tornado.tcpserver — Basic IOStream-based TCP server Coroutines and concurrency tornado.gen — Generator-based coroutines tornado.locks – Synchronization primitives tornado.queues – Queues for coroutines divided into four major components: A web framework (including RequestHandler which is subclassed to create web applications, and various supporting classes). Client- and server-side implementions of HTTP yield is a generator. All generators are asynchronous; when called they return a generator object instead of running to completion. The @gen.coroutine decorator communicates with the generator via the yield

tornado.tcpserver — Basic IOStream-based TCP server Coroutines and concurrency tornado.gen — Generator-based coroutines tornado.locks – Synchronization primitives tornado.queues – Queues for coroutines divided into four major components: A web framework (including RequestHandler which is subclassed to create web applications, and various supporting classes). Client- and server-side implementions of HTTP yield is a generator. All generators are asynchronous; when called they return a generator object instead of running to completion. The @gen.coroutine decorator communicates with the generator via the yield

. . . . . . . . . . . . . . . . . . . . . . . . 1122 25 开发工具 1123 25.1 pydoc —Documentation generator and online help system . . . . . . . . . . . . . . . . . . . . . . . 1123 25.2 doctest —测试交互性的 in that it does not use the module administration —it reads the file unconditionally and does not create a new module.1 The arguments are a file name and two optional dictionaries. The file is parsed and deleter attributes were added. range(stop) range(start, stop[, step]) This is a versatile function to create lists containing arithmetic progressions. It is most often used in for loops. The arguments must

. . . . . . . . . . . . . . . . . . . . . . . . 1122 25 开发工具 1123 25.1 pydoc —Documentation generator and online help system . . . . . . . . . . . . . . . . . . . . . . . 1123 25.2 doctest —测试交互性的 in that it does not use the module administration —it reads the file unconditionally and does not create a new module.1 The arguments are a file name and two optional dictionaries. The file is parsed and deleter attributes were added. range(stop) range(start, stop[, step]) This is a versatile function to create lists containing arithmetic progressions. It is most often used in for loops. The arguments must

. . . . . . . . . . . . . . . . . . . . . . . . 1122 25 开发工具 1123 25.1 pydoc —Documentation generator and online help system . . . . . . . . . . . . . . . . . . . . . . . 1123 25.2 doctest —测试交互性的 in that it does not use the module administration —it reads the file unconditionally and does not create a new module.1 The arguments are a file name and two optional dictionaries. The file is parsed and deleter attributes were added. range(stop) range(start, stop[, step]) This is a versatile function to create lists containing arithmetic progressions. It is most often used in for loops. The arguments must

此行为特性的实现将无法正常使用。 34 Chapter 4. 内置类型 The Python Library Reference, 发布 3.6.15 4.5.1 生成器类型 Python 的generator 提供了一种实现迭代器协议的便捷方式。如果容器对象 __iter__() 方法被实现为一 个生成器，它将自动返回一个迭代器对象（从技术上说是一个生成器对象），该对象提供 __iter__() 和 The Python Library Reference, 发布 3.6.15 copy() 返回原字典的浅拷贝。 classmethod fromkeys(seq[, value]) Create a new dictionary with keys from seq and values set to value. fromkeys() 属于类方法，会返回一个新字典。value 默认为 the creation of (value, key) pairs using zip(): pairs = zip(d.values(), d.keys()). Another way to create the same list is pairs = [(v, k) for (k, v) in d.items()]. 在添加或删除字典中的条目期间对视图进行迭代可能引发RuntimeError

此行为特性的实现将无法正常使用。 34 Chapter 4. 内置类型 The Python Library Reference, 发布 3.6.15 4.5.1 生成器类型 Python 的generator 提供了一种实现迭代器协议的便捷方式。如果容器对象 __iter__() 方法被实现为一 个生成器，它将自动返回一个迭代器对象（从技术上说是一个生成器对象），该对象提供 __iter__() 和 The Python Library Reference, 发布 3.6.15 copy() 返回原字典的浅拷贝。 classmethod fromkeys(seq[, value]) Create a new dictionary with keys from seq and values set to value. fromkeys() 属于类方法，会返回一个新字典。value 默认为 the creation of (value, key) pairs using zip(): pairs = zip(d.values(), d.keys()). Another way to create the same list is pairs = [(v, k) for (k, v) in d.items()]. 在添加或删除字典中的条目期间对视图进行迭代可能引发RuntimeError

com/ 112/531 而节省大量的空间。在 Python 中，这种一边循环一边计算的机制，称 为生成器：generator。 要创建一个 generator，有很多种方法。第一种方法很简单，只要把一个 列表生成式的[]改成()，就创建了一个 generator： >>> L = [x * x for x in range(10)] >>> L [0, 1, 4, 9, 16 g <generator object at 0x1022ef630> 创建 L 和 g 的区别仅在于最外层的[]和()，L 是一个 list，而 g 是一个 generator。 我们可以直接打印出 list 的每一个元素，但我们怎么打印出 generator 的 每一个元素呢？ 如果要一个一个打印出来，可以通过 next()函数获得 generator 的下一个 StopIteration 我们讲过，generator 保存的是算法，每次调用 next(g)，就计算出 g 的 下一个元素的值，直到计算到最后一个元素，没有更多的元素时，抛出 StopIteration 的错误。 当然，上面这种不断调用 next(g)实在是太变态了，正确的方法是使用 for 循环，因为 generator 也是可迭代对象： >>> g = (x * x

next? The next steps for you are to install Scrapy, follow through the tutorial to learn how to create a full-blown Scrapy project and join the community [https://scrapy.org/community/]. Thanks for your Virtual Environments and Packages [https://docs.python.org/3/tutorial/venv.html#tut-venv] on how to create your virtual environment. Once you have created a virtual environment, you can install Scrapy inside a directory where you’d like to store your code and run: scrapy startproject tutorial This will create a tutorial directory with the following contents: tutorial/ scrapy.cfg # deploy configuration

next? The next steps for you are to install Scrapy, follow through the tutorial to learn how to create a full-blown Scrapy project and join the community [https://scrapy.org/community/]. Thanks for your Virtual Environments and Packages [https://docs.python.org/3/tutorial/venv.html#tut-venv] on how to create your virtual environment. Once you have created a virtual environment, you can install Scrapy inside a directory where you’d like to store your code and run: scrapy startproject tutorial This will create a tutorial directory with the following contents: tutorial/ scrapy.cfg # deploy configuration