| .idea/* | |
| *.pyc |
| -- show running queries (pre 9.2) | |
| SELECT procpid, age(clock_timestamp(), query_start), usename, current_query | |
| FROM pg_stat_activity | |
| WHERE current_query != '<IDLE>' AND current_query NOT ILIKE '%pg_stat_activity%' | |
| ORDER BY query_start desc; | |
| -- show running queries (9.2) | |
| SELECT pid, age(clock_timestamp(), query_start), usename, query | |
| FROM pg_stat_activity | |
| WHERE query != '<IDLE>' AND query NOT ILIKE '%pg_stat_activity%' |
| from datetime import datetime | |
| from sqlalchemy import Column, Integer, DateTime, ForeignKey | |
| from sqlalchemy.orm import relationship | |
| from sqlalchemy.ext.declarative import declared_attr | |
| from flask_security import current_user | |
| class AuditMixin(object): | |
| created_at = Column(DateTime, default=datetime.now) | |
| updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now) |
Magic words:
psql -U postgresSome interesting flags (to see all, use -h or --help depending on your psql version):
-E: will describe the underlaying queries of the\commands (cool for learning!)-l: psql will list all databases and then exit (useful if the user you connect with doesn't has a default database, like at AWS RDS)
| /* Useful celery config. | |
| app = Celery('tasks', | |
| broker='redis://localhost:6379', | |
| backend='redis://localhost:6379') | |
| app.conf.update( | |
| CELERY_TASK_RESULT_EXPIRES=3600, | |
| CELERY_QUEUES=( | |
| Queue('default', routing_key='tasks.#'), |
| # Extracted using: $ unzip -p lib/pycharm.jar com/jetbrains/python/PyBundle.properties | grep -B1 INSP.NAME | grep '^#' | sed 's|Inspection||g' | sed -e 's|#\s\{,1\}|# noinspection |' | |
| # noinspection PyPep8 | |
| # noinspection PyPep8Naming | |
| # noinspection PyTypeChecker | |
| # noinspection PyAbstractClass | |
| # noinspection PyArgumentEqualDefault | |
| # noinspection PyArgumentList | |
| # noinspection PyAssignmentToLoopOrWithParameter | |
| # noinspection PyAttributeOutsideInit |
| import org.apache.flink.api.common.functions.MapFunction; | |
| import org.apache.flink.api.java.tuple.Tuple3; | |
| import org.apache.flink.streaming.api.TimeCharacteristic; | |
| import org.apache.flink.streaming.api.datastream.DataStream; | |
| import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; | |
| import org.apache.flink.streaming.api.functions.timestamps.AscendingTimestampExtractor; | |
| import org.apache.flink.table.api.Table; | |
| import org.apache.flink.table.api.TableEnvironment; | |
| import org.apache.flink.table.api.java.StreamTableEnvironment; | |
| import org.apache.flink.types.Row; |
THIS WAS ORIGINALLY POSTED ON MY TUMBLR ON FEB 25, 2011. I forgot I had a Tumblr account. I recently logged in (in light of the acquisition by Automattic), found some old posts, and I'm republishing them exactly as they were with zero modifications.
Amazon announced CloudFormation to the public yesterday, and while the general opinion I could glean from various sources shows that people are excited about this new technology, many are still unsure what it is and how it fits into their current cloud workflow. I feel as though I have a firm grasp on CloudFormation and will attempt to answer some questions here.
Note: I'm definitely not a representative of Amazon in any way, and anything here is simply my educated opinion on the matter.