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Showing content from https://open-telemetry.github.io/opentelemetry-sqlcommenter/python/SQLAlchemy below:

SQLAlchemy | opentelemetry-sqlcommenter

• Introduction
• Requirements
• BeforeExecuteFactory
• Fields
• End to end examples
• With Flask
• References

sqlcommenter-sqlalchemy provides a factory to create before_cursor_execute, called BeforeExecuteFactory

We provide a BeforeExecuteFactory that takes options such as

CommenterCursorFactory(with_opencensus=<True or False>)

We provide options such as with_opencensus because

Since OpenCensus trace_id and span_id are highly ephemeral, including them in SQL comments will likely break any form of statement-based caching that doesn’t strip out comments.

• Python X: any version of Python that is supported by SQLAlchemy
• OpenCensus optionally

pip3 install opentelemetry-sqlcommenter

git clone https://github.com/open-telemetry/opentelemetry-sqlcommenter.git
cd python/sqlcommenter-python && python3 setup.py install

and then we shall perform the following imports in our source code:

BeforeExecuteFactory is a factory that creates a before_cursor_execute hook to your engine to grab information about your application and augment it as a comment to your SQL statement.

from sqlalchemy import create_engine, event
from opentelemetry.sqlcommenter.sqlalchemy.executor import BeforeExecuteFactory

engine = create_engine(...) # Create the engine with your dialect of SQL
event.listen(engine, 'before_cursor_execute', BeforeExecuteFactory(), retval=True)
engine.execute(...) # comment will be appended to SQL before execution

NOTE Please ensure that you set retval=True when listening for events

and this will produce such output on for example a Postgresql database logs:

2019-06-30 18:01:16.315 PDT [96973] LOG:  statement: SELECT * FROM polls_question
/*traceparent='00-ade4c36dc5e43b503a5bba237ea11746-578a74a562044332-01'*/

To enable the comment cursor to also attach information about the current OpenCensus span (if any exists), pass in option with_opencensus=True when invoking BeforeExecuteFactory, so

engine = create_engine("postgresql://:$postgres$@127.0.0.1:5432/quickstart_py")
event.listen(engine, 'before_cursor_execute', BeforeExecuteFactory(with_opencensus=True), retval=True)
engine.execute(...) # comment will be appended to SQL before execution

NOTE Please ensure that you set retval=True when listening for events

from sqlalchemy import create_engine, event
from opentelemetry.sqlcommenter.sqlalchemy.executor import BeforeExecuteFactory
from opencensus.trace.samplers import AlwaysOnSampler
from opencensus.trace.tracer import Tracer

DB_URL = '...'  # DB connection info

class NoopExporter():
    def emit(self, *args, **kwargs):
        pass

    def export(self, *args, **kwargs):
        pass


def main():
    tracer = Tracer(exporter=NoopExporter, sampler=AlwaysOnSampler())
    engine = create_engine(DB_URL)

    listener = BeforeExecuteFactory(with_opencensus=True)
    event.listen(engine, 'before_cursor_execute', listener, retval=True)

    with tracer.span():
        result = engine.execute('SELECT * FROM polls_question')
        for row in result:
            print(row)


if __name__ == '__main__':
    main()

#!/usr/bin/env python3

from sqlalchemy import create_engine, event
from opentelemetry.sqlcommenter.sqlalchemy.executor import BeforeExecuteFactory

DB_URL = '...'  # DB connection info

def main():
    engine = create_engine(DB_URL)

    listener = BeforeExecuteFactory(with_db_framework=True)
    event.listen(engine, 'before_cursor_execute', listener, retval=True)

    result = engine.execute('SELECT * FROM polls_question')
    for row in result:
        print(row)

if __name__ == '__main__':
    main()

#!/usr/bin/env python3

from sqlalchemy import create_engine, event
from opentelemetry.sqlcommenter.sqlalchemy.executor import BeforeExecuteFactory

DB_URL = '...'  # DB connection info

def main():
    engine = create_engine(DB_URL)

    listener = BeforeExecuteFactory(with_db_driver=True)
    event.listen(engine, 'before_cursor_execute', listener, retval=True)

    result = engine.execute('SELECT * FROM polls_question')
    for row in result:
        print(row)

if __name__ == '__main__':
    main()

python3 main.py
(1, 'Wassup?', datetime.datetime(2019, 5, 30, 13, 51, 12, 910545, tzinfo=psycopg2.tz.FixedOffsetTimezone(offset=-420, name=None)))
(2, 'Wassup?', datetime.datetime(2019, 5, 30, 13, 57, 45, 905771, tzinfo=psycopg2.tz.FixedOffsetTimezone(offset=-420, name=None)))
(3, 'Wassup?', datetime.datetime(2019, 5, 30, 13, 57, 46, 908185, tzinfo=psycopg2.tz.FixedOffsetTimezone(offset=-420, name=None)))
(4, 'Wassup?', datetime.datetime(2019, 5, 30, 13, 57, 47, 557196, tzinfo=psycopg2.tz.FixedOffsetTimezone(offset=-420, name=None)))
(5, 'Wassup?', datetime.datetime(2019, 5, 30, 13, 57, 47, 853424, tzinfo=psycopg2.tz.FixedOffsetTimezone(offset=-420, name=None)))

Examining our Postgresql server logs

2019-07-18 14:10:15.228 -03 [30071] LOG:  statement: SELECT * FROM polls_question
/*traceparent='00-bf66750ad4c76f614c0a99d843758cbb-e6b27c3caf35de73-01'*/

2019-07-18 14:11:19.576 -03 [30108] LOG:  statement: SELECT * FROM polls_question
/*db_framework='sqlalchemy%3A1.3.5'*/

2019-07-18 14:03:33.426 -03 [29858] LOG:  statement: SELECT * FROM polls_question
/*db_driver='psycopg2'*/

When coupled with the web framework flask, we provide a class (BeforeExecuteFactory) to correlate your web applications with your SQL statements from psycopg2.

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