Saravanan666/pypi-org huggingface dataset:
Package: ydl-podcast
ydl-podcastA simple tool to generate Podcast-like RSS feeds from youtube (or other
youtube-dl supported services) channels, usingyoutube-dl.SetupInstall package with requirements:Youtube-dl:pip install ydl-podcast[youtube-dl]yt-dlp:pip install ydl-podcast[yt-dlp]ConfigurationEdit the config.yaml file to list your podcast sources and configure them,
as well as edit general configuration.The available settings are the following.General settingsoutput_dir: local directory where the downloaded media will be stored, and
the podcast xml files generated.url_root: root url for the static files (used in the generation of the XML
to point to the media files.subscriptions: a list of feeds to subscribe to.youtube-dl-module: Alternative youtube-dl python module. By default, this
usesyoutube-dl, but can leverage forks
such asyt-dlp.Feed settingsMandatoryname NAME: Name of the podcast source. Used as the podcast title, and media
directory name.url URL: source url for the youtube (or other) channel.Optionalaudio_only True/False: ifTrue, audio will be extracted from downloaded
videos to create an audio podcast.retention_days N: only download elements newer thanNdays, and
automatically delete elements older.download_last N: only download the latestNvideos.initialize True/False: ifTrue, then downloads everything on the first
run, no matter thedownload_lastorretention_daysspecified.output_dir: local directory where the downloaded media will be stored, and
the podcast xml files generated.url_root: root url for the static files (used in the generation of the XML
to point to the media files.format: file format to force youtube-dl to use (eg mp4, webm, mp3 for audio
only…)best: force best quality (only useful when specifying a format).ydl_options: list of raw youtube-dl options to use. For experienced users,
since this will likely yield issues if not understood.nfo_files: generates nfo files for subscriptions and downloaded episodes (simulates a "tvshow" nfo for the subscription and "tvshow episode" for each video). This helps plex, kodi, jellyfin import correct metadata. Does NOT supportaudio_onlyfeeds at this point.skip_download: Don't perform download, just generate the Atom feed from the existing files. Mandatoryurlparameter can be skipped ifskip_downloadis set totruedownload_as_playlist: Pass the url to the downloader directly, without processing the metadata of each item in the playlist. This is helpful with generic urls, and a few specific extractors.UsageUsing cron or your favorite scheduler, run:ydl_podcast [configfile.yaml]You can then use your favorite web server to serve the files (a good idea is to
exclude the*.jsonand*.partfiles from being served as the first might
leak information, and the second is unnecessary.eg with nginx:root /var/www/static/podcasts/;
location ~ (\.json$|\.part$) {
  return 403;
}
Package: ydnlp
简介利用 onnxruntime以及PaddleNLP提供的UIE模型,对文本，段落，篇章内容进行结构化提取使用模型UIE(Universal Information Extraction)：Yaojie Lu等人在ACL-2022中提出了通用信息抽取统一框架UIE。该框架实现了实体抽取、关系抽取、事件抽取、情感分析等任务的统一建模，并使得不同任务间具备良好的迁移和泛化能力。为了方便大家使用UIE的强大能力，PaddleNLP借鉴该论文的方法，基于ERNIE 3.0知识增强预训练模型，训练并开源了首个中文通用信息抽取模型UIE。该模型可以支持不限定行业领域和抽取目标的关键信息抽取，实现零样本快速冷启动，并具备优秀的小样本微调能力，快速适配特定的抽取目标。UIE的优势使用简单：用户可以使用自然语言自定义抽取目标，无需训练即可统一抽取输入文本中的对应信息。实现开箱即用，并满足各类信息抽取需求。降本增效：以往的信息抽取技术需要大量标注数据才能保证信息抽取的效果，为了提高开发过程中的开发效率，减少不必要的重复工作时间，开放域信息抽取可以实现零样本（zero-shot）或者少样本（few-shot）抽取，大幅度降低标注数据依赖，在降低成本的同时，还提升了效果。效果领先：开放域信息抽取在多种场景，多种任务上，均有不俗的表现。参考PaddleNLP-UIE安装pipinstallydnlp实例代码fromydnlp.uie_predictimportUIEPredictor# 开放域抽取texts=['个人经济收入证明抽取兹证明张三为本单位职工，已连续在我单位工作5年。ABC大学毕业，目前在我单位担任总经理助理职位。近一年内该员工在我单位平均月收入（税后）为63500元。（大写：陆万叁仟伍佰元']schema1={'姓名','工作时间','毕业学校','职位','收入'}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)# 开放域抽取texts=['2月8日上午北京冬奥会自由式滑雪女子大跳台决赛中中国选手谷爱凌以188.25分获得金牌！']schema1={'时间','选手','赛事名称'}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)# 情感分类texts=['这个产品用起来真的很流畅，我非常喜欢']schema1={'情感倾向[正向，负向]'}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)# 评价维度抽取texts=['总体挺好的，电池续航不行']schema1={'评价维度':['观点词','情感倾向[正向，负向]']}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)# 触发词抽取texts=['中国地震台网正式测定：5月16日06时08分在云南临沧市凤庆县(北纬24.34度，东经99.98度)发生3.5级地震，震源深度10千米。']schema1={'地震触发词':['地震强度','时间','震中位置','震源深度']}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)TODO支持自定义schema的微调工具包丰富常见的schema种类更多需求调研:505991554@qq.comQ&A预置的schema列表是否可以查询？预设的schema没有统计过，提供预设的schema对抽取没有多大用处，因为不同的样本形式同一个schema抽取效果也是不一样，我们给出的建议是对于自己任务，都是需要微调一下
Package: ydocr
简介利用 onnxruntime 及 PaddleOCR 提供的模型, 对图片中的文字进行检测与识别.使用模型文字检测:ch_PP-OCRv3_det_infer方向分类:cls mobile v2文字识别:ch_PP-OCRv2_rec_infer参考PaddleOCR手把手教你使用ONNXRunTime部署PP-OCR安装pipinstallydocr使用importcv2fromydocr.predict_systemimportTextSystem,order_onrowtext_sys=TextSystem()# 识别单行文本res=text_sys.ocr_single_line(cv2.imread('single_line_text.png'))print(res)# 批量识别单行文本res=text_sys.ocr_lines([cv2.imread('single_line_text.png')])print(res[0])# 检测并识别文本img=cv2.imread('test.png')res=text_sys.detect_and_ocr(img)forboxed_resultinres:print("{},{:.3f}".format(boxed_result.ocr_text,boxed_result.score))# 检测并识别文本（换行执行）fromydocr.predict_systemimportTextSystem,order_onrowimg=cv2.imread('test.png')res=text_sys.detect_and_ocr(img)res=order_onrow(res)#检测并识别文本，图片源是网络图片fromurllib.requestimporturlopendefcv_imread_url(img_url):resp=urlopen(img_url)img=np.asarray(bytearray(resp.read()),dtype=np.uint8)img=cv2.imdecode(img,cv2.IMREAD_COLOR)returnimgimg=cv_imread_url('https://imgurl.png')
Package: ydot
ydotR-like formulas for Spark Dataframes.DocumentationPyPiGitterNow you have the expressive power of R-like formulas to produce design matrices for your experimental needs. This API is based off ofpatsy, but for use with Apache Spark dataframes. Given a Spark dataframe, you can express your design matrices with something that resembles the following.y ~ x1 + x2 + (x3 + a + b)**2Here's a short and sweet example.fromydot.sparkimportsmatricesspark_df=get_a_spark_dataframe()formula='y ~ x1 + x2 + (x3 + a + b)**2'y,X=smatrices(formula,spark_df)Software CopyrightCopyright 2020 One-Off Coder

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.Book CopyrightCopyright 2020 One-Off CoderThis work is licensed under aCreative Commons Attribution 4.0 International LicensebyOne-Off Coder.Art CopyrightCopyright 2020 Daytchia VangCitation@misc{oneoffcoder_ydot_2020,
title={ydot, R-like formulas for Spark Dataframes},
url={https://github.com/oneoffcoder/pyspark-formula},
author={Jee Vang},
year={2020},
month={Dec}}
Package: ydown
ydown is a complete library for getting information about or downloading youtube videos. It can show all the videos information:For example it shows:AuthorTitleLikes and DislikesViewsRelated VideosDescriptionIt also have a good download function that shows you the download status.YDOWNLIBydownlib is the library that download a video. This is an example of the use:import time
from ydown import ydownlib

#THIS IS AN EXAMPLE OF THE USE OF ydownlib
#OPEN THE VIDEO
video=ydownlib.yvideo("http://www.youtube.com/watch?v=1T__uN5xmC0")

#DISPLAY THE VIDEO TITLE
print video.getTitle()

#DISPLAY THE FILE VIDEO URL
print video.getUrl()

#START DOWNLOAD IN ANOTHER THREAD
video.download()

#THIS WHILE DISPLAY THE DOWNLOAD STATUS
while(1):
    if video.isStarted(): #START TRACING WHEN THE DOWNLOAD IN STARTED

        #DISPLAY THE PERCENT
        print str(video.getPercent()) + "%"

        #DISPLAY DOWNLOADED AND TOTAl FILE SIZE
        print str(video.getDownloaded()) + "/" + str(video.getTotalSize())

        time.sleep(1) #SLEEP 1 SECOND AFTER EACH REPORT
        #IF THE DOWNLOAD IS FINISHED, QUIT
        if video.getPercent()==100:
            breakYDATALIBydatalib is the library that show you the video’s informations. This is an example of the use:from ydown import ydatalib

#OPEN YOUTUBE VIDEO
video=ydatalib.ydata("http://www.youtube.com/watch?v=1T__uN5xmC0")

#GET VIDEO INFORMATION
print "TITLE"
print video.getTitle()
print "VIEWS"
print video.getViews()
print "LIKES"
print video.getLikes()
print "DISLIKES"
print video.getDislikes()
print "DESCRIPTION"
print video.getDescription()
print "LIST OF RELATED VIDEO URL"
print video.getRelated()USAGE OF YDOWNLIBUsing ydownlib is very simple:FIRST CREATE A yvideo OBJECTform ydown import ydownlib
video=ydownlib.yvideo(“YOUTUBE URL”)NOW YOU CAN USE ALL THE ydownlib FUNCTIONUSAGE OF YDATALIBUsing ydatalib is very simple:FIRST CREATE A ydata OBJECTform ydown import ydatalib
video=ydatalib.ydata(“YOUTUBE URL”)NOW YOU CAN USE ALL THE ydatalib FUNCTIONFUNCTIONSYDOWNLIBThis is the complete function list:getTitle()this function return the name of the yvideo object loadedgetUrl()this function return the file’s url of the yvideo object loadeddownload()this function start the download in another threadisStarted()return true if the download is startedgetPercent()return the current download percentgetTotalSize()return the total file size of the video in bytesgetDownloaded()return the downloaded part of file in bytesYDATALIBThis is the complete function list:getTitle()this function return the name of the ydata object loadedgetFileUrl()this function return the file’s url of the ydata object loadedgetAuthor()this function return the video’s authorgetLikes()this function return the video’s likesgetDislikes()this function return the video’s dislikesgetRelated()this function return a list with related videosgetDescription()this function return the video’s descriptionVisit the sourceforge pagehttps://sourceforge.net/projects/ydown/
Package: ydsdk
云盾 api sdk for python说明接口基地址： 'https://apiv4.yundun.com/V4/';接口遵循RESTful,默认请求体json,接口默认返回jsonapp_id, app_secret 联系技术客服，先注册一个云盾的账号，用于申请绑定api身份签名算法每次请求都签名，保证传输过程数据不被篡改客户端：sha256签名算法，将参数base64编码+app_secret用sha256签名，每次请求带上签名服务端：拿到参数用相同的算法签名，对比签名是否正确sdk 使用说明环境：python >=3.5支持get/post/patch/put/delete方法参数说明app_id 云盾分配的app_idapp_secert 云盾分配的app_secert, 用于签名数据api_pre api前缀user_id 当前使用者在云盾的用户IDtimeout 请求超时时间，默认10秒，请合理设置每次调用会返回三个参数：(原始字符串，解析后的json字典，错误字符串)注意事项
针对所有请求，uri与get参数是分离的，如https://apiv4.yundun.com/V4/version?v=1, 调用时v=1参数，须通过query传递
raw, body, err = sdk.get('version', query={'v': 1})安装pip install ydsdk使用### 实例化 YdSdk
import logging
from ydsdk import YdSdk

## 添加日志
logger = logging.getLogger()
formatter = logging.Formatter('%(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s')

##日志输出到文件
fileHandle = logging.FileHandler('/tmp/ydsdk.log', encoding='utf-8')
fileHandle.setFormatter(formatter)
logger.addHandler(fileHandle)

##日志输出到stdout
streamHandle = logging.StreamHandler()
streamHandle.setFormatter(formatter)
logger.addHandler(streamHandle)

sdk = YdSdk({
    "app_id": 'xxxxxxxxxxx',
    "app_secert": 'xxxxxxxxxxxxx', 
    "api_pre": "https://apiv4.yundun.com/V4/",
    "user_id": 1, 
    "timeout": 30,
    "logger": logger,               ##如果不需要，此参数可不传
})

### get 方式请求数据
raw, jsonData, err = sdk.get('test')
print(raw, jsonData, err)

### post 方式请求数据
query    = {}
postData = {'domain_id': 1, 'status': 2}
raw, body, err = sdk.post('test.save', postData = postData, query=query)
print(raw, jsonData, err)

### patch 方式请求数据
query    = {}
postData = {'domain_id': 1, 'status': 2}
raw, body, err = sdk.patch('test.save', postData = postData, query=query)
if err != "":
    print("error: ", err)
else:
    print(raw, jsonData)

### put 方式请求数据
query    = {}
postData = {'domain_id': 1, 'status': 2}
raw, body, err = sdk.put('test.save', postData = postData, query=query)
print(raw, jsonData, err)

### delete 方式请求数据
query    = {}
postData = {'domain_id': 1, 'status': 2}
raw, body, err = sdk.put('test.save', postData = postData, query=query)
print(raw, jsonData, err)


### put方式请求数据
query    = {}
postData = {'domain_id': 1, 'status': 2}
raw, body, err = sdk.put('test.save', postData = postData, query=query)
print(raw, jsonData, err)更新日志2020.04.29 v0.1.7规范demo中的api地址2020.09.14 v0.1.8更新demo中的api访问地址2020.10.13 v0.2.0签名算法升级2020.10.13 v0.2.2修正多维数据签名时，排序算法导致的签名失败问题增加针对多维数据的单元测试2020.10.18 v0.2.3修正多线程并行执行时，变量不安全问题
Package: ydtapi
This is a translate API that was made with requests.post, hashlib, and
randomThe module use 有道翻译 to translateIt’s not open source, so there’s no licenses.Run it with a simple line of code in terminal:::python -m tapiIt will print out the result of translationOr you can use it like this:::xxxxxxxxxxfrom tapi import mainAPImainAPI('Hello', fr='AUTO', to='AUTO')It will return a dict with type(EN2ZH? ZH2ES?……), result, smart
result(With the meaning of words)
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;Author: UNKNOWN
Package: yduie
简介利用 onnxruntime以及PaddleNLP提供的UIE模型,对文本，段落，篇章内容进行结构化提取使用模型UIE(Universal Information Extraction)：Yaojie Lu等人在ACL-2022中提出了通用信息抽取统一框架UIE。该框架实现了实体抽取、关系抽取、事件抽取、情感分析等任务的统一建模，并使得不同任务间具备良好的迁移和泛化能力。为了方便大家使用UIE的强大能力，PaddleNLP借鉴该论文的方法，基于ERNIE 3.0知识增强预训练模型，训练并开源了首个中文通用信息抽取模型UIE。该模型可以支持不限定行业领域和抽取目标的关键信息抽取，实现零样本快速冷启动，并具备优秀的小样本微调能力，快速适配特定的抽取目标。UIE的优势使用简单：用户可以使用自然语言自定义抽取目标，无需训练即可统一抽取输入文本中的对应信息。实现开箱即用，并满足各类信息抽取需求。降本增效：以往的信息抽取技术需要大量标注数据才能保证信息抽取的效果，为了提高开发过程中的开发效率，减少不必要的重复工作时间，开放域信息抽取可以实现零样本（zero-shot）或者少样本（few-shot）抽取，大幅度降低标注数据依赖，在降低成本的同时，还提升了效果。效果领先：开放域信息抽取在多种场景，多种任务上，均有不俗的表现。参考PaddleNLP-UIE安装pipinstallydnlp实例代码fromydnlp.uie_predictimportUIEPredictor# 开放域抽取texts=['个人经济收入证明抽取兹证明张三为本单位职工，已连续在我单位工作5年。ABC大学毕业，目前在我单位担任总经理助理职位。近一年内该员工在我单位平均月收入（税后）为63500元。（大写：陆万叁仟伍佰元']schema1={'姓名','工作时间','毕业学校','职位','收入'}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)# 开放域抽取texts=['2月8日上午北京冬奥会自由式滑雪女子大跳台决赛中中国选手谷爱凌以188.25分获得金牌！']schema1={'时间','选手','赛事名称'}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)# 情感分类texts=['这个产品用起来真的很流畅，我非常喜欢']schema1={'情感倾向[正向，负向]'}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)# 评价维度抽取texts=['总体挺好的，电池续航不行']schema1={'评价维度':['观点词','情感倾向[正向，负向]']}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)# 触发词抽取texts=['中国地震台网正式测定：5月16日06时08分在云南临沧市凤庆县(北纬24.34度，东经99.98度)发生3.5级地震，震源深度10千米。']schema1={'地震触发词':['地震强度','时间','震中位置','震源深度']}predictor=UIEPredictor(512,4,schema1,position_prob=0.5)outputs=predictor.predict(texts)print(outputs)TODO支持自定义schema的微调工具包丰富常见的schema种类更多需求调研:505991554@qq.comQ&A预置的schema列表是否可以查询？预设的schema没有统计过，提供预设的schema对抽取没有多大用处，因为不同的样本形式同一个schema抽取效果也是不一样，我们给出的建议是对于自己任务，都是需要微调一下
Package: yeahyeah
yeahyeahCLI launch manager. Dispense with the 5 manual steps for everything, just say yeah yeah I know just do it come on moveFree software: MIT licenseDocumentation:https://yeahyeah.readthedocs.io.WhatWith yeahyeah you can, for example, do this in a console window:$ jj virus
> launches www.virustotal.com

$ jj search a website
> searches for 'a website' on duckduckgo

$ jj admin url_pattern add 'wikipedia' https://wikipedia.org
> adds an item 'wikipedia' that launches the given url

$ jj w<tab>
website   wikipedia
$ jj wi<tab>
$ jj wikipedia
> tab completion on all items

$ jj my_folder          # launches a set path in new terminal window

$ jj log add writing    # adds a log message 'writing' to clockifiyFeaturesLaunch commands from console/terminalCommand line interface based on python ClickAutocomplete for bash and zshPlugin architecture. Write your ownWildcard commands like ‘Open firefox search on search term X’CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.4.3 (2020-09-23)Added pre-commit config and hooksReformatted all code to black and flake80.2.0 (2019-10-31)Added clockify pluginRewrote much to use click context objects. This makes command interleaving and inheriting contexts much clearerWrote some docs for creating a plugin0.1.5 (2019-07-23)Removed windowraiser plugin. Too UI dependent, simpler scripts work better.0.1.0 (2019-03-12)First release on PyPI.
Package: yearfrac
[![PyPI version](https://badge.fury.io/py/yearfrac.svg)](https://badge.fury.io/py/yearfrac)
[![yearfrac](https://snyk.io/advisor/python/yearfrac/badge.svg)](https://snyk.io/advisor/python/yearfrac)# yearfrac## Installation
Theyearfrac[git repo](http://github.com/kmedian/yearfrac) is available as [PyPi package](https://pypi.org/project/yearfrac)` pip install yearfrac `## Usage
Check the [examples](https://github.com/kmedian/yearfrac/tree/master/examples) folder for notebooks.Functionsisaleapyear– Check if a year is leap yeareastersunday– Determine day and month of an Easter Sunday for a given yearjd_to_dateanddate_to_jd– Julian Day number conversionact_afb– Actual/Actual AFBact_isda– Actual/Actual ISDAd30360e– 30E/360 ISDA daycount methodd30365– 30/365 daycount methodyearfrac– Wrapper for all daycount methods## Appendix### Install a virtual environment` python3.7-mvenv .venv source .venv/bin/activate pip3 install--upgradepip pip3 install-rrequirements.txt pip3 install-rrequirements-dev.txtpip3 install-rrequirements-demo.txt`(If your git repo is stored in a folder with whitespaces, then don’t use the subfolder.venv. Use an absolute path without whitespaces.)### Python Commands
* Check syntax:flake8 –ignore=F401 –exclude=$(grep -v ‘^#’ .gitignore | xargs | sed -e ‘s/ /,/g’)* Run Unit Tests:python -W ignore -m unittest discover* Remove.pycfiles:find . -type f -name “*.pyc” | xargs rm* Remove__pycache__folders:find . -type d -name “__pycache__” | xargs rm -rfPublish`sh # pandoc README.md--frommarkdown--torst-s-oREADME.rst  # RST file is too much trouble python setup.py sdist twine upload-rpypi dist/* `### Support
Please [open an issue](https://github.com/kmedian/yearfrac/issues/new) for support.### Contributors
* Adam Groszer [@agroszer](https://github.com/agroszer)
* Emilio Basualdo [@emiliobasualdo](https://github.com/emiliobasualdo)
* Ivan Nesic [@fatkaratekid](https://github.com/fatkaratekid)
* Vinay Gupta [@vinschess](https://github.com/vinschess)
* Ulf Hamster [@ulf1](https://github.com/ulf1)Please contribute using [Github Flow](https://guides.github.com/introduction/flow/). Create a branch, add commits, and [open a pull request](https://github.com/kmedian/yearfrac/compare/).
Package: yearmaps
YearMaps生成一年的热力图。安装pipinstall--useryearmaps使用Usage:yearmaps[OPTIONS]COMMAND[ARGS]...

Options:-d,--data-dirTEXTDirectorytostoredatas[default:~/.yearmaps]-o,--output-dirTEXTDirectorytostoreoutput[default:$(pwd)]-f,--file-type[svg|png]Filetypetoexport[default:svg]-m,--mode[till_now|year]Generatemodeoftheprogram[default:till_now]-y,--yearINTEGERYeartogenerate,thisoptionwilloverridemodeto"year"-c,--color[red|pink|purple|deeppurple|indigo|blue|lightblue|cyan|teal|green|lightgreen|lime|yellow|amber|orange|deeporange|brown|grey|bluegrey]Colortooverrideproviderdefaultcolor--helpShowthismessageandexit.

Commands:bbdc不背单词biliBilibilicfCodeforcesgithubGitHub# 服务器模式Usage:yearmaps-server[OPTIONS]Options:-l,--hostTEXTHosttolistenon.[default:0.0.0.0]-p,--portINTEGERPorttolistenon.[default:5000]-f,--configTEXTPathtoconfigfile.[default:$(pwd)/yearmaps.yml]--helpShowthismessageandexit.子模块不背单词Usage:yearmapsbbdc[OPTIONS]不背单词

Options:-i,--idTEXT不背单词用户ID[required]-t,--type[time|word]图数据类型--helpShowthismessageandexit.bilibiliUsage:yearmapsbili[OPTIONS]bilibili

Options:-i,--idTEXTbilibiliuid[required]-t,--type[video]图数据类型--helpShowthismessageandexit.CodeforcesUsage:yearmapscf[OPTIONS]Codeforces

Options:-u,--userTEXTCodeforcesusername[required]-t,--type[all|ac]图数据类型--helpShowthismessageandexit.GitHubUsage:yearmapsgithub[OPTIONS]GitHub

Options:-u,--userTEXTGitHubusername[required]-k,--tokenTEXTGitHubaccesstoken[required]-t,--type[contrib]图数据类型--helpShowthismessageandexit.
Package: yeastarAPI
yeastarAPIPython OOP interface for connecting to, authenticating with, and sending SMS messages via any of the 8 connected SIM cards
Currently has a class definition for incoming messages, but not implemented.##Get started:import yeastarapi

if __name__ == '__main__':
    conn = yeastarapi.Connection("Gateway IP", 5038, "apiuser", "apipass")
    print(yeastarapi.SendSMS(conn, 1, "040000000", "Hello World!").Status)
Package: yediemin
YedieminA package for bulletproof attachment serving in Django Rest Framework.Getting StartedRequirementsNginxDjango Rest FrameworkSession AuthenticationDjango Storages (S3)Installation StepsInstall package fromPyPi.pipinstallyedieminAdd the view tourls.pyfromyedieminimportYedieminViewurlpatterns=[re_path(r'^yediemin/(?P<file_name>\S+)/$',YedieminView.as_view(),name='yediemin'),]Configure Nginx. Place the configuration below under your server.location /yediemin-files/ {
            internal;
            resolver 8.8.8.8;
            set $redirect_uri "$upstream_http_redirect_uri";

            proxy_buffering off;
            proxy_pass $redirect_uri;
}UseYedieminFileFieldin serializer forFileField.fromyedieminimportYedieminFileFieldclassAttachmentSerializer(serializers.ModelSerializer):file=YedieminFileField()classMeta:model=Attachmentfields=("id","file",)UsePrivateS3Boto3Storagefor the field inmodels.pyfromyedieminimportPrivateS3Boto3StorageclassAttachment(models.Model):file=models.FileField(storage=PrivateS3Boto3Storage())Upload files to S3 withYedieminFileField. Yediemin requirespresigned object url.SettingsYEDIEMIN_HIDDEN_REDIRECT_PATHDefault:yediemin-files.
It should be same with location in nginx configuration.YEDIEMIN_AUTHENTICATION_CLASSESDefault:[rest_framework.authentication.SessionAuthentication]YEDIEMIN_EXPIRE_INDefault:604800seconds which is 1 week. This is the maximum limit provided by AWS.Using Query Parameters
Package: yedis
The Python interface to the Redis key-value store, extended to support additional features from YugaByteDB.This has been forked fromhttps://github.com/andymccurdy/redis-pyand is intended to be
used against the YEDIS API end point of YugaByteDB. This client also supports additional
commands (such as the time-series related commands) for use against YugaByte DB that
are not part of the official Redis API.Please refer toYugaByte DB docsfor reference.Installationyedis requires a running YugaByteDB instance listening on the YEDIS end point, or a normal Redis server. SeeYugaByteDB quickstartorRedis’s quickstartfor installation instructions.To install yedis, simply:$sudopipinstallyedisor alternatively (you really should be using pip though):$sudoeasy_installyedisor from source:$sudopythonsetup.pyinstallGetting Started>>>importredis>>>r=redis.StrictRedis(host='localhost',port=6379,db=0)>>>r.set('foo','bar')True>>>r.get('foo')'bar'By default, all responses are returned asbytesin Python 3 andstrin
Python 2. The user is responsible for decoding to Python 3 strings or Python 2
unicode objects.Ifallstring responses from a client should be decoded, the user can
specifydecode_responses=TruetoStrictRedis.__init__. In this case, any
Redis command that returns a string type will be decoded with theencodingspecified.API ReferencePlease refer toYugaByte API Referncefor details on
the commmands that Yugabyte’s YEDIS end point supports.
For other use cases, theofficial Redis command documentationdoes a
great job of explaining each command in detail.yedis is forked off redis-py, please refer tohttps://github.com/andymccurdy/redis-pyfor the details of the implementation and limitations.Authoryedis is based on a fork of redis-py, extended to support the additional
commands for use against YugaByteDB’s YEDIS API end point.redis-py is developed and maintained by Andy McCurdy (sedrik@gmail.com).
It can be found here:http://github.com/andymccurdy/redis-py