FLASK - 翻译成英语

• flask

在 中文 中使用 Flask 的示例及其翻译为 英语

Flask和Flask扩展开发者为更大型应用改进的最佳途径就是从用户那里获取反馈。
The best way for the Flask and Flask extension developers to improve the tools for larger applications is getting feedback from users.

Flask社区目前没那么大，因此找到有用的信息并不容易。
The Flask community is currently not as big, and so information may be harder to come by.

Django之后，我转向学习Flask，另一个Web框架，虽然微小，但具有很强的构建可定制性。
From Django, I moved on to Flask, another web framework, but tiny and built for customizability.

它致力于简化在Flask中SQLAlchemy的使用，提供了有用的默认值和额外的助手来更简单地完成常见任务。
It aims to simplify using SQLAlchemy with Flask by providing useful defaults and extra helpers that make it easier to accomplish common tasks.

使用Flask创建一个Python服务器，可以利用WatsonVisualRecognition服务对图像进行分类。
Create a Python server with Flask that can utilize the Watson Visual Recognition service for classifying images.

本书大部分的内容是不会随着Flask较小的更新发生变化，但这是要记住的东西。
Most of the lessons in this book aren't going to change with minor updates to Flask, but it's something to keep in mind nonetheless.

本课程要求学员有使用FlaskWeb开发框架、SQLAlchemy的经验，并理解OAuth2.0的基本原理。
This course assumes you have experience working with the Flask web development framework, SQLAlchemy, and understand the basics of OAuth 2.0.

它需要的只是创建Flask类的实例，然后是显示“HiWelcome”字符串的路由。
Here you need to create an instance of the Flask class, which is followed by a route that shows the“Hi Welcome” string”.

我们还将从flask模块中导入request对象，我们将在稍后使用它。
We will also import the request object from the flask module, which we will use later.

本文转载自：WEB这是FlaskMega-Tutorial系列的第十三部分，我将告诉你如何扩展Microblog应用以支持多种语言。
This is the thirteenth installment of the Flask Mega-Tutorial series, in which I'm going to tell you how to expand Microblog to support multiple languages.

它旨在简化在Flask中使用SQLAlchemy，提供有用的缺省值和额外的帮助器，使其更容易完成常见任务。
It aims to simplify using SQLAlchemy with Flask by providing useful defaults and extra helpers that make it easier to accomplish common tasks.

使用Flask构建webservices是十分简单地，比我在Mega-Tutorial中构建的完整的服务端的应用程序要简单地多。
Building web services with Flask is surprisingly simple, much simpler than building complete server side applications like the one I built in the Mega-Tutorial.

为此，我选择了Flask框架，它允许我们用Python编写应用程序。
For that, I went with Flask, which allows us to write the app in Python.

LSMFlask安全架构的部分实现，最初是为Fluke微内核操作系统开发的。
The LSM is a partial implementation of the Flask security architecture, originally developed for the Fluke microkernel operating system.

你可以在Flask中使用NoSQL，但是方法和工具与其它的数据库引擎迥异。
You can use NoSQL databases with Flask, but the methods and tools vary between engines.

在Flask上运行代码非常简单（例如，显示“HiWelcome”）。
It is very easy to run codes on Flask for instance, reflecting“Hi Welcome”.

首先，我们需要从flask模块导入Flask类，所以我们需要的所有功能都可用。
First of all, we import the Flask class from the flask module, so all the functionality we need becomes available.

对于小规模的服务器端调度，两个框架都很容易封装在诸如Flaskweb服务器中。
For small-scale server-side deployments both frameworks are easy to wrap in e.g. a Flask web server.

我们将创建一些虚拟的JSON数据，发布到在Pythonanywhere上运行的Flask服务器。
We will create some dummy JSON data to post to the Flask server running on Pythonanywhere.

作为其中的一部分，你还将学习如何为flask命令创建自己的CLI扩展。
As part of that effort you will also learn about creating your own CLI extensions to the flask command.