
• synthetics_uptime: General uptime models.
• synthetics_variable_parser: Models for parsing synthetics variables.
• synthetics_warning_type: Models defining warning types for synthetics.

The datadog_api_client.v2.api package is organized into numerous submodules, each corresponding to a specific Datadog service or functional area. Developers can access specialized API endpoints by importing the relevant submodule.

Key functional areas include:

• Logs & Observability: logs_api, logs_archives_api, logs_metrics_api, observability_pipelines_api.
• Real User Monitoring (RUM): rum_api, rum_insights_api, rum_replay_sessions_api, rum_remote_config_api.
• Integrations: gcp_integration_api, jira_integration_api, okta_integration_api, microsoft_teams_integration_api.
• Infrastructure & APM: apm_api, apm_trace_api, metrics_api, network_device_monitoring_api.
• Security & Governance: governance_console_api, ip_allowlist_api, restriction_policies_api.
• On-Call & Incident Management: incidents_api, on_call_api, on_call_paging_api.

The datadog_api_client.v2.api package is organized into numerous submodules, each corresponding to a specific Datadog API functional area. Developers can access specialized API endpoints by importing the relevant submodule.

Common functional areas available in this segment include:

• APM & Tracing: apm_api, apm_retention_filters_api, and apm_trace_api.
• Case Management: case_management_api, case_management_attribute_api, and case_management_type_api.
• CI Visibility: ci_visibility_git_hub_accounts_api, ci_visibility_pipelines_api, and ci_visibility_tests_api.
• Cloud & Integrations: aws_integration_api, aws_logs_integration_api, cloudflare_integration_api, and elastic_cloud_integration_accounts_api.
• Dashboards: dashboards_api, dashboard_lists_api, dashboard_sharing_api, and dashboard_secure_embed_api.
• CSM (Customer Success Management): csm_agents_api, csm_coverage_analysis_api, csm_ownership_api, csm_settings_api, and csm_threats_api.
• Observability & Monitoring: agent_observability_api, agentless_scanning_api, cloud_network_monitoring_api, and downtimes_api.

Each submodule contains the specific methods and models required to interact with that Datadog service.

The datadog_api_client.v1.model package contains a wide array of data models used for configuring and interacting with Datadog Monitors and complex Formula/Function queries.

Key functional areas include:

• Monitor Configuration: Models for defining monitors, including monitor, monitor_asset, monitor_draft_status, and monitor_device_id.
• Formula and Function Queries: A comprehensive set of models for building advanced queries used in monitors. This includes submodules for:
  • metrics_query_definition and metrics_data_source for metric-based queries.
  • event_query_definition and event_aggregation for event-based queries.
  • data_quality_query_definition for data quality monitoring.
  • cost_query_definition for cost-related monitoring.
  • filter_query and join_condition for combining and filtering data sources.
• Metrics Querying: Models for handling metrics metadata, responses, and units (metrics_query_metadata, metrics_query_response, metrics_query_unit).

The following modules define the schema for Table Widgets in Datadog dashboards:

• table_widget_definition: The core definition of a table widget.
• table_widget_definition_type: Enumeration of supported table widget types.
• table_widget_request: Request schema for table widgets.
• table_widget_cell_display_mode: Configuration for how cells are displayed.
• table_widget_has_search_bar: Boolean configuration for the search bar.
• table_widget_text_format_rule: Rules for text formatting within cells.
• table_widget_text_format_match: Logic for matching text patterns.
• table_widget_text_format_match_type: Types of text matching supported.
• table_widget_text_format_palette: Color palettes for text formatting.
• table_widget_text_format_replace: Logic for replacing text.
• table_widget_text_format_replace_all: Logic for replacing all occurrences of text.
• table_widget_text_format_replace_all_type: Types of 'replace all' operations.
• table_widget_text_format_replace_substring: Logic for replacing specific substrings.
• table_widget_text_format_replace_substring_type: Types of substring replacement operations.

The v1.model package contains numerous modules for retrieving and analyzing Datadog usage, attribution, and billing information. These models are used to programmatically inspect how different Datadog products are consuming resources.

Available usage data categories include:

• Logs: usage_analyzed_logs_response, usage_analyzed_logs_hour.
• Hosts & Infrastructure: usage_hosts_response, usage_host_hour, usage_fargate_response, usage_fargate_hour.
• APM & Tracing: usage_ingested_spans_response, usage_ingested_spans_hour, usage_indexed_spans_response, usage_indexed_spans_hour.
• Security: usage_cloud_security_posture_management_response, usage_cloud_security_posture_management_hour.
• Database Monitoring (DBM): usage_dbm_response, usage_dbm_hour.
• CI Visibility: usage_ci_visibility_response, usage_ci_visibility_hour.
• Incident Management: usage_incident_management_response, usage_incident_management_hour.
• CWS (Cloud Workload Security): usage_cws_response, usage_cws_hour.
• Billing Summaries: usage_billable_summary_response, usage_billable_summary_hour, usage_attribution_aggregates.

The datadog_api_client.v2.api package is organized into numerous submodules, each dedicated to a specific Datadog product or functional area. Developers can access specialized API endpoints by importing the relevant submodule.

Commonly used submodules include:

• RUM (Real User Monitoring): rum_replay_viewership_api, rum_retention_filters_api, rum_retention_quotas_api, rum_teams_ownership_api
• APM (Application Performance Monitoring): apm_api, apm_retention_filters_api, apm_trace_api
• Security & Compliance: security_monitoring_api, sensitive_data_scanner_api, stegadography_api
• Integrations: salesforce_integration_api, service_now_integration_api, slack_integration_api, twilio_integration_accounts_api, webhooks_integration_api
• Infrastructure & Observability: agent_observability_api, spans_api, spans_metrics_api, synthetics_api, software_catalog_api
• User & Access Management: users_api, service_accounts_api, teams_api, seats_api
• Automation & Workflow: workflow_automation_api, app_builder_api

To use a specific API, identify the product area and import the corresponding module from datadog_api_client.v2.api.