Python in Azure Functions 基于Python的Azure Functions实践 赵健 - Microsoft 目录 CONTENTS Python 在 Azure 中无处不在 粘合剂 – Azure Functions Azure Functions 实践 Python 在 Azure 中无处不在 IEEE Spectrum’s sixth annual interactive Dev Tools Azure DevOps Azure NoteBook 运行 Python 代码 VM App Service Functions AKS ACI Azure Batch Notebook 连接 & 集成 Azure服务 Functions 认知服务 CosmosDB Event Grid Blob … Python 应用在Azure中的多种方式 Cloud-Optimized Cost control and Operations model Azure Azure 粘合剂 – Azure Functions Serverless in Azure – FaaS 是 Serverless 架构的核心 什么是 Azure Functions .NET, Node, Java, Docker, PHP, Ruby, Python Staging & deployment

为 Python Function 自动生成 Web UI 彭未康 Touch-Callable The web framework for less serious application. Touch-Callable vs (Flask, Django) • Django, Flask • 起步快且容易（getting started quick and easy） • 扩展为复杂应用（scale 3.6 例子：生成测试用户 例子：生成测试用户 例子：生成测试用户 例子：远程控制饮水机 接下来： • 支持更多的数据类型 • 类型对应的控件可配置 大胆的想法： • 直接使用 Function 构建小型应用的管理后台？ • Serverless 管理后台？ 谢谢大家

is a static type checker for Python. Type checkers help ensure that you’re using variables and functions in your code correctly. With mypy, add type hints (PEP 484 [https://peps.python.org/pep-0484/]) inference Types from libraries Next steps Type hints cheat sheet Variables Useful built-in types Functions Classes When you’re puzzled or when things are complicated Standard “duck types” Forward references (and lambdas) Union types Optional types and the None type Disabling strict optional checking Type aliases Named tuples The type of class objects Generators Class basics Instance and class attributes Annotating

is a static type checker for Python. Type checkers help ensure that you’re using variables and functions in your code correctly. With mypy, add type hints (PEP 484 [https://peps.python.org/pep-0484/]) inference Types from libraries Next steps Type hints cheat sheet Variables Useful built-in types Functions Classes When you’re puzzled or when things are complicated Standard “duck types” Forward references type Tuple types Callable types (and lambdas) Union types Optional types and the None type Type aliases Named tuples The type of class objects Generators Class basics Instance and class attributes Annotating

is a static type checker for Python. Type checkers help ensure that you’re using variables and functions in your code correctly. With mypy, add type hints (PEP 484) to your Python programs, and mypy will ONE CONTENTS 1.1 Getting started This chapter introduces some core concepts of mypy, including function annotations, the typing module, stub files, and more. If you’re looking for a quick intro, see typing A function without type annotations is considered to be dynamically typed by mypy: def greeting(name): return 'Hello ' + name By default, mypy will not type check dynamically typed functions. This

is a static type checker for Python. Type checkers help ensure that you’re using variables and functions in your code correctly. With mypy, add type hints (PEP 484) to your Python programs, and mypy will ONE CONTENTS 1.1 Getting started This chapter introduces some core concepts of mypy, including function annotations, the typing module, stub files, and more. If you’re looking for a quick intro, see typing A function without type annotations is considered to be dynamically typed by mypy: def greeting(name): return 'Hello ' + name By default, mypy will not type check dynamically typed functions. This

essential to making the software in the environments work well. Activation entails two primary functions: adding entries to PATH for the environment and running any activation scripts that the environment frequently an "output" in a recipe that builds some variant of another package. Mutex metapackages function as a tool to help achieve mutual exclusivity among packages with different names. Let's look at set to False. Running conda config --describe ssl_verify shows: # # ssl_verify (bool, str) # # aliases: verify_ssl # # conda verifies SSL certificates for HTTPS requests, just like a web (continues

essential to making the software in the environments work well. Activation entails two primary functions: adding entries to PATH for the environment and running any activation scripts that the environment frequently an "output" in a recipe that builds some variant of another package. Mutex metapackages function as a tool to help achieve mutual exclusivity among packages with different names. Let's look at set to False. Running conda config --describe ssl_verify shows: # # ssl_verify (bool, str) # # aliases: verify_ssl # # conda verifies SSL certificates for HTTPS requests, just like a web (continues

essential to making the software in the environments work well. Activation entails two primary functions: adding entries to PATH for the environment and running any activation scripts that the environment frequently an "output" in a recipe that builds some variant of another package. Mutex metapackages function as a tool to help achieve mutual exclusivity among packages with different names. Let's look at set to False. Running conda config --describe ssl_verify shows: # # ssl_verify (bool, str) # # aliases: verify_ssl # # conda verifies SSL certificates for HTTPS requests, just like a web (continues

essential to making the software in the environments work well. Activation entails two primary functions: adding entries to PATH for the environment and running any activation scripts that the environment frequently an "output" in a recipe that builds some variant of another package. Mutex metapackages function as a tool to help achieve mutual exclusivity among packages with different names. Let's look at set to False. Running conda config --describe ssl_verify shows: # # ssl_verify (bool, str) # # aliases: verify_ssl # # conda verifies SSL certificates for HTTPS requests, just like a web (continues