Saravanan666/pypi-org huggingface dataset:
Package: birdcage
Use Birdcage to constrain tweets.Library to take text collections and create a Phrase of those text collections
and fit within the specified length.This is what the library does:$ birdcage/example.py
No maximum set, generate phraseexpecting: one hour, fourty-five minutes until armageddon strikes the earth
expecting: one hour, fourty-five minutes until armageddon strikes the earthNo maximum length set, generate phrase with “: “ as the delimiterexpecting: one hour, fourty-five minutes: until armageddon strikes the earth
expecting: one hour, fourty-five minutes: until armageddon strikes the earthSet a maximum length of 40 charactersexpecting: 1h45m until armageddon strikes the ea…
expecting: 1h45m until armageddon strikes the ea…
Package: birdclient
Python BIRD ClientThebirdclientPython package provides a BIRD client implemented in Python.LicensePermission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
of the Software, and to permit persons to whom the Software is furnished to do
so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: bird-cloud-gnn
Bird Cloud GNNSynopsisThis software produces a graph representation derived from point cloud data, which is then used as input for a Graph Neural Network (GNN).This allows to increase the amount of data by the factor of 1000.Code exampleMotivationIn scenarios where labeled data is limited, there's a pressing need to expand the dataset effectively. One effective strategy involves altering the data's representation. In this context, we adopted such an approach by acquiring a graph representation from point cloud data. Depending on the chosen parameters, this transformation can augment the dataset by a factor of up to 1000. Subsequently, this graph representation is harnessed as input for Graph Neural Networks (GNNs). GNNs are highly sought after due to their innate ability to adeptly capture and leverage the inherent properties of graph-structured data. They excel in modeling intricate network relationships, autonomously acquiring informative features, and facilitating effective knowledge transfer.InstallationTo install bird_cloud_gnn from GitHub repository, do:git clone https://github.com/point-cloud-radar/bird-cloud-gnn.gitcd bird-cloud-gnnpython3 -m pip install .DocumentationThe documentation can be found onRead the Docs.ContributingIf you want to contribute to the development of bird_cloud_gnn,
have a look at thecontribution guidelines.CreditsThis package was created withCookiecutterand theNLeSC/python-template.
Package: birdepy
BirDePy: Birth-and-death processes in PythonBirDePy is a Python package for working with continuous time birth-and-death processes. It includes functions which can be used to approximate transition probabilities (birdepy.probability()), estimate parameter values from data (birdepy.estimate()), simulate sample paths (birdepy.simulate.discrete()andbirdepy.simulate.continuous()) and generate forecasts (birdepy.forecast()). The main focus of the package is the estimation of parameter values from discretely-observed sample paths, however the much more straightforward case of estimation of parameter values from continuously observed sample paths is also included.Please visit our website:https://birdepy.github.io/
Package: bird-feeder
Bird Feeder (the bird)Feed the Birds …Bird Feeder is parsing Thredds catalogs and local directories withNetCDFfiles and publishes metadata with download URLs to a Solr index service with a birdhouse schema.Install from Anaconda$condainstall-cbirdhousebird-feederInstall from GitHub$gitclonehttps://github.com/bird-house/bird-feeder.git$cdbird-feeder$makeinstallStart Solr service onhttp://localhost:8983/solr/birdhouse:$makestart$makestatusUsing the command lineHelp:$birdfeeder-husage:birdfeeder[<options>]<command>[<args>]FeedsSolrwithDatasets(NetCDFFormat)fromThreddsCatalogsandFileSystem.optionalarguments:-h,--helpshowthishelpmessageandexit--debugenabledebugmode--serviceSERVICESolrURL.Default:http://localhost:8983/solr/birdhouse--maxrecordsMAXRECORDSMaximumnumberofrecordstopublish.Default:-1(unlimited)--batch-sizeBATCH_SIZEBatchsizeofrecordstopublish.Default:50000command:Listofavailablecommands{clear,from-thredds,from-directory}Run"birdfeeder <command> -h"togetadditionalhelp.clearClearsthecompletesolrindex.Usewithcaution!from-threddsPublishdatasetsfromThreddsCatalogtoSolr.from-directoryPublishNetCDFfilesfromdirectorytoSolr.Parse a Thredds catalog (recursively until depth level 2):$birdfeederfrom-thredds--catalog-urlhttp://example.com/thredds/catalog.xml--depth=2Parse local NetCDF files:$birdfeederfrom-directory--start-dir/home/data/myarchiveAuthorsCarsten Ehbrecht ehbrecht at dkrz.deChange History0.1.2 (2015-09-18)Fixed #3: convert relative path to abs path for feeding from directory.0.1.1 (2015-07-28)Initial Release.
Package: birdfeeder-coinalpha
birdfeederHelper library for CoinAlpha projectsUsageThe library is published to pypi asbirdfeeder-coinalphaInstallingpip install birdfeeder-coinalphapoetry add 'birdfeeder-coinalpha@^1'How to install old versionsIn pyproject.toml:birdfeeder-coinalpha = { git = "https://github.com/coinalpha/birdfeeder.git", branch = "master" }
birdfeeder-coinalpha = { git = "https://github.com/coinalpha/birdfeeder.git", rev = "29cdd7229d0d35a989322f5026382400d1332da4" }
birdfeeder-coinalpha = { git = "https://github.com/coinalpha/birdfeeder.git", tag = "0.1.0" }pip:git+https://github.com/coinalpha/birdfeeder.git@master#egg=birdfeeder
git+https://github.com/coinalpha/birdfeeder.git@29cdd7229d0d35a989322f5026382400d1332da4#egg=birdfeeder
git+https://github.com/coinalpha/birdfeeder.git@0.1.0#egg=birdfeederDevelopmentTo install library for development in conda environment, run./installAlternativelly (preferred), you can use poetry env:poetry install
poetry shellHow to add a dependencyIf you're running in conda, you need to install required package first.Then, see installed version inconda env exportTake this version and add into pyproject.toml, into[tool.poetry.dependencies](or dev section, if the package is needed for development only). Specify version (or range) according toDependency SpecificationIf using poetry:Runpoetry add <package>Releasing a new versionIdea: we're keeping own version and dependencies info inpyproject.toml, and then generatingsetup.pyso that the library could be installed via tools like pip. We're also generatingenvironment.ymlfile because we're mostly using conda to manage development environments at CoinAlpha.Change version inpyproject.tomlandbirdfeeder/__init__.pyGeneratesetup.py:dephell deps convertGenerateenvironment.yml:poetry2conda --dev pyproject.toml environment.ymlCommit updatesgit add -u && git commitCreate git tagx.y.z:git tag -s x.y.zRungit push && git push --tagsPublish to pypi:poetry publish --build
Package: birdhousebuilder.recipe.celery
Introductionbirdhousebuilder.recipe.celeryis aBuildoutrecipe to install and configureCeleryDistributed Task Queue withAnaconda.
This recipe is used by theBirdhouseproject.The recipe is based oncollective.recipe.celery.UsageThe recipe requires that Anaconda is already installed. You can use the buildout optionanaconda-hometo set the prefix for the anaconda installation. Otherwise the environment variableCONDA_PREFIX(variable is set when activating a conda environment) is used as conda prefix.The recipe will install thecelerypackage from a conda channel in a conda enviroment defined byCONDA_PREFIX. It deploys aSupervisorconfiguration for Celery in{{prefix}}/etc/supervisor/conf.d/celery.conf. Supervisor can be started with{{prefix}}/etc/init.d/supervisordstart.The recipe depends onbirdhousebuilder.recipe.condaandbirdhousebuilder.recipe.supervisor.Supported optionsanaconda-homeBuildout option pointing to the root folder of the Anaconda installation. Default:$HOME/anaconda.Buildout options forcelery:appThe application instance to use for the celery worker.eggsA list of additional eggs you want to make available to Celery. Use this to
add additional dependencies and the module(s) containing your task definitions.use-celeryconfigGenerate and use theceleryconfig.py. Set tofalseif Celery is configured e.a. bypyramid_celery. Default:true.Celery configuration optionsThe following configuration options are supported. SeeCelery documentationfor more details.broker-urlThe url of the broker. Default:redis://localhost:6379/0celery-result-backendThe url of the backend used to store task results. Default:redis://localhost:6379/0celery-importsList of modules to import when celery starts.celeryd-concurrencyThe number of concurrent worker processes/threads/green threads executing tasks. Defaults to the number of available CPUs.loglevelLogging level, choose between DEBUG, INFO, WARNING, ERROR, CRITICAL, or FATAL. Default: WARNINGExample usageThe following examplebuildout.cfginstalls Celery with Anaconda and default options:[buildout]parts=celeryanaconda-home=/home/myself/anaconda[celery]recipe=birdhousebuilder.recipe.celeryapp=mystuff_appeggs=mysuffThe next example shows a configuration withpyramid_celeryand enabled Flower monitoring:[buildout]parts=celeryanaconda-home=/home/myself/anaconda[celery]recipe=birdhousebuilder.recipe.celeryapp=pyramid_celery.celery_app --ini default.inieggs=mysuffuse-celeryconfig=falseAuthorsCarsten Ehbrecht ehbrecht at dkrz.deChanges0.2.0 (2016-07-04)using bool_option from zc.buildout.using zc.recipe.deployment.removed flower.0.1.3 (2016-06-13)added update-conda option.use flower, redis and pymongo only if necessary.0.1.2 (2016-06-03)added CELERY_MONGODB_BACKEND_SETTINGS config option0.1.1 (2015-12-10)Renamed celeryconfig.py template.0.1.0 (2015-12-10)Initial Release.
Package: birdhousebuilder.recipe.docker
Introductionbirdhousebuilder.recipe.dockeris aBuildoutrecipe to generate aDockerfileforBirdhouseapplications.UsageThe recipe will generate a Dockerfile for your Birdhouse application. You can find the Dockerfile in the root folder of the application.Supported optionsThis recipe supports the following options:appThe name of your application. Default: birdhousemaintainerThe maintainer of the Dockerfile.descriptionDescription of the Dockerfile.vendorThe vendor of the application. Default: BirdhouseversionThe version of the application. Default: 1.0.0hostnameThe hostname of the docker container. Default: localhosthttp-portThe HTTP port of the app service. Default: 8080https-portThe HTTPS port of the app service. Default: 8443output-portThe WPS output port of the wps apps service. Default: 8000Example usageThe following examplebuildout.cfggenerates a Dockerfile:[buildout]parts=docker[docker]recipe=birdhousebuilder.recipe.dockerapp=emumaintainer=Birdhousedescription=Emu WPS Applicationversion=0.5.0hostname=emu-demo.localhttp-port=8094output-port=38094AuthorsCarsten Ehbrecht ehbrecht at dkrz.deChanges0.5.3 (2017-05-11)added volume for etc/ in Dockerfile.0.5.2 (2016-10-21)changed default ports, generate .env file for docker-compose0.5.1 (2016-10-20)fix folder permissions of etc/ and var/run/ in Dockerfile.0.5.0 (2016-10-19)update recipe to buildout deployment.simplified Dockerfile.removed custom.cfg template.0.4.8 (2015-12-23)update readme.fixed settings and buildout-options.0.4.7 (2015-12-23)fixed /data volume permissions.added update-user as default command.add buildout-options for docker.cfg.added default envs hostname and user.0.4.6 (2015-12-22)using only volume /data for /var/lib in Dockerfile.0.4.5 (2015-12-17)fixed command generation in Dockerfile.0.4.4 (2015-12-16)addedcommandoption.custom.cfg for docker is copied to.docker.cfg.added.dockerignorefile.0.4.3 (2015-12-15)added settings option to generate a custom.cfg for docker image.0.4.2 (2015-12-14)added git-url, git-branch, subdir and buildout-cfg options.0.4.1 (2015-12-10)fixed setting of EXPOSE in Dockerfile.0.4.0 (2015-12-10)added environment and expose options.enabled travis.0.3.2 (2015-09-25)fixed malleefowl default port in dockerfile template.changed dockerfile volumes.0.3.1 (2015-09-24)updated Dockerfile template.added output-port option.0.3.0 (2015-09-22)updated Dockerfile template.more options added.0.2.2 (2015-08-05)cleaned up … removed conda dependency.update to buildout 2.x.0.2.1 (2015-04-13)Updated Dockerfile template for CentOS builds (sudo was missing).0.2.0 (2015-03-16)Updated Dockerfile template for birdhouse environments.0.1.1 (2014-11-13)Updated Dockerfile template … starts only supervisord.Fixed example in Readme.0.1.0 (2014-11-05)Initial Release.
Package: birdhousebuilder.recipe.mongodb
Introductionbirdhousebuilder.recipe.mongodbis aBuildoutrecipe to install and setupMongoDBwithAnaconda.
This recipe is used by theBirdhouseproject.UsageThe recipe requires that Anaconda is already installed. You can use the buildout optionanaconda-hometo set the prefix for the anaconda installation. Otherwise the environment variableCONDA_PREFIX(variable is set when activating a conda environment) is used as conda prefix.The recipe will install themongodbpackage from a conda channel in a conda environment defined byCONDA_PREFIX. It setups aMongoDBdatabase in{{prefix}}/var/lib/mongodb. It deploys aSupervisorconfiguration for MongoDB in{{prefix}}/etc/supervisor/conf.d/mongodb.conf. Supervisor can be started with{{prefix}}/etc/init.d/supervisorstart.The recipe depends onbirdhousebuilder.recipe.condaandbirdhousebuilder.recipe.supervisor.Supported optionsThe recipe supports the following options:anaconda-homeBuildout option pointing to the root folder of the Anaconda installation. Default:$HOME/anaconda.Buildout options formongodb:bind-ipThe IP address that mongodb binds to in order to listen for connections from applications. Default: 127.0.0.1portThe TCP port on which the MongoDB instance listens for client connections. Default: 27017Example usageThe following examplebuildout.cfginstalls MongoDB with Anaconda:[buildout]
parts = myapp_mongodb

[myapp_mongodb]
recipe = birdhousebuilder.recipe.mongodb
port = 27020AuthorsCarsten Ehbrecht ehbrecht at dkrz.deChanges0.4.0 (2016-10-20)updated to yaml config for mongodb 2.6pep80.3.0 (2016-06-19)using zc.recipe.deployment.separate conda env from install-prefix.0.2.2 (2015-10-07)bind_ipandportare now configurable.logs to supervisor.0.2.1 (2015-06-25)added user option.0.2.0 (2015-02-24)installing in conda enviromentbirdhouse.using$ANACONDA_HOMEenvironment variable.separation of anaconda-home and installation prefix.0.1.1 (2014-08-01)Updated documentation.0.1.0 (2014-07-10)Initial Release.
Package: birdhousebuilder.recipe.postgres
ContentsIntroductionUsageSupported optionsExample usageAuthorsChange History0.2.0 (2015-03-31)0.1.0 (2015-03-30)Introductionbirdhousebuilder.recipe.postgresis aBuildoutrecipe to install and configurePostgresdatabase withAnaconda.Postgreswill be deployed as aSupervisorservice.The recipe is based onhttps://github.com/makinacorpus/makina.recipe.postgres.This recipe is used by theBirdhouseproject.UsageThe recipe requires that Anaconda is already installed. It assumes that the default Anaconda location is in your home directory~/anaconda. Otherwise you need to set theANACONDA_HOMEenvironment variable or the Buildout optionanaconda-home.It installs thepostgresqlpackage from a conda channel in a conda environment namedbirdhouse. The location of the birdhouse environment is.conda/envs/birdhouse. It deploys aSupervisorconfiguration forPostgresin~/.conda/envs/birdhouse/etc/supervisor/conf.d/postgres.conf. Supervisor can be started with~/.conda/envs/birdhouse/etc/init.d/supervisorstart.The Postgres database files are by default in~/.conda/envs/birdhouse/var/lib/postgres.The recipe depends onbirdhousebuilder.recipe.condaandbirdhousebuilder.recipe.supervisor.Supported optionsThe recipe supports the following options:anaconda-homeBuildout option with the root folder of the Anaconda installation. Default:$HOME/anaconda.
The default location can also be set with the environment variableANACONDA_HOME. Example:export ANACONDA_HOME=/opt/anacondaSearch priority is:anaconda-homeinbuildout.cfg$ANACONDA_HOME$HOME/anacondaportPort used for Postgres. Default: 5433.pgdatapath to the database files. Default:~/.conda/envs/birdhouse/var/lib/postgresinitdbOptions for Postgres initialisation. Default:--auth=trustcmdspsqlcommands to setup your database schema and users.Example usageThe following examplebuildout.cfginstallsPostgreswith Anaconda:[buildout]
parts = postgres

anaconda-home = /home/myself/anaconda

[postgres]
recipe = birdhousebuilder.recipe.postgres
port = 5433
cmds =
     createuser -p 5433 --createdb --no-createrole --no-superuser --login demo
     createdb -p 5433 --owner=demo demoAfter installing with Buildout start thePostgresservice with:$ cd /home/myself/.conda/envs/birdhouse
$ etc/init.d/supervisord start  # start|stop|restart
$ bin/supervisorctl status      # check that postgres is runningAuthorsCarsten Ehbrecht ehbrecht at dkrz.deChange History0.2.0 (2015-03-31)using postgresql from anacondarefactored postgres setupusing subprocess instead of os.system0.1.0 (2015-03-30)Initial Release.
Package: birdhousebuilder.recipe.r
ContentsIntroductionUsageSupported optionsExample usageAuthorsChanges0.1.4 (2014-12-02)0.1.3 (2014-08-01)0.1.2 (2014-07-30)0.1.1 (2014-07-21)0.1.0 (2014-07-10)Introductionbirdhousebuilder.recipe.ris aBuildoutrecipe to installR Projectpackages withAnaconda.UsageThe recipe requires that Anaconda is already installed. It assumes that Anaconda is installed at the default location in your home directory~/anaconda. Otherwise you need to set the Buildout optionanaconda-hometo the correct location.It installs therpackage from a conda channel with additional packages from a givenRrepository.Rwill then be available in Anaconda~/anaconda/bin/R.The recipe depends onbirdhousebuilder.recipe.conda.Supported optionsThe recipe supports the following options:anaconda-homeBuildout option with the root folder of the Anaconda installation. Default:$HOME/anaconda.repoR Projectrepository withRpackages.pkgsList ofRpackages which should be installed (space separated).on-updateIf set to false don’t update R packages on buildout update. Default:false.Example usageExample usage in yourbuildout.cfgto installRwith Anaconda and additionalRpackages (sp,raster,ncdf) from aRrepository:[buildout]
parts = r_pkgs

anaconda-home = /home/myself/anaconda

[r_pkgs]
recipe = birdhousebuilder.recipe.r
repo = http://ftp5.gwdg.de/pub/misc/cran
pkgs = sp raster ncdf
on-update = falseAuthorsCarsten Ehbrecht ehbrecht at dkrz.deChanges0.1.4 (2014-12-02)Fixed on-update option.0.1.3 (2014-08-01)Updated documention.0.1.2 (2014-07-30)Bugfix: use R from anaconda home.0.1.1 (2014-07-21)Bugfix: conda install of R package fails on CentOS0.1.0 (2014-07-10)Initial Release.
Package: birdhousebuilder.recipe.redis
ContentsIntroductionUsageSupported optionsExample usageAuthorsChangesIntroductionbirdhousebuilder.recipe.redisis aBuildoutrecipe to install and configureRedisin-memory datastore withAnaconda.
This recipe is used by theBirdhouseproject.UsageThe recipe requires that Anaconda is already installed. It assumes that the default Anaconda location is in your home directory~/anaconda. Otherwise you need to set theANACONDA_HOMEenvironment variable or the Buildout optionanaconda-home.It installs theredispackage from a conda channel in a conda enviroment namedbirdhouse. The location of the birdhouse environment is.conda/envs/birdhouse. It deploys aSupervisorconfiguration for Redis in~/.conda/envs/birdhouse/etc/supervisor/conf.d/redis.conf. Supervisor can be started with~/.conda/envs/birdhouse/etc/init.d/supervisordstart.The recipe depends onbirdhousebuilder.recipe.condaandbirdhousebuilder.recipe.supervisor.Supported optionsThis recipe supports the following options:anaconda-homeBuildout option with the root folder of the Anaconda installation. Default:$HOME/anaconda.
The default location can also be set with the environment variableANACONDA_HOME. Example:exportANACONDA_HOME=/opt/anacondaSearchpriorityis:1.``anaconda-home``in``buildout.cfg``2.``$ANACONDA_HOME``3.``$HOME/anaconda``portAccept connections on the specified port. Default: 6379.loglevelSpecify the server verbosity level (debug, verbose, notice, warning). Default: warning.Example usageThe following examplebuildout.cfginstalls Redis with Anaconda and default options:[buildout]parts=redisanaconda-home=/home/myself/anaconda[redis]recipe=birdhousebuilder.recipe.redisAuthorsCarsten Ehbrecht ehbrecht at dkrz.deChanges0.1.0 (2015-12-10)Initial Release.
Package: birdhousebuilder.recipe.solr
Introductionbirdhousebuilder.recipe.solris aBuildoutrecipe to install and configureSolrusingAnaconda.Solrwill be deployed as aSupervisorservice.This recipe is used by theBirdhouseproject.UsageThe recipe requires that Anaconda is already installed.
You can use the buildout optionanaconda-hometo set the prefix for the anaconda installation.
Otherwise the environment variableCONDA_PREFIX(variable is set when activating a conda environment) is used as conda prefix.It installs thesolrpackage from a conda channel in a conda environment defined byCONDA_PREFIX.
The intallation folder is given by theprefixbuildout option.
It deploys aSupervisorconfiguration for Solr in${prefix}/etc/supervisor/conf.d/solr.conf.
Supervisor can be started with${prefix}/etc/init.d/supervisordstart.By defaultSolrwill be available onhttp://localhost:8983/solr.The recipe depends onbirdhousebuilder.recipe.condaandbirdhousebuilder.recipe.supervisor.Supported optionsThe recipe supports the following options:anaconda-homeBuildout option pointing to the root folder of the Anaconda installation. Default:$HOME/anaconda.hostnameThe hostname of theSolrservice (nginx). Default:localhost.http-portThe http port of theSolrservice (nginx). Default:8983.java-homePath to your JAVA_HOME. By default it uses the java installation from conda (packageopenjdk).
Default:${prefix}.Example usageThe following examplebuildout.cfginstallsSolrwith Anaconda:[buildout]
parts = solr

[solr]
recipe = birdhousebuilder.recipe.solr
hostname = localhost
http-port = 8983AuthorsCarsten Ehbrecht ehbrecht at dkrz.deChange History0.2.2 (2017-01-27)pep8.update Readme.fixed travis.0.2.1 (2016-08-20)fixed permissions of solr-home.added solr-jetty-context.xml to configure jetty tempDirectory.0.2.0 (2016-06-19)using zc.recipe.buildout.0.1.5 (2016-01-06)set SOLR_HOME to var/lib/solr.fixed recipe update mode.0.1.4 (2015-08-04)using conda java-jdk (OpenJDK) package.SOLR_JAVA_HOME set to birdhouse java.0.1.3 (2015-07-30)cleaned up schema.using tags as default search field.0.1.2 (2015-07-28)added source type in schema.xml.0.1.1 (2015-07-24)added fields for birdhouse in schema.xml.cleaned up configuration files.0.1.0 (2015-07-15)Initial Release.