Scrapy 2.5 documentation Scrapy is a fast high-level web crawling [https://en.wikipedia.org/wiki/Web_crawler] and web scraping [https://en.wikipedia.org/wiki/Web_scraping] framework, used to crawl websites which are detailed in this paper [https://www.evanjones.ca/memoryallocator/], got merged in Python 2.5, but this only reduces the problem, it doesn’t fix it completely. To quote the paper: Unfortunately spider (Spider object) – the spider associated with the response headers_received New in version 2.5. scrapy.signals.headers_received(headers, request, spider) Sent by the HTTP 1.1 and S3 download handlers

modules | next | Celery 2.5.5 documentation » This document describes an older version of Celery (2.5). For the latest stable version please go here. Celery - Distributed Task Queue Contents: Getting Cookbook Contributing Community Resources Tutorials Frequently Asked Questions What’s new in Celery 2.5 Change history API Reference Internals Indices and tables Index Module Index Search Page © Copyright documentation » This document describes an older version of Celery (2.5). For the latest stable version please go here. Getting Started Release: 2.5 Date: February 04, 2014 Introduction Synopsis Overview Example

files CSV files Others Weblate’s Web API Notification hooks Exports RSS feeds Changes weblate 2.5 weblate 2.4 weblate 2.3 weblate 2.2 weblate 2.1 weblate 2.0 weblate 1.9 weblate 1.8 weblate 1.7 weblate you will see an overview of projects and components and their translation progress. New in version 2.5. By default, this will show the components of projects you are subscribed to, cross- referenced with to 2.1 Upgrade from 2.1 to 2.2 Upgrade from 2.2 to 2.3 Upgrade from 2.3 to 2.4 Upgrade from 2.4 to 2.5 Upgrading to Django 1.7 Migrating from Pootle Authentication User registration Authentication backends

（这里通篇的链接都指向它们）可以在 usage documentation 中找到——请不要 忘了一并阅读。 Fabric 是什么？ 如 README 所说： Fabric 是一个 Python (2.5-2.7) 的库和命令行工具，用来提高基于 SSH 的 应用部署和系统管理效率。 更具体地说，Fabric 是： 一个让你通过 命令行 执行 无参数 Python 函数 的工具； 一个让通过 SSH Continue anyway?"): abort("Aborting at user request.") [...] 为了引入这个新特性，我们需要添加一些新东西： 在 Python 2.5 中，需要从 __future__ 中导入 with ； Fabric contrib.console 子模块提供了 confirm 函数，用于简单的 yes/no 提示。 settings 上 上一页 | Fabric 文档 » 上下文管理器 Context managers for use with the with statement. 注解 When using Python 2.5, you will need to start your fabfile with from __future__ import with_statement in order to make use

springframework.org/schema/beans/spring-beans-2.5.xsd http://www.springframework.org/schema/tx http://www.springframework.org/schema/tx/spring-tx-2.5.xsd http://www.springframework.org/schema/aop org/schema/aop http://www.springframework.org/schema/aop/spring-aop-2.5.xsd"> 启动控制台 springframework.org/schema/beans/spring-beans-2.5.xsd http://www.springframework.org/schema/tx http://www.springframework.org/schema/tx/spring-tx-2.5.xsd http://www.springframework.org/schema/aop

update({'bath': '2.5 bath', 'sqft': '1100'}) >>> query = House.update(features=new_features) >>> query.where(House.id == h.id).execute() 1 >>> h = House.get(House.id == h.id) >>> h.features {'bath': '2.5 bath', to use this functionality you must be using the correct version of Postgres with psycopg2 version 2.5 or greater. To use BinaryJSONField, which has many performance and querying advantages, you must have override this method to create a customized JSON wrapper. Note You must be using Postgres 9.2 / psycopg2 2.5 or greater. Note If you are using Postgres 9.4, strongly consider using the BinaryJSONField instead

update({'bath': '2.5 bath', 'sqft': '1100'}) >>> query = House.update(features=new_features) >>> query.where(House.id == h.id).execute() 1 >>> h = House.get(House.id == h.id) >>> h.features {'bath': '2.5 bath', to use this functionality you must be using the correct version of Postgres with psycopg2 version 2.5 or greater. To use BinaryJSONField, which has many performance and querying advantages, you must have database it will be returned as a Python data structure. Note You must be using Postgres 9.2 / psycopg2 2.5 or greater. Note If you are using Postgres 9.4, strongly consider using the BinaryJSONField instead

to use this functionality you must be using the correct version of Postgres with psycopg2 version 2.5 or greater. To use BinaryJSONField, which has many performance and querying advantages, you must have update({'bath': '2.5 bath', 'sqft': '1100'}) >>> query = House.update(features=new_features) >>> query.where(House.id == h.id).execute() 1 >>> h = House.get(House.id == h.id) >>> h.features {'bath': '2.5 bath', database it will be returned as a Python data structure. Note You must be using Postgres 9.2 / psycopg2 2.5 or greater. Note If you are using Postgres 9.4, strongly consider using the BinaryJSONField instead

update({'bath': '2.5 bath', 'sqft': '1100'}) >>> query = House.update(features=new_features) >>> query.where(House.id == h.id).execute() 1 >>> h = House.get(House.id == h.id) >>> h.features {'bath': '2.5 bath', to use this functionality you must be using the correct version of Postgres with psycopg2 version 2.5 or greater. To use BinaryJSONField, which has many performance and querying advantages, you must have database it will be returned as a Python data structure. Note You must be using Postgres 9.2 / psycopg2 2.5 or greater. Note If you are using Postgres 9.4, strongly consider using the BinaryJSONField instead

update({'bath': '2.5 bath', 'sqft': '1100'}) >>> query = House.update(features=new_features) >>> query.where(House.id == h.id).execute() 1 >>> h = House.get(House.id == h.id) >>> h.features {'bath': '2.5 bath', to use this functionality you must be using the correct version of Postgres with psycopg2 version 2.5 or greater. To use BinaryJSONField, which has many performance and querying advantages, you must have database it will be returned as a Python data structure. Note You must be using Postgres 9.2 / psycopg2 2.5 or greater. Note If you are using Postgres 9.4, strongly consider using the BinaryJSONField instead