Saravanan666/pypi-org huggingface dataset:
Package: rlupat.toyrobot
Toy Robot SimulationOverviewThe application is a simulation of a toy robot moving on a square table top, of dimensions 5 units x 5 units.
There are no other obstructions on the table surface.
The robot is free to roam around the surface of the table, but will be prevented from falling to destruction.
Any movement that would result in the robot falling from the table will be ignored,
however further valid movement commands will still be allowed.Valid CommandsThe console applications can read in commands in the following form:PLACE X,Y,FMOVELEFTRIGHTREPORTPLACEwill put the toy robot on the table in positionX,Yand facingNORTH,SOUTH,EASTorWEST.The origin (0,0) can be considered to be the SOUTH WEST most corner.It is required that the first command to the robot is aPLACEcommand, after that,
any sequence of commands may be issued, in any order, including anotherPLACEcommand.The application will discard all commands in the sequence until a validPLACEcommand has been executed.MOVEwill move the toy robot one unit forward in the direction it is currently facing.LEFTandRIGHTwill rotate the robot 90 degrees in the specified direction without changing the position of the robot.REPORTwill announce the X,Y and F of the robot to stdout.ConstraintsA robot that is not on the table will ignore theMOVE,LEFT,RIGHTandREPORTcommands.Toy robot can not fall off the table during movement. This also includes the initial placement of the toy robot.
Any move that cause the above will be ignored.Example of Valid CommandsPLACE 1,2,EAST
MOVE
MOVE
LEFT
MOVE
REPORTInstallationRequirementsPython version 3.6 / 3.7 / 3.8 / 3.9.Option 1: From PyPiSetup virtual environmentpython3 -m venv toyrobot-envActivate virtual environmentsource toyrobot-env/bin/activateInstall source-codepip install rlupat.toyrobotOption 2: From sourceClone this github repositorySetup virtual environmentpython3 -m venv toyrobot-envActivate virtual environmentsource toyrobot-env/bin/activateInstall source-codepip install <path-to-downloaded-source>Option 3: DockerPull latest image from dockerhubdocker pull rlupat/toyrobotUsagePlease ensure virtual environment has been activatedsource toyrobot-env/bin/activateOption 1: Binarytoyrobot -i <path-to-input-file>Example:toyrobot -i ./resources/test1.txtOption 2: Pythonpython -m toyrobot.app -i <path-to-input-file>Example:python -m toyrobot.app -i ./resources/test1.txtOption 3: Dockerdocker run -v <local-mount-dir-test-data>:/test_data rlupat/toyrobot -i test_data/test1.txtExtended Usage Infousage:toyrobot[-h]-iINPUT[-xSIZEX][-ySIZEY][-d]RunToyRobotSimulation

optionalarguments:-h,--helpshowthishelpmessageandexit-iINPUT,--inputINPUTfileconsistingofrobotmovementcommands(required)-xSIZEX,--sizeXSIZEXdimensionoftabletop[5]-ySIZEY,--sizeYSIZEYdimensionoftabletop[5]-d,--debugturnondebugging[False]
Package: rlutils
rlutils: A utility package for implementing reinforcement learning simulations.rlutils is a python package containing utility functions to implement reinforcement learning simulations.
The goal of rlutils is to provide a useful base library to help implement reinforcement learning (RL) research projects.
Theexamplesdirectory contains jupyter notebooks demonstrating how to use rlutils.rlutils provides an API to implement RL agents, policies, and simulate them in a control task (also called environment or Markov Decision Process (MDP)). rlutils also provides implementations to some basic policies, value iteration, and Q-learning. Other utility functions are also included to collect trajectories, store them, and replay them.
rlutils' goal is to provide a framework and utility functions for implementing RL algorithms.If you have any questions about rlutils, please send email tolucas_lehnert@brown.edu.Installationrlutils is tested on python 3.5, 3.6, 3.7, and 3.8.This package can be installed using pip:pip install rlutilsAlternatively, the repository can also be cloned and the package can be installed without pulling from PyPI:git clone https://github.com/lucaslehnert/rlutils.git
cd rlutils
pip install .
Package: rlviser-py
rlviser-pyPython implementation that manages a UDP connection to RLViser, it launches theRLViser binaryfrom the current working directory upon first calling any render function.The backbone of RLGym'senv.render()functionality.Example usageimporttimeimportrlviser_pyasvisimportRocketSimasrsgame_mode=rs.GameMode.SOCCAR# Create example arenaarena=rs.Arena(game_mode)# Set boost pad locationsvis.set_boost_pad_locations([pad.get_pos().as_tuple()forpadinarena.get_boost_pads()])# Setup example arenacar=arena.add_car(rs.Team.BLUE)car.set_state(rs.CarState(pos=rs.Vec(z=17),vel=rs.Vec(x=50),boost=100))arena.ball.set_state(rs.BallState(pos=rs.Vec(y=400,z=100),ang_vel=rs.Vec(x=5)))car.set_controls(rs.CarControls(throttle=1,steer=1,boost=True))# Run for 3 secondsTIME=3steps=0start_time=time.time()foriinrange(round(TIME*arena.tick_rate)):arena.step(1)# Render the current game statepad_states=[pad.get_state().is_activeforpadinarena.get_boost_pads()]ball=arena.ball.get_state()car_data=[(car.id,car.team,car.get_config(),car.get_state())forcarinarena.get_cars()]vis.render(steps,arena.tick_rate,game_mode,pad_states,ball,car_data)# sleep to simulate running real time (it will run a LOT after otherwise)time.sleep(max(0,start_time+steps/arena.tick_rate-time.time()))steps+=1# Tell RLViser to exitprint("Exiting...")vis.quit()
Package: rlvoice
pyttsx3is a text-to-speech conversion library in Python. Unlike alternative libraries, it works offline, and is compatible with both Python 2 and 3.Installationpip install pyttsx3> If you get installation errors , make sure you first upgrade your wheel version using :pip install –upgrade wheelLinux installation requirements :If you are on a linux system and if the voice output is not working , then  :Install espeak , ffmpeg and libespeak1 as shown below:sudo apt update && sudo apt install espeak ffmpeg libespeak1Usage :import pyttsx3
engine = pyttsx3.init()
engine.say("I will speak this text")
engine.runAndWait()Changing Voice , Rate and Volume :import pyttsx3
engine = pyttsx3.init() # object creation

""" RATE"""
rate = engine.getProperty('rate')   # getting details of current speaking rate
print (rate)                        #printing current voice rate
engine.setProperty('rate', 125)     # setting up new voice rate


"""VOLUME"""
volume = engine.getProperty('volume')   #getting to know current volume level (min=0 and max=1)
print (volume)                          #printing current volume level
engine.setProperty('volume',1.0)    # setting up volume level  between 0 and 1

"""VOICE"""
voices = engine.getProperty('voices')       #getting details of current voice
#engine.setProperty('voice', voices[0].id)  #changing index, changes voices. o for male
engine.setProperty('voice', voices[1].id)   #changing index, changes voices. 1 for female

engine.say("Hello World!")
engine.say('My current speaking rate is ' + str(rate))
engine.runAndWait()
engine.stop()

"""Saving Voice to a file"""
# On linux make sure that 'espeak' and 'ffmpeg' are installed
engine.save_to_file('Hello World', 'test.mp3')
engine.runAndWait()Full documentation of the LibrarySee the included docs folderIncluded TTS engines:sapi5nsssespeakFeel free to wrap another text-to-speech engine for use withpyttsx3.Project Links:PyPI (https://pypi.python.org)GitHub (https://github.com/Akul-AI/rlvoice)
Package: rlvoice-1
Credits tonateshmbhatfor creating the original library pyttsx3.Offline Text To Speech (TTS) converter for PythonRLVoiceis a text-to-speech conversion library in Python. Unlike alternative libraries,it works offline.Installation :pip install rlvoice-1If you get installation errors , make sure you first upgrade your wheel version using :pip install --upgrade wheelDO NOT USEpip install rlvoice, make sure you add the-1next to it, or it will download the wrong package.Linux installation requirements :If you are on a linux system and if the voice output is not working , then  :Install espeak , ffmpeg and libespeak1 as shown below:sudo apt update && sudo apt install espeak ffmpeg libespeak1OS X installation requirements :If you are on a MacOS system and if you get an error such asNameError: name 'objc' is not defined. Did you mean: 'object'?, then  :Install thepyobjclibrary as shown below:pip install pyobjc==9.0.1Features :✨FullyOFFLINEtext to speech conversion🎈 Choose among different voices installed in your system🎛 Control speed/rate of speech🎚 Tweak Volume📀 Save the speech audio as a file❤️ Simple, powerful, & intuitive APIUsage :importrlvoiceengine=rlvoice.init()engine.say("I will speak this text")engine.runAndWait()Single line usage with speak function with default optionsimportrlvoicerlvoice.speak("I will speak this text")Changing Voice , Rate and Volume :importrlvoiceengine=rlvoice.init()# object creation""" RATE"""rate=engine.getProperty('rate')# getting details of current speaking rateprint(rate)# printing current voice rateengine.setProperty('rate',125)# setting up new voice rate"""VOLUME"""volume=engine.getProperty('volume')# getting to know current volume level (min=0 and max=1)print(volume)# printing current volume levelengine.setProperty('volume',1.0)# setting up volume level  between 0 and 1"""VOICE"""voices=engine.getProperty('voices')# getting details of current voice# engine.setProperty('voice', voices[0].id)  #changing index, changes voices. o for maleengine.setProperty('voice',voices[1].id)# changing index, changes voices. 1 for femaleengine.say("Hello World!")engine.say('My current speaking rate is '+str(rate))engine.runAndWait()engine.stop()"""Saving Voice to a file"""# On linux make sure that 'espeak' and 'ffmpeg' are installedengine.save_to_file('Hello World','test.mp3')engine.runAndWait()Full documentation is located in thedocsfolder.Included TTS engines:sapi5nsssespeakcoqui_ai_ttsFeel free to wrap another text-to-speech engine for use withrlvoice-1.Project Links :PyPI (https://pypi.org/project/rlvoice-1)GitHub (https://github.com/Akul-AI/rlvoice-1)
Package: rlvortex
vortexA reinforcement learning algorithm framework1. quick start2. run testsRun the following commands under project root directory (rlvortex/)test gym environments withtarget environmentandrenderoption.$ make -f runs/run_tests.mk [target_environment(-render)]target_envrionment in [carpole, mountaincarc]-render can not optional; if render is enabled, the test will run with GUI.example (cartpole):run cartpole headless testmake -f runs/run_tests.mk cartpolerun cartpole with GUI testmake -f runs/run_tests.mk cartpole-rendertest all gym environments headlesslymake -f runs/run_tests.mk all-headlesstest all gym environments with GUImake -f runs/run_tests.mk all-render3. benchmarkRun the following commands under project root directory (rlvortex/)'''
$ make -f run_trainers.mk [target_environment(-render)]'''
'''
$ make -f runs/run_trainers.mk [cartpole-vpg]
'''
Package: rlwsd
This repository contains scripts and expriments related to theSense frequencies project, and anrlwsdpython package for WSD (word sense disambiguation) for Russian language.rlwsd packageThis package can perform WSD for Russian nouns described in the
of Active Dictionary of Russian (currently, only the first volume is published
with letters “А” - “Г”).InstallationThe package currently works only on CPython 3.4+. Install with pip:pip3 install rlwsdThe package requires models that are not hosted on PyPI and most be
downloaded separately (about 2.3 Gb total):python3 -m rlwsd.downloadModels are re-downloaded even if they are already present.
In case of problems (download does not finish, etc.) you can download models
manually fromrlwsd.download.MODELS_URLand extract them into themodelsfolder insiderlwsd(package) folder.UsageMost functionality is provided by the model class. Model for each word
must be loaded separately:>>> import rlwsd
>>> model = rlwsd.SphericalModel.load('альбом')
>>> model.senses
{'1': {'meaning': 'Вещь в виде большой тетради ...',
       'name': 'альбом 1'},
 '2': {'meaning': 'Книга тематически связанных изобразительных материалов ...',
       'name': 'альбом 2.1'},
 '3': {'meaning': 'Собрание музыкальных произведений ...',
       'name': 'альбом 2.2'}}
>>> model.disambiguate('она задумчиво листала', 'альбом', 'с фотографиями')
'2'You can also get a list of all words with models:>>> import rlwsd
>>> rlwsd.list_words()
['абрикос',
 'абсурд',
 'авангард',
 ...
 'гусь',
 'гуща']A large word2vec model is used internally. By default it is loaded once,
one the first call to.disambiguatemethod, which takes noticeable time.
There is an option to load word2vec
model in a separate process by runningw2v-servercommand, which starts
a server, and exportingW2VSRVenvironment variable with any non-empty value:# in the first terminal window
$ w2v-server
running...
# in the second terminal window
$ export W2VSRV=yes
$ pythonIn this way you can leave thew2v-serverrunning and save time on word2vec
model reloads.LicenseLicense is MIT
Package: rl_wsd_labeled
Contexts sampled from RuTenTen and RNC. Sense definitions from Active Dictionary.
Some words have two annotators. Number of contexts is 100 for most words
and 500 for 7 words.Annotators (words):Анастасия Лопухина (47)Константин Лопухин (11)Александра Удальцова (2)Анастасия К. (2)Анна Кот (2)Анна Татаренко (2)Борис Иомдин (2)Иван Самойленко (1)Contexts are stored inrl_wsd_labeled/:rl_wsd_labeled
├── adjectives
│   └── RuTenTen
├── nouns
│   ├── RNC
│   └── RuTenTen
└── verbs
    └── RuTenTenA python interface is provided. Intall the package first:pip install rl_wsd_labeledand then in order to get labeled contexts:>>> import rl_wsd_labeled
>>> f = rl_wsd_labeled.contexts_filename('nouns', 'RuTenTen', 'горшок')
>>> rl_wsd_labeled.get_contexts(f)

({'1': 'Округлый глиняный сосуд для приготовления пищи (печной горшок)',
  '2': 'Расширяющийся кверху сосуд с отверстием в дне (цветочный горшок)',
  '3': 'Ночной горшок'},
 [(('телевизор, - ковер, , - музыкальный центр, - стол, - аквариум, - 3 шкафа, - цветы в',
    ' горшках',
    ', - мелкие аксессуары.'),
  '2'),
  ...
  (('ибо настанет срок и оно будет разрушено течением времени либо войною, будто старый',
    ' горшок',
    ' с вином в трюме торгового корабля, попавшего в бурю и разбившегося о скалы.'),
  '1')
 ])Apart from senses, there are two special annotations: “0” means
“I don’t know/the context is unclear/the contexts is invalid”, and “max sense + 1”
mean “other sense, not listed among given senses”. Contexts marked as “0” or “other”
are not returned, unlesswith_skipped=Trueis passed.
If there was more then one annotator, contexts where annotators did not agree are also
not included. There is a functionrl_wsd_labeled.get_agreementthat returns the
ratio of senses where where both annotators gave either the
same concrete sense, or both skipped the senses (so “0” and “other” are considered equal).
Package: rlxcrypt
rlxcryptseamlessly encrypt, distribute and load python modulesUsageyou have a.pyfile that you want to distribute such as|
 +- mymodule.py
 +- main.pyand inmain.pyyou use it:# main.py
import mymodule as m  
m.some_func()to distributemodule.pyencrypted (in a shell):> rlxcrypt encrypt mymodule.py
> mv mymodule.py some_private_folderso you have|
+- mymodule.pye
+- main.pyand then inmain.py# main.py
import rlxcrypt
import mymodule as m  
m.some_func()Notesrlxcryptuses RSA encryption as part of the import hooks to detect encrypted files and decrypts them on the fly during the import process.rlxcryptis distributed only as a binary for your architecture, which contains all mechanics to encrypt and decrypt.rlxcryptsources are obfuscated in several custom steps (no public obfuscation library is used) and then compiled into binary code.it is not 100% bullet proof, it just makes it very hard to crack as it would require to reverse engineer the binary file AND the obfuscation logic.
Package: rlyehian
RlyehianTranslate to the language of the "old ones" with the serpent's tong in the digital world.Inspired by H.P. LovecraftUsing the digital serpent's package, you can translate english to the language of the "old ones"Spread a̶͙̓̓̓͛̿̓͘ḯ̵̡̲̟̼͎̩͉̬̙̈̀͆͜m̴̨̺̖͇͔̝̤̖͊̏̌̅̔̿͜͜͝ģ̶̺͚̬̣̣̜͉̃̒͜ŗ̷͖͇͖̘͍̹̳̈̑͐͌̇̆͘͜͝ͅ'̴̢͉͎͇͔̬̖̽̈̕͜ļ̷̛̥̹̰͎̤͉̫̱̗͗̈́͗͆̾͒̄̅͠ű̸̖̼͇̏̈́̉̊̌̃̕ḩ̷̧̲̬͔̉ͅGetting StartedFollow the scripture below to begin to transcribe into the words of the "old ones".InstallationsInstall the following Serpent dependencies.Install rlyehian$ pip install rlyehianIf you want to use the projects version of the translator, do the following:Install the Python dependencies:pip install -r requirements.txtUsageSample Translation CodeBelow is a code sample on how to translate english to R'lyehian:Place the following in a python fileimportrlyehian,argparse,osdefmain():parser=argparse.ArgumentParser(description='Rlyehian Translator.  Speak the language of the old ones.')parser.add_argument('-t','--text',help='Text to Translate',required=True)args=vars(parser.parse_args())text=args['text']ahahog_compendium()text=ainghft(text)print(text)if__name__=="__main__":``main()Run the following command$pythontest.py-t"I pray to the mother of skin"Current Development9/7/18 - Simple translation with no checks for word typing.  Only translating in English at the moment.Built WithPython 3.6AuthorJimmy Le-JldevopsLicenseLicensed under theMIT License
Package: rm
Installation$[sudo]pipinstallrmFeaturesremovesdirsandfilesno exception- skip if path not existsExamples>>>importrm>>>rm.rm("path/to/file")# rm file>>>rm.rm("path/to/dir")# rm dir>>>rm.rm(["path/to/dir","path/to/file"])# rm multiple paths>>>rm.rm("not-existing")# no exceptionreadme42.com
Package: rm-anime-bg
rm_anime_bgA simple CLI of anime background remover withSkyTNT/anime-segmentationImage source, licensed under CC-BY-SA-3.0, Funa FunaSetup# For CPUpipinstall-U'rm_anime_bg[cpu]'# For GPUpipinstall-U'rm_anime_bg[gpu]'Usagerm_anime_bg-o[Outputdirectory][Input1][Input2][Input3]...[InputN]--cpu: Force use of CPURunrm_anime_bg --helpto check full command optionsExamplerm_anime_bg-o/path/to/output_dirinput1.pnginput2.pngLinkshttps://github.com/SkyTNT/anime-segmentationAnother image background remover:rembgLicenseApache License 2.0
Package: rmate
Thermateprogram enables editing files on a remote computer with
TextMate 2 via an SSH connection. This is a port ofthe official Ruby
versionand was made for system that cannot (or just preferably do not) have
Ruby installed. This version (very intentionally) has no dependencies beyond
the Python standard library and has been tested with Python versions 2.4 - 3.5.This port is probably compatible with Sublime Text, Atom, or other editors that
use thermateprotocol, but it is not officially tested.InstallStandalonermateis a single file script, so you can simply download it to a location
in yourPATH. For example, assuming/usr/local/binis in thePATHwget https://raw.githubusercontent.com/sclukey/rmate-python/master/bin/rmate
chmod +x ./rmate
mv ./rmate /usr/local/bin/rmatePyPIYou can also installrmatewithpippip install rmateSSH Connection SettingsForrmateto be able to connect back to TextMate, a port must be tunneled
through the ssh connection. By default,rmateuses port 52698, and the port
can be tunneled for an individual connection on the command linessh -R 52698:localhost:52698 user@example.comor for all connections by adding a rule to your~/.ssh/configHost *
RemoteForward 52698 localhost:52698UsageYou can usermate--helpto see the usageusage: rmate [OPTION]... FILE...

      --host HOST  Connect to HOST. Use 'auto' to detect the host from
                   SSH. Defaults to localhost
  -p, --port PORT  Port number to use for connection. Defaults to 52698
  -w, --[no-]wait  Wait for file to be closed by TextMate
  -l, --line LINE  Place carat on line LINE after loading the file.
                   TextMate selection strings can be used
  -m, --name NAME  The display name shown in TextMate
  -t, --type TYPE  Treat file as having TYPE
  -f, --force      Open even if the file is not writable
  -v, --verbose    Verbose logging messages
  -h, --help       Show this help and exit
      --version    Show version and exit

When FILE is -, read standard input.More information can be found inthis blog post
Package: rmb-client
元数据大脑 Reliable Meta Brain（RMB）Feature （功能）DataSource 支持 Excel/CSV/MySQL支持以对话方式查询数据支持多轮对话支持更新 Meta（字典/同义词），以识别意图，提高准确率提供Restful API & Python SDKExcel的跨表关联查询Meta增强（获取数据样例便于生成准确的包含常量的Query语句，比如需要让LLM知道是sex='男'还是sex=1）Backlog（计划）支持微信文档中的表格支持飞书、钉钉表格、Airtable表格支持跨数据源（MySQL+MySQL,MySQL+Hive）的联合查询Installation（安装）安装客户端pip install rmb-client
rmb-client -a https://api.rmb.datamini.ai/ -t token01安装&运行服务端方法1：通过pip$ pip install rmb-server
$ rmb-server方法2：通过docker（推荐）
镜像维护在hub.docker.com$ docker run -d -p 5000:5000 datamini/rmb-server多租户RMB 采用多租户架构，每个租户只可以查看自己的数据源、对话等信息。参考文档README_AUTH.md客户端CLI&SDKRMB 客户端提供了命令行CLI和Python SDK两种方式来访问RMB。参考文档rmbclient/README.md参与开发本地环境启动先git clone ...编辑配置文件  在目录rmbserver/config/下，执行cp default.py custom.py然后编辑custom.py文件启动服务python rmbserver/run.py [<host> <port>]运行客户端python rmbclient/cli.py [-a http://localhost:5000/ -t token01]
Package: rmc-discord
rmc-discordReverseMonteCarlo refinement ofdiffusescattering andcorrelateddisorder from single crystalsrmc-discordis an atomistic program for the analysis of single crystal diffuse scattering from disordered materials capable of extracting short-range magnetic, occupational, and displacive correlations.There are two required inputs:CIF file of the average structureNeXus file of the scattering dataThere are several outputs:CIF file of disordered structureCSV file of spherically averaged pair correlationsVTK file of three-dimensional pair correlationsVTK file of recalculated diffuse scattering patternThe program is written in Python with underlying performance-critical extensions written in Cython and includes a PyQt5 GUI.https://doi.org/10.1107/S1600576721010141
Package: rmchars
RECURSIVELY REMOVE INVALID CHARS IN PATHSA simple script to find and remove invalid characters in file and directory
names. Inspired by the need to workaround limitations ofEgnyte's unsupported
character types.The chars are currently hardcoded into the script, but like the list of servers
to run on, this should really be added to a config/lst file.The aforementioned list should reside in $HOME/.ELC.lst. The format is one line
per server and lines beginning with # will be ignored.There is a really convoluted bash version and a nice simple Python version and a
W.I.P Powershell version...run.sh is a bash wrapper script for mounting a list of servers to run the python
script on.INSTALLATIONpip install rmcharsCLI USAGEusage: rmchars [-h] (-i | -a | -t | -q | -f) [path]

Remove invalid characters from a given path.

positional arguments:
  path               a valid path

optional arguments:
  -h, --help         show this help message and exit
  -i, --interactive  prompt before renaming each path
  -a, --automate     rename each path without prompting
  -t, --dry_run      preform a dry run to see what would be renamed
  -q, --quiet        run silently
  -f, --find         print a list of invalid pathsTODOAdd support for unicode and control charactersAdd char list to config fileFinish Powershell version