Saravanan666/pypi-org huggingface dataset:
Package: rr-bot
Ringing Room BotA bot for Ringing Room that can fill in any set of bells to increase the scope of potential practices.This bot is designed to be a'ninja helper with no ego'.It will ring all unassigned bells perfectly whilst fitting in with whatever you are doing, adjusting to
your changes in rhythm.
It will never try to take control of the ringing by giving instructions or powering on with a
different rhythm to everyone else (unless you tell it to).
However, by default it will adjust only to changes to overall rhythm - it will ignore individual
bells holding up and ring in the 'right' place regardless.Only one ringer needs to run the command and it will ring with you after anyone callsLook toin
Ringing Room.
It will understand all Ringing Room calls -Go,Look to,That's allandStand nextwill
take effect the handstroke after they are called, andBobandSinglewill result in14and1234lead end calls.Notable featuresConfigurable rhythm detection that updates in real timeAutomatic correction for Ringing Room using multiple server URLs for load balancingVery light resource footprint, as it doesn't interact with a browser to communicate with Ringing RoomContributingContributions are very welcome!  Seeherefor guidance.If you have any issues/suggestions, eithermake an issue, or drop me a messageon Facebook.QuickstartInstallation (using Pip)Run the following command to install or update to the latest version of the bot:pip3install--upgraderr-bot(usepip install --upgrade rr-boton Windows).Pick an example below to run the bot!ExamplesRun the bot withrr-bot [ARGS].Join aringingroom.comtower with (9 digit) id[ID NUMBER]and ring Plain Bob Major (tower
bell style - wait forGoandThat's all):rr-bot[IDNUMBER]--method"Plain Bob Major"Make the bot ring 'up, down and in' rather than waiting for 'go':rr-bot--up-down-in--id[IDNUMBER]--method"Plain Bob Major"# orrr-bot[IDNUMBER]-u--method"Plain Bob Major"Make the bot ring full handbell style, i.e. 'up, down and in' and standing at rounds (-His
equivalent to-us):rr-bot[IDNUMBER]--up-down-in--stop-at-rounds--method"Plain Bob Major"# orrr-bot[IDNUMBER]-us--method"Plain Bob Major"# orrr-bot[IDNUMBER]-H--method"Plain Bob Major"Join a server other thanringingroom.com:rr-bot[IDNUMBER]--urlotherserver.com--method[METHODTITLE]Ring rows taken from a (public) composition fromcomplib.org, in this
casehttps://complib.org/composition/65034:rr-bot[IDNUMBER]--comp65034Make the bot wait for people to ring rather than pushing on with the rhythm:rr-bot[IDNUMBER]--method"Plain Bob Major"--waitMake the bot completely ignore other users' changes in rhythm (useful if it's ringing most of
the bells and you don't want it to randomly change speed when you make mistakes):rr-bot[IDNUMBER]--method"Plain Bob Major"--inertia1.0# orrr-bot[IDNUMBER]--method"Plain Bob Major"-i1.0Print a nice help string:rr-bot--help# orrr-bot-h
Package: rrb-package
rrb_packageMyPackage is a Python package that provides a set of useful utilities for working with data in Python. It includes a number of functions and classes for data preprocessing, cleaning, and visualization, as well as tools for machine learning and data analysis.FeaturesMyPackage includes the following features:Data preprocessing: MyPackage provides functions for cleaning and transforming data, including tools for handling missing data, standardizing data, and encoding categorical variables.Data visualization: MyPackage includes classes and functions for creating various types of plots and visualizations, including scatter plots, histograms, and heatmaps.Machine learning: MyPackage includes tools for building and training machine learning models, including support for popular algorithms like linear regression, logistic regression, and decision trees.Data analysis: MyPackage provides tools for statistical analysis and hypothesis testing, including functions for calculating summary statistics, conducting t-tests, and performing ANOVA.InstallationYou can install MyPackage using pip:Copy codepip install mypackageUsageTo use MyPackage, simply import it into your Python code:arduinoCopy codeimport mypackageYou can then access its functions and classes by calling them directly:pythonCopy codedata = mypackage.preprocess(data)
visualization = mypackage.plot(data)
model = mypackage.train_model(data)
result = mypackage.analyze(data)LicenseMyPackage is licensed under the MIT License. See LICENSE for more information.
Package: rrcf-outlier-detector-MA
Random Robust Cut Forest - Moody's AnalyticsInstallationpip install RRCF_Outlier_DetectionObjectivesUse the RRCTree included inrrcfpackage as a week learner for creating a forest, incrementing the outlierdetection power.Do the code more user-friendly for its fast implementationAutomatize the process of outlier detection through the usage of 3 Sigma analysisFunctionsOutlier_Detector ( x, num_trees, num_samples per tree )Trains the RRCForestParameters:xNumpy Array / Data from which we want to detect outliersnum_treesint / Number of trees that are going to be used a weak learners for the forestnum_samples per treeint / Number of samples per tree. this parameter is recommended to be established as (1 / Estimated Proportion of Outliers)Attributes:rrcf_outlier_score ()Returns a Pandas' series with the CoDist scores for all input samplesrrcf_outlier_detector ()Returns a Numpy array with the detected outliers from the input samplesCitingM. Bartos, A. Mullapudi, & S. Troutman, rrcf: Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams, in: Journal of Open Source Software, The Open Journal, Volume 4, Number 35. 2019
Package: rrcgeoviz
GeoVizGeoViz is an Exploratory Data Analysis tool designed to empower data analysts to visualize and interpret spatio-temporal data. It offers a user-friendly, interactive web interface built on Panel, ensuring simplicity and maximal explainability. The software provides visualizations, including 3D geographical coordinates, seasonality analysis, heatmap displays, and categorization/clustering using Natural Language Processing (NLP). With a focus on simplicity and shareability, GeoViz enhances data analysis for a broader audience.The documentation can be found at ourreadthedocs page.Example UsageFirst, install GeoViz:pipinstallrrcgeovizOnce done, create an options.json file for your spatio-temporal CSV dataset. Here's a basic example:{"columns":{"latitude_column":"latitude","longitude_column":"longitude","time_column":"date"},"features":["month_year_heatmap","test_option_name","yearly_range","one_year","all_months","one_year_months","threeD","nlp_clustering"],"features_customizations":{"hover_text_columns":["victim"],"filter_one_year_column":"victim"},}Finally, run GeoViz with the following command:rrcgeovizpath/to/dataset.csvpath/to/options.jsonA tab should open in your browser with all of the enabled features!Brief overview of how it works (for contributers)When running from the command line, the main() function in src/rrcgeoviz/geoviz_cli.py runs. The options and dataset are stored in anArguments object.The Arguments object is first passed to theGeneratedDataclass. The GeneratedData class checks whether to pull data from the cache or not. If it needs new data, then it calls any relevant classes in the DATA_GENERATORS array to make it for it to store. The data is then passed back to the Arguments object as the .generateddata attribute.The Arguments object with the data, options, and generated data is passed to theGeoVizPanelDashboard class. Here, the data is checked (i.e. it is not null, it's in the correct range, etc.) and then the relevant classes in the ALL_FEATURE_CLASSES  array are called to create the features for GeoViz. These don't make any data, just render what's there into pretty visualizations.Here's a general flow of how to add new components:If new data is required (e.g. distance to nearest POI) create a new subclass of theParentGeneratorClassin src/rrcgeoviz/datagenerators. Look atGeneratorExamplefor reference.If a new data generator was made, add it to the DATA_GENERATORS array at the top of the GeneratedData file.Create the panel component as a subclass ofParentGeovizFeaturesin src/rrcgeoviz/features. Look at other features in the directory for a sense of what they look like.Add the new feature to the ALL_FEATURE_CLASSES array at the top of the GeoVizPanelDashboard file.That's pretty much it!
Package: rr-cilantro
# cilantro> Python Robot API for the CamJam Edukit 3## Example usage```pythonfrom cilantro import Robotfrom time import sleep# Create instance of robotrobot = Robot()# Go forward for 5 seconds then stoprobot.motors.m0 = 100robot.motors.m1 = 100sleep(5)robot.motors.m0 = 0robot.motors.m1 = 0```## DistributeCreate source distribution```python setup.py sdist```Create wheel```python setup.py bdist_wheel```Upload to pypi```twine upload dist/*```
Package: rrdata
rrdata is python project for china stock analysis.default database id rrdataanalysis database is rralpha/rqfactorrrdatad is fetch all data form open source(web/api);
include:
(stock--sina/eastmoney/tusharepro;
index --- swsindex.com / legulegu.com /
fund --
)
cron  record  to database rrdata;rrdatac is api to get data from my database server or web(realtime/spot)sefult analysis alpha factor to database rralpha cronly.usage:1.rrdsk init;a. run rqLocalize for mkdir ~/.rrsdk/setting for configb. cp config.json and config.ini to path(setting)c. config include: sql password / database-server-ip/name/port, sql-uri, tusharepro-token and so on.d. .rrsdk save to romepeng/.rrsdk.git (private) by git push;get rrdata --data(index/stock/fund/bond) by rrdatac(rrdata) api;get quant alpha factor from database rqfactor or rralphayou can show your analysis results to web by streamlit / pyecharts / hightcharts  and so on;
Package: rr-delete-unused-packages
rr-delete-unused-packagesThis library is designed to reduce the size of your Python virtual environment based on the actual usage of libraries in
your project. The primary objective is to eliminate any unused libraries to optimize resource utilization effectively.
The process is straightforward and user-friendly. However, it's crucial to refrain from working within the tested
environment until the process is complete. At the conclusion of the process, you'll have the flexibility to decide
whether to retain the newly created environment or revert to the previous one, depending on your specific requirements.Environment and InstallationsEnsure that you have Python version 3.10 or higher installed.Navigate to the relevant project where you want to test the virtual environment.Ensure that a requirements.txt file is present in the project's root path.Install the rr-delete-unused-packages package from PyPI using the following command:pipinstallrr-delete-unused-packagesTest your virtual environmentRun this script from the project's root path:importos
fromrr_process.delete_unused_libsimportUnusedDependenciesif__name__=='__main__':project_main_fp,venv_fp=os.getcwd(),f"<project_env_file_path>"UnusedDependencies(main_path=project_main_fp,venv_path=venv_fp).run()The second option is start a new session by terminal command:python3./<script_env_file_path>/delete_unused_libs.py././<project_env_file_path>Please make sure to replace <project_env_file_path> & <script_env_file_path> with the actual path to your project's environment path.
Package: rrdtool
python-rrdtoolPython bindings forRRDtoolfor Python 2 and 3.The bindings are based on the code of the original Python 2 bindings module for rrdtool by Hye-Shik Chang and are now shipped with the RRDtool distribution. This project is maintained separately to provide a more pythonic way to install those bindings viaPyPI.FeaturesNative extension (written in C) for performance reasons.Uses library functions as exposed by librrd.Works with Python 2.7, 3.5 and later.InstallationThe most convenient way to install (on POSIX-like systems) is to use pip:pip install rrdtoolNote:Unless binary versions are available for your target system, the command above requires rrdtool development files (headers, libraries, dependencies) to be installed, otherwise building the module will fail.In case you'd like to build the module on your own (regardless of whether binary versions are available for your system), you can obtain a copy of the source code and runpython setup.py installin its destination folder to build the module.Usageimportrrdtool# Create Round Robin Databaserrdtool.create('test.rrd','--start','now','--step','300','RRA:AVERAGE:0.5:1:1200','DS:temp:GAUGE:600:-273:5000')# Feed updates to the RRDrrdtool.update('test.rrd','N:32')DocumentationYou can find the latest documentation for this project athttps://pythonhosted.org/rrdtool.LicenseGNU Lesser General Public License version 2.1.
Package: rrdtool_cffi
Main goal is to have rrdtool available in pypy.
The API is close to the bindings comming with rrdtool itself.
It supportspython2.6python2.7python3.2python3.3pypy2.0You have to install the rrdtool library before using the bindings:apt-getinstall rrdtoolFurthermore the ‘cffi’ library must be present:apt-getinstalllibffi-devChangelog0.1 - Mai 17, 2013Initial release
Package: rreader
rReader is RSS reader client for CLI(Command Line Interface), spinned off fromrterm.rReader requires Python version 3.7 and above.rReader는 한국어 RSS 피드를 지원합니다.rReaderは日本語RSSフィードをサポートしています。rReader该库支持中文RSS。rReader該庫支持中文RSS。ScreenshotGetting StartedTry it with:pip3 install rreader
rrYou can clone the git repo:git clone https://github.com/rainygirl/rreader
cd rreader
python3 setup.py install
rrRSS feedsYou can add/modify RSS feeds on ~/.rreader/feeds.jsonShortcut keys[H], [?] : Help[Up], [Down], [W], [S], [J], [K] : Select from list[Shift]+[Up], [Shift]+[Down], [PgUp], [PgDn] : Quickly select from list[O] : Open canonical link[:] : Select by typing a number from list[Tab], [Shift]+[Tab] : Change the category tab[Q], [Ctrl]+[C] : QuitContributingFeel free to fork & contribute!LicenserReader is released under the MIT license.CreditsLee JunHaeng aka rainygirl.
Package: rrec
rrec - automatically record your favourite program from WDR radioThis script will download and parse the program listings of different WDR radio
stations, grep them for preconfigured words and writes streamripper cronjobs to
record them.seerrec-hfor usage helpAs this script only creates cronjobs,cronandstreamripperare
required to actually record the programs.copyright (c) 2013 Tobias Bengfort <tobias.bengfort@gmx.net>
license: GPL-3+
Package: rref
Reduced Row-Echelon Form (RREF) libraryThis is a simple library for transforming a 2-D matrix to reduced row-echelon form (RREF)1.Definition2:In linear algebra, a matrix is in echelon form if it has the shape resulting from a Gaussian elimination.A matrix being in row echelon form means that Gaussian elimination has operated on the rows, and column echelon form means that Gaussian elimination has operated on the columns. In other words, a matrix is in column echelon form if its transpose is in row echelon form. Therefore, only row echelon forms are considered in the remainder of this article. The similar properties of column echelon form are easily deduced by transposing all the matrices.A matrix is in reduced row-echelon form if it satisfies the following:In each row, the left-most nonzero entry is 1 and the column that contains this 1 has all other entries equal to 0. This 1 is called a leading 1.The leading 1 in the second row or beyond is to the right of the leading 1 in the row just above.Any row containing only 0's is at the bottom.Below is a screenshot showing RREF matrices3:Example Usageimportrref### Create an uninstanced matrix helper (MatrixMadness)mm=rref.main.MatrixMadness()### Create a sample matrix of 20 x 20 with random integers### in the range of -5 to 20.matrix=mm.creatrix(20,[-5,20])### Create an RREF instance with your matrix.r=rref.RREF(matrix)### Run the processor# Note: The output matrix will be in the r.mm.matrix variable.r.run()### Print the matrix to check results.result=r.mm.matrixprint([iforiinresult])
Package: r-repeat
Simple library for gathering results from stochastic functionsUsage:pip install r_repeatOpen upthe wikito see how everything works or check the examplesEnjoyExample:fromr_repeatimportrepeat,seed@repeat(n=1e6)# run this function 1000000 times@seed(kwarg=['rng1','rng2'])# insert random numbers into rng1 and rng2deff(rng1,bias,rng2):return(rng1+bias)>=rng2g=f(bias=0.078)# pass remaining argumentssum=g.collect()# gather all resultsprint(f'{sum}wins and{len(g)-sum}losses')Output:22%|██▏       | 217913/1000000 [00:21<01:18,  9952.1it/s]    (while working)
574945 wins and 425055 losses    (after finished)
Package: rrg
Keyczar Use demonstated here -http://www.saltycrane.com/blog/2011/10/notes-using-keyczar-and-python//usr/local/bin/python2.7 setup.py install
installs scripts to /usr/local/bin/Keyczar - efforts from fogtest serverkeys built in ~/.keyczar, using virtualenv source ~/envs/p27-dj1.7/bin/activaterun web server
bash-4.3# gunicorn rrg.app:app
[2017-02-06 01:24:04 +0000] [9978] [INFO] Starting gunicorn 19.6.0
[2017-02-06 01:24:04 +0000] [9978] [INFO] Listening at: http://127.0.0.1:8000 (9978)
[2017-02-06 01:24:04 +0000] [9978] [INFO] Using worker: sync
[2017-02-06 01:24:04 +0000] [9991] [INFO] Booting worker with pid: 9991running the containerdocker run -v /src/python-source:/src/python-source-v /datadir:/datadir -v /keyczar:/keyczar -v /backups:/backups -it –rm  –name flask-test -e RRG_SETTINGS=/src/python-source/sherees-commissions/config/default -e AWS_ACCESS_KEY_ID=AIMF3Q -e AWS_SECRET_ACCESS_KEY=Mojxrd111V -e AWS_BUCKET=php-cluster -e DATADIR=/datadir/rrg -e RRG_PORT=9000 -e MYSQL_SERVER_PORT_3306_TCP_ADDR=12.30.0.251 -e MYSQL_SERVER_PORT_3306_TCP_PORT=3306 -e DB=rrg -e MYSQL_PASS=my_vet_password -e MYSQL_USER=root -e KEYZCAR_DIR=/keyzcar flask-dev /bin/bash
Package: rrgp
Human Activity Recognition Using SmartphonesThis project aims to train a model to recognise human activities (like walking,
standing, or sitting) based on accelerometer and gyroscope data collected with
a smartphone.For installation and usage instructions, please refer toour documentation.DatasetThis package use the "Human Activity Recognition Using Smartphones Data Set".
For more information about it, please refer to theoriginal publication.Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. A Public Domain Dataset for Human Activity Recognition Using Smartphones. 21th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013. Bruges, Belgium 24-26 April 2013.LicenseThis repository is made publicly available under theMIT License.AuthorsGeoffrey RaposoPatrick Audriaz
Package: rr-graph
SymbiFlow Routing Resources Graph (rr-graph) Python LibrariesThis repository contains a Python library and utilities for working with"Routing Resource Graph" (rr-graph) filesused bySymbiFlowandVerilog to Routing.It supports both theXMLandCap'n'Protoformats ofrr-graphfiles.
The Cap'n'Proto schema is generated from theXML schema @vtr-verilog-to-routing/vpr/src/route/rr_graph.xsdusing theuxsdcxx tool.For information on the schema generation can be found in theSCHEMA_GENERATOR.mdfile in Verilog to Routing.ContributingA full contribution guide can be found indocs/contributing.md.A few important points;All contributions should be sent asGitHub Pull requests.By contributing you agree to thecode of conduct.Allcommits are required to include aDCOsign off line.LicenseAll software (code, associated documentation, support files, etc) in this
repository is licensed under the very permissiveISC Licence.A copy can be found in theLICENSEfile.All new contributions must also be released under this license.InstallingFrom PyPIpip install rr-graphFYI:Builds areautomaticallypublished to GitHub on every push to this repository.Direct from GitHubpip install git+https://github.com/SymbiFlow/symbiflow-rr-graph.git#egg=rr-graphDirect from checkoutpython setup.py installorpython setup.py developDevelopingTo setup a local development environment use themake venvtarget which will
build you aPython virtualenv(in thevenvdirectory) with the needed packages and tools.Themake versiontarget will output the current version of therr-graphlibrary.Running testsTo run the tests, runmake test.If you have an issue with the CI disagreeing with the output of your localmake testoutput, you can also try themake test-like-citarget to closer
match how the CI system runs the tests.FormattingTo run automated formatting over the repository, usemake format.Updating GitHub ActionsThemake format-ghatarget will update the GitHub Actions under.github/workflowswith the latest version of the
included tasks.It is recommended that you commit these updates separately from your other
changes.
Package: rri
Registry Reporting InterfacePython client library for theICANN Registry Reporting Interface.Free software: MIT licenseFeaturesrri supports all features of theICANN Registry Reporting Interface(v8)Status checking and submission of:Data Escrow ReportsData Escrow NotificationsRegistry Functions Activity ReportPer-Registrar Transactions ReportInstallationYou can download and install the latest version of this software from the
Python package index (PyPI) as follows:pip install --upgrade rriUsageimport rri

rric = RRIClient('example', 'exampleuser', 'examplepassword')

if rric.report.check():
    print("We have notified ICANN our .example escrow has been deposited")CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.1 (2018-08-08)First release on PyPI.
Package: rria-api
RRIA-APITherria-apiis an easy-to-use package that provides a common interface to control robots used by the Residence in Robotics
and AI at the UFPE's informatics center. The API currently supports the use of Kinova Gen3 lite and Niryo NED, with
plans to support a Denso robot.RequirementsPython 3.9+Kortex API .whl packageInstallationDownload the v2.3.0 Kortex API .whl package (required for controlling the Kinova Gen3 and Gen3 lite):kortex_api-2.3.0.post34-py3-none-any.whl.Install the downloaded package withpip:$ pip install <path to kortex_api-2.3.0.post34-py3-none-any.whl>Install the latestrria-apipackage withpip:$ pip install rria-apiExamplefromrria_api.robot_objectimportRobotObjectfromrria_api.robot_enumimportRobotEnum# Create gen3 RobotObjectgen3_lite=RobotObject('192.168.2.10',RobotEnum.GEN3_LITE)# Create Niryo NED RobotObjectned=RobotObject('169.254.200.200',RobotEnum.NED)gen3_lite.connect_robot()ned.connect_robot()gen3_lite.move_joints(30.0,30.0,30.0,30.0,30.0,30.0)ned.move_joints(30.0,30.0,30.0,30.0,30.0,30.0)gen3_lite.get_joints()ned.get_joints()gen3_lite.close_gripper()ned.close_gripper()gen3_lite.open_gripper()ned.open_gripper()gen3_lite.move_to_home()ned.move_to_home()gen3_lite.safe_disconnect()ned.safe_disconnect()