Saravanan666/pypi-org huggingface dataset:
Package: biolookup
BiolookupGet metadata and ontological information about biomedical entities.🔍 Querying the Biolookup ServiceThe Biolookup Service has an endpoint/api/lookup/<curie>for retrieving metadata and ontological
information about a biomedical entity via its compact identifier (CURIE).importrequestsres=requests.get("http://localhost:5000/api/lookup/doid:14330").json()assertres["name"]=="Parkinson's disease"assertres["identifier"]=="14330"assertres["prefix"]=="doid"assertres["definition"]isnotNone# not shown for brevityTheINDRA Labhosts an instance of the Biolookup Service athttp://biolookup.io, so you can alternatively usehttp://biolookup.io/api/lookup/doid:14330.The same can be accomplished using thebiolookuppackage:importbiolookupres=biolookup.lookup("doid:14330")assertres["name"]=="Parkinson's disease"# ... same as beforeIf you've configured theBIOLOOKUP_SQLALCHEMY_URIenvironment variable (or any other valid way
withpystowto point directly at the database for an instance
of the Biolookup Service, it will make a direct connection to the database instead of using the
web-based API.🕸️ Running the Lookup AppYou can run the lookup app in local mode with:$biolookupweb--lazyThis means that the in-memory data frompyoboare used. If you have a large external database, you
can run in remote mode with the--sqlflag:$biolookupweb--sql--uripostgresql+psycopg2://postgres:biolookup@localhost:5434/biolookupIf--uriis not given for thewebsubcommand, it
usespystow.get_config("biolookup", "sqlalchemy_uri)to look up fromBIOLOOKUP_SQLALCHEMY_URIor
in~/.config/biolookup.ini. If none is given, it defaults to a SQLite database
in~/.data/biolookup/biolookup.db.🗂️ Load the Database$biolookupload--uripostgresql+psycopg2://postgres:biolookup@localhost:5434/biolookupIf--uriis not given for theloadsubcommand, it
usespystow.get_config("biolookup", "sqlalchemy_uri)to look up fromBIOLOOKUP_SQLALCHEMY_URIor
in~/.config/biolookup.ini. If none is given, it creates a defaults a SQLite database
at~/.data/biolookup/biolookup.db.🚀 InstallationThe most recent release can be installed fromPyPIwith:$pipinstallbiolookupThe most recent code and data can be installed directly from GitHub with:$pipinstallgit+https://github.com/biopragmatics/biolookup.gitTo install in development mode, use the following:$gitclonegit+https://github.com/biopragmatics/biolookup.git
$cdbiolookup
$pipinstall-e.👐 ContributingContributions, whether filing an issue, making a pull request, or forking, are appreciated. SeeCONTRIBUTING.rstfor more
information on getting involved.👀 Attribution⚖️ LicenseThe code in this package is licensed under the MIT License.🎁 SupportThe Biolookup Service was developed by theINDRA Lab, a part of theLaboratory of Systems Pharmacologyand theHarvard Program in Therapeutic Science (HiTS)atHarvard Medical School.💰 FundingThis project has been supported by the following grants:Funding BodyProgramGrantDARPAAutomating Scientific Knowledge Extraction (ASKE)HR00111990009🍪 CookiecutterThis package was created with@audreyfeldroy'scookiecutterpackage
using@cthoyt'scookiecutter-snekpacktemplate.
Package: biolord
biolord - biological representation disentanglementA deep generative framework for disentangling known and unknown attributes in single-cell data.We assume partial supervision over known attributes (categorical or ordered) along with single-cell measurements.
Given the partial supervisionbiolordfinds a decomposed latent space, and provides a generative model to
obtain single-cell measurements for different cell states.For more details read ourpubicationinNature Biotechnology.Getting startedPlease refer to thedocumentation.InstallationThere are several alternative options to install biolord:Install the latest release ofbiolordfromPyPI:pipinstallbiolordInstall the latest development version:pipinstallgit+https://github.com/nitzanlab/biolord.git@mainRelease notesSee thechangelog.ContactFeel free to contact us bymail.
If you found a bug, please use theissue tracker.Citation@article{piran2024disentanglement,
  title={Disentanglement of single-cell data with biolord},
  author={Piran, Zoe and Cohen, Niv and Hoshen, Yedid and Nitzan, Mor},
  journal={Nature Biotechnology},
  pages={1--6},
  year={2024},
  publisher={Nature Publishing Group US New York}
}
Package: bioluigi
BioluigiReusable and maintained Luigi tasks to incorporate in bioinformatics pipelinesFeaturesProvides Luigi tasks for tools fromsamtools,bcftools,STAR,RSEM,vcfanno,GATK,Ensembl VEPand much more!Reuses as much as possible theExternalProgramTaskinterface from theexternal_program contrib moduleand extends its feature to make it work on modern scheduler such asSlurm.Provides basic resource management for a local scheduler: all tasks are annotated with reasonable defaultcpusandmemoryparameters that can be tuned and constrained via the[resources]configuration. In the case of externally scheduled tasks, the resource management is deferred.Provides a command-line interface for interacting more conveniently with Luigi scheduler.bioluigilist[--statusSTATUS][--userUSER][--detailed]TASK_GLOB
bioluigishowTASK_IDToolsHere's a list of supported tools:sratoolkitwithprefetchandfastq-dumpbcftoolsFastQCMultiQCSchedulerslocalSlurmExamplesThe most convenient way of using the pre-defined tasks is to yield them dynamically in the body of therunfunction. It's also possible to require them since they inherit fromluigi.Task.importluigifrombioluigi.tasksimportbcftoolsdefMyTask(luigi.Task)definput(self):returnluigi.LocalTarget('source.vcf.gz')defrun(self):yieldbcftools.Annotate(self.input().path,annotations_file,self.output().path,...,scheduler='slurm',cpus=8)defoutput(self):returnluigi.LocalTarget('annotated.vcf.gz')You can define your own scheduled task by implementing theScheduledExternalProgramTaskclass. Note that the default scheduler islocaland will use Luigi's[resources]allocation mechanism.importdatetimefrombioluigi.scheduled_external_programimportScheduledExternalProgramTaskclassMyScheduledTask(ScheduledExternalProgramTask):scheduler='slurm'walltime=datetime.timedelta(seconds=10)cpus=1memory=1defprogram_args(self):return['sleep','10']
Package: biolxyUtil
The is a test versionInstallationbiolxyUtil runs on Python 2 and Python 3. Your operating system might already provide Python
2.7, which you can check on the command line:python --versionIf your operating system already includes Python 2.6, I suggest either usingconda(see below) or installing Python 2.7 alongside the existing Python 2.6
instead of attempting to upgrade it in-place. Your package manager might provide
both versions of Python.To run the recommended segmentation algorithms CBS and Fused Lasso, you will
need to also install the R dependencies (see below).From a Python package repositoryReasonably up-to-date biolxyUtil packages are available onPyPIand can be installed usingpip(usually works on Linux if the
system dependencies listed below are installed):pip install biolxyUtilFrom sourceThe scriptbiolxyUtil.pyrequires no installation and can be used in-place. Just
install the dependencies.To install the main program, supporting scripts andcnvlibPython library,
usesetup.pyas usual:python setup.py build
python setup.py install
Package: biom3d
📘Documentation|HighlightsBiom3d automatically configures the training of a 3D U-Net for 3D semantic segmentation.The default configuration matches the performance ofnnUNetbut is much easier to use both for community users and developers. Biom3d is flexible for developers: easy to understand and easy to edit.Code architecture of Biom3d versus code architecture of nnU-Net:Biom3d modulesnnUNet modulesIllustrations generated withpydepsmoduleDisclaimer: Biom3d does not include the possibility to use 2D U-Net or 3D-Cascade U-Net or Pytorch distributed parallel computing (only Pytorch Data Parallel) yet. However, these options could easily be adapted if needed.We target two main types of users:Community users, who are interested in using the basic functionalities of Biom3d: GUI or CLI, predictions with ready-to-use models or default training.Deep-learning developers, who are interested in more advanced features: changing default configuration, writing of new Biom3d modules, Biom3d core editing etc.🔨 InstallationFor the installation details, please check our documentation here:InstallationTL;DR: here is a single line of code to install biom3d:pip install torch biom3d✋ UsageFor Graphical User Interface users, please check our documentation here:GUIFor Command Line Interface users, please check our documentation here:CLIFor Deep Learning developers, the tutorials are currently being cooked stayed tuned! You can check the partial API documentation already:APITL;DR: here is a single line of code to run biom3d on theBTCV challengeand reach the same performance as nnU-Net (no cross-validation yet):python -m biom3d.preprocess_train\
 --img_dir data/btcv/Training/img\
 --msk_dir data/btcv/Training/label\
 --num_classes 13\
 --ct_norm⚠ DisclaimerWarning: This repository is still a work in progress and comes with no guarantees.📑 CitationIf you find Biom3d useful in your research, please cite:@misc{biom3d,
  title={{Biom3d} Easy-to-use Tool for 3D Semantic Segmentation of Volumetric Images using Deep Learning},
  author={Guillaume Mougeot},
  howpublished = {\url{https://github.com/GuillaumeMougeot/biom3d}},
  year={2023}
  }💰 Fundings and AcknowledgementsThis project has been inspired by the following publication: "nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation", Fabian Isensee et al, Nature Method, 2021.This project has been supported by Oxford Brookes University and the European Regional Development Fund (FEDER). It was carried out between the laboratories of iGReD (France), Institut Pascal (France) and Plant Nuclear Envelop (UK).
Package: biomage-programmatic-interface
\n# biomage-programmatic-interfaceAboutThis python package provides an easy way to create projects and upload samples into Biomage.InstallationTo install the package execute the following line:pip install biomage-programmatic-interfaceUsageIn order to use the package you first need to create an account in Biomage (https://scp.biomage.net/) if you don't have one yet.Then the package is used in the following way:importbiomage_programmatic_interfaceasbpi# 1. Authenticate user and create a connection tunnel with the api# Default instance-url: https://api.scp.biomage.net/connection=bpi.Connection('email','password','instance_url')# 2. Create an experimentexperiment=connection.create_experiment('experiment name')# 3. Upload samples associated with the experimentexperiment.upload_samples('local/path/to/samples')Once the upload is complete you can navigate toBiomageand process your project there.ConnectionclassThe object accepts 3 parameters:email- Biomage emailpassword- Biomage passwordinstance_url- Biomage instance urlCopy the url of the Biomage instanceexcludinghttps://If the url ishttps://scp.biomage.net/enter just the domain name:scp.biomage.netDevelopmentIf you cloned the repository and want to try using your local version, do the following:Install the local version of the pip package:cdprogrammatic_interface
makeinstallNow you can import the package and use your local versionimportbiomage_programmatic_interfaceasbpiNOTE: There isNOneed to runmake installevery time you make changes to the package. When the local changes have been saved the changes will be automatically reflected.Running with local instance of CellenicsWhen creating theconnectionobject set theinstance_urltolocal. Now the programmatic interface will use your local api (https://localhost:3000)importbiomage_programmatic_interfaceasbpiconn=bpi.Connection(<YOUREMAIL>,<YOURPASSWORD>,'local')...Running with staged environmentSet the full path of the instance url (e.g.https://api-{ENVIRONMENT NAME}.scp-staging.biomage.net/)importbiomage_programmatic_interfaceasbpiconn=bpi.Connection(<YOUREMAIL>,<YOURPASSWORD>,'https://api-{ENVIRONMENT NAME}.scp-staging.biomage.net/')...NOTE: the url is that of the api (i.e.api-) and not that of the ui
Package: biomaj-cli
# AboutPackage to use BioMAJ providing biomaj-cli# Examplebiomaj-cli.py –proxyhttp://biomaj-public-proxy–api-key XYZ_MYAPIKEY –update –bank Anopheles_gambiaeTo get help usage:biomaj-cli -hIf proxy is not specifed, a monolitic and local BioMAJ installation is expectedTo create users, see biomaj-user repo or BioMAJ wiki3.1.11:Add –data-list and –data-import to import an example bank (needs biomaj-data package)3.1.10:Add –history option3.1.9:Add option –stats, needs biomaj-daemon >= 3.0.13
Add option –json, needs biomaj-daemon >= 3.0.133.1.8:Add option –schedule3.1.7:If no arg given, display help3.1.6:Add options –last-log and –tail to get last log of a bank, needs biomaj-daemon >= 3.0.83.1.5:Add missing biomaj-core req3.1.4:Add whatsup option
Fix default value for –config3.1.2:Add missing README
Fix for monolithic usage3.1.1:Use biomaj daemon utils for options management
Fix config setup when using local install
Rename biomaj-daemon-cli to biomaj-cli3.1.0:Create client for biomaj with micro services
Package: biomaj-core
BiomajBiomaj core libraryProperties can be overriden by environment variables with pattern BIOMAJ_X_Y_Z for property x.y.zExample:use BIOMAJ_LDAP_HOST for ldap.host3.0.28:
use pytest instead of nose (deprecated)
python3 only support3.0.27:
add .tgz extension support3.0.26:
check use_ldap and use_elastic as bool (true/false or 0/1)3.0.25:
utils/get_folder_size: if file not found, catch error and continue3.0.24:
get_more_recent_file, return also file info3.0.23:
PR #9 Add missing ssh defaults for download3.0.21 [3.0.22 ,tag issue]:
Pin elasticsearch dependency, v7 breaks some API calls3.0.20:
PR #7 from institut-de-genomique/retry_method, rename default values of retryer.
Rename wait_condition to wait_policy in default values
PR #6 from institut-de-genomique/retry_method, add default values for retryer
Add default values for retryer (see the corresponding branch biomaj-download).3.0.19:
Add ftps and directftps protocols
#4 Harden hardlinks
copy_files_with_regexp: remove duplicates
Add utils fonctions
Code cleanup3.0.18:
Allow to use hardlinks in copy_files and copy_files_with_regexp3.0.17:
Fix --log option3.0.16:
Add some warnings if some file is missing3.0.15:
Fix check on bank properties config file when args is empty vs not defined3.0.14:
Fix checks on local_endpoint_XXX in config.yml
In rabbitmq not defined on config.yml add an empty dict3.0.13:
Add archive integrity checks3.0.12:
Add irods support3.0.11:
Add get_module_version static method, checks module version and latest version on pypi
Allow .args fo process to be empty3.0.10:
Add env variables WEB_LOCAL_ENDPOINT_XX with XX as a service (defined in utils.py Utils.services) to define an endpoint per service3.0.9:
#1 Add checks on bank properties3.0.8:
Add DOCKER_URL, MONGO_URL, MONGO_DB env variable in override
Do not fail on elasticsearch index creation, just log
Add rsync check3.0.7:
set logging only if necessary3.0.6:
Fix configparser import for python 2 vs 33.0.5:
Add config override with env variables3.0.4:
Code cleanup3.0.3:
Put index management in core3.0.2:
Add missing deps3.0.1:
Add README etc..3.0.0:
separation of biomaj and biomaj_core
Package: biomaj-cron
# BioMAJ cron servicebiomaj-cron manages the cron task to update BioMAJ banks.It can be used as a library or as a micro-service.[![PyPI version](https://badge.fury.io/py/biomaj-cron.svg)](https://badge.fury.io/py/biomaj-cron)# Installpip install biomaj-cron# Micro service## Run# to reload cron tasks from database (in case of micro service)
biomaj_load_cron.pyexport BIOMAJ_CONFIG=path_to_config.yml
gunicorn -b 0.0.0.0:5000 biomaj_cron.biomaj_cron_web:app## APIEndpoint /api/cron# Generate documentationpip install sphinx
pip install sphinxcontrib-httpdomain
cd doc
make html# Release notes## 3.0.3Fix traefik prefix## 3.0.2Add tags for traefik support## 3.0.1Allow proxy endpoint definition for daemon, else use default web.local_endpoint## 3.0.0Creation
Package: biomaj-data
This repository contains sample db properties and post processes for BioMAJ.Bank properties examples are under biomaj_data/db_properties directoryIf you want to know how to write :Your own bank.properties file:https://biomaj.genouest.org/how-to-create-a-bank-properties-file/Your own process:https://biomaj.genouest.org/how-to-create-processes/All contributors are welcomed.All those files are under license GPL-V3+
Package: biomaj-ftp
# Biomaj ftpBiomaj FTP server to access production banksanonymous access is allow with loginanonymousand any fake password.
Existing users can access server with the login and API key as password.Only public or owned banks are accessible# Configconfig.yml contains the server configuration.
Mongo configuration should be the same one than biomaj.Web endpoint refers to the biomaj API endpoint# Runexport BIOMAJ_CONFIG=path_to_config.ymlpython bin/biomaj_ftp_service.py# DockerTo run in a Docker container, do not forget to open passive ports range (60000, 65535)3.0.7:update dependencies and pyyaml loader3.0.6:Add ftp/masquerade_address in config or MASQUERADE_ADDRESS env variable to define address ftp server should advertise (mainly for docker)3.0.5:Allow proxy endpoint definition for daemon, else use default web.local_endpoint3.0.4:Add passive ports setup, range(60000, 65535)
Modify login: use login and api key to access to all available banks instead of connecting to one bank3.0.3:Set consul checks3.0.2:Allow override of config
Fix user authentication
Load database settings from global.properties to match same database than biomaj3.0.1:Fix anonymous access and case where web/local_endpoint is not defined in config.yml3.0.0:FTP server to access banks
Package: biomaj-process
# About[![PyPI version](https://badge.fury.io/py/biomaj-process.svg)](https://badge.fury.io/py/biomaj-process)Microservice to manage the process execution of biomaj.A protobuf interface is available in biomaj_process/message/message_pb2.py to exchange messages between BioMAJ and the download service.
Messages go through RabbitMQ (to be installed).# ProtobufTo compile protobuf, in biomaj_process/message:protoc –python_out=. message.proto# Developmentflake8  biomaj_processCONFIG=tests/config.yml python -m pytest -v tests/biomaj_tests.py# Run## Message consumer:export BIOMAJ_CONFIG=path_to_config.yml
python bin/biomaj_process_consumer.py## Web serverIf package is installed via pip, you need a file namedgunicorn_conf.pycontaining somehwhere on local server:def worker_exit(server, worker):from prometheus_client import multiprocess
multiprocess.mark_process_dead(worker.pid)If you cloned the repository and installed it via python setup.py install, just refer to thegunicorn_conf.pyin the cloned repository.export BIOMAJ_CONFIG=path_to_config.yml
rm -rf ..path_to/prometheus-multiproc
mkdir -p ..path_to/prometheus-multiproc
export prometheus_multiproc_dir=..path_to/prometheus-multiproc
gunicorn -c ..path_to/gunicorn_conf.py biomaj_download.biomaj_process_web:appWeb processes should be behind a proxy/load balancer, API base url /api/processA prometheus /metrics endpoint is exposed on web server3.0.19Replace nose by pytest3.0.18:Normalize yaml setup with other biomaj components3.0.17:Fix yaml load warnings3.0.16:In case of proxy comm failure, sleep a few seconds before retry3.0.15:Add proc name in logs for waiting and result3.0.14:Add env var BIOMAJ_HOST_DATA_DIR to use withdockerprocess executor to specify data.dir location if different between host and container (if BIOMAJ_DATA_DIR not a subdirectory of BIOMAJ_DIR for example)If variable is not set, container wil mount data.dir between host and container,
else will mount BIOMAJ_HOST_DATA_DIR:data.dir3.0.13:Fix traefik prefix3.0.12:Update pika dependency release
Add tags for traefik support3.0.11:Catch exception for microservices if remote server is not reachable
Rename package for protobuf to avoid collisions3.0.10:README doc fixes
Add dependency banks additional volumes for Docker3.0.9:Allow local_endpoint definition per service
Fix volumes for docker with dependency banks3.0.8:Fix #1, DRMAA needs colon in front of output and error path (mandatory depending on versions)3.0.7:fix case if process desc or type is missing in bank properties3.0.6:disable web thread logging3.0.5:retry in case of contact failure with proxy3.0.4:for docker, restrict directory to bank directory and dependencies
add host in prometheus stats3.0.3:fix prometheus + gunicorn multi process
add consul supervision3.0.2:add logging info
execute docker processes in biomaj micro service3.0.1:bug fixes3.0.0:move process management out of biomaj main package
Package: biomaj-release
# About[![PyPI version](https://badge.fury.io/py/biomaj-release.svg)](https://badge.fury.io/py/biomaj-release)Biomaj remote bank release watcherScan every day remote banks release modifications and send stats to prometheus and influxdb about new release detection.
When a new release is detected, according to minimal delay configuration (in global or bank properties), a new bank update is sent.If influxdb is available and updated with bank updates, minimal delay will also be computed based on mean workflow duration. In any case, minimal duration is 1 day.Properties in global.properties and/or your bank property file:schedule.delay=3 # minimal 3 days between checks
schedule.auto=true # Default=true, if false, auto scan is disabledProgram will try to increase delay between updates when no new release is detected and to decrease it when a new release occurs.# Requirementsredis# Developmentflake8 –ignore E501 biomaj-release# Prometheus metricsEndpoint:/metrics
/api/release/schedule/bank : schedule checks for all banks
/api/release/schedule/bank/<bank> : schedule check forbank# Runpython bin/biomaj_release.py3.0.3:Fix traefik prefix3.0.2:Allow per service endpoint definition
If bank failed, try anyway
Add tags for traefik support3.0.1:Start internal web server even if consul is not declared3.0.0:Micro service to watch remote bank releases
Package: biomaj-user
# Biomaj userBiomaj user management libraryCreation/deletion/… scripts should not be accessible to end user, only to admin.
End users can have access to their API Key via the biomaj-watcher interface.# Web serverexport BIOMAJ_CONFIG=path_to_config.yml
gunicorn biomaj_user.biomaj_user_service:appWeb processes should be behind a proxy/load balancer, API base url /api/user# Managing usersusage: biomaj-users.py [-h] -A ACTION [-C </path/to/config.yml>] [-E EMAIL] -U <username> [-P <password>]Availables actions: create, delete, update, view, renew (apikey)3.0.12:Normalize yaml loader between biomaj components and fix dependencies3.0.11:Force yaml loader3.0.10:Force yaml loader to skip warning on output3.0.9:Add json output to biomaj_user script3.0.8:Fix traefik prefix3.0.7:Add tags for traefik support3.0.6:update ldap3 requirement version to use more recent release3.0.5:fix ldap authentication3.0.4:fix api key checks via API3.0.3:move biomaj_create_user and biomaj_delete_user to biomaj_users script with cmd line options3.0.2:add scripts to add/remove a user3.0.1:move biomaj_user_service.py to package3.0.0:separation of biomaj and biomaj_user
Package: biomapy
biomapyThis is a library that has just one function that maps a list of gene IDs from one to another.Supported IDs are Uniprot, entrez, ensembl, and Gene_symbol.The usage is straightforward the gene_mapping_many() takes as argument the list of IDs As a Python object list), source ID type  and target ID type.The funciton update_mapping_datasets() serves to update the mapping datasets and to be sure that your mappings are up-to-date.Be careful that the data type is compatible when you map. Entrez have to be ints and not strings.Future implementations will fous on expanding the IDs that are supported (e.g. diseases)InstallationBiomapy can be installed via pippip install biomapyUsageA tipical call for gene_mapping_many() is as follows:import biomapy as bp

gene_symbol_list=['A1BG','TGFB','BMP2']

gene_entrez_list=bp.gene_mapping_many(gene_symbol_list,'symbol','entrez')

gene_entrez_list

[1,7040,650]