代替那存在着阶级和阶级对立的资产阶级旧社会的，将是这样一个联合体，在那里，每个人的自由发展是一切人的自由发展的条件 In place of the old bourgeois society with its classes and class conflicts there will be an association in which the free development of each is the condition for the free development of all. 只有自证不缺钱，才能从银行借到钱，而有经济能力的人必不滥用那借贷。 只有内心渴望劳动，才能拥有随时不

此乃《好中文的样子》课程小组作业

原文: Import Python Weekly Newsletter - Issue No 116 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… 如何从内存中恢复丢失的 python 源代码? core-python I used “git checkout –” on the wrong file and managed to delete the code I had just written… but it was still running in a process in a docker container. Here’s how I got it back, using https://pypi.python.org/pypi/pyrasite/ and https://pypi.python.org/pypi/uncompyle6 (是也乎: 可怜的人… ) PEP 308 以及为毛俺依然恨 Python core-python I’m not a Python guy, but it seems that every job I’ve had has slowly pushed me into doing more and more Python until I end up doing nothing but Python all day. And I hate doing Python all day. (是也乎: 简单的说怼数学计算时,被 Py 的任性怒了… ) python 的怪代码 code snippets Code snippets that makes you wonder what’s happening? (是也乎: 所谓活久见… ) MetPy：驯服天气与Python - 剧集100 podcast What’s the weather tomorrow? That’s the question that meteorologists are always trying to get better at answering. This week the developers of MetPy discuss how their project is used in that quest and the challenges that are inherent in atmospheric and weather research. It is a fascinating look at dealing with uncertainty and using messy, multidimensional data to model a massively complex system. Django 周刊 30 newsletter If you use Django framework and want to keep updated with what’s happening in the Django world, check out django weekly 有效的 Python 学习姿势 video When learning a programming language, how do you know whether the effort you’re putting in is working or whether you’re wasting your time?. We’ll be chatting with Michael Herman and Evan Moore about techniques you can use to be more effective during your Python learning adventures. (是也乎: 关键就是得有一套靠谱的不依赖其他人的明确自己作的是否对的指标 ) 从 past 引入 bytes_literals Intel 的 Python 发行版提供数学能力的大提升 intel The still-in-beta Python distribution uses Math Kernel Library to speed up processing on Intel hardware. (是也乎: Intel 这么博爱… ) 客户数据驱动灯光秀 IOT Fast_Multi_Style_Transfer-tf Implementation of Google Brain’s A Learned Representation For Artistic Style in Tensorflow. You can mix various type of style images using just One Model and it’s still Fast. (是也乎: TF 中艺术风格的嗯哼 ) 诊断并修复 Python 中的内存嗯哼 debugging, memory leaks One thing we’ve learned from building complex software for the cloud is that a language is only as good as its debugging and profiling tools. Logic errors, CPU spikes, and memory leaks are inevitable, but a good debugger, CPU profiler, and memory profiler can make finding these errors significantly easier and faster. (是也乎: CPU 中的问题追踪,马上也将过渡到 TPU 的了… ) Python 中拟合高斯过程模型 numpy, stats k 最近邻 machine learning 使用Python和Django Rest Framework创建生产就绪的API - 第3部分 django (是也乎: 上期说的 google 的 fire 也是相似的嗯哼 ) 干掉你的Python代码与装饰 decorators 如何使用Python编写Collectd插件？ collectd, monitoring deployments Collectd is a system statistics collection daemon. It gathers a lot of information about the system it’s running on, and passes it on to a software that can process and visualize that information, e.g. Grafana. Collectd already brings along a lot of built-in plugins to gather information about the system load, the network traffic, available entropy, various sensors, etc. But sometimes there’s a value that you want to log which is not covered by an existing plugin. (是也乎: SCM 一直是 Python 的擅长领域… ) 好物 ~ 包/模块/库/片段… ...

原文: Import Python Weekly Newsletter - Issue No 117 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… Python 的 Memoization 以及 Decorators core-python With memoization, we can “memoize” (remember, store) the result of problems that we’ve dealt with before, and return a stored result instead of repeating calculations. (是也乎: 对计算的缓存.. ) 用 Apache Airflow 开始折腾工作流 airflow Apache Airflow is an open-source tool for orchestrating complex computational workflows and data processing pipelines. If you find yourself running cron task which execute ever longer scripts, or keeping a calendar of big data processing batch jobs then Airflow can probably help you. This article provides an introductory tutorial for people who want to get started writing pipelines with Airflow. 数据科学基本统计: Python 案例集, 第一部分 statistics In this post, we’ll take a step back to cover essential statistics that every data scientist should know. PyMedium PyMedium is an unofficial Medium API written in python flask. It provides developers to access to user, post list and detail information from Medium website. This is a read-only API to access public information from Medium, you can customize this API to fit your requirements and deploy on your own server. (是也乎: 又一个非法接口嗯哼出来了 ) TensorFlow 可视化: Summary 和 TensorBoard tensorflow This article is going to discuss some basic methods and functions in tensorflow used to visualize and monitor the training process. I believe visualization is top priority for the research. Because the deep learning itself is a “black box”. So, if the visualization could help us analyze why the final result is successful or failed. 用 Python, pandas 和线性回归模型 预测住房价格 pandas Pandas & Seaborn - 优雅地处理和可视化数据指南 pandas 折腾 Machine Learning Algorithms machine learning 破解虚拟内存 virtual memory 用 Apache Kafka 和 Python 构建分布式流系统 kafka (是也乎: ) 使用 HTML5 和 Flask 拖放文件 flask 如何使用 IBM Watson 的 语音-文本 功能来转录我们的课程 watson In this step by step guide we’ll show you how to transcribe an audio file using IBM Watson speech-to-text API and a little bit of Python. 如何生成 文本总结 - 介绍深度学习 machine learning, video I’ll show you how you can turn an article into a one-sentence summary in Python with the Keras machine learning library. We’ll go over word embeddings, encoder-decoder architecture, and the role of attention in learning theory. Python 用 Circle CI 进行持续集成 CI 如何在 ModelForm 中动态过滤 ModelChoice 的查询集? django Python 3.6.1 已发布 core-python 几分钟内在 GCP 构建无服务器 Python 应用 google cloud, cloud functions Google’s answer to aws lambda. Django Admin: 昂贵的 COUNT(*) 查询 admin If you have maintained a website with a huge amount of data, you probably already know that Django Admin can become very slow when the database table gets so large. If you log the SQL queries (either using Django logging or using Django Debug Toolbar), you would notice a very expensive SQL query, something like this. 好物 ~ 包/模块/库/片段… ...