Saravanan666/pypi-org huggingface dataset:
Package: rpunct
✏️ rpunct - Restore PunctuationThis repo contains code for Punctuation restoration.This package is intended for direct use as a punctuation restoration model for the general English language. Alternatively, you can use this for further fine-tuning on domain-specific texts for punctuation restoration tasks.
It uses HuggingFace'sbert-base-uncasedmodel weights that have been fine-tuned for Punctuation restoration.Punctuation restoration works on arbitrarily large text.
And uses GPU if it's available otherwise will default to CPU.List of punctuations we restore:Upper-casingPeriod:.Exclamation:!Question Mark:?Comma:,Colon::Semi-colon:;Apostrophe:'Dash:-🚀 UsageBelow is a quick way to get up and running with the model.First, install the package.pipinstallrpunctSample python code.fromrpunctimportRestorePuncts# The default language is 'english'rpunct=RestorePuncts()rpunct.punctuate("""in 2018 cornell researchers built a high-powered detector that in combination with an algorithm-driven process called ptychography set a world recordby tripling the resolution of a state-of-the-art electron microscope as successful as it was that approach had a weakness it only worked with ultrathin samples that werea few atoms thick anything thicker would cause the electrons to scatter in ways that could not be disentangled now a team again led by david muller the samuel b eckertprofessor of engineering has bested its own record by a factor of two with an electron microscope pixel array detector empad that incorporates even more sophisticated3d reconstruction algorithms the resolution is so fine-tuned the only blurring that remains is the thermal jiggling of the atoms themselves""")# Outputs the following:# In 2018, Cornell researchers built a high-powered detector that, in combination with an algorithm-driven process called Ptychography, set a world record by tripling the# resolution of a state-of-the-art electron microscope. As successful as it was, that approach had a weakness. It only worked with ultrathin samples that were a few atoms# thick. Anything thicker would cause the electrons to scatter in ways that could not be disentangled. Now, a team again led by David Muller, the Samuel B.# Eckert Professor of Engineering, has bested its own record by a factor of two with an Electron microscope pixel array detector empad that incorporates even more# sophisticated 3d reconstruction algorithms. The resolution is so fine-tuned the only blurring that remains is the thermal jiggling of the atoms themselves.🎯 AccuracyHere is the number of product reviews we used for finetuning the model:LanguageNumber of text samplesEnglish560,000We found the best convergence around3 epochs, which is what presented here and available via a download.The fine-tuned model obtained the following accuracy on 45,990 held-out text samples:AccuracyOverall F1Eval Support91%90%45,990💻🎯 Further Fine-TuningTo start fine-tuning or training please look intotraining/train.pyfile.
Runningpython training/train.pywill replicate the results of this model.☕ ContactContactDaulet Nurmanbetovfor questions, feedback and/or requests for similar models.
Package: rputils
This is a roleplay utilities program written in python with a qt user interface.How To UseIf you find any issues with it there is a bug tracker [here](https://bitbucket.org/davidcorne/roleplay-utility/issues?)FeaturesIt has D3, D4, D6, D8, D10, D12, D20 and D100 as standard.The ability to add new dice.It can show probability distribution of the dice.Keeps a history of dice rolls.Can read PDFs.ToDoMake PDF reader better.Make add dice work properly.
Package: rpvm
Restricted Python Virtual MachineRestricted Python Virtual Machine (R-PVM) implemented by pure python.specificationaim for complete safe sandboxdesigned for Python3.6 bytecodeexecute one by onegood for smart contract of crypto currencyNo warranty and unstablecheckcannot use MAKE_FUNCTION op (lambda, comprehension and inner fnc)cannot use async/awaitlimit to execute functionYOU must select safe functionInstallpip3 install rpvmHow to usefromrpvm.vmimportVirtualMachinefromRestrictedPythonimportsafe_builtins,safe_globalssource="""a = 1b = 2c = a + b"""code=compile(source,'<example>','exec')b=safe_builtins.copy()l=dict()g=safe_globals.copy()vm=VirtualMachine(code,b,l,g)steps=0max_steps=500whilenotvm.finishandsteps<max_steps:vm.exec()steps+=1print("complete?",vm.finish)print("result",vm.return_value)print("c is",l['c'])testpython3-mpytesttestsAuthor@namuyan_mine
Package: rpvVoterIndex
Voter Power IndexesVote Power Index provides tools to run both Banzhaf Power Index and Shapley–Shubik Index to analyse 2 party poltical geographies like US Congresstional Districts to see if the reapproation process maintained Mintorities communties to elect their candidate of choiceUsagepower_index(df, OtherPopCol, TargetPopCol, Party1, Party2, vIndex=None, filename=None)Parametersdf - Pandas DataframeOtherPopCol - Majority communityTargetPopCol - Minority communityOtherParty - None colitlition party of choiceColilitionParty - Colitlition party of choicevIndex (ssi/bpi/none):Noneboth indexesssiShapley–Shubik IndexbpiBanzhaf Power Indefilename - optional
Package: rpwd
Rename Photos With Date背景文件的排序方式 通常只有【创建时间、修改时间、标题】，但问题是：照片的标题通常是无效的（固定前缀+编号，甚至是无意义字符串）时间也是不准的（创建时间、修改时间  其实与照片的拍摄时间 是不一致的），所以就需要基于现有排序方式  修改相关信息，以便能够已正确的排序显示因此，我就写了这个工具：读取照片的拍摄时间，将其重命名，以便【在以标题排序显示时  是符合预期的】为了避免命名重复，所以命名规则为「年月日时分秒+3位随机数，共15位数字」，示例如下：202204062217.699.png201601011713.247.JPG201602251612.551.JPG201712311343.878.JPG202204041615.719.HEIC202204041615.813.HEIC202204041710.478.HEIC202204041710.595.JPG202204041710.749.HEIC202204041710.750.HEIC安装可通过如下命令 快速安装：$pipinstallrpwd使用查看说明$rpwd-h
usage:rpwd[-h][-d][-v][-l]path

RenamePhotosWithDate

positionalarguments:path待重命名的「文件/目录」的路径

optionalarguments:-h,--helpshowthishelpmessageandexit-d,--debug启用调试模式-v,--verbose显示详细日志-l,--list仅列表显示可能的处理，但不执行具体操作，以便检查查看将要执行的操作$rpwd./photos-l或是指定-v以查看很多信息：$rpwd./photos-lv执行重命名# 可追加 -v、-d 以启用详情、调试模式，以查看更多信息$rpwd./photos
Package: rpweibo
rpweibo=======cURL + Python Weibo Wrapper.## Installing```bashsudo python3 setup.py install```## Usage### Initialize```pythonimport rpweiboexample_app = rpweibo.Application(APP_KEY, APP_SECRET, REDIRECT_URI)weibo = rpweibo.Weibo(example_app)```### Authorize#### with Username and Password```pythonauthenticator = rpweibo.UserPassAutheticator(USERNAME, PASSWORD)try:weibo.auth(authenticator)except rpweibo.AuthorizeFailed:print("Invalid username or password!")```#### with Existing Access Token```pythonauthenticator = rpweibo.AccessTokenAuthenticator(ACCESS_TOKEN)weibo.auth(authenticator)```### Using API#### Styles##### Procedural Style```pythontweets = weibo.get("statuses/user_timeline")["statuses"]for tweet in tweets:print(tweet["text"])weibo.post("statuses/update", status="Hello, world!")```##### Object Style```pythontweets = weibo.api("statuses/user_timeline").get().statusesfor tweet in tweets:print(tweet.text)weibo.api("statuses/update").post(status="Hello, world!")```### Error Handling```pythontry:tweets = weibo.api("statuses/user_timeline").get().statusesexcept rpweibo.RemoteError:# handle API errors likely cause by remote serverprint("Something wrong with the server")except rpweibo.CallerError:# handle API errors likely cause by the clientprint("You shouldn't use the API in this way")except rpweibo.ResultCorrupted:print("Request the API successfully, but got the corrupted result")except rpweibo.NetworkError:print("Somethings wrong with your network")except rpweibo.APIError as e:# Handle all API errors, including RemoteError and CallerError.# NOTE: we handle both two type of API errors already, never reach hereprint("%d - %s" % (e.error_code, e.error_message))```
Package: rpy2
Python -> R bridgeThe project's webpage is here:https://rpy2.github.io/Installationpipshould work out of the box:pipinstallrpy2The package has optional depencies providing
specific functionalities not otherwise required to use the rest of rpy2.For example, to be able to run the unit tests:pipinstallrpy2[test]To install all optional dependencies (numpy, pandas, ipython), use:pipinstallrpy2[all]The package is known to compile on Linux, MacOSX
(provided that developper tools are installed, and you are ready
figure out how by yourself). The situation is currently a little
more complicated on Windows. Check the issue tracker.In case you find yourself with this source without any idea
of what it takes to compile anything on your platform, try firstpythonsetup.pyinstallIssues loading shared C librariesWhenever R is in not installed in a system location, the system might not
know where to find the R shared library.IfRis in thePATH, that is enteringRon the command line successfully starts
an R terminal, but rpy2 does not work because of missing C libraries, try the following
before starting Python:exportLD_LIBRARY_PATH="$(python-mrpy2.situationLD_LIBRARY_PATH)":${LD_LIBRARY_PATH}DocumentationDocumentation is available either in the source tree (doc/),
oronline.Testingrpy2usespytest, with the pluginpytest-covfor code coverage. To
test the package from the source tree, either to check and installation
on your system or before submitting a pull request, do:pytesttests/For code coverage, do:pytest--cov=rpy2.rinterface_lib\--cov=rpy2.rinterface\--cov=rpy2.ipython\--cov=rpy2.robject\testsFor more options, such as how to run specify tests, please refer to thepytestdocumentation.LicenseRPy2 can be used under the terms of the GNU
General Public License Version 2 or later (see the file
gpl-2.0.txt). This is the very same license R itself is released under.
Package: rpy2-r6
rpy2-r6Extension package forrpy2to faciliate
the handling of R6 objects (R6 is an OOP system for R).(an earlier proof-of-concept was in @matthewwardrop's PR on bitbucket -https://bitbucket.org/rpy2/rpy2/pull-requests/73- and this is a proposed-yet-currently incomplete evolution of it)An HTML build of the documention in is available from the rpy2 project pages:https://rpy2.github.io/r6_doc.html
Package: rpyc
RPyC(pronounced likeare-pie-see), orRemote Python Call, is atransparentlibrary forsymmetricalremote procedure calls,clustering, anddistributed-computing.  RPyC makes use ofobject-proxying,
a technique that employs python’s dynamic nature, to overcome the physical
boundaries between processes and computers, so that remote objects can be
manipulated as if they were local.Documentation can be found athttps://rpyc.readthedocs.ioA screenshot of a Windows client connecting to a Linux server.Note that text written to the server’sstdoutis actually printed on
the server’s console.
Package: rpycdec
rpycdecA tools for decompiling and translating Ren'py compiled script files (.rpyc and .rpymc).How it worksAll rpyc files are compiled from rpy files, renpy SDK read every file and parse it to AST object(renpy), and then use pickle to serialize the AST to rpyc file. So we use pickle to deserialize the rpyc file to AST, and then restore the rpy file from AST.We created a fake "renpy" package(unlikely unrpyc) and it's ast objects to make the pickle can be deserialized correctly.
Another reason to create a fake "renpy" package is that we can separate code generate logic (theget_code(...)function) to each AST object, it will be easier to future maintain and for multi-version renpy support.The most difficult part is generating the rpy file from AST. Different renpy version has different AST structure also different grammar.UsageInstall with pip:pipinstallrpycdecor install from source after clone this repo:pipinstall.Decompile a file or directory:rpycdec[--force]<pathtorpycfileordir>Decompile and translate a file or directory:rpycdec--translate<pathtorpycfileordir>Library usageimportrpycdecrpycdec.decompile(filename)DevelopmentUse pipenv to manage dependencies:pipenvinstall--devContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.FAQQ: It always raise pickleimport ** \nModuleNotFoundError: No module named '***'error.A: It's because the our fake packages("renpy","store") is not contains the object you want to decompile. Please open an issue and tell us the renpy version and the rpyc file you want to decompile. Join our telegram group to get help also be better.CommunityWelcome to join our community to discuss and get help.Telegram Group
Package: rpycocotools
rpycocotoolsTherpycocotoolspackage provides tools to load, manipulate, convert and visualize COCO format datasets. The documentation is availablehere.InstallationThe package is available on PyPIhere, and can installed with pip:pip install rpycocotoolsYou can also git clone this repo and build it yourself with:pip install -r requirements/requirements-build.txt
pip install .Usage exampleVisualize image with a givenid:importrpycocotoolscoco_dataset=rpycocotools.COCO("../data_samples/coco_25k/annotations.json","../data_samples/coco_25k/images")coco_dataset.visualize_img(174482)importrpycocotoolscoco_dataset=rpycocotools.COCO("../data_samples/coco_25k/annotations.json","../data_samples/coco_25k/images")anns=coco_dataset.get_img_anns(174482)mask=rpycocotools.mask.decode(anns[0].segmentation)The mask is a numpy array and can be visualized (for example with opencv):BenchmarksDetailsThere are a few benchmarking scripts to compare topycocotools.The results reported here are done on my own PC and presented only to get a general idea. I might run the benchmark on a more reproducible environment in the future.SetupSome of the benchmarks use theinstances_train2017.jsonfiles from the 2017 COCO dataset.Either place this file in thedata_samplesfolder or only run the commands below with the-m "not coco2017"option.pipinstall-rrequirements/requirements-benchmarks.txt
pipinstall.LoadBenchmark how much time it takes load a COCO dataset.python-mpytestbenchmarks/load.py-vvResults:Test NameMean time in srpycocotools on COCOinstances_train2017.json4.4pycocotools on COCOinstances_train2017.json16.5AreaBenchmark how much time it takes to compute the total number of mask pixels in a COCO dataset.python-mpytestbenchmarks/area.py-vv-mcoco2017Results:Test NameMean time in msrpycocotools on COCOinstances_train2017.json880.6pycocotools on COCOinstances_train2017.json19,302.9Decode masksBenchmark how much time it takes to decode all the masks in a COCO dataset.python-mpytestbenchmarks/decode.py-vv-mcoco2017Results:Test NameMean time in srpycocotools on COCOinstances_train2017.json371pycocotools on COCOinstances_train2017.json141Results after converting all the segmentations to RLE before decoding (conversion time not included):Test NameMean time in srpycocotools on COCOinstances_train2017.json300pycocotools on COCOinstances_train2017.json120
Package: rpy-symmetry
Rpy_symmetryLight weight bridge fromRtopythonof thesymmetryR-module.By default, the Symmetry test uses the one from:Mira A (1999) Distribution-free test for symmetry based on Bonferroni's measure. J Appl Stat 26(8):959–972. https://doi.org/10.1080/02664769921963Installation \ RequirementsRneeds to be, for example using condaconda install -c conda-forge r-baseor mamba:mamba install -c conda-forge r-baseThen, one can simply install using pipy:pip install rpy_symmetryThe python interface is built onrpy2, which will be automatically be installed as one of the requirements.ExamplesSee example notebook
Package: rpython
RPython is a translation and support framework for producing implementations of
dynamic languages, emphasizing a clean separation between language
specification and implementation aspects.By separating concerns in this way, it can automatically generate a
Just-in-Time compiler for any dynamic language. It also allows a mix-and-match
approach to implementation decisions, including many that have historically
been outside of a user’s control, such as target platform, memory and threading
models, garbage collection strategies, and optimizations applied, including
whether or not to have a JIT in the first place.LinksDocumentationBug trackerPyPy projectMailing list:pypy-dev@python.orgWarningThis is an experimental release of a randomly chosen, untested version of
RPython. Packaging issues are likely, feedback is welcome.
Package: rpze
rpzeRemote Python, Zombie Endless(or endless rp?)一个远程Python的Plants vs. Zombies TAS及ize测试框架.主库位于GitHub.结构总体分成五个包:rp_extend: 对控制pvz游戏本地运作的基本操作的封装basic: DLL注入, 游戏启动, 汇编代码等基础功能structs: PvZ内数据结构以及部分method的的封装flow: coroutine-like测试编写相关的函数, 和以此实现的IzTest测试功能examples: 上述的测试功能的编写例子其中, 若仅对Python的pvz框架感兴趣则只需关注前三个包, 对ize测试感兴趣则着重模仿examples并大致了解structs的成员(Plants和Zombies).例子生物钟一个生物钟一二路卡相位的例子.fromrpze.basicimportInjectedGamefromrpze.flowimport*withInjectedGame(r"your\game\path")asgame:game.enter_level(70)# 打开编号为70的关卡, 即ize关卡iz_test=IzTest(game.controller).init_by_str('''1000 -11-2zs_j5cptoh...............lz02-6''')# 大家熟悉的izt测试@iz_test.flow_factory.add_flow()asyncdefplace_zombie(_):plist=iz_test.game_board.plant_listflower=plist["2-5"]awaituntil(lambda_:flower.hp<=4)place("cg 2-6")# 2-5花死前一瞬放撑杆star=plist["1-5"]# 1-5杨桃awaituntil_plant_last_shoot(star).after(151-96)awaitrepeat("xg 1-6")# 星星最后一发攻击发出后1双鬼iz_test.start_test(jump_frame=False,speed_rate=5)从有@的那句话开始一句一句看下去:@iz_test.flow_factory.add_flow(): 一句格式代码, 作用是让测试时执行你下面定义的place_zombie. 抄下来就行.async def place_zombie(_): 同样是格式代码.此处, 可以认为async def定义一个非常类似于函数的place_zombie,
这个类似函数的东西接受一个FlowManager类型的参数(在大部分场合用不到, 这里用_表示我用不到)不能不写async!place_zombie一定要是有且仅有一个参数的函数!plist = iz_test.game_board.plant_list:game_board是游戏中当前运行的关卡界面的代名词, 关卡上的所有植物, 僵尸, 你的大多操作都通过透过它进行.plant_list是游戏中存放植物对象的数组, 其中有当前对象数量, 最大数量等等信息.plant_list类型为PlantList, 继承于ObjList[Plant], 提供了使用[int | slice]索引,~plist遍历等功能.flower = plist["2-5"]:[f"{row}-{col}"]是PlantList特有的方法, 获取在1-1的植物.await until(lambda _: flower.hp <= 4): 意为等待2-5花的血量 $\leq$ 4时往下执行.简单的说, 只需要写await until(lambda _: 你希望满足xx条件时再往下执行)即可.具体格式为await until(FlowManager -> bool). 和上面的place_zombie一样, 这里忽略FlowManager参数.place("cg 2-6"): 在2-6放撑杆, 非常简单.  这个函数会返回你刚放下来的僵尸, 有需要的话可以用await until_plant_last_shoot(star).after(151 - 96): 在星星最后一次攻击结束后再过(151 - 96)帧往下执行until_plant_last_shoot(plant): 卡相位函数. 相当于until(lambda _: plant攻击后第一次打不出子弹)until(...).after(time)指等到前面的条件后再过time帧再往下执行.await repeat("xg 1-6")1-6双小鬼.repeat代表连放僵尸, 默认delay20放两个(大家都是这么做的!), 如想delay30放三个则是repeat("xg 1-6", 2, 30)await必须有. 直观理解, 这里前面有await的理由是repeat函数要等放完了才能往后执行.
Package: rpzip
rpzip — a CLI backed by repro-zipfileA lightweight command-line program for creating reproducible/deterministic ZIP archives."Reproducible" or "deterministic" in this context means that the binary content of the ZIP archive is identical if you add files with identical binary content in the same order. It means you can reliably check equality of the contents of two ZIP archives by simply comparing checksums of the archive using a hash function like MD5 or SHA-256.This package provides a command-line program namedrpzip. It is designed as a partial drop-in replacement for the ubiquitouszipprogram and implements a commonly used subset of zip's inferface.For further documentation, see the"rpzip command line program"section of the repro-zipfile README.
Package: rpz-manager
rpz-managerBlock ads and malicious domains with response policy zones.FromWikipedia:A response policy zone (RPZ) is a mechanism to introduce a customized
policy in Domain Name System servers, so that recursive resolvers
return possibly modified results. By modifying a result, access to the
corresponding host can be blocked.This program allows you to build and maintain RPZ zones from domain
blocklist feeds. The resulting zones can be used withISC bind(and other compatible
DNS servers).rpz-manager is easy to deploy. Just copy it to your PATH. Optionally
write a config file, set up logging, or use a cron job to keep your
zone fresh.Before you StartMake sure to understand DNS RPZ before using this tool. These sites
provide great documentation:https://www.dnsrpz.infoConfiguring a DNS firewall with RPZResponse Policy Zone ConfigurationAt minimum, you must create anew zone clausefor RPZ and mention that zone in aresponse-policy statement.How to InstallRun the following as root.# Download rpz-managercurl-Sshttps://raw.githubusercontent.com/stevekroh/rpz-manager/version-0.x/rpz_manager.py\-o/usr/local/bin/rpz-manager# Set the executable bitchmod755/usr/local/bin/rpz-managerAlternatively, create a virtualenv and run pip install rpz-manager.Quick Start# View the help screenrpz-manager--help# Write, then review /etc/rpz-manager.inirpz-manager--init# Optionally set up loggingcurl-Sshttps://raw.githubusercontent.com/stevekroh/rpz-manager/version-0.x/config/rpz-loggers.ini\-o/etc/rpz-loggers.ini# Download block lists then write an RPZ zone filerpz-managerAutomate with AnsibleAdd the following to your role or playbook.# Customize rpz-manager.ini and save it under files-name:upload rpz-manager.inicopy:src:files/rpz-manager.inidest:/etc/rpz-manager.iniowner:rootgroup:rootmode:'u=rw,g=r,o=r'# Customize rpz-loggers.ini and save it under files-name:upload rpz-loggers.inicopy:src:files/rpz-loggers.inidest:/etc/rpz-loggers.iniowner:rootgroup:rootmode:'u=rw,g=r,o=r'# rpz-manager will be updated to the latest version when force=yes-name:download rpz-managerget_url:url:https://raw.githubusercontent.com/stevekroh/rpz-manager/version-0.x/rpz_manager.pydest:/usr/local/bin/rpz-managerforce:yesowner:rootgroup:rootmode:'u=rwx,g=rx,o=rx'# Use a cron job to keep your zone fresh-name:run rpz-manager dailycron:name:rpz-managerspecial_time:dailyjob:/usr/local/bin/rpz-manageruser:rootRun Without RootIt is possible to run rpz-manager without root permissions, though you must
be sure to update all relevant settings pertaining to the user.For example:# Create an administrator belonging to the named groupuseradd-m-Gnamedadmin# Create the user cache directorymkdir-p/home/admin/.cache# Run rpz-managerrpz-manager-orpz.example.com.-z/var/named/rpz.example.com.zone\-uadmin-gnamed-d/home/admin/.cacheInspired byTrellmor/bind-adblock.
Package: rq
RQ (Redis Queue) is a simple Python library for queueing jobs and processing
them in the background with workers.  It is backed by Redis and it is designed
to have a low barrier to entry.  It should be integrated in your web stack
easily.RQ requires Redis >= 3.0.0.Full documentation can be foundhere.Support RQIf you find RQ useful, please consider supporting this project viaTidelift.Getting startedFirst, run a Redis server, of course:$redis-serverTo put jobs on queues, you don't have to do anything special, just define
your typically lengthy or blocking function:importrequestsdefcount_words_at_url(url):"""Just an example function that's called async."""resp=requests.get(url)returnlen(resp.text.split())You do use the excellentrequestspackage, don't you?Then, create an RQ queue:fromredisimportRedisfromrqimportQueuequeue=Queue(connection=Redis())And enqueue the function call:frommy_moduleimportcount_words_at_urljob=queue.enqueue(count_words_at_url,'http://nvie.com')Scheduling jobs are also similarly easy:# Schedule job to run at 9:15, October 10thjob=queue.enqueue_at(datetime(2019,10,10,9,15),say_hello)# Schedule job to run in 10 secondsjob=queue.enqueue_in(timedelta(seconds=10),say_hello)Retrying failed jobs is also supported:fromrqimportRetry# Retry up to 3 times, failed job will be requeued immediatelyqueue.enqueue(say_hello,retry=Retry(max=3))# Retry up to 3 times, with configurable intervals between retriesqueue.enqueue(say_hello,retry=Retry(max=3,interval=[10,30,60]))For a more complete example, refer to thedocs.  But this is the essence.The workerTo start executing enqueued function calls in the background, start a worker
from your project's directory:$rqworker--with-scheduler*** Listening for work on defaultGot count_words_at_url('http://nvie.com') from defaultJob result = 818*** Listening for work on defaultThat's about it.InstallationSimply use the following command to install the latest released version:pip install rqIf you want the cutting edge version (that may well be broken), use this:pip install git+https://github.com/rq/rq.git@master#egg=rqRelated ProjectsCheck out these below repos which might be useful in your rq based project.rq-dashboardrqmonitordjango-rqFlask-RQ2rq-schedulerProject historyThis project has been inspired by the good parts ofCelery,Resqueandthis snippet, and has been created as a lightweight alternative to the
heaviness of Celery or other AMQP-based queueing implementations.