Merge pull request #97 from anthonychu/20200328-update-readme-devcontainer

Update readme with limitations, quickstart link

Author: priyaananthasankar

README.md

@@ -5,7 +5,7 @@
 
 # Durable Functions for Python
 
-The `azure-functions-durable` [pip](https://pypi.org/project/azure-functions-durable/) package allows you to write [Durable Functions](https://docs.microsoft.com/en-us/azure/azure-functions/durable/durable-functions-overview) for Python(https://docs.microsoft.com/en-us/azure/azure-functions/functions-reference-python). Durable Functions is an extension of [Azure Functions](https://docs.microsoft.com/en-us/azure/azure-functions/functions-overview) that lets you write stateful functions and workflows in a serverless environment. The extension manages state, checkpoints, and restarts for you. Durable Functions' advantages include:
+The `azure-functions-durable` [pip](https://pypi.org/project/azure-functions-durable/) package allows you to write [Durable Functions](https://docs.microsoft.com/en-us/azure/azure-functions/durable/durable-functions-overview) for [Python](https://docs.microsoft.com/en-us/azure/azure-functions/functions-reference-python). Durable Functions is an extension of [Azure Functions](https://docs.microsoft.com/en-us/azure/azure-functions/functions-overview) that lets you write stateful functions and workflows in a serverless environment. The extension manages state, checkpoints, and restarts for you. Durable Functions' advantages include:
 
 * Define workflows in code. No JSON schemas or designers are needed.
 * Call other functions synchronously and asynchronously. Output from called functions can be saved to local variables.
@@ -25,81 +25,53 @@ A durable function, or _orchestration_, is a solution made up of different types
 
 Durable Functions' function types and features are documented in-depth [here.](https://docs.microsoft.com/en-us/azure/azure-functions/durable/durable-functions-types-features-overview)
 
-## Getting Started
-
-You can follow the instructions below to get started with a function chaining example, or follow the general checklist below:
-
-1. Install prerequisites:
-    - [Azure Functions Core Tools version 2.x](https://docs.microsoft.com/en-us/azure/azure-functions/functions-run-local#install-the-azure-functions-core-tools)
-    - [Azure Storage Emulator](https://docs.microsoft.com/en-us/azure/storage/common/storage-use-emulator) (Windows) or an actual Azure storage account (Mac or Linux)
-    - Python 3.6 or later
+## Current limitations
 
-2. [Create an Azure Functions app.](https://docs.microsoft.com/en-us/azure/azure-functions/functions-create-first-function-python)
+We're actively working on Python support for Durable Functions and we expect a Public Preview announcement in Q2 CY2020. The following are the current known limitations.
 
-3. Install the Durable Functions extension
-
-Run this command from the root folder of your Azure Functions app:
-```bash
-func extensions install -p Microsoft.Azure.WebJobs.Extensions.DurableTask -v 1.8.3
-```
+### Functionality
 
-**durable-functions requires Microsoft.Azure.WebJobs.Extensions.DurableTask 1.7.0 or greater.**
+* `DurableOrchestrationContext.create_timer()` is not yet supported (coming soon [#35](https://github.com/Azure/azure-functions-durable-python/issues/35))
+* Sub-orchestrations are not yet supported (planned [#62](https://github.com/Azure/azure-functions-durable-python/issues/62))
+* Durable Entities are not yet supported (not yet planned [#96](https://github.com/Azure/azure-functions-durable-python/issues/96))
 
-4. Install the `azure-durable-functions` pip package at the root of your function app:
+### Tooling
 
-Create and activate virtual environment
-```
-python3 -m venv env
-source env/bin/activate
-```
+* Python Durable Functions requires updated versions of Azure Functions Core Tools that includes Python worker [1.1.0](https://github.com/Azure/azure-functions-python-worker/releases/tag/1.1.0), templates ([bundle-1.2.0](https://github.com/Azure/azure-functions-templates/releases/tag/bundle-1.2.0)), and extension bundles ([1.2.0](https://github.com/Azure/azure-functions-extension-bundles/releases/tag/1.2.0)) that are not yet released (ETA May 2020). Use the VS Code dev container in the [Getting Started](#getting-started) section to access a development environment with the required versions of the tools installed.
 
-```bash
-pip install azure-durable-functions
-```
+### Deployment
 
-5. Write an activity function ([see sample](./samples/python_durable_bindings/DurableActivity)):
-```python
-def main(name: str) -> str:
-    logging.info(f"Activity Triggered: {name}")
-    # your code here
-```
+* Python Durable Functions requires an updated version of the Azure Functions Python language worker ([1.1.0](https://github.com/Azure/azure-functions-python-worker/releases/tag/1.1.0)) that is not yet available in Azure. Deploy your Python Durable Functions apps in containers (requires Premium or App Service plans). (Linux consumption plan support ETA May 2020)
 
-6. Write an orchestrator function ([see sample](./samples/python_durable_bindings/DurableOrchestrationTrigger)):
+## Getting Started
 
-```python
-def main(context: str):
-    orchestrate = df.Orchestrator.create(generator_function)
-    result = orchestrate(context)
-    return result
-```
+Follow these instructions to get started with Durable Functions in Python:
 
-**Note:** Orchestrator functions must follow certain [code constraints.](https://docs.microsoft.com/en-us/azure/azure-functions/durable-functions-checkpointing-and-replay#orchestrator-code-constraints)
+**🚀 [Python Durable Functions quickstart](https://aka.ms/pythondurable)**
 
-7. Write your client function ([see sample](./samples/DurableOrchestrationClient/)):
+## Samples
 
-TBD
+Take a look at this project's [samples directory](./samples/):
 
-**Note:** Client functions are started by a trigger binding available in the Azure Functions 2.x major version. [Read more about trigger bindings and 2.x-supported bindings.](https://docs.microsoft.com/en-us/azure/azure-functions/functions-triggers-bindings#overview)
+* [Function Chaining](./samples/function_chaining)
+* [Fan-out/Fan-in - Simple](./samples/fan_out_fan_in)
+* [Fan-out/Fan-in - TensorFlow](./samples/fan_out_fan_in_tensorflow)
+* [External Events - Human Interaction & Timeouts](./samples/external_events)
 
-## Samples
+### Orchestrator example
 
-The [Durable Functions samples](https://docs.microsoft.com/en-us/azure/azure-functions/durable-functions-install) demonstrate several common use cases. They are located in the [samples directory.](./samples/) Descriptive documentation is also available:
+```python
+import azure.durable_functions as df
 
-* [Function Chaining - Hello Sequence](https://docs.microsoft.com/en-us/azure/azure-functions/durable-functions-sequence)
-* [Fan-out/Fan-in - Cloud Backup](https://docs.microsoft.com/en-us/azure/azure-functions/durable-functions-cloud-backup)
-* [Monitors - Weather Watcher](https://docs.microsoft.com/en-us/azure/azure-functions/durable-functions-monitor)
-* [Human Interaction & Timeouts - Phone Verification](https://docs.microsoft.com/en-us/azure/azure-functions/durable-functions-phone-verification)
 
-```python
-def generator_function(context):
-    outputs = []
+def orchestrator_function(context: df.DurableOrchestrationContext):
     task1 = yield context.call_activity("DurableActivity", "One")
     task2 = yield context.call_activity("DurableActivity", "Two")
     task3 = yield context.call_activity("DurableActivity", "Three")
 
-    outputs.append(task1)
-    outputs.append(task2)
-    outputs.append(task3)
-
+    outputs = [task1, task2, task3]
     return outputs
+
+
+main = df.Orchestrator.create(orchestrator_function)
 ```