Saravanan666/pypi-org huggingface dataset:
Package: rmti
rmti - An AI application that determines your Myers-Briggs Type Indicator.Description
#############
Right now the app only contains a bot that mines data from Reddit. In the future we are planning on using that
data along with some machine learning algorithms to be able to predict people's types.Setup
#######We are currently working on a setup.py script that will make setting this up really easy. For now just clone the project and follow the steps below.If you do not already have a Reddit application or bot go toReddit <reddit.com/prefs/apps>_ and create an app. One you do
that you should be able to obtain your ownclient_idandclient_secret. Usehttp://localhost:8080as your redirect uri or your user context such as a web site.To protect your credentials create apraw.inifile inside of your root directory. Then place your credentials inside of this file. This is not the best
way to authenticate but it will do for now. We plan on moving toward a token based authentication later on. The password and username are the ones you use
to sign into your reddit account. It should look like this -| [YourBot]
| client_id=...
| client_secret=...
| password=...
| username=..Install all modules in requirements.txt usingpip install -r requirements.txt. If you still need to import modules then runpip install <module>and make a note taht we need to add that module to the requirements.txt.requirements.txtwill be replaced when we establish our setup.py.Configure and create a Reddit intances withpraw.Reddit('YourBot')inside ofredditbot.py.
Just modify this line of code:reddit = praw.Reddit('bot1', config_interpolation="basic"). config_interpolation="basic" is not necessary unless you plan on adding more detail to your bot such as author and version.Now you should be able to run the redditbot in multiple ways. Either using it as a module somewhere in the project,
running it as a script on the command line or even importing it into a Jupyter Notebook file.Resources
###############PRAW Docs <https://praw.readthedocs.io/en/v7.3.0/>_
Package: rm-trash
rm-trashrm-trash is a macOS command-line utility that moves files and directories to the Trash.
Unlikesimilartools,
rm-trash intends to be a complete alternative tormandrmdir, to the extent that you could use aliases
to have rm-trash replace them both.rm-trash works by communicating with Finder
throughAppleScript,
so it's no different from moving files to the Trash
from within Finder itself.InstallationInstall rm-trash withHomebrewvia
theHoukago Tea Tap.brewtapcelsiusnarhwal/htt
brewinstallrm-trashUsageInvoke rm-trash with thetrashcommand, which will become available after installation.trash--helpwill tell you everything you need to know.ReplacingrmandrmdirIf you wish, you can replacermandrmdirwith aliases totrash.aliasrm="trash trash"aliasrmdir="trash dir"trashsupports all options of both commands. Runtrash --helpfor details.Limitationsrm-trash refuses to as root whenSystem Integrity Protection(SIP) is
disabled.
You can still run rm-trash as a non-root user when SIP is disabled, or as any user when SIP is enabled. This limitation
is intended to prevent you from accidentally trashing files and directories that are typically protected by SIP.If you must remove files as root while SIP is disabled, you can always fall back torm.Licenserm-trash is licensed under theMIT License.
Package: rmugicag-chromedriver-autoinstaller
chromedriver-autoinstallerAutomatically download and installchromedriverthat supports the currently installed version of chrome. This installer supports Linux, MacOS and Windows operating systems.Installationpipinstallchromedriver-autoinstallerUsageJust typeimport chromedriver_autoinstallerin the module you want to use chromedriver.Examplefrom selenium import webdriver
import chromedriver_autoinstaller


chromedriver_autoinstaller.install()  # Check if the current version of chromedriver exists
                                      # and if it doesn't exist, download it automatically,
                                      # then add chromedriver to path

driver = webdriver.Chrome()
driver.get("http://www.python.org")
assert "Python" in driver.title
Package: rm-unneeded-f-str
rm_unneeded_f_strFind and replace unneeded f-strings in your code.Installationpip install rm_unneeded_f_strUsageRun via the CLI on a file or folder:rm-unneeded-f-str path/to/file.pyrm-unneeded-f-str path/to/folder/Or use as a pre-commit hook:-repo:https://github.com/dannysepler/rm_unneeded_f_strrev:v0.2.0hooks:-id:rm-unneeded-f-strWill replace-f'hello'+'hello'-f'''hello'''+'''hello'''-rf'hello'+r'hello'-f'''hello-world'''+f'''hello+world'''Will not replacef'hello{world}'f'''hello{world}'''
Package: rmux
rmuxrmuxallows you to run your local project on multiple remote machines in
parallel.The command names comes from remote-tmux as it allows multiplexing commands
on multiple remote machines, synchronized.The original purpose was to allow testing local changes to a project on other
platforms, like running tox on another distribution.Usage# run df locallyrmuxdf# close tmux sessionexit# run df on two remote hosts, syncronized windowsHOSTS="node1 node2"rmuxdf# run a script downloaded from the web (installs pip)rmux-whttps://bootstrap.pypa.io/get-pip.pyIf you fail to define theHOSTSvariable the tool will default to localhost
but it will still use its logic of doing a rsync and running commands using
tmux and ssh.How it worksrmuxwill detect current project by looking for the.gitfolder
it in current directory or its parents.  If it fails to find
any.gitfolder, it will skip the rsync part.The script will not rsync.gitignoredfiles but it will sync untracked
files.The destination folder on remote machines is~/.cache/.rmux/<projectname>which will also become default directory.The remote user is based on host names or your ssh configuration.InstallationpipinstallrmuxWhilermuxis currently only a pure bash script, I used pip wheel as a way
to distribute it as it cross platform and easy to use. In addition, it allows
me to easily upgrade it.If you prefer you can
just download the shell script and add it to your path.See alsotmux- terminal multiplexertmux-xpanes- auto-window layout
for tmux, a current requirement for rmux. Still, it should be possible to
avoid using it if you have only one remote host, just make a feature request
and I can implement it.direnv- define environment variables specific to current directory. This can be very handy if you want to have different set of HOSTS
for each project and avoid mentioning them on the command line.rtoxwhich allows running tox on remote
machines this being the original project. With rmux you will no longer need
rtox as you can just dormux toxinstead ofrtox, the big difference
being that the session is not closed automatically and that you can now
run on multiple remote hosts instead of just one.LinksFree software: Apache licenseSource:https://github.com/pycontribs/rmuxBugs:https://github.com/pycontribs/rmux/issues
Package: rmw
rmw==rmw is short for "remind me when".It's a small service that uses RPC commands to set reminders for certain events.## Version.10 (In-progress)## Installationpip install rmw## Usage### Basic```rmw file foo.txt bar.txt other.txtCreated FileReminder for foo.txtCreated FileReminder for bar.txtCreated FileReminder for other.txttouch foo.txt...Broadcast Message from user@host (somewhere) at 22:12 ...Reminder for foo.txt: has been created```### Other quick reminders```rmw file {-lt,-gt} 3000 log.txt (Remind me when log.txt is less than or greater than 3MB)rmw process {-s} someprocess (Remind me when someprocess is started or stopped)```### Control commands```rmw {start,stop,restart} (Control the port, daemonization, status of the rpc server)...rmw show1. FileReminder for bar.txt2. FileReminder for other.txt...rmw clearAll reminders cleared```## TODO#### Generalallow pip build and installfind another way to do notifications besides 'wall'add 'sticky' reminders### Featuresrmw time -a 201501011159 (Remind me when the time is past 1/1/15 11:59)rmw time -e 1000 (Remind me when 1000 seconds have elapsed)rmw custom -e 500 -m "Don't forget to commit your changes!" (Remind me after 500 seconds to commit changes)
Package: rmwrapper
A simple Python wrapper Redditmetrics.comInstallationpip install rmwrapperDescriptionA very minimal wrapper forRedditmetrics.
Redditmetrics is a website that contains historical and recent data from all aroundReddit, be it subreddit-specific or general. This package aims to make it more comfortable to use that data with a simplistic interface, since Redditmetrics itself doesn't provide an API.Example usagefromrmwrapperimportRedditMetricsWrapper# Subreddit-specific methods take the subreddit names as arguments.RedditMetricsWrapper.subreddit_get_current_subscribers("lain")# Non-subreddit-specific methods don't take any arguments.RedditMetricsWrapper.get_fastest_growing_today()List of all available functionsSubreddit-specific:subreddit_get_subscriber_growth_data(subreddit)# Returns the entire available timeline for a specific subreddit and how many subscribers it gained per day.subreddit_get_subscriber_growth_data(subreddit)# Returns the entire available timeline for a specific subreddit and how many subscribers it had each day.subreddit_get_rank_data(subreddit)# Returns the entire available timeline for a specific subreddit and what the subreddit rank for it was.subreddit_get_current_subscribers(subreddit)# Returns the current subscriber count for a specific subreddit.subreddit_get_current_rank(subreddit)# Returns the current rank for a specific subreddit.General:get_fastest_growing_today()# Returns 300 fastest growing subreddits today.get_fastest_growing_week()# Returns 300 fastest growing subreddits this week.get_fastest_growing_month()# Returns 300 fastest growing subreddits this month.get_non_default_reddits_today()# Returns top 300 non-default subreddits today.get_non_default_reddits_week()# Returns top 300 non-default subreddits this week.get_non_default_reddits_month()# Returns top 300 non-default subreddits this month.get_top_new_reddits_today()# Returns top 300 new subreddits today.get_non_default_reddits_week()# Returns top 300 new subreddits this week.get_non_default_reddits_month()# Returns top 300 new subreddits this month.get_new_reddits_trending_month()# Returns top 300 trending subreddits this month.get_new_reddits_trending_3_months()# Returns top 300 trending subreddits in the last 3 months.get_new_reddits_trending_6_months()# Returns top 300 trending subreddits in the last 6 months.get_top_n_reddits(n)# Returns top n amount of subreddits sorted by subscriber count.
Package: rmy
An asyncio compatible RPC framework for building distributed applications.RMY provides a high level API allowing to expose objects from one process to the other. It frees programmers from having to handle communication between processes while still providing enough control when needed. The simplest possible use of RMY framework looks as follows.importrmyclassDemo:asyncdefgreet(self,name):returnf"Hello{name}!"if__name__=="__main__":rmy.run_tcp_server(8080,Demo())This will expose an instance of theDemoobject which can then be remotely accessed to as follows.importrmyfromhello_rmy_serverimportDemoif__name__=="__main__":withrmy.create_sync_client("localhost",8080)asclient:demo_remote=client.fetch_remote_object(Demo)whileTrue:print('Enter your name:')name=input()print(demo_remote.greet.eval(name))One can easily also asynchronously iterate through results generated by another object remotely. MY provides robust ways to iterate over (asynchronous) iterators applying back pressure if required. This allows to implement trivially Pub-Sub or any other event notification pattern easily. A trivial example of remote generator iteration might look like this.importrandomclassDemo:...asyncdefcount(self):foriinrange(1_000_000):awaitasyncio.sleep(random.uniform())yieldiOne can remotely iterate through the values using a normal loop.foriindemo_remote.count():print(i)For smplicity sake we showcased examples in synchronous code. One can easily make those asynchronous by instanciating an asynchronous client.
Package: rna
OverviewBasic and essential code building blocks of all pythonsLicensed under theMIT LicenseResourcesSource code:https://gitlab.mpcdf.mpg.de/dboe/rnaDocumentation:https://dboe.pages.mpcdf.de/rnaPypi:https://pypi.python.org/pypi/rnaFeaturesThe following features should be highlighted:TODO
Package: rna-cd
RNA Contamination Detectorrna_cd is a python package and command line tool designed to detect
RNA contamination of DNA-seq experiments.For our complete documentation, please checkout ourreadthedocs page.RequirementsPython 3.5+clickscikit-learnpysammatplotlibInstallationPyPI$ pip install rna-cdConda::$ conda install -c bioconda rna-cdLicenseAGPLv3+
Package: rnae
RNAERede Neural Artificial EvolucionáriaInstalation$pipinstallrneaou$pythonsetup.pyinstallUtilizaçãofromnumpy.randomimportshufflefromnumpyimportarrayfrompygenecimportbinarray2intfromrnaeimportRNAEfromrnaeimportIRISasdadosfromrnaeimportIRIS_NAME#Normalização dos dados de entradaentrada=dados[1:,0:-1].astype(float)forkinrange(entrada.shape[1]):entrada[:,k]=((entrada[:,k]-entrada[:,k].min())/(entrada[:,k].max()-entrada[:,k].min()))#Resultado esperado, em inteiro.saidas=dados[1:,-1]saidas=array([list(map(int,list("{0:2b}".format(int(s)).replace(" ","0"))))forsinsaidas])itrain=array(list(range(saidas.shape[0])))shuffle(itrain)etrain=entrada[itrain,:]esaid=saidas[itrain,:]n=int(esaid.shape[0]*0.90)neurons=[4,4,2]rna=RNAE(neurons)rna.treinamento(etrain[0:n,:],esaid[0:n,:],tpop=500,gens=1000,bits=16,pmut=0.1,pcruz=0.6,epidemia=150)rna.salvar_modelo("./modelos/rnae_iris.txt")rna=RNAE.carregar_modelo("./modelos/rnae_iris.txt")pred=rna.propagacao(etrain[n:,:])expct=esaid[n:]expct=binarray2int(expct).reshape((expct.shape[0],1))pred=binarray2int(pred).reshape((expct.shape[0],1))print("\n")print([IRIS_NAME[i]foriinpred.flatten().astype(int)])print("\n")print([IRIS_NAME[i]foriinexpct.flatten().astype(int)])print("\n")accu=100*sum(pred==expct)/expct.sizeprint("Acuracia{}%".format(accu))
Package: rna-genorm
geNormA Python package for RNAseq housekeeping (or, reference) normalisation.Read the docs.You can:Run the geNorm algorithm [1], which automatically selects reference genes by recursively eliminating genes with high $M$
value.Compute the gene-stability measure $M$ for reference genes in a given set of samples.Here, $M$ is defined in terms of the average variation in log-ratio expression:M_j = \sum_{k=1}^n\frac{V_{jk}}{n-1}whereA_{jk}^{(i)} = \log_2 \frac{a_{ij}}{a_{jk}}; V_{jk} = \sqrt{\mathrm{Var}(A_{jk})};with expression $a_{ij}$ referring to gene $j$ in sample $i$.InstallationYou can grabgeNormfrom the Python Package Index:pip3installrna-genormExamplefrompandasimportDataFramefromgenormimportm_measure,genorm# Expression data for three control genes.counts=DataFrame([[1,2,1],[3,6,5],[5,10,9],[3,6,5]],columns=['gene_a','gene_b','gene_c'],index=[f'sample_{i}'foriinrange(1,5)],)# Compute `M` value for this set of control genes.m_measure(counts)# Select top 2 control genes with lowest `M`.gene_names,m_values=genorm(counts,n_stop=2)AcknowledgementsMade by Hylke Donker & Bram van Es and open sourced under theApache 2 license.References:[1]: Vandesompele, Jo, et al. "Accurate normalization of real-time quantitative
RT-PCR data by geometric averaging of multiple internal control genes." Genome biology
3.7 (2002): 1-12.
Package: rnaget-client
Getting startedThis is a Python package that provides a client class, RnaGet, to access RNAget data. RNAget is an API standard implemented by the GA4GH that provides uniform access to large-scale RNAseq expression data across different studies and sources.UsageTo use this package, you need to import the RnaGet class:fromrnaget_clientimportRnaGetgtex=RnaGet(host='gtex')# gtex instanceencode=RnaGet(host='encode')# encode instanceanother_host=RnaGet(host='ANOTHER_URL',token='ACCESS_TOKEN')The host parameter should be set to the URL of the RNAget server that you want to access. You can also pass an optional token parameter to set an access token to access protected data.Available Methods:The RnaGet class provides the following methods to retrieve data from the RNAget server:get_filters(type, params=None): Get model filters, accepted values are: projects, studies, expressions, or continuous.

get_projects(version=None): Get the project list.

get_project(id): Get project by ID.

get_studies(version=None): Get the study list.

get_study(id): Get study by ID.

get_expression_list(format, download=False, **kwargs): Get the expression list.

get_expression(id, download=False, **kwargs): Get the expression object.

get_expression_formats(): Get data formats.

get_expression_units(): Get units.

get_continuous_list(format, download=False, **kwargs): Get the continuous list.For more information about the usage and parameters of these methods, please refer to theRNAget specs.You cangetrnaget-clientfrom PyPI,python-mpipinstallrnaget-client
Package: rnaglib
RNA Geometric Library (rnaglib)RNAglibis a Python package for studying RNA 2.5D and 3D structures. Functionality includes automated data loading, analysis,
visualization, ML model building and benchmarking.We host RNAs annotated with molecule, base pair, and nucleotide level attributes. These include, but are not limited to:Secondary structure3D coordinatesProtein bindingSmall molecule bindingChemical modificationsLeontis-westhof base pair geometry classificationCite@article{mallet2022rnaglib,
  title={RNAglib: a python package for RNA 2.5 D graphs},
  author={Mallet, Vincent and Oliver, Carlos and Broadbent, Jonathan and Hamilton, William L and Waldisp{\"u}hl, J{\'e}r{\^o}me},
  journal={Bioinformatics},
  volume={38},
  number={5},
  pages={1458--1459},
  year={2022},
  publisher={Oxford University Press}
}DataData can be downloaded directrly fromZenodoor through the provided command
line utility$ rnaglib_download.VersionDateTotal RNAsTotal Non-RedundantNon-redundant versionrnaglibcommit1.0.015-02-23575911763.2695446ae2c0.0.020-07-2137398993.186eb25dabdInstallationThe package can be cloned and the source code used directly. We also deploy it as a pip package and recommend using this
install in conda environments.If one wants to use GPU support, one should installPytorchandDGLwith the appropriate options. Otherwise you can just skip this step and
the pip installs of Pytorch and DGL will be used.Then, one just needs to run :pip install rnaglibThen one can start using the packages functionalities by importing them in one's python script.Optional DependenciesTo build 2.5D graphs from scratch locally, for the moment you need to install a fork offr3d-pythonmanually.pip install git+https://github.com/cgoliver/fr3d-python.gitAssociated Repositories:VeRNAlRNAMigosResourcesDocumentationHomepageTwitterContact:rnaglib@cs.mcgill.caReferencesLeontis, N. B., & Zirbel, C. L. (2012). Nonredundant 3D Structure Datasets for RNA Knowledge Extraction and
Benchmarking. In RNA 3D Structure Analysis and Prediction N. Leontis & E. Westhof (Eds.), (Vol. 27, pp. 281–298).
Springer Berlin Heidelberg. doi:10.1007/978-3-642-25740-7_13
Package: rnakinet
RNAkinetRNAkinet is a project dedicated to detecting 5eu-modified reads directly from the raw nanopore sequencing signal. Furthermore, it offers tools to calculate transcript halflives.UsageInstallationpipinstallrnakinetPredict 5EU in your fast5 filesrnakinet-inference--path<path_to_folder_containing_fast5s>--output<predictions_name.csv>This creates a csv file with columnsread_id- the read id,5eu_mod_score- the raw prediction score from 0 to 1,5eu_modified_prediction- Boolean column, True if the read is predicted to be modified by 5EU, False otherwiseNvidia GPU is recommended to run this command. If you want to run inference on a CPU-only machine, use the--use-cpuoption. This will substantially increase runtime.Examplernakinet-inference--pathdata/experiment/fast5_folder--outputpreds.csvCalculate transcript halflivesrnakinet-predict-halflives--transcriptome-bam<path_to_transcriptome_alignment.bam>--predictions<predictions_name.csv>--tl<experiment_tl>--output<halflives_name.csv>The--tlparameter is the duration for which the cells were exposed to 5EU in hoursThe--predictionsparameter is the output file of the 5EU prediction step described aboveThis creates a csv file with columnstranscript- the transcript identifier from your BAM file,reads- the amount of reads available for the given transcript,percentage_modified- the percentage of reads of the given transcript that were predicted to contain 5EU,pred_t5- the predicted halflife of the given transcriptExamplernakinet-predict-halflives--transcriptome-bamalignments/experiment/transcriptome_alignment.bam--predictionspreds.csv--tl2.0--outputhalflives.csvNote that the calculated halflivespred_t5are the most reliable for transcripts with at least 200 reads available
Package: rna-majiq
rna_majiq and rna_voilaThis is a placeholder package to reserve the pypi name and prevent confusion when installing the "majiq" and "voila" packages created by the
Biociphers Lab for quantification and visualization of RNA splicing from RNA-seq data. You most likely didn't mean to install this package
from pypi. Please seehttps://majiq.biociphers.org/for the full download and installation instructions of "majiq" and "voila"
Package: rname
randnamePython module to generate random name.SummaryRandname is a python module for generating random name - first and last. It uses official data from appropiate governmant/scientific reserch centers.Names are drawn with the consideration of their frequency. Therefor moste common name wil be drawn much more often (this feature can be disabled).Currently supported cuntries:
US, PL, ES.Default database is small, and constrained to 10000 records for each first and last names for every country.
Default data size: 60 000 recordsWith the full database downloaded from projectgithub page, the amount of names is increased to around 700 000 records.Table of ContentsProject TitleSummaryTable of ContentsInstallationUsageDocumentationDatabaseContributionAuthors & ContributorsTo DoLicenseInstallationRandnames is availabe in python repository, and can be downloaded with pip.pip3installrnameUsage>>>importrandname# Get name>>>randname.get_name("first")'John'>>>randname.get_name("last")'Doe'# Get first name>>>randname.first_name()'John'# Get last name>>>randname.last_name()'Doe'# Get full name>>>randname.full_name()'John Doe'# Setting dirrection to external database>>>randname.database_path="/path/to/external/database/"DocumentationDetailed documentation of module can by found here:randname documentationDatabaseDefault database included in pypi package is very small. To not make the package unnecessary too large, every country have one set of data for last and first names (with distinction for the male, female, neutral name), for the most recent year. Each file contains up to 10000 records.Currently supprted countries:US:2010, last names (neutral)2018, first names (male, female)PL:2020, last names (male, female)2021, first names (male, female)ES:2020, last names (male)2020, first names (male)Biger databaseFull database is bigger and doesn't have the limit of records. If you wan to use it, dowload it from projectgithub page.To use other databases specify directory by settingdatabase_pathvariable>>>importrandnames>>>randnames.database_path="path_to_your_database"More details about database can be foundhereContributionIf you want to contribute to randname projcet readcontributionfor more information.I am looking especially for help with database creation. More information on how to help/create appropiate data files with names can be found indatabase guideAuthors & ContributorsAuthor: Adam WalkiewiczContributors: Be first!To doSummaryToolsContribution guidelineUnit testsInstruction for database creationAdd equal chances for every nameSupport for other countries namesAdd 9 more countriesLicenseRandnames is licensed under the terms of theMIT license