Saravanan666/pypi-org huggingface dataset:
Package: wandb-offline-sync
Wandb Offline SyncContinuously sync offline wandb runs.Why?If you work on computing nodes without internet access, you can use wandb in offline mode to log your runs. Normally you would sync an offline run to wandb at the end of the run, but if you have a long running job, you may want to sync your run during job's execution.How it worksThis project has two components:Farm: a https server that listens for sync requests and syncs the runs to wandb.Agent: a python module that you use in your code to request the syncs to the farm.QuickstartInstall this package:pip install wandb-offline-syncGenerate a SSL certificate for the sync farm. You can use the command:openssl req -newkey rsa:4096 -nodes -keyout key.pem -x509 -days 365 -out cert.pem. This command will create two files:cert.pemandkey.pem.Runexport WANDB_SYNC_FARM_USERNAME=<your_username>; export WANDB_SYNC_FARM_PASSWORD=<your_password>to set the username and password for the sync farm. You can also put these commands in your.bashrcfile. Replace<your_username>and<your_password>with your credentials. If these variables are not set, the farm will use the default credentials("user", "pass")Run the farm with the commandwandb_sync_farm --cert=<path_to_cert.pem> --key=<path_to_key.pem>in a node with internet connection. The farm will listen for sync requests. Runwandb_sync_farm --helpto see all the available options.Runexport WANDB_SYNC_FARM_HOST=<sync_farm_ip_address_or_hostname>; export WANDB_SYNC_FARM_PORT=<sync_farm_port>to set the hostname and port of the sync farm. You can also put these commands in your.bashrcfile. These variables will be used by the agent.In the code of your job:Import the agent:from wandb_offline_sync import agentAfter callingwandb.init(...), initialize the agent with:agent.init(...). You can pass afrequencyargument to set the minimum time between syncs (in seconds). For example, if you setfrequency=60, the agent will request a sync at most once per minute. The default value for the frequency is 5 minutes.Each timewandb.log(...)is called, the agent will check if the minimum time interval (given by the frequency) between syncs has passed, and if so, it will request a sync to the farm.Whenwandb.finish()is called, the agent will wait some seconds (default is 30) to ensure that previous syncs have been completed, and then it will request a final sync to the farm.NotesIf you run the farm with--verbose, it may happen that in the first minutes of the run, the output shows the error.wandb file is empty, and the run is not synced to the wandb server. Don't worry, after some minutes the data of the run will be available and will be synced to the wandb server.
Package: wandb-testing
<div align="center"><img src="https://app.wandb.ai/logo.svg" width="350" /><br><br></div># Weights and Biases [![ci](https://circleci.com/gh/wandb/client.svg?style=svg)](https://circleci.com/gh/wandb/client) [![pypi](https://img.shields.io/pypi/v/wandb.svg)](https://pypi.python.org/pypi/wandb)The **Weights and Biases** client is an open source library, CLI (wandb), and local web application for organizing and analyzing your machine learning experiments. Think of it as a framework-agnostic lightweight TensorBoard that persists additional information such as the state of your code, system metrics, and configuration parameters.## Local Features*   Store config parameters used in a training run*   Associate version control with your training runs*   Search, compare, and visualize training runs*   Analyze system usage metrics alongside runs## Cloud Features*   Collaborate with team members*   Run parameter sweeps*   Persist runs forever## Quickstart```shellpip install wandb```In your training script:```pythonimport wandbfrom wandb.keras import WandbCallback# Your custom arguments defined hereargs = ...run = wandb.init(config=args)run.config["more"] = "custom"def training_loop():while True:# Do some machine learningepoch, loss, val_loss = ...# Framework agnostic / custom metricsrun.history.add({"epoch": epoch, "loss": loss, "val_loss": val_loss})# Keras metricsmodel.fit(..., callbacks=[WandbCallback()])```Running your training script will save data in a directory named _wandb_ relative to your training script. To view your runs, call `wandb board` from the same directory as your training script.<p align="center"><img src="https://github.com/wandb/client/raw/master/docs/screenshot.jpg?raw=true" alt="Runs screenshot" style="max-width:100%;"></p>## Cloud Usage[Signup](https://app.wandb.ai/login?invited) for an account, then run `wandb init` from the directory with your training script. You can checkin _wandb/settings_ to version control to enable other users on your team to share experiments. Run your script with `wandb run my_script.py` and all metadata will be synced to the cloud.## Detailed UsageFramework specific and detailed usage can be found in our [documentation](http://docs.wandb.com/).## DevelopmentSee https://github.com/wandb/client/blob/master/DEVELOPMENT.md
Package: wandbtocsv
wandbtocsvBackgroundwandbtocsvallows you to quickly export a flat csv file of the top
level metrics, config, etc. from yourWeights &
Biasesruns in an easy to use CLI interface. This
utility will also get peak gpu and system memory usage for each run.InstallpipinstallwandbtocsvHow to use!wandbtocsv-husage: wandbtocsv [-h] [--entity ENTITY] [--project PROJECT]
                  [--output_file OUTPUT_FILE]

options:
  -h, --help                 show this help message and exit
  --entity ENTITY            Entity for the WANDB runs. If not provided,
                             attempts to fetch from environment variable
                             'WANDB_ENTITY'.
  --project PROJECT          Project for the WANDB runs. If not provided,
                             attempts to fetch from environment variable
                             'WANDB_PROJECT'.
  --output_file OUTPUT_FILE  Path to save the output CSV. Default name format:
                             {entity}-{project}-{mmddyy}.csv!wandbtocsv--entityhamelsmu--projectdeepspeed-dataFetching runs... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00% 0:00:01[36m0:00:03
Saved 480 runs to hamelsmu-deepspeed-data-100823.csvBonus, explore your wandb runs inDatasettecsvs-to-sqlitehamelsmu-deepspeed-data-100823.csvhamelsmu-deepspeed-data-100823.db
datasettehamelsmu-deepspeed-data-100823.db-o
Package: wandb-utils
Weights & Biases UtilitiesWhat is it?Weight & Biases (wandb)is a experiment management and hyperparameter tuning utility for machine learning experiments. Please refer totheir websitefor more information. Weights & Biases Utitlities (wandb-utils), is library of some utility functions and command line interface built on top of the official wandb API. This is an unofficial library, meaning that it is not supported by the Weights & Biases team, but is managed by open source contributors and ML researchers.
Package: wandc
A WandB Water & Carbon Metering Plug-inAwandbandcodecarbonwrapper that logs on cloud the water and carbon consumption of your experiments.InstallationpipinstallwandcUsageBasic usagefromwandc.emissions_loggerimportlog_emissions@log_emissions()defyour_function_to_track(project_name='your project name'):# your codeFor other useful parameters see codecarbon documentationhere.Tracking emissions of transformers trainerfromwandc.emissions_loggerimportlog_emissionsfromtransformersimportTrainerclassWandcTrainer(Trainer):@log_emissions()deftrain(self,...,**kwargs,):super().train(...,**kwargs)trainer=WandcTrainer(...)trainer.train()
Package: wand-cli
Wandbox CliA cli tool which uses the wandbox api to compile over 26 languages instantly,Wandboxis a social compilation service.Note: The time for the output totally depends upon how fast your internet can make a post request, it can be as slow as mine or instantaneousInstallationArch LinuxYou can install through theAURyay-SwandPipYou can install it with the python package managerpippipinstallwand-cliAfter installing with pip, you will have the command available for you, so you can directly run bywand[OPTIONS]languageCommandsIf you run the command without any option provided, you will be asked for the language name and then you can write your code in the terminal directly, and run it by pressingesc + enterlistThe list command,wand --listorwand -lis used to show the list of languages available.fileThe file command,wand --file [FILE PATH]orwand -f [FILE PATH]is used to compile a file.editorThe editor command,wand --editor [editor-name]orwand -e [editor-name]is used to open a temporary buffer in an editor to edit files, the code is run after the editor is closed,note: its recommended to use a terminal editor for this, gui editors can cause unexpected behaviour.themeThe theme command,wand --theme [theme name]orwand -t [theme name]is used to change the colorscheme for the in-place text editorthemelistThe themelist command (wand --themelistorwand -tl) is used to list all the available color schemes.helpThe help command,wand --helporwand -hshows a brief description on the command.LanguagesHere's a list of the languages which are available.┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┓
┃    python    ┃      f#      ┃
│     c++      │    scala     │
│      c       │    swift     │
│  javascript  │  typescript  │
│     java     │     vim      │
│   haskell    │     lua      │
│     bash     │     nim      │
│   crystal    │     php      │
│    elixir    │     perl     │
│      d       │     pony     │
│    sqlite    │      go      │
│     lisp     │     ruby     │
│      c#      │ coffeescript │
│     rust     │              │
└──────────────┴──────────────┘
Package: wander
Wanderwanderis a simple Python library that makes it easier to incorporate external data into LLM prompt.InstallationYou can installwanderwithpippipinstallwanderYou need to have Python version 3.10 or above to use this library.UsageAssuming you have an markdown text with a special block!shell.text="""\Today is:```!shelldate```\"""Usingwanderto render it.fromwanderimportRendererfromwander.pluginsimportShellPluginrenderer=Renderer(plugins=[ShellPlugin()])renderer.render(text)Output:Today is:
Wed May 17 16:48:09 +08 2023Writing your own pluginTo write your own plugin, simply inherit thePluginclass and do the following:Specifyplugin_nameproperty. This will be the name of the directive used in your special block.Specifyparserproperty, which is anargparse.ArgumentParserobject to define what CLI-like arguments are accepted after the directive nameImplementrunasync method. It must takes anargsargument holding all the values of the command arguments defined in your parser as well ascontentargument holding all texts in the block.You can find an example inshell.py.
Package: wandering-in-gpt
Wandering in GPT: a role-play gameHow tobrewinstallpython3
pip3installwandering-in-gpt
wigA demo play in EnglishNarrator: it was in 1938 when Ettore Majorana, an Italian theoretical physicist who worked on
neutrino masses, had purchased a ticket to travel by ship from Palermo to Naples, he disappeared
under mysterious circumstances. Alice Wagner, an investigative journalist wants to make the event
clear. So she set her journey to Italy...Narrator: Alice arrived in Palermo and started her investigation. She went to the port and asked the
people there if they had seen Ettore Majorana.Narrator: Suddenly, a young man named Tim Gray approached her. He said he had heard about her
investigation and wanted to help. Alice was surprised but welcomed the help.Narrator: Tim told Alice that he had been working at the port for many years and had seen Ettore
Majorana the day he had purchased his ticket. He said he remembered seeing Ettore talking to a man
in a dark suit, but he couldn't remember who the man was.Narrator: Alice thanked Tim for his help and decided to investigate further. She went to the local
newspaper office and asked to see any articles related to Ettore Majorana's disappearance. After
some searching, she found an article that mentioned a mysterious man in a dark suit who had been
seen with Ettore the day he disappeared.Narrator: Alice was determined to find out who this man was. She decided to go to the police station
and ask if they had any information about the man. After some questioning, the police revealed that
the man in the dark suit was a known criminal who had been involved in several suspicious
activities.Narrator: Alice was shocked to learn that Ettore had been seen with a criminal. She thanked the
police for their help and decided to investigate further. She went to the port and asked around for
anyone who had seen Ettore and the man in the dark suit together. After some searching, she found a
witness who had seen the two men together.Narrator: The witness told Alice that he had seen Ettore and the man in the dark suit talking in a
secluded area of the port. He said that the man had been asking Ettore about something, but he
couldn't remember what it was.Tim Gray: ...A demo play in Chinese旁白: 颜回辞别老师孔子，从鲁国来到镐京，一路风尘仆仆，到达后没有休息就直接求见老子，想问他世间的大道理。旁白: 颜回到了老子的门前，他拜倒在地，恭敬地说：“您好，老子大师，我是颜回，来自鲁国，请您指点迷津！”旁白: 老子抬起头，看着颜回，笑了笑，说：“你来寻求真理，我可以教你，但你必须自己去发现，只有你自己才能找到真理。”旁白: 颜回离开老子的门前，心中充满了希望，他知道自己必须努力去发现真理，而不是依赖别人的指点。他知道，只有自己才能找到真理。旁白: 于是，颜回开始了他的旅程，他去探索，去发现，去求索真理。他走遍了中国，学习了各种学问，接触了各种思想，最终，他发现了真理，并将其传播到世界各地。颜回: 这么多年了，我要回到镐京感谢老子当年的教导颜回: 老子大师，我回来了……
Package: wando-server
Wando Server is a beautiful web server for development - it is not intended to be a production server.
This server is a extension to the really good dev server ofWerkzeug Project. Basically it prints more readable logs to the terminal.It exposes the same api of “run_simple” method fromwerkzeug.serving. You can run the server with this simple code:#!/usr/bin/env python
from wando import run_simple
from my_app import app

run_simple('localhost', 5000, app)If you using Flask, for example, you can just do:#!/usr/bin/env python
from wando import ColoredLogsRequestHandler
from my_app import app

app.run(request_handler=ColoredLogsRequestHandler)
Package: wangankeji-sso
网安 SSO 客户端示例见sample.py需要实现以下功能提供通信接口会校验请求头（加密传输）接收用户的绑定/解绑接收用户的登录校验提供登录接口不校验请求头存储登录的 session、cookie定期检查当前用户的登录状态token 是否仍然存活退出时向SSO发通知实现描述此节点会描述：当系统需要接入时，功能实现的细节。应用内需要提供以下内个地址:通信接口地址 用于处理应用与SSO间数据交换的地址登录接口地址 用于处理应用登录状态（一般用于将登录信息写入 session/cookie），完成后应当转到主页地址主页地址登录接口地址处理完成后，需要跳转到的地址登录地址 登录请求失败或接口处理失败后的跳转地址提供通信接口fromwangankeji_sso.clientimportAbstractSsoRequestHandler,SsoToken,SsoErrorCodesfromtypingimportOptional,ListclassMySsoRequestHandler(AbstractSsoRequestHandler):defget_user(self,user_id:str)->Optional[dict]:"""可选实现"""passdefget_all_users(self)->List[dict]:"""若应用内存在用户体系并且:1. 需要进行用户绑定（校验用户名密码）2. 需要通过此系统校验登录（校验用户是否可用）那么必须实现此接口"""# 数据结构:# [{#     'uid': 用户ID,#     'uname': 用户名,#     'user_rid': 用户角色ID列表，多个ID使用逗号分隔,#     'ext': []# }]passdefget_role(self,role_id:str)->Optional[dict]:"""可选实现"""passdefget_all_roles(self)->List[dict]:"""若应用内存在用户体系并且:1. 需要进行用户绑定（校验用户名密码）2. 需要通过此系统校验登录（校验用户是否可用）那么必须实现此接口"""# 数据结构:# [{#     'rid': 角色ID,#     'rname': 角色名,#     'ext': []# }]passdefdo_login(self,token:SsoToken)->SsoErrorCodes:"""进行用户校验（主要是用户状态的校验，比如：用户已经被删除，用户被禁用等）"""returnSsoErrorCodes.NONEdefdo_logout(self,token:SsoToken):"""可选实现"""passdefdo_bind(self,sso_uid:str,app_uid:str,app_uname:str,password:str)->SsoErrorCodes:"""进行用户校验1. 用户密码是否正确2. 用户状态的校验，比如：用户已经被删除，用户被禁用等"""returnSsoErrorCodes.NONEdefdo_unbind(self,sso_uid:str,app_uid:str,app_uname:str)->SsoErrorCodes:"""可选实现"""returnSsoErrorCodes.NONE实例化客户端fromwangankeji_sso.clientimportSso,SsoOptionoption=SsoOption()# 应用的 APPID# option.app_id = SSO_APP_ID# SSO 的通信地址# option.sso_url = SSO_URL# SSO RSA 公钥（注意：此公钥仅可用于单一应用，多个应用无法通用）# option.sso_public_key = SSO_PUB_KEY# 应用RSA私钥# option.app_private_key = APP_PRIV_KEYsso=Sso(option,MySsoRequestHandler())登录接口示例如下:fromwangankeji_sso.clientimportSsoTokenfromwangankeji_sso.client.utilsimportRsadefpost(request,token:str,main_url:str,login_url:str):""":param request: 请求对象:param token: 使用SSO公钥加密的TOKEN:param main_url: 主页地址:param login_url: 登录页地址:return:"""try:# 解密出明文的 tokenclear_token=SsoToken.parse(Rsa.decrypt(token,options.APP_PRIV_KEY))ifnotclear_token:raiseException('TOKEN 数据无效')exceptExceptionasex:returnHttpResponse('无法解码 TOKEN')# 使用 token，设置当前的登录状态try:# 应用内的登录流程# 添加一个登录方式的标记session['login-by-wa-sso']=1session['wa-sso-token']=str(clear_token)redirect_url=main_urlexceptExceptionasex:redirect_url=login_urlreturnRedirect(redirect_url)检查登录状态建议在应用的中间件上，添加登录状态的的检查。（为了减轻资源消耗，建议缓存检查结果）ifsession.get('login-by-wa-sso')==1:# 是从 sso 登录的token=session.get('wa-sso-token')# sso 来自客户端实例ifnotsso.client.check_login(token):session.remove('login-by-wa-sso')session.remove('wa-sso-token')returnHttpResponse('登录已经超时')
Package: wangls
wanglsA command line tool that gives you the IPs of the devices connected to the same network segment.Free software: MIT licenseDocumentation:https://wangls.readthedocs.io.UsageSimple scan that returns only IPs.$wanglsScanning your whole network with OS detection might take some time especially if there are many devices connected.$wangls-oHistory0.1.0 (2020-02-04)First release on PyPI.0.1.1 (2020-02-05)Updated demos on docs0.1.2 (2020-02-05)Add dependencies requirements0.1.3 (2020-02-05)Added help option0.1.4 (2020-02-05)Fixed minor typos0.1.5 (2020-02-05)Added version option0.1.6 (2020-02-05)Updated version on option
Package: wango
An example package. Generated with cookiecutter-pylibrary.Free software: MIT licenseInstallationpip install wangoDocumentationhttps://wango.readthedocs.io/DevelopmentTo run the all tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.1.0 (2018-10-09)First release on PyPI.
Package: wangyiyunEncrypter
Requirements: execjspip install pyexecjsCall function:(1) Import:from wangyiyunEncrypter.encrypter import WangyiyunEncrypter(2) Construct keywords' data to search songs:encrypted_search_data = WangyiyunEncrypter().construct_search_data(keywords=keywords, limit=limit)(3) Construct song's data to get its real url:encrypted_song_data = WangyiyunEncrypter().construct_song_data(song_id=song_id)(4) Construct lyric's data to get lyric:encrypted_lyric_data = WangyiyunEncrypter().construct_lyric_data(song_id=song_id)(5) Construct comments' data to get the comments:encrypted_comments_data = WangyiyunEncrypter().construct_comments_data(pageNo=pageNo, pageSize=pageSize, song_id=song_id)(6) Params:keywords: the song's name or artist's name you want to search forlimit: the amounts of the search results you wantsong_id: the music idpageNo: the order number of the pages of commentspageSize: comments amounts in per page
Package: wanikani
# wanikaniVarious helpers for working with the [WaniKani API](http://www.wanikani.com/api)## UsageThis is written as a standard Python package, so it can be installed in the standard way.` python setup.py install `First, set your API key` wk set_key <api key> `### Show upcoming reviews` #--currentshow the current level only #--rollup- rollup anything that is due now #--limit10 - Only show the next 10 reviews $ wk upcoming--current--rollup--limit10 Showing upcoming items for level 17 Rolled up reviews Timestamp              Radicals      Kanji      Vocab      Total2014-01-0218:39:34           0          6         15         212014-01-0218:45:00           7         23          1         312014-01-0222:00:00           0          0          1          12014-01-0222:30:00           0          3          0          32014-01-0223:30:00           2          0          0          22014-01-0306:45:00           0          0         10         102014-01-0308:15:00           0          0          1          12014-01-0308:45:00           0          0          5          52014-01-0309:30:00           3          0          0          32014-01-0311:15:00           0          1          0          1 `
Package: wanikani-api
wanikani_apiAn API wrapper for Wanikani (V2)Free software: BSD licenseDocumentation:https://wanikani-api.readthedocs.io.FeaturesEasy access to Wanikani resources associated to your account.Automatic handling of pagination.Automatic fetching of related SubjectsQuickstart>>>fromwanikani_api.clientimportClient>>>v2_api_key="drop_your_v2_api_key_in_here"# You can get it here: https://www.wanikani.com/settings/account>>>client=Client(v2_api_key)>>>user_information=client.user_information()>>>print(user_information)UserInformation{username:Tadgh11,level:8,max_level_granted_by_subscription:60,profile_url:https://www.wanikani.com/users/Tadgh11started_at:2013-07-0912:02:54.952786+00:00,subscribed:True,current_vacation_started_at:None}>>>all_vocabulary=client.subjects(types="vocabulary")>>>forvocabinall_vocabulary:>>>print(vocab.meanings[0].meaning)#Vocabulary may have multiple meanings, we just grab the first in the list.OneOneThingSevenSevenThingsNineNineThingsTwo...TODOMake use of ETags for cachingsimplify APIImprove automatic prefetching of subjects when relevant.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.5.0 (2020-08-18)Remove mock responses that included stage names.0.5.0 (2020-08-18)Removepassedfrom resource.Removesrs_stage_namefrom assignments and reviews0.4.0 (2020-04-30)Add Preferences to User InformationAdd Subscription to User Information0.3.0 (2019-11-09)Addauxiliary_meaningsto Subject0.2.1 (2019-11-05)Fix crash caused by WK removing a field from their API.0.1.1 (2018-06-26)Change Assignment endpoint to reflect the newly dropped fields from the api (levelspecifically).Add some proper String representationWork on the Etag cache, bringing it closer to completion.0.1.0 (2018-06-26)First release on PyPI.
Package: wanikani-notifier
WaniKani NotifierNotifies a WaniKani user for new assignments to do.Free software: MIT licenseDocumentation:https://wanikani-notifier.readthedocs.io.FeaturesCan fetchAssignments that became available in the last x hoursAll available assignmentsSends a notification via different notification systems whenever new reviews and/or lessons are availableList of supported notifiers:ConsolePushoverPushSaferCan send a title and message and optionally a URL and/or and iconCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.HistoryUnreleased0.6.1 (2022-01-08)Fixed python 3.6 no longer supported0.6.0 (2022-01-08)Fixed issue where hidden items were not filtered outImproved performances by caching all subjects0.5.2 (2021-12-30)Updated pushsafer dependencies0.5.1 (2021-10-03)Fixed reviews not filtered against current user level0.5.0 (2021-08-05)Improved notifications by allowing the sending of URLs and iconsAdded min option to available_assignments_now CLI commandTime for available now is no longer set to beginning of hourCaused weird timings for lessonsFix stop-if-empty option not correctly handled in all cases0.4.2 (2021-07-28)Fixed lessons not properly retrievedFixed CLI parameters retrieval for notify0.4.1 (2021-07-28)Fixed missing dependency0.4.0 (2021-07-28)Added possibility to chain generation of messages to notify multiple things at once (CLI)Added support for console and Pushover notifiersAdded Notifier factory systemAdded total available assignments to the notifiable topics0.3.0 (2021-07-23)Changed “hours age” parameter to “since” to improve usability in scripts.Added notifier abstractionAdded the possibility to use multiple notifiersCurrently, there is only one notifier (pushsafer)Changed options name to reflect these changes0.2.0 (2021-07-21)Changed “after” parameter to “hours ago” to improve usability in scripts.0.1.0 (2021-07-21)First release on PyPI.