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http://www.kdnuggets.com/2016/06/mining-twitter-data-python-part-1.htmlPart 1 of a 7 part series focusing on mining Twitter data for a variety of use cases. This first post lays the groundwork, an

# coding:gbkimport sysimport localedef p(f): print '%s.%s(): %s' % (f.__module__, f.__name__, f())# 返回当前系统所使用的默认字符编码p(sys.getdefaultencoding)# 返回用于转换Unicode文件名至系统文件名所使用的编码p(sys.getfiles

总览第一张图基础知识图一包括了基本规则、Python语言特点、计算机语言、如何运行Python、变量赋值五个方面，辅助你快速掌握Python编程的基底知识。第二张图基础知识图二包含了模块结构、布局、IO编程流程、标识符、Python对象、内存管理、动态类型六大模块，两张基础知识导图可以帮助你区域化了解Python的组成部分及基本操作。第三张图学习Py

from sqlalchemy import create_enginefrom sqlalchemy.orm import Sessionfrom sqlalchemy.ext.automap import automap_baseif __name__ == "__main__": engine_str = 'sqlite:///:test.db' engine = cr

import timeimport sqlite3from sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import Column, Integer, String, create_enginefrom sqlalchemy.orm import scoped_session, sessionmak

# 1：保持请求之间的Cookiesimport requestsself.session = requests.Session()self.session.get(login_url) # 可以保持登录态# 2：请求时，会加上headersself.session.get(url, params, headers=headers)#在构造函数中，这样设置是全局的。# 设置请求头

安装pip install sqlalchemy引用import sqlalchemyprint sqlalchemy.__version__连接from sqlclachemy import create_engine# PostgreSQL 默认使用psycopg2# 默认情况(即使用psycopg2)engine = create_engine('

配置远程(就在本地调试的同学可以跳过这步)1.菜单->Tools->Deployment->Configuration我这个pycharm是已经配置完的，有些菜单是亮的，所以请不要纠结为啥有点不一样，点那个Configuration就可以了2.打开之后，填写配置SFTP host 就是远程主机的IP地址，为了安全，我把我的ip改了下。配置的英文意思差不多都明白，说明下Root pa

Tips:在学习Celery过程中，使用的系统为Windows 10、Celery版本为3.1.18①、中间人使用RabbitMQ。C:\Users\foolf>celery --version3.1.18 (Cipater)什么是任务队列任务队列是一种在线程或者机器之间分发任务的机制。消息队列的输入是工作的一个单元，称为任务，独立的职程(Worker)进程持续监视队列中是否有需

1 算法1.1 字符串处理re正则表达式的标准库。StringIO / cStringIO以读写文件的方式来操作字符串（有点类似于内存文件）。cStringIO 是 C 语言实现的，提供高性能；而 StringIO 是 Python 实现的，提供 Unicode 兼容性。chardetchardet 可以猜测任意一段文本的字符集编码。对于编码类型未知的文本，它会很有

http://www.kdnuggets.com/2016/07/mining-twitter-data-python-part-7.htmlThe final part of this 7 part series explores using geolocation and interactive maps with Twitter data.By Marco Bonzanini

http://www.kdnuggets.com/2016/07/mining-twitter-data-python-part-6.htmlPart 6 of this series builds on the previous installments by exploring the basics of sentiment analysis on Twitter data.B

http://www.kdnuggets.com/2016/06/mining-twitter-data-python-part-5.htmlPart 5 of this series takes on data visualization, as we look to make sense of our data and highlight interesting insights.

http://www.kdnuggets.com/2016/06/mining-twitter-data-python-part-4.htmlPart 4 of this series employs some of the lessons learned thus far to analyze tweets related to rugby matches and term co-o

http://www.kdnuggets.com/2016/06/mining-twitter-data-python-part-3.htmlPart 3 of this 7 part series focusing on mining Twitter data discusses the analysis of term frequencies for meaningful term e

http://www.kdnuggets.com/2016/06/mining-twitter-data-python-part-2.htmlPart 2 of this 7 part series on mining Twitter data for a variety of use cases focuses on the pre-processing of tweet text.

cat /etc/redhat-release# CentOS Linux release 7.1.1503 (Core) # 安装依赖yum install readline readline-devel readline-static -yyum install openssl openssl-devel openssl-static wget curl llvm make buil...