Saravanan666/pypi-org huggingface dataset:
Package: be-proxy-ip
BE Proxy IPDefining Proxy IP objectHow to installpipinstallbe-proxy-ipHow to init ProxyIP objectUsing ProxyIP init>>>frombe_proxy_ipimportProxyIP>>>p=ProxyIP(proxy_ip='1.2.3.4',....proxy_port=8888,....proxy_username='hello',....proxy_pwd='doyouknow',....request_ip='1.2.3.4')>>>print(p)ProxyIP(proxy_ip='1.2.3.4',proxy_port=8888,request_ip='1.2.3.4',proxy_id=-1,num_ok_requests=0,num_banned_requests=0,num_timedout_requests=0,proxy_username='hello',proxy_pwd='*********',counted=0)Using ProxyIP.create_from_tupleOrder in PROXY_INFO tupleproxy_idproxy_ipproxy_portproxy_usernameproxy_pwdlast_request_timenum_ok_requestsnum_banned_requestsnum_timedout_requestscountedrequest_ip>>>PROXY_INFO=[...1,'1.2.3.4',3999,'hello-proxy','hellop-proxy-pwd',...-1,11,22,33,44,'4.5.6.7'...]>>>frombe_proxy_ipimportProxyIP>>>p=ProxyIP.create_from_tuple(PROXY_INFO)>>>print(p)ProxyIP(proxy_ip='1.2.3.4',proxy_port=3999,request_ip='4.5.6.7',proxy_id=1,num_ok_requests=11,num_banned_requests=22,num_timedout_requests=33,proxy_username='hello-proxy',proxy_pwd='****************',counted=44)
Package: berconpy
berconpyAn asynchronous Python wrapper over theBattlEye RCON protocol.FeaturesEasy to use event-based interfaceAutomatic network loss recoveryIncluded extension for using Arma-related commandsBasic Usageimportasyncioimportberconpyclient=berconpy.AsyncRCONClient()IP="XXX.XXX.XXX.XXX"PORT=9999PASSWORD="ASCII_PASSWORD"@client.dispatch.on_loginasyncdefon_login():print("We have logged in!")asyncdefmain():asyncwithclient.connect(IP,PORT,PASSWORD):players=awaitclient.send_command("players")print(players)asyncio.run(main())See thedocumentationfor more details.Installation(Python 3.10or higher is required)This package can be installed from PyPi using the following command:# Linux/macOS
python3 -m pip install berconpy

# Windows
py -m pip install berconpyIf you want to install the development version instead, and you have git installed:pip install git+https://github.com/thegamecracks/berconpyRelated resourcesBattlEye RCON protocol specificationBattlEye RCON commandsArma server commandsLicenseThis project uses theMITLicense.
Package: berend
Berend======Berend is a Twisted IRC bot with SSL-support. If you use this module,you will not have to write any of the boilerplate and instead canfocus on programming the behavior of your bot.If you use SSL, there is no certificate checking so beware!Usage-----To build a bot you need to write a bot config file (yaml) and someplugins (simple python modules).The default config file berend will look for is `berend.yaml`. If youwant to use a different config file, then you need to set the`BEREND_CONFIG` environment variable to its path.An example bot config file is included in the distribution and lookslike this:berend.yaml:irc:host: irc.freenode.netssl: trueport: 6697channels:- berend-botje-testnickname: berendrealname: Berend Botje# on_connect is a list of raw commands sent to the server on connect,# use this to identify for example:##  on_connect:#    - "PRIVMSG NickServ :identify berend secret"plugins:berend.plugins.help:myberend.plugins.hello:Add your plugins to the bottom. The key is the importable,dot-separated python module name, the value is passed on to yourplugin's setup method. Look at the help plugin for a fully documentedexample.An example plugin looks like this:myberend/plugins/hello.py:def setup(bot, config):bot.respond('hello', hello, ('hello', 'force bot to greet you'))def hello(bot, user, channel, msg, matches):bot.reply(user, channel, 'hello to you %s' % user)See Also--------The bot is a Twisted IRC client. Check out the [Twisted documentation](http://twistedmatrix.com/documents/12.2.0/api/twisted.words.protocols.irc.IRCClient.html) and the [ircLogBot example](http://twistedmatrix.com/documents/current/core/howto/clients.html#auto5) for more information.Oh and of course: [Berend Botje](http://nl.wikipedia.org/wiki/Berend_Botje_ging_uit_varen)
Package: beret-beige
Bayesian variantEffectInference withGuide counts andEditing outcome.This is a generative-model-based CRISPR screen analysis software for that can account for:bar_chart: Multiple FACS sorting bins:waning_gibbous_moon: Incomplete editing rate:mag: Multiple target variant/bystander edit (under development)BEIGE models the cellular phenotype of CRISPR sorting screen data as mixture distribution. The cells will be sorted based on the theoretical quantile based on (unperturbed) control distribution and your FACS sorting quantiles. The sorted samples (red box in below schematic) are sequenced to produce the final guide counts.Its inference uses SVI (Stochastic Variational Inference) throughPyroto fit the posterior phenotype distribution of target element perturbation.Installationpip install beret-beigeUsageCRISPR screen data without reporter informationbeige myScreen.h5ad --prefix=my_analysis [--fit-pi|--perfect-edit|--guide_activity_column]myScreen.h5admust be formatted inScreenobject inperturb-toolspackage.
If you don't have reporter information measured, you can take one of three options for analysis:--fit-pi: Editing rate is fitted so that overall likelihood of the model is maximized.--perfect-edit: Assuming editing rate is 1 for all guides. This option is recommended over 1) based on the inference accuracy in simulation data.--guide_activity_column=your_col_name: If you want to use external information about guide activity estimated using other software, input the guide activity in the Screen.guides DataFrame (seeScreenobject inperturb-tools).Pass the column name as the argument.(under development)CRISPR screen data with reporter informationbeige myReporterScreen.h5ad --prefix=my_analysis [--rep-pi]myReporterScreen.h5admust be formatted inReporterScreenobject inberetpackage.--rep-pi: If you suspect your biological replicate will have overall different level of editing rates, you can let the model to fit the replicate specific scaling factor of editing rate using this option.CaveatBEIGE assumes the phenotype distribution pre-sort sample is the same as the negative control. Whereas this assumption can be safely considered as true in case of variant screens, this may not hold true if you expect large phenotypical shift for the majority of perturbed elements.
Package: berets
BaseEditing withReporter analysisToolkit.This is an analysis toolkit for the pooled CRISPR reporter or sensor data. The reporter technique transfects cells with plasmid with not only sgRNA but with thetarget sequence surrogatewhich we callreporterorsensor.InstallationDownloading from PyPI:pip install beretsCount reporter screen dataAligns guide with matched reporter allele counts in multiple samples.beret-count-samples\--inputsample_list.csv\# sample with lines 'R1_filepath,R2_filepath,sample_name\n'-bA\# base that is being edited (A/G)-fgRNA_library.csv\# sgRNA information-o.\# output directory-a\# read allele information-r\# read reporter edit information-m\# read matched guide and reporter edit information-t12\# number of threads--nameLDLvar_fullsort\# name of this sample runThis produces.h5adand.xlsxfile with guide and per-guide allele counts..h5adfile follows annotated matrix format compatible withAnnDataand is based onScreenobject inpurturb_toolsand contains the per-guide allele counts.Using as python moduleimport beret as br
cdata = br.read_h5ad("beret_counts_sample.h5ad")See thetutorialfor more detail.
Package: bergamot
bergamot-translatorTheBergamot projectadds and improves client-side
machine translation in a web browser.This package provides Python bindings to bergamot-translator developed as part
of the Bergamot Project and extras assorted in a package to enable further use
of the library developed for local-translation on the consumer machine.Bergamot is a consortium coordinated by the University of Edinburgh with
partners Charles University in Prague, the University of Sheffield, University
of Tartu, and Mozilla.
Package: bergen
BergenIdeaBergen is the API-Client for the Arnheim FrameworkPrerequisitesBergen only works with a running Arnheim Instance (in your network or locally for debugging).UsageIn order to initialize the Client you need to connect it as a Valid Application with your Arnheim Instanceclient=Bergen(host="p-tnagerl-lab1",port=8000,client_id="APPLICATION_ID_FROM_ARNHEIM",client_secret="APPLICATION_SECRET_FROM_ARNHEIM",name="karl",)In your following code you can simple query your data according to the Schema of the Datapointfrombergen.schemaimportNodenode=Node.objects.get(id=1)print(node.name)Access Data from different DatapointsThe Arnheim Framework is able to provide data from different Data Endpoints through a commong GraphQL Interface
. This allows you to access data from various different storage formats like Elements and Omero and interact without
knowledge of their underlying api.Each Datapoint provides a typesafe schema. Arnheim Elements provides you with an implemtation of that schema.Provide a Template for a NodeDocumentation neccesaryTesting and DocumentationSo far Bergen does only provide limitedunit-tests and is in desperate need of documentation,
please beware that you are using an Alpha-VersionBuild withArnheimPydanticFeaturesScssDomain-stylefor code structureBundle Size analysisCode splitting withreact-loadableRoadmapThis is considered pre-Alpha so pretty much everything is still on the roadmapDeploymentContact the Developer before you plan to deploy this App, it is NOT ready for public releaseVersioningThere is not yet a working versioning profile in place, consider non-stable for every releaseAuthors**Johannes Roos ** -Initial work-jhnnsrsSee also the list ofcontributorswho participated in this project.LicenseAttribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)AcknowledgmentsEVERY single open-source project this library used (the list is too extensive so far)
Package: berglas
This library automatically parses berglas references when imported.Only Python 3.6+ is supported currently.You can find the latest, most up to date, documentation onGithub.Quick StartInstall library:pipinstallberglasImport the module:importberglas.auto# noqaWhen imported, theberglasmodule will:1. Detect the runtime environment and call the appropriate API to get the list
of environment variables that were set on the resource at deploy time1. Download and decrypt any secrets that match theBerglas environment
variable reference syntaxReplace the value for the environment variable with the decrypted secretYou can also opt out of auto-parsing and call the library yourself instead:importosfromberglasimportresolverif__name__=='__main__':client=resolver.Client()client.replace("MY_SECRET")print(os.environ["MY_SECRET"])//alternatively,useresolvemethodtosimplygetthevaluewithoutupdatingenvironment:my_secret=client.resolve(os.environ["MY_SECRET"])print(my_secret)Release Notesv0.1First versionDevelopmentGetting StartedAssuming that you have Python,pyenvandpyenv-virtualenvinstalled, set up your
environment and install the required dependencies like this instead of
thepip install berglasdefined above:$gitclonehttps://github.com/maroux/berglas-python.git$cdpython$pyenvvirtualenv3.9.14berglas-3.9...$pyenvshellberglas-3.9$pipinstallsetuptools==58$pipinstall-rrequirements/dev-3.9.txtUpdating Requirements FilesUpdate theinstall_requiresvariable insetup.pyand then from the pyenv virtualenv shell run:
.. code:: sh$ python -m pip install pip==18.0 pip-tools==3.2.0 –upgrade
$ make pip_compileRunning TestsYou can run tests in usingmake test. By default,
it will run all of the unit and functional tests, but you can also specify your ownpy.testoptions.$py.testGetting HelpWe use GitHub issues for tracking bugs and feature requests.If it turns out that you may have found a bug, pleaseopen an issue
Package: berglas-python
OverviewPython library help to useBerglas, to encrypt and to decrypt the secrets stored in a GCP storage.SeeBerglasfor details about bucket bootstrapping and secret creationLibrary UsageYou have to get the librarypip install berglas-pythonThen use it in the same way asGo libraryThe library berglas_python library is able to:Encrypt and upload the secretsDownload and decrypt any secrets that match theBerglas environment variable reference syntaxReplace the value for the environment variable with the decrypted secretHere an example of usageimport os

import berglas_python as berglas

project_id = os.environ.get("MY-PROJECT")

# This higher-level API parses the secret reference at the specified
# environment variable, downloads and decrypts the secret, and replaces the
# contents of the given environment variable with the secret result.

berglas.Replace(project_id, "MY-SECRET")

# This lower-level API parses the secret reference, downloads and decrypts
# the secret, and returns the result. This is useful if you need to mutate
# the result.
my_secret = os.environ.get("MY-SECRET")
plaintext = berglas.Resolve(project_id, my_secret)
os.environ.unsetenv("MY-SECRET")
os.environ.setdefault("MY-SECRET", plaintext)

# This is lower-level API encrypts the plaintext string and uploads the blob
berglas.Encrypt(project_id, 'MY-BUCKET/MY-SECRET-FILE', 'STRING-TO-ENCRYPT')LicenseThis library is licensed under Apache 2.0. Full license text is available inLICENSE.
Package: berhoelodf
Lightweight and limited access to odf files using lxml.It is just used by me for a limited project of converting a
spreadsheet toDjangodata. For me this package works much faster
thanodfpy. Just loading my 5.7MB ods file took 1.5 minutes. This
package is based onlxml, andlxmlparses the XML in 2
seconds, the whole processing toDjangotakes about 1.5 minutes.If you have other requirements, the code should be easily extensible.Installationpip install berhoelodfAvailabilityThe latest version should be available at myGitLabrepository, the
package is avaliable atpypiviapip install berhoelodf.DocumentationDocumentation is hosted onhöllmanns.de.
Package: bericht
Incremental HTML to PDF converter with support for extremely large documents. Bericht does not
hold the HTML or the PDF in memory as it generates PDF pages; instead, it requires you to pass a
generator which produces HTML snippets andberichtgives you a PDF stream iterator. As you iterate
the PDF streamberichtwill parse just enough HTML to produce a single page and return one page
at a time which you can either write to a file, send over http or do whatever you need.Main features:Quickly and efficiently generate on-demand PDFs from databases or other data sources.Use familiar HTML and CSS to define your PDF layout.Re-use the same code to produce HTML and PDF based reports for your users.Ability to generate extremely large PDF files without storing any of the parts (input or output) in memory.Many CSS extensions specifically for print/page related formatting:@page:nth-child(an+b): at-rule to target/style individual pages (non-standard CSS).@page {letterhead-page:1; }: ability to apply specific pages from another PDF as a
watermark/letterhead in your newly generated PDF (the other PDF must be passed as argument
toberichtgenerator to be able to extract pages from it usingletterhead-pageCSS attribute).thead:nth-child(an+b)andtfoot:nth-child(an+b):berichtcan repeat table headers/footers
on subsequent pages when the table does not fit on one page, this rule allows you to style those
rows differently depending on what page they are on (non-standard CSS).0.1.6Font handling bug fix.More tests.0.1.5Table rendering fix.0.1.04Added missing files in MANIFEST.in0.1.03Various bug fixes and refactoring.0.1.02Table cell rendering fix.0.1.01Major rewrite of parser and drawing code to be more forgiving for broken HTML.
Package: berk
Berkis a package for fetching and processingMeerKATdata on a compute cluster usingOxkatfor calibration and imaging, andPyBDSFfor generating object catalogs.Documentation:https://berk.readthedocs.ioLicense:GPL v3Authors:Matt HiltonInstallation:pip install berkSupport:Please use theGitHub issues page,
and/or contactMatt Hilton.Berkshould run on any compute cluster that runs either Slurm or PBS as a
workload manager. It is is being developed and deployed onHippo,
the High Performance Computing facility at the University of KwaZulu-Natal,
and at theCentre for High Performance Computing,
with the aim of using it to perform a serendipitous survey with MeerKAT, and in
turn to generate useful high-level processed MeerKAT data (initially,
continuum images and catalogs) for use by the community.Berkis under active development, and not all documentation may be up to date.
Not all needed features are implemented yet. However, at the moment, data
can be fetched from the archive, processed to images and catalogs, and collected
from multiple compute clusters using only a few shell commands.Berkis named after the faithful servant ofThe Thing Upstairs.
Package: berkeley500A
This is an API for the Berkeley Nucleonics Corp Modell 500 A Digital Delay GeneratorAuthor: Markus J SchmidtVersion: 0.1.0class berkeley500AErrorException class is raisedclass berkeley500AClass object for the delay generator.ExamplecomPort = 'COM1'
delayGen = berkeley500A(comPort)
print(delayGen.gate)
print(delayGen.getEcho())
Package: berkeleydb
This module provides a nearly complete wrapping of the Oracle/Sleepycat C API
for the Database Environment, Database, Cursor, Log Cursor, Sequence and
Transaction objects, and each of these is exposed as a Python type in the
berkeleydb.db module. The database objects can use various access methods:
btree, hash, recno, queue and heap.  Complete support of Oracle Berkeley DB
distributed transactions. Complete support for Oracle Berkeley DB Replication
Manager. Complete support for Oracle Berkeley DB Base Replication.Please see the documents in the docs directory of the source distribution or at
the website for more details on the types and methods provided. The goal is to
mirror most of the real Oracle Berkeley DB API so fall back to the Oracle
Berkeley DB documentation as appropriate.If you need to support ancient versions of Python and/or Oracle Berkeley DB ,
you can use legacybsddb3library.Homepage–Releases (changelog)–Documentation–Mailing List–Donation
Package: berlin-appointment-finder
Bürgeramt appointment finderThis server looks for Bürgeramt appointment every few seconds. You can make it look for any kind of appointment.This is the code behind All About Berlin'sBürgeramt appointment finder.If this tool helped you,make a donation. Building things for Berliners is my full time job.What this tool doesThis tool looks for appointments on service.berlin.de every 3 minutes. When it finds an appointment, it makes a sound. It can be used as a command line tool, or as the backend for aweb-based tool.This tool can't book the appointment for you. It can't look for Ausländerbehörde appointments. These features will not be implemented.Setup1. Install the scriptRun this command in your terminal:# It might be called 'pip3' on your computerpipinstallberlin-appointment-finderYou need Python 3 on your computer. If you have macOS or Linux, you already have it. If you have Windows, you're on your own.If you get aerror: legacy-install-feature, try some of thesolutions listed here. Do not open an issue; the problem is not related to this project.2. Find the appointment type you needPick a service from thelist of services on Berlin.de, and copy the URL. For example,https://service.berlin.de/dienstleistung/120686/for theAnmeldung.3. Run the scriptRun this command and follow the instructions on your screen:appointmentsThe script will check Berlin.de every 3 minutes. When it finds appointments, it lists them. Just keep an eye on the terminal. It will also emit a sound.Updating the scriptIf you have an older version of the script, update it with this command:pip install --upgrade berlin-appointment-finderInstructions for nerdsThis script can be configured with command line arguments or environment variables.Typeappointments --helpto see available command line arguments.These are the available environment variables:BOOKING_TOOL_EMAIL=your@email.comBOOKING_TOOL_ID=johnsmith-devBOOKING_TOOL_URL=https://service.berlin.de/dienstleistung/120686/The script broadcasts broadcasts the appointments it finds with websockets. By default, it broadcasts them on port 80.A Dockerfile is supplied in this repo. It's the same one I use on All About Berlin.The polling rate is limited to 180 seconds (3 minutes), as required by the Berlin.de IKT-ZMS team (ikt-zms@seninnds.berlin.de).Local developmentTo work on this script, install it withpip install -e /path/to/this/repo. When you runappointments, it will run your local version with any changes you have made to it. You only need to run this command once.FAQCan you make it work with Ausländerbehörde appointments?No. It's not possible due to rate-limiting by Berlin.de.You probably don't need an Ausländerbehörde appointmentanyway.I get an HTTP 418 responseThis means that Berlin.de is blocking you as a bot. There is nothing I can do to fix this problem.
Package: berliner
berlinerTools for stellar tracks & isochrones.authorBo Zhang,bozhang@nao.cas.cnhome pagehttps://github.com/hypergravity/berlinerhttps://pypi.org/project/berliner/installfor the lateststableversion:pip install berlinerfor the latestgithubversion:pip install git+git://github.com/hypergravity/berlinerHow to download isochrones from CMD 3.4last tested: 2021-03-31# import CMDfromberliner.parsecimportCMD# initialize itc=CMD()# Example 1: download one isochronec.get_one_isochrone(logage=9.0,# log agez=0.0152,# if [M/H] is not set, z is usedmh=None,# [M/H]photsys_file='2mass_spitzer',# photometric system)# Example 2: download a grid of isochrones# define your grid of logAge and [M/H] as tuple(lower, upper, step)grid_logage=(6,10.2,0.1)grid_mh=(-2.6,0.5,0.1)# download isochrones in parallelisoc_lgage,isoc_mhini,isoc_list_2mass_wise=c.get_isochrone_grid_mh(grid_logage=grid_logage,grid_mh=grid_mh,photsys_file="2mass_spitzer_wise",n_jobs=50,verbose=10)# More ...c.help()# take a look at the output, it may help you!
Package: berlin-opendata-downloader
Download Client for Berlin GeländemodelleDownloadsBerlins' height information(Digitale Geländemodelle – ATKIS DGM - Höheninformationen), can compress them on the fly, and creates GeoJSON, CSV or txt files if desired.Documentation:https://berlin-gelaendemodelle-downloader.readthedocs.io/en/latest/What means 'Compress'Compression means tiles, shaped as windows, are averaged. Because one subset of the data is of shape2000x2000, the tile size, argumentcompress, have to divide 2000 without remainder.The following image (Original) shows the structure of the data subsets (tiles).Getting StartedFollow these instructions to get theberlin-downloaderup and running.Prerequisitespython 3.6 or greaterpip3Installationpip3installberlin-opendata-downloaderor directly from the repository:gitclonehttps://github.com/se-jaeger/berlin-gelaendemodelle-downloadercdberlin-gelaendemodelle-downloader
pythonsetup.pyinstallExample Usageberlin_downloaderdownload~/berlin_height--compress5--keep_original--file-formatcsv--file-formatgeojsonDownloads and saves the data at~/berlin_heightas vsc and geojson file, as well as compressed csv and geojson files.Thank You! :heart:Many thanks tochrisschroerfor the offline discussions and contributions.NoteThis project has been set up using PyScaffold 3.2.3. For details and usage
information on PyScaffold seehttps://pyscaffold.org/.