蠎加载 133
原文: Import Python Weekly Newsletter - Issue No 133 欢迎, 来 PyChina/weekly 共同翻译/增订/推荐 周刊 蠎消息 ;-) 该读 ~ 文章, Blog, 教程… 与 Python 中长时间运行的子进程交互 debugging The Python subprocess module is a powerful swiss-army knife for launching and interacting with child processes. It comes with several high-level APIs like call, check_output and (starting with Python 3.5) run that are focused at child processes our program runs and waits to complete. In this post I want to discuss a variation of this task that is less directly addressed - long-running child processes. (是也乎: 作者脑补出了几种方案, 但是,都不嗯哼… 其实吧长时间运行, 要不服务化, 要不事务化, 就别想着中间还能嗯哼什么, 毕竟这是冯机体系不是代码和运行时一致的 LISP 世界. ) 传说: 一个深度学习分类器,可以压缩 Unicode 和奇怪的 Youtube 评论 machine learning One of the things I’ve been thinking about recently is how to do natural language processing (NLP) effectively with deep neural networks using real world language examples. An example would be to classify the youtube comment 探索并清洗科学家联盟的卫星数据库 data science The Union of Concerned Scientists maintains a database of ~1000 Earth satellites. For the majority of satellites, it includes kinematic, material, electrical, political, functional, and economic characteristics, such as dry mass, launch date, orbit type, country of operator, and purpose. The data appears to have been mirrored on other satellite search websites, e.g. http://satellites.findthedata.com/ . This iPython notebook describes a sequence of interactions with a snapshot of this database using the bayeslite implementation of BayesDB, using the Python bayeslite client library. The snapshot includes a population of satellites defined using the UCS data as well as a constellation of generative probabilistic models for this population. 实体提取和网络分析 machine learning How you can extract meaningful information from raw text and use it to analyze the networks of individuals hidden within your data set. 使用 scikit-learn 制作电子商务业务决策 machine learning, scikit-learn Today, let’s learn how to build a simple linear regression model using Python’s Pandas and Scikit-learn libraries. Our goal is to build a model that analyses customer data and solves a problem for a (simulated) e-commerce business. (是也乎: 反复强调了简单的, 即无实用价值的… ) Python 怪癖: 注释 core-python 使用 Locust.io 和 Docker Swarm 进行负载测试 testing, docker, locust FAT Python : Python优化的下一章 optimization The FAT Python project was started by Victor Stinner in October 2015 to try to solve issues of previous attempts of “static optimizers” for Python. Victor has created a set of changes to CPython (Python Enhancement Proposals or “PEPs”), some example optimizations and benchmarks. We’ll explore those 3 levels in this article. K 平均聚类在 Python 中 machine learning f-strings For the Win f-strings It has been a long time coming, but I am now actively migrating existing projects to Python 3. Python 3.6 specifically, because when I am done I will be able to take advantage of my new favourite feature everywhere! That feature is f-strings. (是也乎: PEP-0498 的心声 Python 3.6.1 (…) Type “help”, “copyright”, “credits” or “license” for more… name = ‘Albert’ f’Hello, {name}!' ‘Hello, Albert!’ 嚓, f 算子… ) ...