Saravanan666/pypi-org huggingface dataset:
Package: zhenxun-plugin-chatgpt
nonebot-plugin-chatgpt✨ ChatGPT AI 对话 ✨📖 介绍智能对话聊天插件。💿 安装使用 nb-cli 安装在 nonebot2 项目的根目录下打开命令行, 输入以下指令即可安装nb plugin install nonebot-plugin-chatgpt使用包管理器安装在 nonebot2 项目的插件目录下, 打开命令行, 根据你使用的包管理器, 输入相应的安装命令pippip install nonebot-plugin-chatgptpdmpdm add nonebot-plugin-chatgptpoetrypoetry add nonebot-plugin-chatgptcondaconda install nonebot-plugin-chatgpt打开 nonebot2 项目的bot.py文件, 在其中写入nonebot.load_plugin('nonebot_plugin_chatgpt')⚙️ 配置在 nonebot2 项目的.env文件中添加下表中的必填配置（在ARM平台，可能必须使用CHATGPT_SESSION_TOKEN登录）⚠️Windows系统下需要在.env.dev文件中设置FASTAPI_RELOAD=false配置项必填默认值说明CHATGPT_SESSION_TOKEN否空字符串ChatGPT 的 session_token，如配置则优先使用CHATGPT_ACCOUNT否空字符串ChatGPT 登陆邮箱，未配置则使用 session_tokenCHATGPT_PASSWORD否空字符串ChatGPT 登陆密码，未配置则使用 session_tokenCHATGPT_CD_TIME否60冷却时间，单位：秒CHATGPT_PROXIES否None代理地址，格式为：http://ip:portCHATGPT_REFRESH_INTERVAL否30session_token 自动刷新间隔，单位：分钟CHATGPT_COMMAND否空字符串触发聊天的命令，可以是字符串或者字符串列表。如果为空字符串或者空列表，则默认响应全部消息CHATGPT_TO_ME否True是否需要@机器人CHATGPT_TIMEOUT否30请求服务器的超时时间，单位：秒CHATGPT_API否https://chat.openai.com/API 地址，可配置反代CHATGPT_IMAGE否False是否以图片形式发送。如果无法显示文字，请点击此处查看解决办法CHATGPT_IMAGE_WIDTH否500消息图片宽度，单位：像素CHATGPT_PRIORITY否999事件响应器优先级CHATGPT_BLOCK否True是否阻断消息传播CHATGPT_PRIVATE否True是否允许私聊使用CHATGPT_SCOPE否private设置公共会话或私有会话private：私有会话，群内成员会话各自独立public：公共对话，群内成员共用同一会话CHATGPT_DATA否插件目录下插件数据保存目录的路径CHATGPT_MAX_ROLLBACK否5设置最多支持回滚多少会话CHATGPT_DETAILED_ERROR否否是否允许输出详细错误信息获取 session_token登录https://chat.openai.com/chat，并点掉所有弹窗按F12打开控制台切换到Application/应用选项卡，找到Cookies复制__Secure-next-auth.session-token的值，配置到CHATGPT_SESSION_TOKEN即可🎉 使用默认配置下，@机器人加任意文本即可。如果需要修改插件的触发方式，自定义CHATGPT_COMMAND和CHATGPT_TO_ME配置项即可。指令需要@范围说明刷新会话/刷新对话是群聊/私聊重置会话记录，开始新的对话导出会话/导出对话是群聊/私聊导出当前会话记录导入会话/导入对话 + 会话ID + 父消息ID(可选)是群聊/私聊将会话记录导入，这会替换当前的会话保存会话/保存对话 + 会话名称是群聊/私聊将当前会话保存查看会话/查看对话是群聊/私聊查看已保存的所有会话切换会话/切换对话 + 会话名称是群聊/私聊切换到指定的会话回滚会话/回滚对话是群聊/私聊返回到之前的会话，输入数字可以返回多个会话，但不可以超过最大支持数量🤝 贡献🎉 鸣谢感谢以下开发者对该项目做出的贡献：
Package: zhihu
## 关于Zhihu-API 的初衷是希望提供一套简洁、优雅的、Pythonic的API接口，面向的用户是对知乎数据有兴趣的群体，它可以用在数据分析、数据挖掘、增长黑客、以及希望通过程序自动完成知乎某个操作等应用场景。注意:只支持Python3## 安装```pythonpip install -U zhihu# 或者安装最新包pip install git+git://github.com/lzjun567/zhihu-api --upgrade```## 快速上手```pythonfrom zhihu import Zhihuzhihu = Zhihu()#获取用户基本信息profile = zhihu.profile(user_slug="xiaoxiaodouzi")print(profile)>>>{'name': '我是x','headline': '程序员','gender': -1,'user_type': 'people','is_advertiser': False,'url_token': 'xiaoxiaodouzi','id': '1da75b85900e00adb072e91c56fd9149','is_org': False}# 发送私信>>> zhihu.send_message(content="私信测试", user_slug="xiaoxiaodouzi")<Response [200]># 关注用户>>> zhihu.follow(user_slug="xiaoxiaodouzi"){'follower_count': 12, 'followed': True}# 取消关注>>> zhihu.unfollow(user_slug="xiaoxiaodouzi"){'follower_count': 11, 'followed': False}>>> from zhihu import Answer>>> answer = Answer(url="https://www.zhihu.com/question/62569341/answer/205327777")# 赞同回答>>> answer.vote_up(){'voting': 1, 'voteup_count': 260}# 反对>>> answer.vote_down(){'voting': -1, 'voteup_count': 259}# 中立>>> answer.vote_neutral(){'voting': 0, 'voteup_count': 260}# 感谢回答>>> answer.thank(){'is_thanked': True}# 取消感谢>>> answer.thank_cancel(){'is_thanked': False}```## 贡献者欢迎 PR, 所有贡献者都将出现在这里，排名不分先后* [@BigBorg](https://github.com/BigBorg)* [@xiaowenlong100](https://github.com/xiaowenlong100)* [@chenghengchao](https://github.com/chenghengchao)* [@MaxPoon](https://github.com/MaxPoon)* [@Oopswc](https://github.com/Oopswc)## 交流群已经加不进，可以先加微信：lzjun567 拉你入群![群](https://dn-mhke0kuv.qbox.me/30f70119cd4a840560d4.jpeg)
Package: zhihuapi
UNOFFICIALAPI forzhihu. This package supports only Python 3.x.ANode.js implementationis also available.Installation$pipinstallzhihuapiQuich Startimportzhihuapiasapiwithopen('cookie')asf:api.cookie(f.read())data=api.user('zhihuadmin').profile()print(data)The result is:{"url_token":"zhihuadmin","avatar_url":"https://pic3.zhimg.com/34bf96bf5584ac4b5264bd7ed4fdbc5a_is.jpg","avatar_url_template":"https://pic3.zhimg.com/34bf96bf5584ac4b5264bd7ed4fdbc5a_{size}.jpg","type":"people","name":"知乎小管家","headline":"欢迎反馈问题和建议！","is_org":false,"url":"https://www.zhihu.com/people/zhihuadmin","badge":[{"type":"identity","description":"知乎官方帐号"}],"user_type":"people","is_advertiser":false,"id":"3d198a56310c02c4a83efb9f4a4c027e"}LicenseMIT
Package: zhihubackup
退乎前备份知乎回答：zhihubackup每个知乎答主都有退乎的梦想，但退乎前如果删光回答，则十分可惜。因此，我用Python写了60行的脚本，可以在退乎前备份自己的所有回答和文章，以免事后后悔。安装pipinstallzhihubackup[node]如果已安装Node.js，则可以去掉[node]。使用假如你是@贱贱，你的id是splitter，那么可以执行命令：zhihubackupsplitter静等一段时间。运行结束后，可以看到产生了名为splitter的文件夹：- splitter
|- answer   (842 files)
|- article  (101 files)
|- pin      (3214 files)
|- question (57 files)备份已经成功，现在可以删光回答和文章了。
Package: zhihu-cli
zhihuzhihu 是一个简单的知乎信息获取工具，可以免登陆实现获取知乎的用户(User)，提问(Question)，回答(Answer)信息installpip3 install zhihu-cliUsage用户类 User可以通过用户的自定义ID(customized_id)或者内部ID(internal_id)初始化用户信息，其中自定义ID从用户URL中即可获得例如 知乎小管家URL：https://www.zhihu.com/people/zhihuadmin/activities自定义ID即为zhihuadmin内部ID是形如3d198a56310c02c4a83efb9f4a4c027e这样的ID，需要通过其他手段拿到。而这两种ID均可以初始化User类fromzhihuimportUseruser=User('zhihuadmin')而此时就可以通过user.internal_id来获取到知乎小管家的内部ID(就是上面的3d198a56310c02c4a83efb9f4a4c027e)用户类的属性包括：属性类型描述customized_idstr自定义IDinternal_idstr内部IDnicknamestr昵称genderstr昵称avatarstr头像URLheadlinestr个人简介is_vipbool盐选会员follower_countint关注者数量following_countint关注的人数量followersgenerator 对象关注者followingsgenerator 对象关注的人answer_countint回答数量question_countint提问数量articles_countint文章数量voteup_countint获得赞同数infodict以上所有信息提问类 Question通过问题ID(qid)初始化一个问题问题ID可以通过问题URL获得例如：《如何使用知乎？》问题URL:https://www.zhihu.com/question/19550225问题ID即为19550225fromzhihuimportQuestionquestion=Question('19550225')问题类的属性包括：属性类型描述qidstr问题IDtitlestr标题detailstr详细描述typestr问题状态createddatetime发布时间updateddatetime最后一次更新时间authorUser 对象提问人infodict以上所有信息answers()generator 对象所有回答的生成器answers()接受sort_by = default|updated参数，返回类型为 Answer 对象回答类 Answer通过回答ID(aid)初始化一个回答回答ID可从一个回答的URL中获得：例如：https://www.zhihu.com/question/19550225/answer/95067981回答ID即为95067981fromzhihuimportAnsweranswer=Answer('95067981')回答类的属性包括：属性类型描述aidstr回答IDtypestr该回答状态authorUser 对象回答者excerptstr摘要contentstr回答的原始内容(包含HTML内容)textstr回答的纯文字(不包含HTML内容)comment_countint回答评论数voteup_countint回答赞同数createddatetime回答时间updateddatetime最后一次修改时间questionQuestion 对象回答的问题对象infodict以上所有信息
Package: zhihu-crawler
zhihu_crawler本程序支持关键词搜索、热榜、用户信息、回答、专栏文章、评论等信息的抓取项目目录__init__.py 为程序的对外统一入口constants.py 常量exceptions.py 自定义异常extractors.py 数据清洗page_iterators.py 简单的页面处理zhihu_scraper.py 页面请求、cookie设置zhihu_types.py 类型提示、检查。项目自定义类型注意事项: 项目内有部分异步操作，在模块引用之前需要使用猴子补丁; 同时该项目没有对ip限制、登录做针对性处理安装pipinstallzhihu_crawler使用if__name__=='__main__':# 设置代理; 如采集量较大，建议每次请求都切换代理set_proxy({'http':'http://127.0.0.1:8125','https':'http://127.0.0.1:8125'})# 设置cookieset_cookie({'d_c0':'AIBfvRMxmhSPTk1AffR--QLwm-gDM5V5scE=|1646725014'})# 搜索采集使用案例:forinfoinsearch_crawl(key_word='天空',count=10):print(info)# 可传入data_type 指定搜索类型forinfoinsearch_crawl(key_word='天空',count=10,data_type='answer'):print(info)# 用户信息回答列表使用案例(采集该用户信息及50条回答信息,每条回答包含50条评论):forinfoinuser_crawler('wo-men-de-tai-kong',answer_count=50,comment_count=50):print(info)# 用户信息提问列表使用案例(采集该用户信息及10条问题信息,每条问题包含10条回答，每条回答包含50条评论):forinfoinuser_crawler('wo-men-de-tai-kong',question_count=10,drill_down_count=10,comment_count=50):print(info)# 热点问题采集使用案例# 采集 前10个问题, 每个问题采集10条回答forinfoinhot_questions_crawl(question_count=10,drill_down_count=10):print(info)# 可传入period 指定热榜性质。如小时榜、日榜、周榜、月榜# 传入domains 采集指定主题的问题forinfoinhot_questions_crawl(question_count=10,period='day',domains=['1001',1003]):print(info)
Package: zhihu-oauth
Zhihu-OAuth近况由于知乎给 Github 发了DMCA要求删除zhihu-oauth 仓库，所以 Github 把仓库设置为不可公开访问了。所以目前我只能把最新版代码同步到我自己个人的 Git Server 上了。虽然一直有用户和我反馈还在使用这个库，并且某些功能也确实可以继续正常使用，但由于本人已经不用知乎多年，所以这个库其实有两年多没更新过了。这次移动到个人站点之后，由于本站点不对外开放注册，游客就没法使用 Issue 和 PR 功能，所以可以预见的未来估计也不会有什么更新了，这里基本只提供代码备份和下载功能。由于以上原因，README 中的捐款渠道也已一并删除。如果你有想交流的问题，请使用邮件，或者Twitter联系我。—— 2019.10.19简介同学们，由于知乎新的 API 验证 UA，0.0.14 之前的版本已经不可用了，请尽快升级到 0.0.14 以上版本。最近在尝试解析出知乎官方未开放的 OAuth2 接口，顺便提供优雅的使用方式，作为zhihu-py3项目的继任者。恩，理论上来说会比 zhihu-py3 更加稳定，原因如下：知乎 API 相比前端 HTML 来说肯定更加稳定和规范这次的代码更加规范网络请求统一放在基类中属性解析统一放在装饰器中，各知乎类只用于声明有哪些属性可供使用统一翻页逻辑，再也不用一个地方一个逻辑了翻页时的自动重试机制（虽然不知道有没有用吧）这一新库与 zhihu-py3 相比速度更快。有关速度对比的详细信息请点击这里。这个库是 Py2 和 Py3 通用的！但是 Py3 的优先级比 Py2 高，也就是说，我会优先保证在 Py3 下的稳定性和正确性。毕竟在我学的时候选了 Py3，所以对 2 与 3 的差异了解不是很清楚，Py2 只能尽力而为了，后期的计划是这样的：0.0.x 这个阶段是 alpha 期，主要做的是补齐功能的工作。基本上 TODO 里的功能都会在这个时期实现。其中 0.0.5 版本计划完成和 zhihu-py3 同样多的功能（已完成）。0.1.x 这个阶段是 beta 期，主要做完善测试，修复 bug，提升性能，改善架构之类的工作吧。以上两个阶段变化很大，有可能出现不兼容老版本的更新。使用需要注意。0.2.x 及以后就是 stable 期，只要 API 不变，基本上代码结构就不会变了，接口可能会增加但一定不会减。由于现在使用的 CLIENT_ID 和 SECRET 的获取方法并不正当，所以请大家暂时不要大规模宣传，自己用用就好啦，Thanks。等我什么时候觉得时机成熟（等知乎真•开放 OAuth 申请？），会去知乎专栏里宣传一波的。最近更新目前版本是 0.0.41，没更新的快更新一下，更新说明在这里。0.0.41 版本修复了 Feed 流的一些问题，加上了Topic.activities接口。0.0.40 版本增加了 Feed 首页信息流的支持。使用安装pipinstall-Uzhihu_oauth如果安装遇到问题，请查看文档：安装登录请参见文档：登录获取基础信息代码：fromzhihu_oauthimportZhihuClientclient=ZhihuClient()client.load_token('token.pkl')me=client.me()print('name',me.name)print('headline',me.headline)print('description',me.description)print('following topic count',me.following_topic_count)print('following people count',me.following_count)print('followers count',me.follower_count)print('voteup count',me.voteup_count)print('get thanks count',me.thanked_count)print('answered question',me.answer_count)print('question asked',me.question_count)print('collection count',me.collection_count)print('article count',me.articles_count)print('following column count',me.following_column_count)输出：name 7sDream
headline 二次元普通居民，不入流程序员，http://0v0.link
description 关注本AI的话，会自动给你发私信的哟！
following topic count 35
following people count 101
followers count 1294
voteup count 2493
get thanks count 760
answered question 258
question asked 18
collection count 9
article count 7
following column count 11更多功能请参见文档：使用方法文档完整的文档可以在这里找到。我写的文档好吧，可详细了……有啥问题先去找文档。我写的那么累你们看都不看我好不服啊！（貌似 ReadTheDocs 在伟大的国家访问速度有点慢，建议自备手段。）TODO保证对 Python 2 和 3 的兼容性用户私信支持Live 支持Pin（分享）支持搜索功能（还差电子书搜索）用户首页 Feed知乎电子书获取用户消息。新关注者，新评论，关注的回答有新问题Token check/refreshSetting规范、完善的测试article.voters 文章点赞者，貌似 OAuth2 没有这个 APIcollection.followers 这个 API 不稳定，没法返回所有关注者协助开发通过代码Fork从 dev 分支新建一个分支编写代码，更新 Changelog 和 sphinx 文档，如果可能的话加上测试PR 到原 dev 分支通过捐款由于开发不积极，不再接受捐款。捐款记录LICENSEMIT
Package: zhihu-py3
通知由于知乎前端老是改阿改的，每次我都要更新弄的我好烦的说……所以我开发了一个新的项目Zhihu-OAuth。这个新项目用了一些黑科技手段，反正应该是更加稳定和快速了！而且还支持 Python 2 哟！稳定我倒是没测，但是这里有一个速度对比。如果你是准备新开一个项目的话，我强烈建议你看看我的新项目~如果你已经用 Zhihu-py3 写了一些代码的话，我最近会写一个从 Zhihu-py3 转到 Zhihu-OAuth
的简易指南，你也可以关注一下哟。毕竟嘛，有更好的方案的话，为什么不试试呢？功能由于知乎没有公开API，加上受到zhihu-python项目的启发，在Python3下重新写了一个知乎的数据解析模块。提供的功能一句话概括为，用户提供知乎的网址构用于建对应类的对象，可以获取到某些需要的数据。简单例子：fromzhihuimportZhihuClientCookies_File='cookies.json'client=ZhihuClient(Cookies_File)url='http://www.zhihu.com/question/24825703'question=client.question(url)print(question.title)print(question.answer_num)print(question.follower_num)print(question.topics)foranswerinquestion.answers:print(answer.author.name,answer.upvote_num)这段代码的输出为：关系亲密的人之间要说「谢谢」吗？
627
4322
['心理学', '恋爱', '社会', '礼仪', '亲密关系']
龙晓航 50
小不点儿 198
芝士就是力量 89
欧阳忆希 425
...另外还有Author（用户）、Answer（答案）、Collection（收藏夹）、Column（专栏）、Post（文章）、Topic（话题）等类可以使用，Answer,Post类提供了save方法能将答案或文章保存为HTML或Markdown格式，具体请看文档，或者zhihu-test.py。安装本项目依赖于requests、BeautifulSoup4、html2text已将项目发布到pypi，请使用下列命令安装(sudo)pip(3)install(--upgrade)zhihu-py3希望开启lxml的话请使用：(sudo)pip(3)install(--upgrade)zhihu-py3[lxml]因为lxml解析html效率高而且容错率强，在知乎使用<br>时，自带的html.parser会将其转换成<br>...</br>，而lxml则转换为<br/>，更为标准且美观，所以推荐使用第二个命令。不安装lxml也能使用本模块，此时会自动使用html.parser作为解析器。PS 若在安装lxml时出错，请安装libxml和libxslt后重试：sudoapt-getinstalllibxml2libxml2-devlibxslt1.1libxslt1-dev准备工作第一次使用推荐运行以下代码生成 cookies 文件：fromzhihuimportZhihuClientZhihuClient().create_cookies('cookies.json')运行结果====== zhihu login =====
email: <your-email>
password: <your-password>
please check captcha.gif for captcha
captcha: <captcha-code>
====== logging.... =====
login successfully
cookies file created.运行成功后会在目录下生成cookies.json文件。以下示例皆以登录成功为前提。建议在正式使用之前运行zhihu-test.py测试一下。用法实例为了精简 Readme，本部分移动至文档内。请看文档的「用法示例」部分。登录方法综述为了精简 Readme，本部分移动至文档内。请看文档的「登录方法综述」部分。文档终于搞定了文档这个磨人的小妖精，可惜 Sphinx 还是不会用 T^T
先随意弄成这样吧：Master版文档Dev版文档其他有问题请开Issue，几个小时后无回应可加最后面的QQ群询问。友链：zhihurss：一个基于 zhihu-py3 做的跨平台知乎 rss(any user) 的客户端。TODO List[x] 增加获取用户关注者，用户追随者[x] 增加获取答案点赞用户功能[x] 获取用户头像地址[x] 打包为标准Python模块[x] 重构代码，增加ZhihuClient类，使类可以自定义cookies文件[x] 收藏夹关注者，问题关注者等等[x]ZhihuClient增加各种用户操作（比如给某答案点赞）[ ] Unittest （因为知乎可能会变，所以这个有点难[x] 增加获取用户关注专栏数和关注专栏的功能[x] 增加获取用户关注话题数和关注话题的功能[x] 评论类也要慢慢提上议程了吧联系我Github：@7sDream知乎：@7sDream新浪微博：@Dilover邮箱：给我发邮件编程交流群：478786205
Package: zhijie-toolbox
Project descriptionInstallpip install zhijie_toolboxMethodcreate_package_template(current_path, project_name, version="0.0.1", license_type="MIT")This will help you to create a package template that speed up publishing package.Usage:from zhijie_toolbox import toolbox
toolbox.create_package_template(current_path, project_name)version_control(current_path, runs_name, not_save_list=[".git", "runs"], log="")This will help you to copy current codes to a runs folder where we can record our codes locally
We can define not save list by ourself by specify files nameUsage:from zhijie_toolbox import toolbox
toolbox.version_control(current_path, runs_name)create_project_template(current_path, add_folder=None)This function will help you create a project template.
Basic folders are ["configs", "datasets", "experiments", "scripts", "tests", "packages"]Usage:from zhijie_toolbox import toolbox
toolbox.create_project_template(current_path)
Package: zhinst
Zurich Instruments LabOne PackagesThezhinstpackage is purely a metapackage that installs the whole Python API
stack for LabOne®, the Zurich Instruments control software.It includes the following packages:zhinst-core(native Python API for LabOne)zhinst-utils(utility functions for zhinst-core)zhinst-toolkit(high-level Python API for LabOne)This package includes everything required to interface with LabOne form within Python.
For more information see the dedicated package documentation or theonline documentation.WARNING: Upgrading from version <= 22.02 to 22.08 requires to uninstall this package first and the reinstalling it,--upgradewill corrupt the package.
Package: zhinst-core
Zurich Instruments LabOne APIThezhinst-corepackage allows communication with Zurich Instruments devices from
the Python programming language. It's the native Python API of LabOne®, the
Zurich Instruments control software.The documentation for thezhinst.corebinary extension can be accessedonlineor via the built-inhelpcommand:importzhinst.corehelp(zhinst.core)More information about programming with Zurich Instruments devices is available
in theLabOne Programming
Manual.
Package: zhinst-deviceutils
Device Utils for Zurich Instrumentszhinst-deviceutils provides a set of helper functions for the native LabOne Python API
calledzhinst.ziPython.It offers higher level functions to ease the communication withZurich Instrumentsdevices. It is not intended to be a
separate layer abovezhinst.ziPythonbut rather as an addition.It currently has utility functions for the following devices:SHFQASHFSGSHFQCTo see the device utils in action check out theLabOne API examples.InstallationPython 3.7+ is required.pip install zhinst-deviceutilsUsageimport zhinst.deviceutils.shfqa
import zhinst.deviceutils.shfsg
import zhinst.deviceutils.shfqc

help(zhinst.deviceutils.shfqa)
help(zhinst.deviceutils.shfsg)
help(zhinst.deviceutils.shfqc)AboutMore information about programming with Zurich Instruments devices is available in thepackage documentationand theLabOne Programming Manual.
Package: zhinst-hdiq
Zurich Instruments HDIQ (zhinst-hdiq)zhinst-hdiqis a package for Python 3.7+ to control aZurich Instruments HDIQ IQ Modulatorvia Ethernet connection. Please note that this package is valid only for instruments with serial numbers14100 and above.StatusThezhinst-hdiqpackage is considered stable for general usage. The interface may be subject to incompatible changes between releases, which we will indicate by a change of the major version. Please check thechangelogif you are upgrading.InstallInstall the package withpip:$pipinstallzhinst-hdiqExampleThe example below shows how to connect an HDIQ instrument to a host computer and control operation modes of the HDIQ channels.importzhinst.hdiq.utilsfromzhinst.hdiqimportHdiqhdiq_devices=zhinst.hdiq.utils.discover_devices()print(f'Found devices:{hdiq_devices}')hdiq_serial,hdiq_ip=hdiq_devices[0]print(f'Connecting to{hdiq_serial}(IP:{hdiq_ip})')hdiq=Hdiq(hdiq_ip)channel=1# HDIQ channel 1; HDIQ has 4 channels: 1, 2, 3, 4hdiq.set_rf_to_calib(channel)# calibration mode in channel 1, set RF to Calib. port# hdiq.set_rf_to_exp(channel)             # RF mode in channel 1, set RF to Exp. port# hdiq.set_lo_to_exp(channel)             # LO mode in channel 1, set LO to Exp. portstatus=hdiq.get_channel_status(channel)# get status of channel 1print(f'channel{channel}->{status}')ContributingWe welcome contributions by the community, either as bug reports, fixes and new code. Please use the GitHub issue tracker to report bugs or submit patches. Before developing something new, please get in contact with us.LicenseThis software is licensed under the terms of the MIT license. SeeLICENSEfor more detail.
Package: zhinst-labber
Zurich Instruments Labber DriversThe Zurich Instruments Labber Drivers is a python package that is able to
automatically generate and update instrument drivers for all Zurich Instruments
devices for the scientific measurement softwareLabber.The Labber drivers are based on theZurich Instruments Toolkit(zhinst-toolkit), a high level driver of our Python core API.WARNINGUpgrading from zhinst-labber versions lower than 0.3 needs some special attention
since version 0.3 breaks the API in many ways and measurements need to be adapted.
If you need more Information on the upgrading process or need assistance feel
free to contact the Zurich Instruments support at any time. (support@zhinst.com)StatusThe Zurich Instruments Labber Drivers are well tested and considered stable
enough for general usage. The interfaces may have some incompatible changes
between releases. Please check the changelog if you are upgrading to the latest version.LabOne softwareAs a prerequisite, the LabOne software version 22.02 or later must be installed.
It can be downloaded for free athttps://www.zhinst.com/labone. Follow the
installation instructions specific to your platform. Verify that you can
connect to your instrument(s) using the web interface of LabOne. If you are
upgrading from an older version, be sure to update the firmware of all
Zurich Instruments devices in use by using the web interface.In principle LabOne can be installed in a remote machine, but we highly
recommend to install it on a local machine where you intend to run the experiment.Getting StartedLabber comes with its own Python distribution that is used by default.
If not specified otherwise (Preferences -> Advanced -> Python distribution) the
following command needs to be executed within this distribution.
(C:\Program Files\Labber\python-labber\Scripts\pip.exe or similar).pip install zhinst-labberThe drivers for an device can now be generated using the command line interface.For example the following command generated the driver for the Device DEV1234
inside the Labber driver folder of the ZI user.zhinst-labber setup "C:\Users\ZI\Labber\Drivers" DEV1234 localhostDocumentationFor a full documentation seehere.ContributingWe welcome contributions by the community, either as bug reports, fixes and new
code. Please use the GitHub issue tracker to report bugs or submit patches.
Before developing something new, please get in contact with us.LicenseThis software is licensed under the terms of the MIT license.
SeeLICENSEfor more detail.
Package: zhinst-qcodes
Zurich Instruments Drivers for QCoDeS (zhinst-qcodes)The Zurich Instruments drivers for QCoDeS (zhinst-qcodes) is a package of
instrument drivers for devices produced byZurich Instrumentsfor QCoDeS.QCoDeSis a Python-based data
acquisition framework developed to serve the needs of nanoelectronic device
experiments, but not limited to that. It is intended to be used within QCoDeS
and not as standalone package. The QCoDeS instrument drivers are based on theZurich Instruments Toolkit. So if
you are looking for a framework independent high level python API, zhinst-toolkit
it the right place for you.StatusThe zhinst-qcodes is well tested and considered stable enough for general usage.
The interfaces may have some incompatible changes between releases. Please check
the changelog when updating.Refactoring with version 0.3Version 0.3 is a more or less complete new driver and breaks the API compared
to the previous version in many ways. If you upgrade from an older version take
a look at the dedicateddocumentation pagefor more information.InstallInstall the package with pip:pip install zhinst-qcodesDocumentationSee the documentation pagehere.
Since zhinst-qcodes is based on zhinst-toolkit and has exactly the same interface
and functions, thedocumentationfor zhinst-toolkit can be applied nearly one to one and has much more examples.ContributingWe welcome contributions by the community, either as bug reports, fixes and new
code. Please use the GitHub issue tracker to report bugs or submit patches.
Before developing something new, please get in contact with us.LicenseThis software is licensed under the terms of the MIT license.
SeeLICENSEfor more detail.
Package: zhinst-seqc-compiler
Zurich Instruments SeqC CompilerThezhinst-seqc-compilerpackage contains a standalone compiler for the Zurich
InstrumentsLabOne® AWG Sequencer programming
language, SeqC. Please see the corresponding sections in the user manuals for
more detail, e.g.,SHFQA,SHFQC,
orHDAWG.This package exposes a single function,zhinst.seqc_compiler.compile_seqc,
which takes SeqC source code and returns the compiled program and waveforms as
an ELF file, which can be uploaded through theLabOne
API.The same function is available in thezhinst-corepackage.zhinst.core.compile_seqcwill forward the call tozhinst.seqc_compiler.compile_seqcif a compatible version of this package is
installed. A version is compatible if major and minor package versions match,
and the revision of ´zhinst-seqc-compiler´ is greater or equal to the revision
ofzhinst-core. A warning will be issued if the versions do not match.This package has the main purposes to enable faster deployment of bug fixes
independently fromzhinst-coreand the LabOne release cycle.
Package: zhinst-timing-models
Feedback Latency Model ParametersFeedback Data Latency model for PQSC, SHF- and HDAWG systems.Table of ContentsInstallationUsageLicenseInstallationpip install zhinst-timing-modelsUsagefromzhinst.timing_modelsimport(PQSCMode,QAType,QCCSFeedbackModel,SGType,get_feedback_system_description,)model=QCCSFeedbackModel(description=get_feedback_system_description(generator_type=SGType.HDAWG,analyzer_type=QAType.SHFQA,pqsc_mode=PQSCMode.DECODER,))awg_clock_cycles=model.get_latency(...)Licensezhinst-timing-modelsis distributed under the terms of theMITlicense.