Python Azure Create Container

In the Azure Portal, click the Create a resource button (green plus in the left-upper corner) Next, search for azure container instance and click. Configure application and database deployment, using Continuous Deployment (CD) in the Azure DevOps. Before digging into query syntax and operations, create a resource group using the az group create command and three container instances using the az container create command. Create container image: from the model in the workspace, we create a container image with GPU support; Deploy container image: from the image in the workspace, we deploy the image to compute that supports GPUs; Machine Learning SDK. Register an MLflow model with Azure ML and build an Azure ML ContainerImage for deployment. js, Python, PHP, batch, bash, Java, or any executable. BlockBlobService(). I work with Azure Functions a lot. Create an Azure Container Registry (ACR), AKS and Azure SQL server. This sample shows how to use the Python SDK to create, retreive, and delete Azure Container Instances. Today lets do a proof of concept for Azure Blob not using. You are first going to pull the Azure IoT Edge containers down to your local machine, tag them and then push them to your own ACR. Alternatively you can use it via a Docker container. ), we are going to create docker images to quickly start running (on-demand) Memcached containers which can be operated individually. Posted on Wednesday, January 24, 2018. Once deployed, you will be able to access the Function Apps page. Downloadin an Azure Storage Blob Container with complex path of folders and sub folders - python-azure-blob-storage-download. Use the tools and languages you know. You can use the Azure portal as a graphical interface to build an Azure Container Service cluster. This represents the first release of the ground-up rewrite of the client libraries to ensure consistency, idiomatic design, and excellent developer experience and productivity. Last but not least, we’ve made it easy to get started with Windows Server Containers in Azure via a dedicated virtual machine image. Python code can run within containers and has many deployment options like Azure Kubernetes Service (AKS) and A zure Container Instances (ACI). This topic describes how to perform the required tasks in Azure. Use the management library to create and manage Azure container instances in Azure. - Install Python locally. Create a Secret to hold the registry credentials. Microsoft has made the preview of Azure Container Service (ACS) available to a broader set of developers. For the container image to get created, we need to tell Azure ML about the environment needed by the model. 2) Create a storage in Azure portal and make note of account name, access key and storage url. With Azure Functions, your applications scale based on demand and you pay only for the resources you consume. Writing Azure Functions in Python offers a great way to run Python code serverless on Azure. With LUIS, you can use pre-existing, world-class, pre-built models from Bing and Cortana whenever they suit your purposes -- and when you need specialized models,LUIS guides you through the process of quickly building them. Python is a programming language. This article describes how to make REST calls to Azure Resource Manager (ARM) from Python. We will use the existing Azure/phippyandfriends GitHub repo. The post however doesn't give a complete resolution but gives a pretty good idea of what needs to be done. It's time for us to package and deploy the model as a container image which will be exposed as a web service. There is a quick glance pane on the right side that shows the SSH port that you can connect to, the DNS name, virtual IP, and other core values. Teams & Organizations Create Teams to manage access control to your Organization's repos and builds. To create a client object, you will need the storage account's blob service account URL. For a more general view of Azure and Python, you can go on thePython Developer Center for Azure User Documentation 1. In this post, I'll discuss what Azure Containers can do and how they can be used and managed in Azure. 7 or $ 200 to spend for the first 30 days, free access to most popular Azure products for 12 months and access to more than 25 products that are always free. First, start with a fresh empty. The "container as a service" lets you rapidly create and launch containerized applications, including from Kubernetes, without any overhead and with an easily scriptable set of commands Azure. Getting Started New to OpenShift? Get your first application up and running and learn the basics. BlockBlobService(). baseblobservice. Setup an Azure Function. az container create -g MyResourceGroup --name MyApp --image myimage:latest --cpu 1 --memory 1. Once deployed, you will be able to access the Function Apps page. Docker Cloud allows you to connect to any registry that supports the Docker Registry API. The preview of our Visual Studio Tools for Docker, which enables developers to build and publish ASP. Azure Blob Storage is a service for storing large amounts of unstructured object data, such as text or binary data. This document will help you to learn about Azure Container Services and how to create a Container Host Virtual Machine. Microsoft: We want you to learn Python programming language for free. In a single Azure app service, you can host N number of web apps. This article will explain you the commands that you need to use inside Azure CLI to manage storage account. - Install Python locally. Azure Storage Blob Service REST API: Sample code to create a new container under a specified account. What you'll do is create a blob in container assets but name that blob as "images/myimage. Azure Storage is described as a service that provides storages that is available, secure, durable, scalable, and redundant. This view works on my local machine, but fails once it is. Azure SDK for Python Documentation, Release 2. Interaction with these resources starts with an instance of a client. Setting up a VM on Azure using the Python SDK. Named Volumes Introduced in Docker 1. Resources Webinars, datasheets, reference architectures, demo videos and more. The AWS Elastic Beanstalk Python platform is a set of environment configurations for Python web applications that can run behind an Apache proxy server with WSGI. OpenShift Container Platform; Overview Run OpenShift in your data center or private cloud. A PAT token. Shay also specializes in performance management & diagnosti. Therefore, always specify all options relevant to the container. #Azure Functions Provider Documentation. The location of a Dockerfile that defines the contents of the container. If the module needs to recreate the container, it will only use the options provided to the module to create the new container (except image). The resulting Azure ML ContainerImage will contain a webserver that processes model queries. You can mount a Blob Storage container or a folder inside a container to Databricks File System. You can create an ASP. Install Chilkat for Node. Create an Azure Container Instance and add it to Azure Container Registry by uploading a local Docker image. It will not run on the ARM32v6 processor found in the Raspberry Pi Zero. Management APIs. We have trained over 90,000 students from over 16,000 organizations on technologies such as Microsoft ASP. 0 was the last release to support Python 2. Python Tools for Visual Studio is a completely free extension, developed and supported by Microsoft with contributions from the community. The Logic Apps instance controls the workflow and is instantiated by the trigger signal, creating a container group with a single container based on the image stored in the registry. How to import Python extension modules in Azure Functions Posted on November 3, 2016 | Michael McKenna An awesome feature of Azure Functions is its ability to run a wide range of languages, C#, F#, Node. Before Web Apps for Linux there needed to be explicit support for a language in Azure or you had to create a complicated Kudo Extention to enable a. Azure Blob Storageとは Azure Blob StorageとはAzure Storageのサービスの一つで、バイナリなどのデータを大量に置くことができるストレージサービスです Blobは1つのファイルやデータを表し. Resources Webinars, datasheets, reference architectures, demo videos and more. But first, let’s make sure you understand what serverless is. If you are interested in using. You can vote up the examples you like or vote down the ones you don't like. After over a day of going through their documentation, reading GitHub issues, going through the SDK unit tests and shudder the second page of google results, here's how:. Tutorial: Running a Python Web Application in Windows Azure The Windows Azure SDK includes command-line tools that make it easy to package and deploy almost anything to the cloud. Currently, there are no items in this container. For me, its failing all the time when I try to create a container, but for one of my colleague, he is getting mixed results; sometimes it goes through in 15seconds, sometimes it takes upto 10 minutes and most of the times it is bailing out. Please note that several. Using the following DockerFile, we can see that we have a full Python + Tensorflow libraries in just under 1 GB running on Windows Server (Nano). Docker Documentation Get started with Docker Try our multi-part walkthrough that covers writing your first app, data storage, networking, and swarms, and ends with your app running on production servers in the cloud. Azure Web Apps deploy - Deploy an application to Azure Web Apps. 3 Upload the Python Installer Upload the Python installer which you want to use. gz Deploying a scoring service to the Azure Container Service (AKS) This hands-on lab guides us through deploying a Machine Learning scoring function to a remote environment using Azure Machine Learning. Learn more by reading the Azure Container Instances overview. I'm writing some python code against Azure Blob Storage and running into something that appears to be a bug. During deployment, the images are registered in Azure Container Registry (ACR). Here is how to create a container in Azure storage. They can be customized to build a web app for a small business or a personal web app. Azure SDK for Python Documentation, Release 2. All the blobs must be inside a container in your storage. Persistent Storage and Volumes using Kubernetes on Azure with AKS or Azure Container Service 26 januari 2018 26 januari 2018 / Pascal Naber Many applications hosted in a Docker container need a volume to store data on or to read from. Use the tools and languages you know. An Introduction to Using Python with Microsoft Azure If you build technical and scientific applications, you're probably familiar with Python. I've been playing around with Python and Machine Learning recently, so I thought I'd give this one a try and create an AzureML Web Service using a machine learning model built with Python. At the same time, working with Azure Container Registry is very similar to working with Docker Hub. Azure Storage consists of 1) Blob storage, 2) File Storage, and 3) Queue storage. Rather than jumping into ARM portal you can easily create Azure Storage Account with few commands. NET 5 Web Apps or console applications directly to a Docker container, has been updated to include support for today’s preview of Windows Server Containers. 5 --registry-login-server myregistry. Getting Started. Fun with Azure Container Instances Azure Container Instances were recently announced, making it easy for developers to spin up a container on-demand without having to provision and maintain a VM or a cluster. Azure Container Services Azure Container Service helps us to create, configure, manage, scale and leverage the virtual machines, which are preconfigured to run with containerized Applications. Service Description Azure Container Instances offers the fastest and simplest way to run a container in Azure, without having to provision any virtual machines and without having to adopt a higher-level service. To create a client object, you will need the storage account's blob service account URL. Create a Secret to hold the registry credentials. The path is relative to the devcontainer. The location of a Dockerfile that defines the contents of the container. Currently, there are no items in this container. Create an ACS Cluster and Deploy the Web App (02_DeployOnACS. Microsoft has made the preview of Azure Container Service (ACS) available to a broader set of developers. Azure Blob container has been created successfully as shown above. You can either use the Azure Portal UI or use the Cloud shell to do so. Best of all: when you use Visual St. What you might not know is that there are now tools available that make it easy for you to put your Python applications on Microsoft Azure, Microsoft's cloud computing platform. The post however doesn't give a complete resolution but gives a pretty good idea of what needs to be done. Dockerfiles contain a set of instructions that specify what environment to use and which commands to run. Tutorial: Running a Python Web Application in Windows Azure The Windows Azure SDK includes command-line tools that make it easy to package and deploy almost anything to the cloud. Do more and make the New Relic Platform your own with APIs, SDKs, code snippets, tutorials, and more developer tools. Open a command prompt and execute the following statements to pull the Azure IoT Edge runtime modules down to your machine. It took us a while to figure it out and ran into a bunch of issues. Welcome to Azure Container Service Tools documentation!¶ The ACS CLI is a Python application, as such you should be able to run it on any platform that has Python 3 installed. Chilkat Python Downloads Python Module for Windows, Linux, Alpine Linux,. The image is now in the Azure Container Registry. js and Electron using npm at Chilkat npm packages for Node. You are first going to pull the Azure IoT Edge containers down to your local machine, tag them and then push them to your own ACR. The Logic Apps instance controls the workflow and is instantiated by the trigger signal, creating a container group with a single container based on the image stored in the registry. Create a container registry. During deployment, the images are registered in Azure Container Registry (ACR). Writing Azure Functions in Python offers a great way to run Python code serverless on Azure. (Python) Get Container Properties. Please note that several. NET, Microsoft Office, Azure, Windows, Java, Adobe, Python, SQL, JavaScript, Angular and much more. Docker is able to automatically build images using instructions from a Docker file. Management APIs. You can use the IBM Cloud Container Registry to deploy containers from IBM Cloud public images and your private images into the default namespace of your IBM Cloud Kubernetes Service cluster. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. I've been playing around with Python and Machine Learning recently, so I thought I'd give this one a try and create an AzureML Web Service using a machine learning model built with Python. js, PHP, Python, and Ruby. If you haven't - visit the Microsoft Azure Cloud website and try it for free for 90 days. namedtuple (typename, field_names, *, rename=False, defaults=None, module=None) ¶ Returns a new tuple subclass named typename. NET) Azure Storage: Create Container. This comprises one aspect of the platform as a service (PaaS) offerings for the Microsoft Azure Platform. How to use Azure storage for. This Docker container is 125MB with the compiled Python dependencies weighing in at 31. Azure Container Instances is a simple mechanism to run a container in Azure. There is a quick glance pane on the right side that shows the SSH port that you can connect to, the DNS name, virtual IP, and other core values. This sample application demonstrates several common Azure Container Instances operations in Python using the Azure libraries for Python. The following command will create a single. Requirements ¶ The below requirements are needed on the host that executes this module. You can create an ASP. For a more general view of Azure and Python, you can go on thePython Developer Center for Azure User Documentation 1. Click on Ok button to create Blob container. API Access to the Storage Account and Containers. In this post, we'll walked through some of the common input triggers and output bindings and showed how they can be used in Python. The image is now in the Azure Container Registry. During deployment, the images are registered in Azure Container Registry (ACR). In this post, I'll discuss what Azure Containers can do and how they can be used and managed in Azure. As we'll see with the options we've selected, these will appear in the settings when the container is created along with other settings we don't specify, but we'll need to note when we create our template. You can optionally expose the container to the internet with a public IP address. OpenShift Container Platform can be configured to access a Microsoft Azure infrastructure, including using Azure disk as persistent storage for application data. This view works on my local machine, but fails once it is. Deploy Python to Azure. Contribute to Azure/azure-storage-python development by creating an account on GitHub. This article will show you how to delete and create Windows Containers running on Microsoft Azure. Teams & Organizations Create Teams to manage access control to your Organization's repos and builds. Azure SDK for Python Documentation, Release 2. Using Python operating Azure Blob Service Revision 1 posted to TechNet Articles by EngSoonCheah on 12/16/2014 4:40:05 PM In the previous article we briefly introduce the Azure SDK for Python, and demonstrates how to use Management Service API, and design, this article will begin to serve as the focus on Azure, demonstrate how to use the SDK to. Create container groups, get the logs of a container and more. At the same time, working with Azure Container Registry is very similar to working with Docker Hub. With LUIS, you can use pre-existing, world-class, pre-built models from Bing and Cortana whenever they suit your purposes -- and when you need specialized models,LUIS guides you through the process of quickly building them. There is a quick glance pane on the right side that shows the SSH port that you can connect to, the DNS name, virtual IP, and other core values. When you get to the Configure Container Section click on it to open a new blade. 0 specifications. For example, you can choose to delete the entire resource group in one simple step later. Deployment tutorials. Setting up a VM on Azure using the Python SDK. Downloadin an Azure Storage Blob Container with complex path of folders and sub folders - python-azure-blob-storage-download. In the Azure Portal, click the Create a resource button (green plus in the left-upper corner) Next, search for azure container instance and click. collections. This Graphical PowerShell runbook connects to Azure using an Automation Run As account and starts all V2 VMs in an Azure subscription or in a resource group or a single named V2 VM. I have updated this package but Microsoft has broken compatibility with the stable release of their SDK again. Chilkat Python Downloads Python Module for Windows, Linux, Alpine Linux,. NET Core application using the Azure DevOps Demo Generator tool. This allows you to host microservicess on a fully-managed. I have updated this package but Microsoft has broken compatibility with the stable release of their SDK again. Create Azure IoT Hub and Register a Device. Teams & Organizations Create Teams to manage access control to your Organization's repos and builds. Azure Storage consists of 1) Blob storage, 2) File Storage, and 3) Queue storage. Azure Monitor - Container Insights metrics for Kubernetes clusters. Once Blob container is created successfully, click on the Blob to Open. Each configuration corresponds to a version of Python, such as Python 3. All blobs must be located in a container. # Get all Files from an Azure Storage Blob Container Azure Storage is described as a service that provides storages that is available, secure, durable, scalable, and redundant. Deploying Azure Container Service using the azurerm Python library Posted on October 15, 2016 by Guy Bowerman Azure Container Service is an easy to deploy container framework for Azure. Microsoft labs for learning to build models and create services with Azure Machine Learning View on GitHub Download. When you get to the Configure Container Section click on it to open a new blade. 5 cluster, you should be able to read your files from the blob with dbfs:/mnt/. The intended audience for this post are IT pros, such as consultants, engineers, operators. Azure Container Instance. Azure doesn't allow just anyone to be able to create containers on your Azure subscription. To create a client object, you will need the storage account's blob service account URL. It has new plans for cloud and container capability, too. This post will answer those questions and walk you through a simple introduction to serverless using Azure’s serverless platform with Python. As we'll see with the options we've selected, these will appear in the settings when the container is created along with other settings we don't specify, but we'll need to note when we create our template. Azure DevOps - Never manually create a Docker container again! Posted on October 9, 2018 by Justin Paul | 0 Comments Azure DevOps is a suite of offerings from Microsoft that aims to help companies deliver better software faster. Let me define preconfigured Blob Containers, Tables, Queue in ARM template Right now we can define storage account, account location, name, type of redundancy and some other minor parameters - and it's cool!. 5 cluster, you should be able to read your files from the blob with dbfs:/mnt/. The post however doesn't give a complete resolution but gives a pretty good idea of what needs to be done. This view works on my local machine, but fails once it is. (Python) Get Container Properties. This document will walk you through the process of deploying an application to Kubernetes with Visual Studio Code. Container Linux is designed to be updated automatically with different schedules per channel. One of my clients recently faced this issue of downloading an Azure Storage blob container with complex path of folders and sub-folders to his local machine. Also, since Functions play nicely with others (C#, F#, Node. Let's start by creating a container image for our Python code. Four different clients are provided to to interact with the various components of the Blob Service:. How to use Azure storage for. I work with Azure Functions a lot. This represents the first release of the ground-up rewrite of the client libraries to ensure consistency, idiomatic design, and excellent developer experience and productivity. NET) Azure Storage: Create Container. For documentation please see the Microsoft Azure Python Developer Center and our API Reference (also available on readthedocs). Azure SDK for Python Documentation, Release 2. Windows If necessary, see the pip documentation for instructions on installing pip. More than 1 year has passed since last update. We will then pass a Python script that includes code to predict the values based on an inbound data point. Install prerequisites. The script retrieves data from an Azure SQL database, operates on the data and then writes the results back to the database as shown in the diagram below. So today let’s use NodeJS to create a thumbnail image anytime a new image is uploaded to an Azure Blob Storage container. Azure's offerings for containers began with Azure Container Service (ACS), which gives you the option to choose between the most popular container orchestrators: Mesos, Swarm, and Kubernetes. Azure App Service has got more versatile because it can now run Linux. js, PHP and Ruby on Linux. python-swiftclient version 2. This article describes how to make REST calls to Azure Resource Manager (ARM) from Python. Tip : even if you download a ready-made binary for your platform, it makes sense to also download the source. baseblobservice. Using the AWS Elastic Beanstalk Python Platform. Create one service and expose it to several service protocols including SOAP. This project provides a client library in Python that makes it easy to consume Microsoft Azure Storage services. Azure Container Instances is a simple mechanism to run a container in Azure. This sample is an end-to-end scenario for getting started with Azure Container Service (ACS) and, optionally, Azure Container Registry (ACR) using the Azure SDK for Python. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. How to import Python extension modules in Azure Functions Posted on November 3, 2016 | Michael McKenna An awesome feature of Azure Functions is its ability to run a wide range of languages, C#, F#, Node. Creating an Azure Container Service Docker Swarm. As we'll see with the options we've selected, these will appear in the settings when the container is created along with other settings we don't specify, but we'll need to note when we create our template. I'm hacking with a customer today who is using Python and needs to upload images to Azure IoT Hub using the File Upload API. Once deployed, you will be able to access the Function Apps page Once deployed, you can test your Function App:. Create the client. Create a container Upload a blob into a container Download blobs List the blobs in a container Delete a blob Installing the SDK: My machine is a. Manage Azure Storage Account using Azure CLI. The code in this project is ingested into one or more articles on docs. After Microsoft Azure is configured properly, some additional configurations need to be completed on the OpenShift Container Platform hosts. In this part, we'll move briefly away from Python to look at R together with Shiny as a dynamic reporting and visualisation capability pulling data from a Postgres database. The steps are given below, which are required to create a container, using. js, or Python, or select from several open source applications from a gallery to deploy. Running Azure Functions anywhere with the power of containers 03 December 2017 Comments Posted in Serverless, Container, Functions, cross-platform. Azure Storage Blob Service REST API: Sample code to fetch the list of blobs in the specified container. NET Core project and choosing 'Add -> Docker Support'). The script retrieves data from an Azure SQL database, operates on the data and then writes the results back to the database as shown in the diagram below. This post will explain how to set up a custom ACR and connect it to an existing k8s cluster to ensure images will be pulled from the private container registry. After Microsoft Azure is configured properly, some additional configurations need to be completed on the OpenShift Container Platform hosts. gz Deploying a scoring service to the Azure Container Service (AKS) This hands-on lab guides us through deploying a Machine Learning scoring function to a remote environment using Azure Machine Learning. First we will look at some of the basics involved in accessing an Azure storage account and the containers hosted therein. 0 specifications. There are 2 identical implementations, one using REST and the other using the. Azure Functions provides an intuitive, browser-based user interface allowing you to create scheduled or triggered pieces of code implemented in a variety of programming languages 0 1. As you might know from the Docs, Azure Functions for Python actually uses a container image to host your code. Today, let's do a proof of concept for Azure Blob not using the. 7 or $ 200 to spend for the first 30 days, free access to most popular Azure products for 12 months and access to more than 25 products that are always free. Any serious Azure developer should have this installed right alongside Visual Studio and Azure Management Studio. Using the SDK to create and save a file in an Azure Storage Account Creating a Storage Account on Microsoft Azure From the Azure Portal, go to, Data Services, Storage, Quick-Create and fill in the required information. You can attach a recurring schedule to this runbook to run it at a specific time. When we create the Azure free account, at the same time we get a free trial subscription. Once deployed, you will be able to access the Function Apps page. This solution requires USB camera pass through into a Docker container as well as Azure IoT Edge support. Containers are grouped in "databases", which are analogous to namespaces above containers. Create a Secret to hold the registry credentials. # Use an official Python runtime as a parent image FROM python:2. collections. txt Run The Sample Update placeholders. Create an Azure Container Instance and add it to Azure Container Registry by uploading a local Docker image. Configure Azure. Create sub-folders inside container in azure storage Use Case: I'm designing a multi-tenant application and each user need to have their own directory/work area. It's time for us to package and deploy the model as a container image which will be exposed as a web service. Hello everyone, in last blog post of Azure Storage we discussed about Blobs and it's types. The Python SDK for Azure Functions provides a rich API layer for binding to HTTP requests, timer events, and other Azure services, such as Azure Storage, Azure Cosmos DB, Service Bus, Event Hubs, or Event Grid, so you can use productivity enhancements like autocomplete and Intellisense when writing your code. If you want to learn how to automatically deploy a Function App to Azure using Azure DevOps, check out this post. Package managers make this go away most of the time, but sometimes there are things you need installed at the OS level to build or run. Those examples assume that you are familiar with the basic concepts of those technologies. For quick access to the Azure CLI consider using the Azure Cloud Shell. API Access to the Storage Account and Containers. They are extracted from open source Python projects. Install the management package via pip:. Not only can you run Web App for Containers, and publish Docker containers to Azure, but there is built-in support for ASP. An insight into the future of Microservices with containers and serverless computing; About : Microsoft Azure is rapidly evolving and is widely used as a platform on which you can build Microservices that can be deployed on-premise and on-cloud heterogeneous environments through Microsoft Azure Service Fabric. sh shown above. NET) Azure Storage: Create Container. I work with Azure Functions a lot. Create a resource group. Running Azure Functions anywhere with the power of containers 03 December 2017 Comments Posted in Serverless, Container, Functions, cross-platform. To start using it, build a new container image with the following: sudo docker build -t my_application_img. Once the container is up and running the user can send requests to be scored using the model and check the model performance. Create container image: from the model in the workspace, we create a container image with GPU support; Deploy container image: from the image in the workspace, we deploy the image to compute that supports GPUs; Machine Learning SDK. Container Linux is designed to be updated automatically with different schedules per channel. Using Docker simplifies the deployment. Shay also specializes in performance management & diagnosti. I stumbled onto this stack overflow post. For me, its failing all the time when I try to create a container, but for one of my colleague, he is getting mixed results; sometimes it goes through in 15seconds, sometimes it takes upto 10 minutes and most of the times it is bailing out. Before you start make sure you read the series of articles I published about Windows Containers on Microsoft Azure before continuing. The Azure Machine Learning service has a Machine Learning SDK for Python. Downloadin an Azure Storage Blob Container with complex path of folders and sub folders - python-azure-blob-storage-download. Pull Containers. Create a Serverless Angular App With Azure Functions and Blob Storage Learn how to create a serverless Angular app, and get rid of concerns like elasticity, scale, and resiliency so you can. Originally announced at AzureCon in October 2015, the service went into private tech. Spend less time integrating and more time delivering higher-quality software, faster. So, in my search engine, I will type “Install Miniconda”, and this will lead me to the “Conda installer. 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: