Django Celery Database

Sadly we don't have the resources or funds required to improve the situation, so we're looking for contributors and partners willing to help. This service needs to run a Django environment almost identical to that used by the web service, as it will use the same codebase, need access to the same database and so on. Dia mendukung aneka teknologi untuk antrian tugas dan aneka paradigma untuk pekerja. If you want to store task results in the Django database then you still need to install the django-celery library for that (alternatively you can use the SQLAlchemy result backend). django_celery_results. First steps with Django; Frequently Asked Questions. Now when you start Celery, you should see your queues get created automatically on Amazon SQS. py migrate djcelery 0001 --fake. This extension enables you to store Celery task results using the Django ORM. 17 Camera requires django. Django Channels¶ Channels is a project that takes Django and extends its abilities beyond HTTP - to handle WebSockets, chat protocols, IoT protocols, and more. py에 아래 내용을 추가한다. py and include the following:. When a user call the action (the view to execute a certain task), Django immediately response back to the user and it's done. Django Ping is utility that provides a lightweight endpoint for availability and uptime monitoring services. broker – RabbitMQ 3. sqlite3' When using the SQLite backend, the database file will be saved in the Docker volume. I'm trying to use celery with Django, and I was able to set them up so, that I can start celery with (virtualenv)$ celery -A dbbs worker -l info and it does tasks sent by Django server. Setting up Django Celery has already been documented elsewhere so I'll simply list the settings I used to get things working (Note: I'm assuming that you're running a. Model): """ Email templates get stored in database so that admins can change emails on the fly """ subject = models. For example, your Django app might need a Postgres database, a RabbitMQ message broker and a Celery worker. dev1 A better alternative to the transaction signals Djangowill never have. This extension enables you to store Celery task results using the Django ORM. Pessimistic locking is a simple way to make your code wait until it's safe. The periodic tasks can be managed from the Django Admin interface, where you can create, edit and delete periodic tasks and how often they should run. 现在我们只需要知道Celery需要broker, 使用django自身便可以充当broker. For functions doing database operations, adding retrying if the operation fails. In this tutorial, we will create the Django models that define the fields and. We can connect to our isolated environment using ssh interface and run django application. Celery is a Python project, but there is an app, django-celery, which plugs into Django. There are many reasons why I like developing web applications with Python and Django but the main one is the awesome community and projects around the language and framework. x, you'll need to fake the newly added migration 0001, since your database already has the current djcelery_* and celery_* tables: $ python manage. backends, not duration). I have some tasks which should return result, and some tasks that don't. Django-celery is a Django wrapper for Celery that makes it work with Django more nicely. last_update is updated via django signals whenever anything is changed in the PeriodicTask model. So, before you can instantiate your task, you need to do two things: set DJANGO_SETTINGS_MODULE=settings in your environment. 0 web app that uses celery to schedule one task and collects data, a simple CRUD app. django_statsd. Python Database Tutorials. Download:. Django provides a straightforward API in the django. on_commit signal instead of doing it immediately. When Django finalize its job processing the request, it sends back a response to the user who finally will see something. The Perfect Django Settings File. PeriodicTasks This model is only used as an index to keep track of when the schedule has changed. requirements. Celery is a nice tool to use when you don't want your users to wait for some process to finish when they request one of your views. Notice that although this article is written for django-rq it should also help people that have the same problems with other async job systems (like celery or django-q). I'm trying to use celery with Django, and I was able to set them up so, that I can start celery with (virtualenv)$ celery -A dbbs worker -l info and it does tasks sent by Django server. from django. In general, it's an overwritten apply_async method in task, a class that sets up a task in transaction. Other parts of django-celery were released as django-celery-beat (Database-backed Periodic Tasks) and django-celery-results (Celery result backends for Django). The code above will transcode mp3 files into provided format. Questions: I am trying to come up with a testing methodology for our django-celery project. Setting up an asynchronous task queue for Django using Celery and Redis May 18 th , 2014 Celery is a powerful, production-ready asynchronous job queue, which allows you to run time-consuming Python functions in the background. When Django finalize its job processing the request, it sends back a response to the user who finally will see something. Django is supported out of the box now so this document only contains a basic way to integrate Celery and Django. Django Celery Database Setup. This is part 2 of our Kubernetes hackday series. django-celery-beat – Database-backed Periodic Tasks with Admin interface. Tedious work such as creating database backup, reporting annual KPI, or even blasting email could be made a breeze. Celery Result Backends using the Django ORM/Cache framework. This extension enables you to store Celery task results using the Django ORM. The Perfect Django Settings File. Python Django Framework Developer specialised on system integration projects. Menu Automate the Django Task Queue with Celery and Redis 01 March 2016 on python, django, automation, mariadb-server, celery, task queue, message broker, REST API, Django-REST-Framework, supervisord. beat import Scheduler, ScheduleEntry from celery. Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. We use Celery basically for everything that needs to be scheduled for the future, and using RabbitMQ as our Queue-broker is amazing since it fully integrates with Django and Celery storing on our database results of the tasks done so we can see if anything fails immediately. celery는 그 작업을 할 수 있도록 도와주는 파이썬 프레임워크입니다. 难道是我setting里面的设置问题吗?我没有用django-celery. 9, channels are available as a separate django-channels package that is still in beta and under development. Celery Worker Database Connection Pooling. Django’s primary goal is to ease the creation of complex database-driven websites. Django Ping is utility that provides a lightweight endpoint for availability and uptime monitoring services. Googling for "Django Oracle Celery DatabaseError" gets some queries about sharing threads on a single connection, but I'm not sure if that applies to me as I have "threaded=TRUE" in my Database config in project. This project included some interesting requirements that were outside of the scope of simple apps I have put together with Django. managers) to_model_schedule() (djcelery. Continued from the previous Kubernetes minikube (Docker & Kubernetes 2 : minikube Django with Postgres - persistent volume), we'll use Django with additional apps such as Redis and Celery. I also set up a unit tests and functional tests and tested the core functionalities of the application. Using a web interface a user submits some data which is POSTed to a web service and that web service in turn uses Django-celery to start a background task. from django. django_statsd. The execution units, called tasks, are executed concurrently on a single or more worker servers using multiprocessing, Eventlet, or gevent. To deal with this, you can Google “task transaction implementation”. This is where docker-compose comes in. py startproject simple_django_project, and then create an app in the project with python manage. 17 Camera requires django. Since this instance is used as the entry-point for everything you want to do in Celery, like creating tasks and managing workers, it must be possible for other modules to import it. I want to force tasks which shouldn't return result not to write anything in result backend (for example None). Tedious work such as creating database backup, reporting annual KPI, or even blasting email could be made a breeze. This extension enables you to store Celery task results using the Django ORM. pip install celery. django_statsd. It defines a single model (django_celery_results. But if Celery is new to you, here you will learn how to enable Celery in your project, and participate in a separate tutorial on using Celery with Django. For this project, you need to create a Dockerfile, a Python dependencies file, and a docker-compose. Django receive this request and do something with it. Docker-compose allows developers to define an application's container stack including its configuration in a single yaml file. And when run on a remote server, without using resources of the main Django app. Dia mendukung aneka teknologi untuk antrian tugas dan aneka paradigma untuk pekerja. It supports various technologies for the task queue and various paradigms for the workers. Django can get a plausible application going very fast. We can then easily lookup the results within the database using the normal Django ORM or even use things. Function objects decorated for ztask have self-evidently named curried sub-functions as attributes, such that e. Setting up an asynchronous task queue for Django using Celery and Redis May 18 th , 2014 Celery is a powerful, production-ready asynchronous job queue, which allows you to run time-consuming Python functions in the background. DatabaseBackend attribute) TaskSetManager (class in djcelery. Celery is an open source asynchronous task queue or job queue which is based on distributed message passing. 9, channels are available as a separate django-channels package that is still in beta and under development. Python Database Tutorials. 难道是我setting里面的设置问题吗?我没有用django-celery. This tutorial gives a complete understanding of Django. First, we install Celery with the PIP Package Manager. 1 $ pip install celery Next, add this package to your requirements. For part 2, we're going to delve into the architecture required for running a Django application on Kubernetes, as well as some of the tooling we used to assist us. In this post we will learn, how to implement celery to django application, to handle asynchronous tasks with Celery. The main (and only) functionality of testcele is that it let users create 1000 model objects by clicking a button in the template and they can see the progress of the task :. schedulers:DatabaseScheduler. py` in any application that wishes to run an asynchronous. Celery is the de facto choice for doing background task processing in the Python/Django ecosystem. Note that it won't log the queries executed by RunPython. Django-celery is a Django wrapper for Celery that makes it work with Django more nicely. x, you’ll need to fake the newly added migration 0001, since your database already has the current djcelery_* and celery_* tables: $ python manage. base import BaseCommand from django. Happy to see this through if something like this makes sense for Django. Celery is the de facto choice for doing background task processing in the Python/Django ecosystem. django_statsd. Using a web interface a user submits some data which is POSTed to a web service and that web service in turn uses Django-celery to start a background task. Celery is a task queue based on distributed message passing. The problem is that Celery doesn’t know that it’s running in the context of a Django app. , of a view) is complete. Using django-celery - learnings from Yipit. I have been fighting the Django/Celery documentation for a while now and need some help. [djcelery를 위해] Django 설정 settings. save() method and handles session management transparently. It is used to handle long running asynchronous tasks. models ¶ Database models. db - the service running the Postgres database container, needed for the Django apprabbitmq - service running the RabbitMQ container, needed for queuing jobs submitted by Celeryapp - the service containing Django app containerworker - the service that runs the Celery worker containerweb - the service that runs the Nginx con…. Hello everyone, I'm doing this post because I just got stuck in this a while ago and thought it would be nice to share. from django. How to create Periodic Tasks with Django Celery? Celery provides asynchronous job queues, which allows you to run Python functions in the background. I am trying to create an integration test with Celery, but I can't figure out how to connect Celery to this ephemeral test database. from celery import Celery # set the default Django settings module for the ' celery ' program. py` in any application that wishes to run an asynchronous. Python Django Framework Developer specialised on system integration projects. conf import settings from django. ####Django-Celery Django-Celery comes to the rescue here. RabbitMQ is the queue, while Celery and Django-Celery are the Python components that provide simple programming constructs for queueing and dequeuing jobs. This project was adopted and adapted from this repo. When Django finalize its job processing the request, it sends back a response to the user who finally will see something. Photo by Jamie Street on Unsplash Why am I reading this? The objective of the following post is to get a bird's eye view of what it's like to implement a Django based solution, using Celery and Redis, to deliver real-time push notifications upon user interaction in a mobile app through Firebase Cloud Messaging(a. Next, install django-celery with pip install django-celery and then modify the settings. The majority of web pages were static. With default prefork concurrency, celery tasks running Django ORM code would work very nicely with non-zero CONN_MAX_AGE. A Django application that exposes a bunch of PostgreSQL database metrics. The first thing you need is a Celery instance, this is called the celery application or just app in short. Most Django users prefer to use PostgreSQL as their database server. async(**opts)` to dispatch and run it asynchronously. django_celery_results. Django celery setup. Celery is the de facto choice for doing background task processing in the Python/Django ecosystem. py at the root of the project, which initializes the aforementioned celery. schema ¶ Logs the SQL queries that are executed during schema changes to the database by the migrations framework. py startproject simple_django_project, and then create an app in the project with python manage. celery worker deserialized each individual task and made each individual task run within a sub-process. I would like to be able to run Periodic Tasks using django-celery. The way it works is that it calls Django’s migrate in two different ways. When Django finalize its job processing the request, it sends back a response to the user who finally will see something. py migrate The last step is to inform your worker to read from custom scheduler: django_celery_beat. conf import settings os. Celery: an overview of the architecture and how it works by Vinta. This is a simple tutorial to get started with Django and the asynchronous task queuing system called Celery. WorkerState attribute) TaskStateManager (class in djcelery. changed(task) Note that this will reset the state as if the periodic tasks have never run before. async(**opts)` to dispatch and run it asynchronously. We will implement a model storing log entries. I have some tasks which should return result, and some tasks that don't. The Celery Signal docs explain how to do custom initialization when a worker is created so I added the following code to my tasks. I have installed all the required packages like celery, rabbitMQ and permissions as well. Source code for django_celery_beat. Database Backend - djcelery. 만약 task의 결과를 장고 database에 저장하고 싶다면 우선 django-celery 라이브러리를 먼저 설치해야 합니다. on_commit signal instead of doing it immediately. Consequently, if you ever need to perform a long-running operation, you should always perform it outside of the request-response cycle. sh - will migrate the database and start the Django development server on port 8000. This stores a single row with ident=1. In this post I will walk you through the celery setup procedure with django and SQS on elastic beanstalk. django-transaction-hooks Documentation, Release 0. 许多Django应用需要执行异步任务, 以便不耽误http request的执行. py install The last command must be executed as a privileged user if you are not currently using a virtualenv. As with any distributed system, Celery. The periodic tasks can be managed from the Django Admin interface, where you can create, edit and delete periodic tasks and how often they should run. 6 and Celery 3. In this video learn what it takes to setup Celery for deferred tasks, and as your cron. py migrate The last step is to inform your worker to read from custom scheduler: django_celery_beat. We can then easily lookup the results within the database using the normal Django ORM or even use things. Celery requires something known as message broker to pass messages from invocation to the workers. Using Django models to store task state. DatabaseBackend attribute) taskstate_set (djcelery. 我们暂时使用django runserver来启动celery. Sadly we don’t have the resources or funds required to improve the situation, so we’re looking for contributors and partners willing to help. Questions: I am trying to come up with a testing methodology for our django-celery project. Since we don’t need our virtualenv active for this part, run the following command to deactivate:. A Simple Celery with Django How-To I've been wanting to give Celery a try for a while now, but every time I tried I ran into a major issue. Celery: an overview of the architecture and how it works by Vinta. django-celery provides Celery integration for Django; Using the Django ORM and cache backend for storing results, autodiscovery of task modules for applications listed in INSTALLED_APPS, and more. First, we install Celery with the PIP Package Manager. pytest/celery - Failed: Database access not allowed I'm having some trouble getting pytest to test a celery task that's part of a django Displays Failed. This code snippet sets the default Django settings module for the celery program, defines the address for broker and discovers all tasks from registered apps and load them. I'm trying to use celery with Django, and I was able to set them up so, that I can start celery with (virtualenv)$ celery -A dbbs worker -l info and it does tasks sent by Django server. Any call to the methods filter , get , save , delete or any other function involving a database connection will now be done at the tenant's schema, so you shouldn't need to change. 7です。まだLinux上では動かしていません。. We will be continuing our courtside project and sending out sign up emails through celery. Now when you start Celery, you should see your queues get created automatically on Amazon SQS. django-transaction-hooks Documentation, Release 0. models import PeriodicTask, PeriodicTasks >>> PeriodicTask. This extension enables you to store Celery task results using the Django ORM. Add Cron entry. Note: In Celery 3. Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. transaction_retry (max_retries=1) [source] ¶ Decorate a function to retry database operations. If we need to explain whole process very roughly, when we use celery, what we are going to do is to create a queue and worker, define the jobs. Using django-celery; Documentation; Installation; Getting Help; Bug tracker; Wiki; Contributing; License; Getting Started. so achieve @ beginning started using django-celery databasescheduler store periodictasks (with expiration) database described more or less here. django-celery provides Celery integration for Django using the Django ORM and cache backend for storing results, autodiscovery of task modules for applications listed in INSTALLED_APPS, and integration of task monitoring through the Django admin interface. Run the Django database migrations and access the One thing you'll notice is that the celery, flower, and django containers use the same image as they're really. py mytask in django root. exception django_celery_results. 장고 ORM와 Cache를 Celery결과 백엔드로 이용해 봅시다. For example, if you want to create a drop down of countries in Django template, you can use the below code. What else do you need? However, we tend to abuse its easiness and we quickly forget that an application grows; and with it the amount of code processed as well as the amount of data saved on the database. Part 1 goes over how we spent the day and what the goals and motivations are. Is this the correct way to go in order to implement a SOA design for Django 2. Django Ping is utility that provides a lightweight endpoint for availability and uptime monitoring services. py and it seems to work exactly like you would expect. You will use the same API as non-Django users so it's recommended that you read the First Steps with Celery tutorial first and come back to this tutorial. There are also libraries that were used to run code when the current transaction is committed, such as django_atomic_celery and django-transaction-signals, but those are now legacy and should not be used. Django Celery - Provides Django hooks to run Celery within the Django context. First, there exists a celery. mock celery task (7) When a Django test case runs, it creates an isolated test database so that database writes get rolled back when each test completes. Django is supported out of the box now so this document only contains a basic way to integrate Celery and Django. The reason for the urllib. Django management command to delete old celery tasks from database using batches of adaptive size - cleanup_tasks. Why Celery ? Celery is very easy to integrate with existing code base. py` within each application, you must create a file `tasks. Quickstart: Compose and Django Estimated reading time: 7 minutes This quick-start guide demonstrates how to use Docker Compose to set up and run a simple Django/PostgreSQL app. Django-Celery First of all you need […]. requirements. Some reasons you might want to use REST framework: The Web browsable API is a huge usability win for your developers. report_builder_scheduled. PeriodicTasks (*args, **kwargs) [source] ¶ Helper table for tracking updates to periodic tasks. By antonpirker. Next, install django-celery with pip install django-celery and then modify the settings. Django provides a straightforward API in the django. This is used so that application data can hook into specific sites and a single database can manage content for multiple sites. Model): """ Email templates get stored in database so that admins can change emails on the fly """ subject = models. Meet Django. The Perfect Django Settings File. RabbitMQ, on the other hand, is message broker which is used by Celery to send and receive messages. Django: How to trigger events based on datetimes in the database python,django,database,celery,django-celery I have a simple Django app with a database which stores a series of messages and datetime at which I want them to printed to screen. It consists of a web view, a worker, a queue, a cache, and a database. py migrate The last step is to inform your worker to read from custom scheduler: django_celery_beat. 现在我们只需要知道Celery需要broker, 使用django自身便可以充当broker. To deal with this, you can Google “task transaction implementation”. Survey results need to be inserted in a SQL Server Database table. For functions doing database operations, adding retrying if the operation fails. after goin through the documentation of celery i have wrriten my code but when i am firing the command. For my basic Django project, running all by itself in Vagrant, the command “ps aux”, shows these memory values in percent:. Celery in Production on the Caktus Group blog contains good practices from their experience using Celery with RabbitMQ, monitoring tools and other aspects not often discussed in existing documentation. This message broker can be redis, rabbitmq or even Django ORM/db although that is not a recommended approach. 보통 웹 서비스에서 응답 시간은 서비스의 생명과 직결되므로 비동기로 작업을 처리하게 넘기고 바로 응답을 하는 경우가 많습니다. However, it also hints that this can be replaced with a custom backend. Use this for production, it just passes through to the real actual pystatsd. Celery is written in Python and makes it very easy to offload work out of the synchronous request lifecycle of a web app onto a pool of task workers to perform jobs asynchronously. In general, it’s an overwritten apply_async method in task, a class that sets up a task in transaction. For example: maybe production, staging, and development all share a common ADMINS setting. (但在部署时, 我们最好使用更稳定和高效的broker, 例如Redis. Configuring django apps for heroku. 6 and Celery 3. Для подключения celery к новому проекту так или иначе приходится подглядывать в предыдущие, чтобы вспомнить необходимые шаги: какие настройки задавать, как запускать, как останавливать и т. The django-celery library implements result backends using the Django ORM and the Django Cache frameworks. At this stage, these scripts won't work as we'd like them to because we haven't yet configured them. For those that are already using django-celery 2. database, queue server, celery processes, etc. This is a third part of Celery and RabbitMQ in Django series. The article was originally appeared in OverIQ. Now when you start Celery, you should see your queues get created. util import Finalize from celery import current_app from celery import schedules from celery. Ensure 'django_celery_beat' is in INSTALLED_APPS; Add 'report_builder_scheduled' to INSTALLED_APPS; Schedule a celery periodic task to process the report builder scheduled tasks. Perhaps you have to make calls to a separate API server, and don’t want to nest the latency of HTTP calls. Everything works fine in the development environment using manage. django_celery_results. schedulers:DatabaseScheduler. We are big fans of Celery and it’s an important part of our stack. Install a technology to manage the Celery queue (RabbitMQ is recommended). You received this message because you are subscribed to the Google Groups "Django users" group. The Django object-relational mapper (ORM) works best with an SQL relational database. It's fairly typical; a blank test database (REUSE_DB=0) that is pre-populated via a fixture at test time. Now, sometimes Celery workers on different machines need database access to my django frontend machine (two different servers). Caleb walks through creating a brand-new Django project, defining a data model and fields, querying the database, and using Django's built-in URL handlers, views, and templates to structure the rest of the backend. Saving the form response to the database is different, instead of using a global database session Django lets us call the model's. db import models from django. db import connection from django. In this post I will walk you through the celery setup procedure with django and SQS on elastic beanstalk. This stores a single row with ident=1. While this works well under some loads, a more traditional DBMS can improve performance in production. It uses the commit_on_success decorator, that will commit the transaction when the view returns, or roll back if the view raises an exception. Actually runs the tasks. django_celery_results. At this stage, these scripts won't work as we'd like them to because we haven't yet configured them. Django, Multiple Test Files and Database Not Resetting As per the new options for organizing tests, I put my tests for an app into a folder called tests. conf import settings from django. The Django database backend for celery beat has been relaunched as django-celery-beat, and may an easier transition to settings-based scheduling. This extension enables you to store Celery task results using the Django ORM. over 3 years Django 1. A Simple Celery with Django How-To I've been wanting to give Celery a try for a while now, but every time I tried I ran into a major issue. after goin through the documentation of celery i have wrriten my code but when i am firing the command. requirements. Debugging Celery Tasks in Django Projects. Django is supported out of the box now so this document only contains a basic way to integrate Celery and Django. Celery gets tasks done asynchronously and also supports scheduling of tasks as well. Deploying django, celery, redis, mysql. If we need to explain whole process very roughly, when we use celery, what we are going to do is to create a queue and worker, define the jobs. django-celery provides Celery integration for Django; Using the Django ORM and cache backend for storing results, autodiscovery of task modules for applications listed in INSTALLED_APPS, and more. Async Tasks (Celery) Authentication Backends; Class based views; Context Processors; Continuous Integration With Jenkins; CRUD in Django; Custom Managers and Querysets; Database Routers; Database Setup; Database transactions; Debugging; Deployment; Django and Social Networks; Django from the command line. Then it runs migrate for every tenant in the database, this time only syncing the tenant apps. Best practices for scaling Django. Celery is perfectly suited for tasks which will take some time to execute but we don. Does anyone hav. Django can get a plausible application going very fast. Celery is a task queue which can run background or scheduled jobs and integrates with Django pretty well. I'm trying to use celery with Django, and I was able to set them up so, that I can start celery with (virtualenv)$ celery -A dbbs worker -l info and it does tasks sent by Django server. This means each request will not be returned until all processing (e. after goin through the documentation of celery i have wrriten my code but when i am firing the command. For my basic Django project, running all by itself in Vagrant, the command “ps aux”, shows these memory values in percent:. Celery Worker Database Connection Pooling. Write your tasks in your project as django management commands. Django Ping is utility that provides a lightweight endpoint for availability and uptime monitoring services. Photo by Jamie Street on Unsplash Why am I reading this? The objective of the following post is to get a bird’s eye view of what it’s like to implement a Django based solution, using Celery and Redis, to deliver real-time push notifications upon user interaction in a mobile app through Firebase Cloud Messaging(a. This would automate this process for all kinds of tasks which operate on the database and make the code much cleaner (see this blog post for Django example). What problem would this feature solve? ===== Currently, async task results are stored in the Django database, using the package django-celery, which is deprecated Who has this problem? ===== Code Maintainers How do you know that the users identified above have this problem? ===== django-celery is deprecated and may break in future versions of Django. When Django finalize its job processing the request, it sends back a response to the user who finally will see something. TaskResult) used to store task results, and you can query this database table like any other Django model. Celery is a task queue which can run background or scheduled jobs and integrates with Django pretty well. Using a database for this means your worker processes will have to be constantly querying looking for new messages to processes which isn't very efficient. Before starting, install Compose. Redis server for cache and tasks queue, see Background tasks using Celery. almost 4 years database not updating when `CELERYBEAT_SCHEDULE` almost 4 years DatabaseError: DatabaseWrapper objects created in a thread can only be used in that same thread. For this article I wrote a simple Django application. The django-celery package may still exist for some time to provide additional utilities like the django-admin monitor. django-celery - Celery Integration for Django. $ tar xvfz django-celery-beat-tar. The fact-checkers, whose work is more and more important for those who prefer facts over lies, police the line between fact and falsehood on a day-to-day basis, and do a great job. Today, my small contribution is to pass along a very good overview that reflects on one of Trump’s favorite overarching falsehoods. Namely: Trump describes an America in which everything was going down the tubes under  Obama, which is why we needed Trump to make America great again. And he claims that this project has come to fruition, with America setting records for prosperity under his leadership and guidance. “Obama bad; Trump good” is pretty much his analysis in all areas and measurement of U.S. activity, especially economically. Even if this were true, it would reflect poorly on Trump’s character, but it has the added problem of being false, a big lie made up of many small ones. Personally, I don’t assume that all economic measurements directly reflect the leadership of whoever occupies the Oval Office, nor am I smart enough to figure out what causes what in the economy. But the idea that presidents get the credit or the blame for the economy during their tenure is a political fact of life. Trump, in his adorable, immodest mendacity, not only claims credit for everything good that happens in the economy, but tells people, literally and specifically, that they have to vote for him even if they hate him, because without his guidance, their 401(k) accounts “will go down the tubes.” That would be offensive even if it were true, but it is utterly false. The stock market has been on a 10-year run of steady gains that began in 2009, the year Barack Obama was inaugurated. But why would anyone care about that? It’s only an unarguable, stubborn fact. Still, speaking of facts, there are so many measurements and indicators of how the economy is doing, that those not committed to an honest investigation can find evidence for whatever they want to believe. Trump and his most committed followers want to believe that everything was terrible under Barack Obama and great under Trump. That’s baloney. Anyone who believes that believes something false. And a series of charts and graphs published Monday in the Washington Post and explained by Economics Correspondent Heather Long provides the data that tells the tale. The details are complicated. Click through to the link above and you’ll learn much. But the overview is pretty simply this: The U.S. economy had a major meltdown in the last year of the George W. Bush presidency. Again, I’m not smart enough to know how much of this was Bush’s “fault.” But he had been in office for six years when the trouble started. So, if it’s ever reasonable to hold a president accountable for the performance of the economy, the timeline is bad for Bush. GDP growth went negative. Job growth fell sharply and then went negative. Median household income shrank. The Dow Jones Industrial Average dropped by more than 5,000 points! U.S. manufacturing output plunged, as did average home values, as did average hourly wages, as did measures of consumer confidence and most other indicators of economic health. (Backup for that is contained in the Post piece I linked to above.) Barack Obama inherited that mess of falling numbers, which continued during his first year in office, 2009, as he put in place policies designed to turn it around. By 2010, Obama’s second year, pretty much all of the negative numbers had turned positive. By the time Obama was up for reelection in 2012, all of them were headed in the right direction, which is certainly among the reasons voters gave him a second term by a solid (not landslide) margin. Basically, all of those good numbers continued throughout the second Obama term. The U.S. GDP, probably the single best measure of how the economy is doing, grew by 2.9 percent in 2015, which was Obama’s seventh year in office and was the best GDP growth number since before the crash of the late Bush years. GDP growth slowed to 1.6 percent in 2016, which may have been among the indicators that supported Trump’s campaign-year argument that everything was going to hell and only he could fix it. During the first year of Trump, GDP growth grew to 2.4 percent, which is decent but not great and anyway, a reasonable person would acknowledge that — to the degree that economic performance is to the credit or blame of the president — the performance in the first year of a new president is a mixture of the old and new policies. In Trump’s second year, 2018, the GDP grew 2.9 percent, equaling Obama’s best year, and so far in 2019, the growth rate has fallen to 2.1 percent, a mediocre number and a decline for which Trump presumably accepts no responsibility and blames either Nancy Pelosi, Ilhan Omar or, if he can swing it, Barack Obama. I suppose it’s natural for a president to want to take credit for everything good that happens on his (or someday her) watch, but not the blame for anything bad. Trump is more blatant about this than most. If we judge by his bad but remarkably steady approval ratings (today, according to the average maintained by 538.com, it’s 41.9 approval/ 53.7 disapproval) the pretty-good economy is not winning him new supporters, nor is his constant exaggeration of his accomplishments costing him many old ones). I already offered it above, but the full Washington Post workup of these numbers, and commentary/explanation by economics correspondent Heather Long, are here. On a related matter, if you care about what used to be called fiscal conservatism, which is the belief that federal debt and deficit matter, here’s a New York Times analysis, based on Congressional Budget Office data, suggesting that the annual budget deficit (that’s the amount the government borrows every year reflecting that amount by which federal spending exceeds revenues) which fell steadily during the Obama years, from a peak of $1.4 trillion at the beginning of the Obama administration, to $585 billion in 2016 (Obama’s last year in office), will be back up to $960 billion this fiscal year, and back over $1 trillion in 2020. (Here’s the New York Times piece detailing those numbers.) Trump is currently floating various tax cuts for the rich and the poor that will presumably worsen those projections, if passed. As the Times piece reported: