Saravanan666/pypi-org huggingface dataset:
Package: honeycomb-opentelemetry
Honeycomb OpenTelemetry Distro for PythonSTATUS: this library is BETA.You're welcome to try it, and let us know your feedback in the issues!This is Honeycomb's Distribution of OpenTelemetry for Python.
It makes getting started with OpenTelemetry and Honeycomb easier!Latest release built with:OpenTelemetry version 1.22.0/0.43b0RequirementsPython 3.7 or higherGetting StartedHoneycomb's Distribution of OpenTelemetry for Python allows you to streamline configuration and to instrument as quickly and easily as possible.DocumentationExamplesFlaskDjangoSeeDEVELOPING.mdfor additional instructions for building and testing this project in development.Why would I want to use this?Streamlined configuration for sending data to Honeycomb!Easy interop with existing instrumentation with OpenTelemetry!Deterministic sampling!Multi-span attributes!Local visualizations!LicenseApache 2.0 License.
Package: honeydb
To learn more about HoneyDB visitAbout HoneyDB.To lean more about the HoneyDB API visitHoneyDB REST API.Thehoneydbcommand is a CLI tool for interacting with the HoneyDB API.Installation$pipinstallhoneydbCLI usage$exportHONEYDB_API_ID=<yourapiid>$exportHONEYDB_API_KEY=<yourapikey>$honeydb--bad-hostsModule usagefromhoneydbimportapihoneydb=api.Client('api_id','api_key')print(honeydb.bad_hosts())More details and the latest updates can be found on theGitHub Project Page.
Package: honeywell-hpma115s0
Honeywell HPMA115S0 Particulate Sensor Python interfaceA basic python interface for interacting with the Honeywell HPMA115S0 Particulate Matter sensor.  This code has been tested with the following devices: HPMA115S0.This wrapper is based on:https://github.com/FEEprojects/plantowerThis wrapper has been developped as part of on-going work on the use of low-cost PM sensors to monitor air quality in urban areas.
Package: honeywell-imtcc-poller
Honeywell IMTCC PollerTool for polling heating data fromHoneywell International My Total Connect Comfort, combining it with the outside temperature from theOpenWeather APIand presenting them asPrometheusmetrics.InstallationThis is not yet packaged. To run, you will need to clone the repo withgitand install the required prerequisites:Python 3.10.4or abovePoetry 1.2.0or aboveYou can then runpoetry installto install the required python libraries.UsageCreate environment variables containing your Honeywelllogin credetials:$exportHONEYWELL_EMAIL_ADDRESS="foo@example.com"$exportHONEYWELL_PASSWORD="ThisIsNotARealPassword"Create environment variables containing your OpenWeatherAPI keyand co-ordinates for where you want the outside temperature to reflect:$exportOPENWEATHER_API_KEY="foo-openweather-api-key"$exportOPENWEATHER_LATITUDE="51.476852"$exportOPENWEATHER_LONGITUDE="0.0005"You can then run the tool via poetry:$poetryrunpoll-honeywell
Kitchen:20.0
HarrysRoom:20.5
Lounge:19.5
MainBedroom:19.5
HotWater:48.0
Outside:16.36The tool will authenticate with the Honeywell API using the login credentials supplied. It will make the calls every 60 seconds in order to get location and zone data.The Prometheus metrics are made available for scraping onhttps://localhost:8000while the tool is running.LimitationsAssumes you have zero or one hot water systemsLimited error handlingDevelopingRunning tests:$maketestLicenseThis project is licensed under the terms of theMIT License.
Package: hongery-chat
Pandora潘多拉，一个不只是命令行的ChatGPT。实现了网页版ChatGPT的主要操作。能过Cloudflare，理论上速度还可以。为什么要用高峰期能绕过官方限制，继续使用。应答速度直逼PLUS，白嫖用户的福音。官方故障的时候，它可能还是能跑。多模式：网页/命令行/API，私有化部署。不会像官方那样无故断线、报错。界面截图如何运行Python版本目测起码要3.7pip安装运行pipinstallpandora-chatgpt
pandora如果你想支持gpt-3.5-turbo模式：pipinstall'pandora-chatgpt[api]'pandora如果你想启用cloud模式：pipinstall'pandora-chatgpt[cloud]'pandora-cloud编译运行pipinstall.
pandora如果你想支持gpt-3.5-turbo模式：pipinstall'.[api]'pandora如果你想启用cloud模式：pipinstall'.[cloud]'pandora-cloudDocker Hub运行dockerpullpengzhile/pandora
dockerrun-it--rmpengzhile/pandoraDocker编译运行dockerbuild-tpandora.
dockerrun-it--rmpandora输入用户名密码登录即可，登录密码理论上不显示出来，莫慌。简单而粗暴，不失优雅。程序参数可通过pandora --help查看。-p或--proxy指定代理，格式：protocol://user:pass@ip:port。-t或--token_file指定一个存放Access Token的文件，使用Access Token登录。-s或--server以http服务方式启动，格式：ip:port。-a或--api使用gpt-3.5-turboAPI请求，你可能需要向OpenAI支付费用。--sentry启用sentry框架来发送错误报告供作者查错，敏感信息不会被发送。-v或--verbose显示调试信息，且出错时打印异常堆栈信息，供查错使用。Docker环境变量PANDORA_ACCESS_TOKEN指定Access Token字符串。PANDORA_PROXY指定代理，格式：protocol://user:pass@ip:port。PANDORA_SERVER以http服务方式启动，格式：ip:port。PANDORA_API使用gpt-3.5-turboAPI请求，你可能需要向OpenAI支付费用。PANDORA_SENTRY启用sentry框架来发送错误报告供作者查错，敏感信息不会被发送。PANDORA_VERBOSE显示调试信息，且出错时打印异常堆栈信息，供查错使用。使用Docker方式，设置环境变量即可，无视上述程序参数。关于 Access Token使用Access Token方式登录，可以无代理直连。这个服务可以帮你安全有效拿到Access Token，无论是否第三方登录。其中accessToken字段的那一长串内容即是Access Token。Access Token可以复制保存，其有效期目前为1个月。不要泄露你的Access Token，使用它可以操纵你的账号。HTTP服务文档如果你以http服务方式启动，现在你可以打开一个极简版的ChatGPT了。通过你指定的http://ip:port来访问。API文档见：doc/HTTP-API.md操作命令对话界面连敲两次Enter发送你的输入给ChatGPT。对话界面使用/?可以打印支持的操作命令。/title重新设置当前对话的标题。/select回到选择会话界面。/reload重新加载当前会话所有内容，F5你能懂吧。/regen如果对ChatGPT当前回答不满意，可以让它重新回答。/continue让ChatGPT继续输出回复的剩余部分。/edit编辑你之前的一个提问。/new直接开启一个新会话。/del删除当前会话，回到会话选择界面。/token打印当前的Access Token，也许你用得上，但不要泄露。/clear清屏，应该不用解释。/version打印Pandora的版本信息。/exit退出潘多拉。高阶设置本部分内容不理解的朋友，请勿擅动！环境变量OPENAI_API_PREFIX可以替换OpenAI Api的前缀https://api.openai.com。如果你想持久存储Docker中Pandora产生的数据，你可以挂载宿主机目录至/data。如果你在国内使用pip安装缓慢，可以考虑切换至腾讯的源：pip config set global.index-url https://mirrors.cloud.tencent.com/pypi/simple镜像同步版本可能不及时，如果出现这种情况建议切换至官方源：pip config set global.index-url https://pypi.org/simple默认使用sqlite3存储会话数据，如果你希望更换至mysql，可以这么做：执行pip install PyMySQL安装驱动。设置环境变量：DATABASE_URI为类似mysql+pymysql://user:pass@localhost/dbname的连接字符串。环境变量指定OPENAI_EMAIL可以替代登录输入用户名，OPENAI_PASSWORD则可以替代输入密码。Cloud模式搭建一个跟官方很像的ChatGPT服务，不能说很像，只能说一样。该模式使用pandora-cloud启动，前提是你如前面所说安装好了。Docker环境变量：PANDORA_CLOUD启动cloud模式。该模式参数含义与普通模式相同，可--help查看。其他说明项目是站在其他巨人的肩膀上，感谢！报错、BUG之类的提出Issue，我会修复。因为之后ChatGPT的API变动，我可能不会跟进修复。喜欢的可以给颗星，都是老朋友了。不影响PHP是世界上最好的编程语言！
Package: honkairail
HonkaiRailA simple and convenient model for Mihoyo API which is complemented by other resourcesInstall:pip install honkairailUses:fromhonkairailimportstarrailapiimportasyncio#The sample code below matches version 1 (v = 1), but you can set it to 1 or 2. The second version is newer and contains a bit more data.asyncdefmain(uid,lang):r=starrailapi.StarRailApi(lang,v=2)data=awaitr.get_full_data(uid)print(data)asyncio.run(main(700649319,"en"))Usage example:fromhonkairailimportstarrailapiimportasyncioasyncdefmain(uid,lang):r=starrailapi.StarRailApi(lang)data=awaitr.get_full_data(uid)print("====Player====")print(f"Name:{data.player.name}")print(f"UID:{data.player.uid}")print(f"Level:{data.player.level}")print(f"World Level:{data.player.worldlevel}")print(f"Friends:{data.player.friends}")print(f"Pass Area Progress:{data.player.pass_area_progress}")print(f"Achievement:{data.player.achievement}")print(f"Characters:{data.player.characters}")print(f"Light Cone:{data.player.light_cone}")print(f"Icon:{data.player.icon}")print(f"Signature:{data.player.signature}")print('\n\n')print("====Characters====")forcharacterindata.characters:print(f"Name:{character.name}|{character.id}")print(f"Rarity:{'★'*character.rarity}")print(f"LVL:{character.level}")print(f"===={character.rank_text}====")forrankincharacter.rank_icons:print(f"Icon:{rank.icon}\nUnlock:{rank.unlock}")print("====Skill====")forskillincharacter.skill:print(f"Icon:{skill.icon}\nLVL:{skill.level}")print("=============")ifnotcharacter.light_coneisNone:print(f"Light Cone:{character.light_cone.name}")print(f"Rarity:{'★'*character.light_cone.rarity}")print(f"LVL:{character.light_cone.level}| R{character.light_cone.rank}")print(f"Icon:{character.light_cone.icon}")print(f"Portrait:{character.light_cone.portrait}")light_cone=awaitr.get_light_cone_info(character.light_cone)print(f"ATK:{light_cone.atk}| HP:{light_cone.hp}| DEF:{light_cone.defense}")print(f"Path:{light_cone.patch.name}\nImage:{light_cone.patch.url}")print("====Stats====")forpropertyincharacter.property:ifproperty.additionisNone:print(f"{property.name}:{property.base}\nIcon:{property.icon}")else:print(f"{property.name}:{property.base}({property.addition})\n==Icon:{property.icon}")print('\n\n')print("====Relic====")foriincharacter.relic:print(f"{character.relic[i].name}:{character.relic[i].level}lvl |{'★'*character.relic[i].rarity}")print(f"{character.relic[i].main_property.name}:{character.relic[i].main_property.value}")forsub_propertyincharacter.relic[i].sub_property:print(f"=={sub_property.name}:{sub_property.value}\n====Icon:{sub_property.icon}")print('\n')print("\n\n")asyncio.run(main(700649319,"en"))Languages SupportedLanguegeCodeLanguegeCodeLanguegeCodeEnglishenрусскийruChinesechsTiếng ViệtviไทยthTaiwancnportuguêspt한국어krdeutschde日本語jp中文zhespañoles中文zhIndonesianidfrançaisfrУкраїнськийua
Package: honkaistarrail
Asynchronous module for working with API Honkai: Star RailAt the moment it only supports counting guarantors and getting a jumpsInstallation:pip install honkaistarrailPyPi:OPENYou can also see other usage examples here:OPENInstructions for getting a link to the history of jumps:OPENID Banned:1- Event Banner2- Light Cone3- Standart BannerLaunc:# Copyright 2023 DEViantUa <t.me/deviant_ua># All rights reserved.'''This method returns the full history of jumps for thelast 3 months, does not return the results of jumpsand how much is left before the guarantor.'''importasynciofromhonkaistarrailimportstarrailasyncdefget_jump_history():link=""asyncwithstarrail.Jump(link=link,banner=1,lang="en")ashist:asyncforkeyinhist.get_history():forinfoinkey:print(f'[{info.type}] Name:{info.name}({info.rank}*) -{info.time.strftime("%d.%m.%Y %H:%M:%S")}')asyncio.run(get_jump_history())In developing:Automatic code redemption.Automatic collection of daily marks on HoYoLab.
Package: honorific
honorificДанный пакет позволяет изменять форму обращения к человеку.
С неформальной ("ты") на более уважительную ("Вы"), и наоборот.УстановкаУстановка пакетаpython-mpipinstallhonorificПри первом запуске скачается пакетru_core_news_lgдляspacy, но можно установить его заранееpython-mspacydownloadru_core_news_lgПример>>>honorific.honor("Как твои дела?")'Как ваши дела?'>>>honorific.honor("Так ты скажешь, откуда ты?")'Так вы скажете, откуда вы?'ОписаниеВ данный момент обрабатываютсяглаголыместоимениякраткие прилагательные и причастия(+модальные глаголы).TODOобработка глаголов в прошедшем времени в СППобработка сложных конструкций(пропуск пунктуации и т.д)обработка устойчивых выражений("ух ты" и т.д.)обработка возвратно-притяжательных местоименийМетрикиGold Standart - соответствие проф. разметке = 100%Adequacy - соответствие нормам русского языка = 94%Accuracy - правильность измененных словоформ = 100%
Package: honto
hontoHOmophilyNetworkTOolhontois a tool designed for assessing and measuring homophily in networks whose nodes have categorical attributes, namely when the nodes of networks come partitioned into classes.Homophily evaluation is performed through the comparison between the relative edge density of the subgraphs, induced by each class, and the corresponding expected relative edge density under a null model.The novelty of our approach consists in prescribing an endogenous null model, namely, the sample space of the null model is built on the input network itself. This allows us to give exact explicit expressions for the z-scores of the relative edge density of each class as well as other related statistics.InstallThe tool is available throughpipandconda.
Please, use one of the following commands to start working withhonto:# Install with pip
pip install honto

# Install with conda
conda install -c conda-forge hontoPlease note thathontois also available as a Galaxy tool. It's wrapper is available under the official Galaxy ToolShed athttps://toolshed.g2.bx.psu.edu/view/fabio/hontoUsageOnce installed, you can start runninghontoby specifying some arguments:honto --input_edges ~/edges.txt \
      --input_nodes ~/nodes.txt \
      --verboseList of standard arguments:--input_edges           -- Path to the file with the list of edges
--input_nodes           -- Path to the file with nodes and colors
--weight_threshold      -- Threshold for considering edges based in their weight
--isolated              -- Insert isolated nodes
--nproc                 -- Make the computation of the z-scores parallel for singletons
--overwrite             -- Overwrite results if already exist
--verbose               -- Print results in real time
-v, --version           -- Print current honto version and exitList of arguments for log-transforming z-scores:--log_transform     -- Log-transform z-scores
--scale_factor      -- Rescale z-scores with this constant before log-transforming values
--scale_from_one    -- Set z-scores to 1 if lower than 1 before log-transforming valuesList of arguments for customizing the heatmap--cmap      -- Heatmap colormap
--vmin      -- Min value to anchor the colormap
--vmax      -- Max value to anchor the colormap
--center    -- The value at which to center the colormap when plotting divergant data
--cbar      -- Whether to draw a colorbarCreditsPlease credit our work in your manuscript by citing:Manuscript in preparationNicola Apollonio, Paolo G Franciosa, and Daniele Santoni.A novel method for assessing and measuring homophily in networks through
second-order statistics. Scientific reports, 12(1):1–18, 2022,https://doi.org/10.1038/s41598-022-12710-7ContributingLong-term discussion and bug reports are maintained via GitHub Issues, while code review is managed via GitHub Pull Requests.Please, (i) be sure that there are no existing issues/PR concerning the same bug or improvement before opening a new issue/PR; (ii) write a clear and concise description of what the bug/PR is about; (iii) specifying the list of steps to reproduce the behavior in addition to versions and other technical details is highly recommended.
Package: honyx
HONyxHONyx is a Python package for generating and analyzing Higher-Order Networks modelsSource:https://gitlab.univ-nantes.fr/queyroi-f/honyxBug reports:https://gitlab.univ-nantes.fr/queyroi-f/honyx/-/issuesUsage>>>importhonyx>>>importnetworkxasnx>>>sequences=[['a','b','r','a','c','a','d','a','b','r','a']]>>>fon2=honyx.generate_hon(sequences,"fix-order",max_order=2)>>>pos=nx.spring_layout(fon2)>>>node_cols=['blue'iflen(v)==1else'green'forvinfon2.nodes()]>>>nx.draw(fon2,pos=pos,with_labels=True,node_size=1000,node_color=node_cols,alpha=0.5)>>>nx.draw_networkx_edge_labels(fon2,pos,edge_labels=nx.get_edge_attributes(fon2,'weight'))>>>honyx.pagerank_hon(fon2){'a':0.40849881734049087,'d':0.14318783763461537,'c':0.1478373488011564,'r':0.15427265837422358,'b':0.14620333784951386}CitingTo cite HONyx, please use the following publication:Julie Queiros, François Queyroi (2023). 
Construction de Réseaux d'Ordre Supérieur à partir de Traces : Méthodes et Outils. 
https://hal.science/hal-04085138PDFBibTeXInstallUsing  Python 3.8, 3.9, or 3.10.Install the latest version of HONyx:$ pip install honyxRequired dependancies includeNetworkX,NumpyandScipy.LicenseReleased under the MIT license (seeLICENSE.txt)::Copyright (C) 2004-2023 HONyx Developers
Julie Queiros <julie.queiros@univ-nantes.fr>
François Queyroi <francois.queyroi@univ-nantes.fr>
Simon Artus <simon.artus@etu.univ-nantes.fr>
Package: hoocron
hoocronHoocron is cron alternative with different hooks to trigger immediate execution of jobsInstallationpip3 install hoocronUsage examplesSimple cronWe will run 'echo' with arguments.Simplest case:$hoocron.py-jTICKecho...tick-tock...-pTICK10s
startedcronthreadwith1jobs:TICK
runTICKfromcron
...tick-tock...
ReturncodeforTICK:0runTICKfromcron
...tick-tock...
ReturncodeforTICK:0This command configuresjob(what to run, command and arguments) andhook(when to run). This very similar to cron. Here we have job named 'TICK' which runsecho ...tick-tock...and configured cron period (-p) for job TICK to 10 seconds.We can run many jobs at once, lets add another echo$hoocron.py-jEcho5echotick-tock5seconds-jEcho10echotick-tock10seconds-pEcho55-pEcho1010### immediately, 0s from startrunEcho5fromcron
runEcho10fromcron
tick-tock5seconds
tick-tock10seconds
ReturncodeforEcho5:0ReturncodeforEcho10:0### 5s from startrunEcho5fromcron
tick-tock5seconds
ReturncodeforEcho5:0### 10s from startrunEcho5fromcron
runEcho10fromcron
tick-tock5seconds
tick-tock10seconds
...Webhook HTTP triggerHTTP plugin provides HTTP GET and HTTP POST interface to start cron job right now.Now, lets make it more interesting, we will also run job if get HTTP request using--http-getoption (or just--get).$hoocron.py-jJ/bin/touch/tmp/touch-pJ5m--getJ
Loadinghoocron_plugin.cron
Loadinghoocron_plugin.http
Loadinghoocron_plugin.redis
startedcronthreadwith1jobs:J
startedhttpthreadon:5152with1jobs:J
runJfromcron
ReturncodeforJ:0Hoocron immediately runs Job (because cron plugin runs each job for first time right from start) and waits 5 minutes for next run. We do not want this, so we do:$curlhttp://localhost:5152/J
OKThis triggers hoocron execution of job J:run J from HTTP GET request from 127.0.0.1
Return code for J: 0Cron with HTTP POST methodIf you want to use HTTP POST method, use--post(or--http-postalias) instead of--get.Running hoocron with http in productionIf you need extra HTTP features, such as https support or additional access control, run hoocron behind real webserver working as reverse proxy.Throttling and policiesHoocron guarantees that only one copy of job (with same job name) is running at same time (same jobs will not overlap): hoocron will never start second copy of same job until first one is finished.But hoocron can not prevent same script started from any other source (e.g. from shell).There are two policies for job,ignore(default) andasap.With policyignore, if hoocron gets request to start job, and this job is already running, request is ignored.With policyasap, if hoocron gets request to start job, and this job is already running, it will set special flag and will run same job again immediately after first instance of job is finished (and again, new request will raise flag again). Note, if there are many requests during one execution of job, it will be executed just once.To see difference, compare ignore policy (default) with this command:hoocron.py-jJsleep10-pJ3and same withasappolicyhoocron.py-jJsleep10-pJ3--policyJasapSee alsoRedis plugin
Package: hoocron-plugin-redis
hoocron-plugin-redisRedis support forHoocron. Hoocron is cron with hooks.Installationpip3 install hoocron-plugin-redisExample simple usageStart hoocron with redis plugin, configure--redis:$ hoocron.py --redis TICK

Loading hoocron_plugin.cron
Loading hoocron_plugin.http
Loading hoocron_plugin.redis
connect to redis over network: localhost:6379
started redis thread, watch list 'hook'Now send hook name to list 'hook' (we will use redis-cli for this):127.0.0.1:6379> LPUSH hook TICK
(integer) 1hoocron will run jobTICKin less then 1 second (default sleep period)Other options--redis JOB [JOB ...]
                        Jobs to bind with redis hook
  --redis-url REDIS_URL Path to redis def: redis://localhost:6379/0
  --redis-list KEY      name of redis key to trigger jobs. def: hook--redis-urlcould be set from environment variableREDIS_URL
Package: hoocron-plugin-websocket
hoocron-plugin-websocketWebsocket client plugin for HoocronInstallpip3 install hoocron-plugin-websocketUsage$ hoocron.py --ws TICK --wsroom myapps::u1 --wsurl http://localhost:8899/ --wssecret myapps-pass
...
started websocket thread, watch room 'myapps::u1' on http://localhost:8899/
Websocket connected to http://localhost:8899/

run TICK from websocket
Tick! (uptime: 6 seconds)
Result(TICK): tickedServer-sideRedisSET ws-emit::secret::myapps myapps-passws-emitws-emit.py -a 0.0.0.0:8899 --cors '*' --secret 123curlcurl -d @/tmp/x.json -H "Content-Type: application/json" -X POST http://localhost:8899/emit/tmp/x.json:{
	"event": "update",
	"room": "myapps::u1",
	"data": "TICK",
	"namespace": null,
	"secret": "123"
}See alsohoocron: cron with hooksws-emit: emit websocket messages from any source, even from CLI with curl
Package: hoocs
Higher Order OCclusion (hoocs)IntroductionHoocs implements a broad range of model-agnostic attributionsPredDiff[1][2]Shapley values[3]KernelSHAP[4]Recently, there has been increasing interest in more in-depth analysis of models. To meet this needs, the analysis of
feature interactions is inevitable. Therefore, this package allows to calculate arbitrary higher-order explanations.
Tt is extendable to other methods, which rely on marginalizing features in input space.Installationpip install hoocsImplement new imputersTo enable reliable attributions, hooks enables simple incorporation of customimputersfor any kind of data modality.
To add a new imputer, the user is requested to inherent from the abstract baseImputerclass inhoocs.imputers.abstract_imputers.py.
This class performs basic type checking and ensures a consistent interface.References[1]Explaining classifications for individual instances.[2]PredDiff: Explanations and interactions from conditional expectations[3]An efficient explanation of individual classifications using game theory[4]A Unified Approach to Interpreting Model Predictions
Package: hoodat-vertex-components
Hoodat Pipeline ComponentsThis repository provides an SDK and a set of components that perform
tasks in hoodat.It is modelled after this repository of shared components for GCP:https://github.com/kubeflow/pipelines/tree/google-cloud-pipeline-components-1.0.1/components/google-cloudTo create new release of package and push to pypi:Update the version with commitizen:# cz bump --dry-runczbumpPush to main branchgitpushCreate a new release in github.The package will be built and pushed to pypi in a github action.## MakefileThere is a Makefile at the root of this project which provides some
useful functionality for developing and publishing components. In the
next sections of this document some of this funcitonality will be
described.Important to the use of the Makefile is the creation of anenv.shfile with necessary arguments populated. Seeenv.sh.examplefor an
example of what this file should look like. Copy it toenv.shand
replace the default arguments with your own.To create a new component with your own DockerfileNew components should be added to thehoodat_vertex_components/componentssubdirectory. See already existing
examples. Here is a common file structure for a component:├── make_cascade_file
│   ├── Dockerfile
│   ├── cascades.csv
│   ├── component.yaml
│   ├── make_cascade_file.py
│   ├── poetry.lock
│   ├── pyproject.toml
│   └── tests
│       └── test_filter_cascades.pyTo run a components docker container in interactive modeThis function will be useful for running a components docker image
interactively. Update theenv.shwith the name of the component and
run:makerun_interactiveTo run a pipeline with a single component in itIt may be useful to test a component in a pipeline. To do this, update
theenv.shwith the name of the component and run:makepush_and_pipelineTo create a new python componentLook at video_to_frames for an example.Once you're happy, run:COMPONENT_NAME=video_to_framescdhoodat_vertex_components/components/$COMPONENT_NAMEpoetryrunpythoncomponent.py
Package: hoodex
hoodexHoodex checks your plex instance and get the url of the latest uploaded contentFree software: Apache Software License 2.0Documentation:https://hoodex.readthedocs.io.InstallInstall using pip from pypi:pipinstallhoodexUsageYou can set your variables via argument when running hoodex or via config file.With Arguments:hoodex--usermy_user--passwordmy_password--servermy_server--librariesMovies,TVWith a config file:hoodex--configconfig.iniConfigYou can create a ini config file with the following content:[hoodex]PlexUserName=your_userPlexPassword=your_passwordPlexServer=your_serverPlexLibraries=Movies,TVFeaturesConnect to your Plex Server and get the last added elements of a list of librariesHistory0.1.0 (2019-05-25)First release on PyPI.