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@ -20,6 +20,10 @@ PyHubWeekly是一个精选Github上优质Python小工具的项目，宗旨，
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# 2020年
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### 九月
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⭐️[第25期](./docs/25-pyhubweekly.md)
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### 八月
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⭐️[第24期](./docs/24-pyhubweekly.md)
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@ -0,0 +1,190 @@
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## 前言
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PyHubWeekly每周定期更新，精选GitHub上优质的Python项目/小工具。
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我把PyHubWeekly托管到了Github，感兴趣的可以**搜索Github项目**[PyHubWeekly](https://github.com/Jackpopc/PyHubWeekly)，如果喜欢，麻烦给个Star支持一下吧。此外，**欢迎大家通过提交issue来投稿和推荐自己的项目**~
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本期为大家推荐GitHub上5个优质的Python项目，它们分别是：
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- **txtai**
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- **Orchest**
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- **watchdog**
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- **Gitutor**
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- **DearPyGui**
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下面分别来介绍一下上述5个GitHub项目。
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### txtai
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**Star：262**
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[txtai](https://github.com/neuml/txtai)是一款基于AI在文本上建立索引的工具，能够把相似的文本关联在一起，用于内容搜索。
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例如，搜索**feel good story**，它能够根据索引相似性返回**Maine man wins 25 lottery ticket**。
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搜索**health**，它能够返回**US tops 5 million confirmed virus cases**。
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**安装**
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可以通过`pip`命令轻松安装txtai：
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```
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$ pip install txtai
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```
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**示例**
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首先，需要创建Embeddings实例，它是txtai的主要入口点。Embeddings实例定义了用于标记文本部分并将其转换为嵌入向量的方法。
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```
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from txtai.embeddings import Embeddings
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```
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下面，就演示如何用Embeddings搜索相似概念：
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```
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import numpy as np
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sections = ["US tops 5 million confirmed virus cases",
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"Canada's last fully intact ice shelf has suddenly collapsed, forming a Manhattan-sized iceberg",
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"Beijing mobilises invasion craft along coast as Taiwan tensions escalate",
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"The National Park Service warns against sacrificing slower friends in a bear attack",
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"Maine man wins $1M from $25 lottery ticket",
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"Make huge profits without work, earn up to $100,000 a day"]
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print("%-20s %s" % ("Query", "Best Match"))
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print("-" * 50)
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for query in ("feel good story", "climate change", "health", "war", "wildlife", "asia", "north america", "dishonest junk"):
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# Get index of best section that best matches query
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uid = np.argmax(embeddings.similarity(query, sections))
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print("%-20s %s" % (query, sections[uid]))
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```
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输出结果：
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```
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Query Best Match
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--------------------------------------------------
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feel good story Maine man wins $1M from $25 lottery ticket
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climate change Canada's last fully intact ice shelf has suddenly collapsed, forming a Manhattan-sized iceberg
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health US tops 5 million confirmed virus cases
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war Beijing mobilises invasion craft along coast as Taiwan tensions escalate
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wildlife The National Park Service warns against sacrificing slower friends in a bear attack
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asia Beijing mobilises invasion craft along coast as Taiwan tensions escalate
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north america US tops 5 million confirmed virus cases
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dishonest junk Make huge profits without work, earn up to $100,000 a day
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```
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### Orchest
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**Star：222**
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[Orchest](https://github.com/orchest/orchest)是一款用于创建数据科学工作量的工具。
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Orchest是一款Web数据科学工具，可在文件系统上运行。使用Orchest，你可以实现如下功能：
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- 通过其可视界面构建数据科学工作流
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- 自动并行运行工作流
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- 在你喜欢的编辑器中开发代码
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- ...
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orchest的使用依赖Docker，所以，如果你想要尝试，需要首先安装和配置Docker。
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```
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$ git clone https://github.com/orchest/orchest.git
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$ cd orchest
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$ ./orchest.sh start
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```
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### watchdog
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**Star：4.2k**
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[watchdog](https://github.com/gorakhargosh/watchdog)是一款用于监控系统事件的Python工具，它在Python代码中和命令行下都可以使用。
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首先，来看一下在Python中以API方式使用系统事件监控：
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```
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import sys
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import time
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import logging
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from watchdog.observers import Observer
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from watchdog.events import LoggingEventHandler
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if __name__ == "__main__":
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logging.basicConfig(level=logging.INFO,
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format='%(asctime)s - %(message)s',
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datefmt='%Y-%m-%d %H:%M:%S')
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path = sys.argv[1] if len(sys.argv) > 1else'.'
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event_handler = LoggingEventHandler()
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observer = Observer()
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observer.schedule(event_handler, path, recursive=True)
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observer.start()
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try:
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whileTrue:
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time.sleep(1)
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except KeyboardInterrupt:
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observer.stop()
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observer.join()
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```
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再看一下命令行下使用，下面这个示例忽略无关的文件，只监控和py和txt相关的事件：
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```
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watchmedo log \
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--patterns="*.py;*.txt" \
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--ignore-directories \
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--recursive \
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.
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```
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### Gitutor
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**Star：6**
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[Gitutor](https://github.com/artemisa-mx/gitutor)是一款用Python开发，让git命令更加简单的工具。
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git是项目开发过程中经常会用到的一种工具，它用于代码的版本控制。
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但是，对于初学者它不是特别友好，代码提交、版本回退、代码比较...
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而Gitutor让你通过一行命令就可以轻松实现代码版本控制，让git的门槛进一步被拉低。
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**安装**
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```
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$ pipx install gitutor
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```
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然后，使用`gt --help`命令就可以查看能够使用的命令：
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- `gt init`：初始化本地和远程仓库
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- `gt save`：把代码变动保存到本地和远程仓库
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- `gt goback`：回退到前一个commit
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- `gt compare`：对比当前状态和前一个commit
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- `gt ignore`：忽略选中的文件
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- `gt lesson`：阅读gitutor文档
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### DearPyGui
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**Star：273**
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[DearPyGui](https://github.com/hoffstadt/DearPyGui)是一个易于使用且功能强大的Python GUI框架，它提供了DearImGui的包装。
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它与其他Python GUI框架从根本上存在不同，在后台DearPyGui使用即时模式范式，这样能够实现更加灵活的动态界面。此外，DearPyGui不使用本机窗口小部件，而是使用计算机的GPU绘制窗口小部件，它支持如下平台：
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- **Windows 10**
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- **macOs**
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- **Linux**
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DearPyGui提供与DearImGui相同的方式为游戏开发人员提供了一种创建工具的简单方法，DearPyGui提供了一种简单的方法为Python开发人员创建快速而强大的GUI。
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---
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给大家推荐1个宝藏公众号【**七步编程**】，专注于Python、AI、大数据领域内容分享。创作内容坚持原创与高质量，发表内容已经被诸多公众号大V转发，备受欢迎。现在关注，后台回复关键**567**就可以获得我精心整理的机器学习、深度学习、Python、推荐系统等技术方向的干货！
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