psycopg2-mq 0.9

A message queue written around PostgreSQL.

psycopg2_mq is a message queue implemented on top of PostgreSQL, SQLAlchemy, and psycopg2.

Currently the library provides only the low-level constructs that can be used to build a multithreaded worker system. It is broken into two components:

• psycopg2_mq.MQWorker - a reusable worker object that manages a single-threaded worker that can accept jobs and execute them. An application should create worker per thread. It supports an API for thread-safe graceful shutdown.

• psycopg2_mq.MQSource - a source object providing a client-side API for invoking and querying job states.

It is expected that these core components are then wrapped into your own application in any way that you see fit, without dictating a specific CLI or framework.

Data Model

Queues

Workers run jobs defined in queues. Currently each queue will run jobs concurrently, while a future version may support serial execution on a per-queue basis. Each registered queue should contain an execute_job(job) method.

Jobs

The execute_job method of a queue is passed a Job object containing the following attributes:

• id

• queue

• method

• args

• cursor

As a convenience, there is an extend(**kw) method which can be used to add extra attributes to the object. This is useful in individual queues to define a contract between a queue and its methods.

Cursors

A Job can be scheduled with a cursor_key. There can only be one pending job and one running job for any cursor. New jobs scheduled while another one is pending will be ignored and the pending job is returned.

A job.cursor dict is provided to the workers containing the cursor data, and is saved back to the database when the job is completed. This effectively gives jobs some persistent, shared state, and serializes all jobs over a given cursor.

Delayed Jobs

A Job can be delayed to run in the future by providing a datetime object to the when argument. This, along with a cursor key, can provide a nice throttle on how frequently a job runs. For example, delay jobs to run in 30 seconds with a cursor_key and any jobs that are scheduled in the meantime will be dropped. The assumption here is that the arguments are constant and data for execution is in the cursor or another table. As a last resort, a conflict_resolver callback can be used to modify properties of the job when arguments cannot be constant.

Schedules

A JobSchedule can be defined which supports RFC 5545 RRULE schedules. These are powerful and can support timezones, frequencies based on calendars as well as simple recurring rules from an anchor time using DTSTART. Cron jobs can be converted to this syntax for simpler scenarios.

psycopg2-mq workers will automatically negotiate which worker is responsible for managing schedules so clustered workers should operate as expected.

Example Worker

from psycopg2_mq import (
    MQWorker,
    make_default_model,
)
from sqlalchemy import (
    MetaData,
    create_engine,
)
import sys

class EchoQueue:
    def execute_job(self, job):
        return f'hello, {job.args["name"]} from method="{job.method}"'

if __name__ == '__main__':
    engine = create_engine(sys.argv[1])
    metadata = MetaData()
    model = make_default_model(metadata)
    worker = MQWorker(
        engine=engine,
        queues={
            'echo': EchoQueue(),
        },
        model=model,
    )
    worker.run()

Example Source

engine = create_engine()
metadata = MetaData()
model = make_default_model(metadata)
session_factory = sessionmaker()
session_factory.configure(bind=engine)

dbsession = session_factory()
with dbsession.begin():
    mq = MQSource(
        dbsession=dbsession,
        model=model,
    )
    job = mq.call('echo', 'hello', {'name': 'Andy'})
    print(f'queued job={job.id}')

Changes

0.9 (2023-04-21)

• Add support for Python 3.10, and 3.11.

• [breaking] Prevent retrying of collapsible jobs. Require them to be invoked using call instead for an opportunity to specify a conflict_resolver.

• Fix a bug in the default model schema in which the collapsible database index was not marked unique.

• Copy trace info when retrying a job.

• Capture the stringified exception to the job result in the message key, alongside the existing tb, exc, and args keys.

• The worker was not recognizing capture_signals=False, causing problems when running the event loop in other threads.

• Blackify the codebase and add some real tests. Yay!

0.8.3 (2022-04-15)

• [breaking] Remove MQWorker.make_job_context.

0.8.2 (2022-04-15)

• Drop Python 3.6 support.

• [breaking] Require SQLAlchemy 1.4+ and resolve deprecation warnings related to SQLAlchemy 2.0.

• [breaking] Rename update_job_id to updated_job_id in the JobCursor model.

0.8.1 (2022-04-15)

• Ensure the trace attribute is populated on the JobContext.

• Add MQWorker.make_job_context which can be defined to completely override the JobContext factory using the Job object and open database session.

0.8.0 (2022-04-15)

• [breaking] Add update_job_id foreign key to the JobCursor model to make it possible to know which job last updated the value in the cursor.

• [breaking] Add trace json blob to the Job model.

• Support a trace json blob when creating new jobs. This value is available on the running job context and can be used when creating sub-jobs or when making requests to external systems to pass through tracing metadata.

  See MQSource.call’s new trace parameter when creating jobs. See JobContext.trace attribute when handling jobs.

• Add a standard FailedJobError exception which can be raised by jobs to mark a failure with a custom result object. This is different from unhandled exceptions that cause the MQWorker.result_from_error method to be invoked.

0.7.0 (2022-03-03)

• Fix a corner case with lost jobs attached to cursors. In scenarios where multiple workers are running, if one loses a database connection then the other is designed to notice and mark jobs lost. However, it’s possible the job is not actually lost and the worker can then recover after resuming its connection, and marking the job running again. In this situation, we do not want another job to begin on the same cursor. To fix this issue, new jobs will not be run if another job is marked lost on the same cursor. You will be required to recover the job by marking it as not lost (probably failed) first to unblock the rest of the jobs on the cursor.

0.6.2 (2022-03-01)

• Prioritize maintenance work higher than running new jobs. There was a chicken-and-egg issue where a job would be marked running but needs to be marked lost. However marking it lost is lower priority than trying to start new jobs. In the case where a lot of jobs were scheduled at the same time, the worker always tried to start new jobs and didn’t run the maintenance so the job never got marked lost, effectively blocking the queue.

0.6.1 (2022-01-15)

• Fix a bug introduced in the 0.6.0 release when scheduling new jobs.

0.6.0 (2022-01-14)

• [breaking] Add model changes to mark jobs as collapsible.

• [breaking] Add model changes to the cursor index.

• Allow multiple pending jobs to be scheduled on the same cursor if either:

  1. The queue or method are different from existing pending jobs on the cursor.

  2. collapse_on_cursor is set to False when scheduling the job.

0.5.7 (2021-03-07)

• Add a schedule_id attribute to the job context for use in jobs that want to know whether they were executed from a schedule or not.

0.5.6 (2021-02-28)

• Some UnicodeDecodeError exceptions raised from jobs could trigger a serialization failure (UntranslatableCharacter) because it would contain the sequence \u0000` which, while valid in Python, is not allowed in postgres. So when dealing with the raw bytes, we’ll decode it with the replacement character that can be properly stored. Not ideal, but better than failing to store the error at all.

0.5.5 (2021-01-22)

• Fixed some old code causing the worker lock to release after a job completed.

0.5.4 (2021-01-20)

• Log at the error level when marking a job as lost.

0.5.3 (2021-01-11)

• Copy the schedule_id information to retried jobs.

0.5.2 (2021-01-11)

• [breaking] Require call_schedule to accept an id instead of an object.

0.5.1 (2021-01-09)

• Drop the UNIQUE constraint on the background job lock_id column.

0.5 (2021-01-09)

• Add a scheduler model with support for emitting periodic jobs based on RRULE syntax. See https://github.com/mmerickel/psycopg2_mq/pull/11

• Enable the workers to coordinate on a per-queue basis who is in control of scheduling jobs. See https://github.com/mmerickel/psycopg2_mq/pull/12

• Reduce the number of advisory locks held from one per job to one per worker. See https://github.com/mmerickel/psycopg2_mq/pull/12

0.4.5 (2020-12-22)

• Use column objects in the insert statement to support ORM-level synonyms, enabling the schema to have columns with different names.

0.4.4 (2019-11-07)

• Ensure the advisory locks are released when a job completes.

0.4.3 (2019-10-31)

• Ensure maintenance (finding lost jobs) always runs at set intervals defined by the timeout parameter.

0.4.2 (2019-10-30)

• Recover active jobs when the connection is lost by re-locking them and ensuring they are marked running.

0.4.1 (2019-10-30)

• Attempt to reconnect to the database after losing the connection. If the reconnect attempt fails then crash.

0.4 (2019-10-28)

• Add a worker column to the Job model to track what worker is handling a job.

• Add an optional name argument to MQWorker to name the worker - the value will be recorded in each job.

• Add a threads argument (default=``1``) to MQWorker to support handling multiple jobs from the same worker instance instead of making a worker per thread.

• Add capture_signals argument (default=``True``) to MQWorker which will capture SIGTERM, SIGINT and SIGUSR1. The first two will trigger graceful shutdown - they will make the process stop handling new jobs while finishing active jobs. The latter will dump to stderr a JSON dump of the current status of the worker.

0.3.3 (2019-10-23)

• Only save a cursor update if the job is completed successfully.

0.3.2 (2019-10-22)

• Mark lost jobs during timeouts instead of just when a worker starts in order to catch them earlier.

0.3.1 (2019-10-17)

• When attempting to schedule a job with a cursor and a scheduled_time earlier than a pending job on the same cursor, the job will be updated to run at the earlier time.

• When attempting to schedule a job with a cursor and a pending job already exists on the same cursor, a conflict_resolver function may be supplied to MQSource.call to update the job properties, merging the arguments however the user wishes.

0.3 (2019-10-15)

• Add a new column cursor_snapshot to the Job model which will contain the value of the cursor when the job begins.

0.2 (2019-10-09)

• Add cursor support for jobs. This requires a schema migration to add a cursor_key column, a new JobCursor model, and some new indices.

0.1.6 (2019-10-07)

• Support passing custom kwargs to the job in psycopg2_mq.MQSource.call to allow custom columns on the job table.

0.1.5 (2019-05-17)

• Fix a regression when serializing errors with strings or cycles.

0.1.4 (2019-05-09)

• More safely serialize exception objects when jobs fail.

0.1.3 (2018-09-04)

• Rename the thread to contain the job id while it’s handling a job.

0.1.2 (2018-09-04)

• Rename Job.params to Job.args.

0.1.1 (2018-09-04)

• Make psycopg2 an optional dependency in order to allow apps to depend on psycopg2-binary if they wish.

0.1 (2018-09-04)

• Initial release.