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Events and logs

As dbt runs, it generates events. The most common way to see those events is as log messages, written in real time to two places:

  • The command line terminal (stdout), to provide interactive feedback while running dbt.
  • The debug log file (logs/dbt.log), to enable detailed debugging of errors when they occur. The text-formatted log messages in this file include all DEBUG-level events, as well as contextual information, such as log level and thread name. The location of this file can be configured via the log_path config.
CLI
21:35:48  6 of 7 OK created view model dbt_testing.name_list......................... [CREATE VIEW in 0.17s]
logs/dbt.log
============================== 2021-12-02 21:29:35.417263 | c83a0afc-7ed3-49e7-8c0e-797af7f9d7b6 ==============================
21:29:35.417263 [info ] [MainThread]: Running with dbt=1.0.0-rc3
21:29:35.417955 [debug] [MainThread]: running dbt with arguments Namespace(cls=<class 'dbt.task.run.RunTask'>, debug=None, defer=None, exclude=None, fail_fast=None, full_refresh=False, log_cache_events=False, log_format=None, partial_parse=None, printer_width=None, profile=None, profiles_dir='/Users/jerco/.dbt', project_dir=None, record_timing_info=None, rpc_method='run', select=None, selector_name=None, send_anonymous_usage_stats=None, single_threaded=False, state=None, static_parser=None, target=None, threads=None, use_colors=None, use_experimental_parser=None, vars='{}', version_check=None, warn_error=None, which='run', write_json=None)
...
21:29:35.814348 [debug] [Thread-1  ]: On model.my_project.my_table: BEGIN

Structured logging​

For more details about how the eventing system has been implemented in dbt-core, see the events module README.

Python interface​

danger

The EVENT_HISTORY object has been deprecated and removed in dbt Core v1.4+

Older versions of dbt-core made available a full history of events fired during an invocation, in the form of an EVENT_HISTORY object.

The Python interface into events is significantly less mature than the structured logging interface. For all use cases, we recommend parsing JSON-formatted logs.

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