Saravanan666/pypi-org huggingface dataset:
Package: bioturbation
Bioturbation ModelA simple model of earthworm bioturbation, using a layered soil profile. The model predicts the mixing of mass pools (e.g. of contaminants) over time as a function of earthworm density.QuickstartThe model can be installed usingpip:$pipinstallbioturbationAlternatively, you can download the source code and use the provided Conda environment file to install the relevant dependencies:$gitclonehttps://github.com/samharrison7/bioturbation-model.git
$cdbioturbation-model
$condaenvcreate-fenvironment.ymlUsageCheck out theexamplesdirectory for examples of how to use the model.ConceptualisationSee theconceptualisationnotebook for a mathematical description of how the model works.LimitationsNo guarantee is given as the to scientific validity of this model for your data. The onus is on the user to verify this validity. Indeed, there are a number of limitations to the model as it stands which might limit its applicability:Transport is only betweenadjacentsoil layers, therefore neglecting preferential flow pathways, e.g. representing deep burrowing earthworms transporting tracers directly from upper to lower layers.No change in soil properties due to bioturbation is modelled. That is, there is an implicit assumption that the amount of soil mixed between layers is negligible. This assumption might not always be valid.We welcome requests for collaboration if you are interested in exploring the validity of the model for your own research. Pleaseget in touch.
Package: bio-util
bio_utilLibrary of bioinformatics-related utilitiesFree software: MIT licenseDocumentation:https://bio-util.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.0.1 (2018-09-13)First release on PyPI.0.0.2 (2018-09-14)Added load_references and run_cmd methods
Package: bioutils
bioutils provides some common utilities and lookup tables for bioinformatics.bioutils.accessions – parse accessions, infer namespacesbioutils.assemblies – Human assembly information (from NCBI/GRCh)bioutils.cytobands – map cytobands to coordinates (from UCSC cytoband tables)bioutils.digests – implementations of various digestsbioutils.normalize – allele normalization (left shuffle, right shuffle, expanded, vcf)To use an E-Utilities API key run add it to an environment variable
calledncbi_api_keyand it will be used in the E-Utilities request.
Package: bioversions
BioversionsWhat's the current version for each biological database?A daily updated static listing of all current versions (that are incorporated) can be found athttps://biopragmatics.github.io/bioversions.🚀 Installation$pipinstallbioversions💪 Usageimportbioversionsassertbioversions.get_version('biogrid')=='4.2.192','This was true on Dec 5th, 2020!'# If you want more information, use the resolve() functionbioversion=bioversions.resolve('biogrid')assertbioversion.version=='4.2.192'By default, the results are cached and only refreshed once per day with the help
ofcachier. The cache is stored in~/.data/bioversions. The cache location
can be overridden by setting theBIOVERSIONS_HOMEenvironment variable viapystow.🌐 Web ApplicationWhilehttps://biopragmatics.github.io/bioversionsprovides a daily updated static listing of the database, you can run a
dynamic version with an API from your shell with:$bioversionswebOptions can be listed withbioversions web --help.You can navigate tohttp://localhost:5000to see all versions as HTML or programmatically resolve given databases with
thehttp://localhost:5000/database/<name>endpoint like in the following:importrequestsres=requests.get('http://localhost:5000/database/biogrid').json()assertres['success']assertres['result']['name']=='BioGRID'assertres['result']['version']=='4.2.192','This was true on Dec 5th, 2020!'CLI UsageYou can usebioversions getto incorporate the latest versions in your shell scripts or REPL usage like in:$wget"https://downloads.thebiogrid.org/Download/BioGRID/Release-Archive/BIOGRID-$(bioversionsgetbiogrid)/BIOGRID-ALL-$(bioversionsgetbiogrid).mitab.zip"🙏 ContributingTo add more databases to the list, you can create a new submodule ofbioversions.sourcesand extend thebioversions.utils.Getterclass to identify the most recent version for your
target database. Seebioversions.sources.biogridas an example.👋 Attribution⚖️ LicenseCode is licensed under the MIT License.🎁 SupportThe Bioversions service was developed by theINDRA Lab, a part of theLaboratory of Systems Pharmacologyand theHarvard Program in Therapeutic Science (HiTS)atHarvard Medical School.💰 FundingThe development of the Bioregistry is funded by the DARPA Young Faculty Award W911NF2010255 (PI:
Benjamin M. Gyori).
Package: biowardrobe-airflow-analysis
BioWardrobe backend (airflow+cwl)AboutPython package to replaceBioWardrobe'spython/cron scripts. It usesApache-Airflowfunctionality withCWL v1.0.InstallAdd biowardrobe MySQL connection into Airflow connectionsselect*fromairflow.connection;insertintoairflow.connectionvalues(NULL,'biowardrobe','mysql','localhost','ems','wardrobe','',null,'{"cursor":"dictcursor"}',0,0);Installsudopip3install.RequirementsMake sure your system satisfies the following criteria:Ubuntu 16.04.3python3.6sudoadd-apt-repositoryppa:jonathonf/python-3.6
sudoapt-getupdate
sudoapt-getinstallpython3.6pip3curlhttps://bootstrap.pypa.io/get-pip.py|sudopython3.6
pip3install--upgradepip3setuptoolspip3installsetuptoolsdockersudoapt-getupdate
sudoapt-getinstallapt-transport-httpsca-certificatescurlsoftware-properties-common
curl-fsSLhttps://download.docker.com/linux/ubuntu/gpg|sudoapt-keyadd-
sudoadd-apt-repository"deb [arch=amd64] https://download.docker.com/linux/ubuntu$(lsb_release-cs)stable"sudoapt-getupdate
sudoapt-getinstalldocker-ce
sudogroupadddocker
sudousermod-aGdocker$USERLog out and log back in so that your group membership is re-evaluated.libmysqlclient-devsudoapt-getinstalllibmysqlclient-devnodejssudoapt-getinstallnodejsGet the latest version ofcwl-airflow-parser.
IfApache-Airfloworcwltoolaren't installed,
installation will be done automatically with recommended versions. SetAIRFLOW_HOMEenvironment
variable to airflow config directory default is~/airflow/.gitclonehttps://github.com/datirium/cwl-airflow-parser.gitcdcwl-airflow-parser
sudopip3install.If required, addextra airflow packagesfor extending Airflow functionality, for instance, with MySQL supportpip3 install apache-airflow[mysql].RunningTo create BioWardrobe's dags runbiowardrobe-initin airflow's dags directorycd ~/airflow/dags
./biowardrobe-initRun Airflow scheduler:airflowschedulerUseairflow trigger_dagwith input parameter--conf "JSON"where JSON is either job definition or biowardrobe_uid
and explicitly specified cwl descriptordag_id.airflowtrigger_dag--conf"{\"job\":$(cat./hg19.job)}""bowtie-index"wherehg19.jobis:{"fasta_input_file":{"class":"File","location":"file:///wardrobe/indices/bowtie/hg19/chrM.fa","format":"http://edamontology.org/format_1929","size":16909,"basename":"chrM.fa","nameroot":"chrM","nameext":".fa"},"output_folder":"/wardrobe/indices/bowtie/hg19/","threads":6,"genome":"hg19"}All the output will be moved from temporary directory intooutput_folderparameter
of the job.
Package: biowardrobe-airflow-plugins
BioWardrobe Airflow PluginsInstallbiowardrobe-airflow-pluginsfrom PyPipip3 install biowardrobe-airflow-pluginsRunbiowardrobe-plugin-initin any folderbiowardrobe-plugin-initTo trigger all available plugins by experiment UIDairflowtrigger_dag--conf"{\"uid\":\"UID\"}"biowardrobe_pluginsTo trigger the specific plugin by experiment UIDairflowtrigger_dag--conf"{\"uid\":\"UID\"}"<plugin'sname>
Package: biowardrobe-cwl-workflows
WorkflowsCWL workflows forBioWardrobeproject. This package includes
all the original BioWardrobe's pipelines, simplifies import
for biowardrobe-airflow-analysis. It also includes extra pipelines for new project SciDAP.Installpip3installbiowardrobe-cwl-workflowsor from sourcesgitclonehttps://github.com/datirium/workflows
pip3install.Usagefrombiowardrobe_cwl_workflowsimportavailable_path_to_workflow=available(workflow='chipseq-se.cwl')Extra features in CWLMetadata & Upstreams'sd:metadata':-"../metadata/chipseq-header.cwl"'sd:upstream':genome_indices:"genome-indices.cwl"control_file:"chipseq-se.cwl"To enable users to extend user interface (dynamic form) with extra input fields not required by a workflow'sd:metadata'field were introduced. It defines a list of workflows where inputs field just used for constructing and storing the input object.To simplify selection of already analyzed common data’sd:upstream’were introduced. It defines the upstream workflows of the process. The process is ready to run when upstream output data is available.Example of extra input fields for user interface:cwlVersion:v1.0class:Workflowinputs:cells:type:stringlabel:"Cells"sd:preview:position:1conditions:type:stringlabel:"Conditions"sd:preview:position:3alias:type:stringlabel:"Experimentshortname/Alias"sd:preview:position:2catalog:type:string?label:"Catalog#"description:type:string?'sd:type':'text'label:"Description"outputs:[]steps:[]CWL VisualPlugins for output dataoutputs:...fastx_statistics:type:Filelabel:"FASTQstatistics"format:"http://edamontology.org/format_2330"doc:"fastx_quality_statsgeneratedFASTQfilequalitystatisticsfile"outputSource:fastx_quality_stats/statistics_file'sd:visualPlugins':-line:Title:'Basefrequencyplot'xAxisTitle:'Nucleotideposition'yAxisTitle:'Frequency'colors:["#b3de69","#99c0db","#fb8072","#fdc381","#888888"]data:[$12,$13,$14,$15,$16]...
Package: biowdl-input-converter
BioWDL input converterbiowdl-input-converter converts human-readable samplesheets into
a format that can be easily processed by BioWDL pipelines.Check out the documentation onhttps://biowdl-input-converter.readthedocs.iofor more information on installation and usage.For more information on BioWDL check out the documentation onhttps://biowdl.github.io.
Package: bip32key
bip32keyThe implementation of Hierarchical Deterministic (HD) wallets generator for Ethereum blockchainInstallationInstall bip32keypip install bip32keyUsageImport entropyfrom bip32key import BIP32KEY, BIP32KEY_HARDEN
import binascii

# Import entropy
entropy = binascii.hexlify(b"Meheret Tesfaye Batu")
master_key = BIP32KEY.fromEntropy(entropy)Import Path# Added master key path
master_key = master_key.fromPath("m/44'/69'/12'/5/0")Or Import Index# This is same with fromPath
master_key = master_key.fromIndex(44 + BIP32KEY_HARDEN)
master_key = master_key.fromIndex(69 + BIP32KEY_HARDEN)
master_key = master_key.fromIndex(12 + BIP32KEY_HARDEN)
master_key = master_key.fromIndex(5)
master_key = master_key.fromIndex(0)Get All# Get All Information
print(master_key.print())

# Get Address
print(master_key.address())
# Get Wallet Import Format
print(master_key.walletImportFormat())
# Get Finger Print
print(master_key.fingerPrint().hex())
# Get Chain Code
print(master_key.chainCode())
# Get Private Key
print(master_key.privateKey().hex())
# Get Public Key
print(master_key.publicKey().hex())

##### Serialized #####

# Get Private Key Hex
print(master_key.extendedKey(private=True, encoded=False).hex())
# Get Public Key Hex
print(master_key.extendedKey(private=False, encoded=False).hex())
# Get XPrivate Key Base58
print(master_key.extendedKey(private=True, encoded=True))
# Get XPublic Key Base58
print(master_key.extendedKey(private=False, encoded=True))ExampleMetamask and MyEtherWallet uses this path/indexmaster_key = master_key.fromPath("m/44'/60'/0'/0/0")master_key = master_key.fromIndex(44 + BIP32KEY_HARDEN)
master_key = master_key.fromIndex(60 + BIP32KEY_HARDEN)
master_key = master_key.fromIndex(0 + BIP32KEY_HARDEN)
master_key = master_key.fromIndex(0)
master_key = master_key.fromIndex(0)Author# Meheret Tesfaye@meherett.
Package: bip32template
Python implementation of BIP32 path template parser finite state machine(compatible withmicropython)This repository contains an implementation of specification of the parser for BIP32 path templates
described inbip-path-templates.mediawikiand specified by TLA+ specification athttps://github.com/dgpv/bip32_template_parse_tplaplus_specThe implementation is inbip32template/__init__.pyThe tests is intests/To run tests on micropython, usemicropython_unittest.py(you will need micropython-os.path module to run the tests)to run static type checking, userun_mypy.shExample usage:>>>frombip32templateimportBIP32Template>>>tpl=BIP32Template.parse('m/0h/[1-9,23]/*')>>>tplBIP32Template([[(2147483648,2147483648)],[(1,9),(23,23)],[(0,2147483647)]],is_partial=False,hardened_marker="h")>>>tpl.sections[[(2147483648,2147483648)],[(1,9),(23,23)],[(0,2147483647)]]>>>str(tpl)'m/0h/[1-9,23]/*'>>>str(BIP32Template(tpl.sections,hardened_marker="'",is_partial=True))"0'/[1-9,23]/*">>>tpl.to_path()isNoneTrue>>>tpl.match([0x80000000,3,33])True>>>tpl.match([0x80000000,99,33])False>>>BIP32Template.parse('m/0/1/[2-3]',is_format_onlypath=True)...bip32template.BIP32TemplateExceptionUnexpectedCharacter:unexpectedcharacteratposition7>>>ptpl=BIP32Template.parse('m/0h/1/2',is_format_onlypath=True)>>>ptplBIP32Template([[(2147483648,2147483648)],[(1,1)],[(2,2)]],is_partial=False,hardened_marker="h")>>>ptpl.to_path()[2147483648,1,2]>>>tpl.match(ptpl.to_path())True>>>str(BIP32Template.from_path(ptpl.to_path(),is_partial=True))"0'/1/2">>>str(BIP32Template.from_path(ptpl.to_path(),is_partial=False,hardened_marker="h"))'m/0h/1/2'Authors and contributorsThis implementation was created by Dmitry Petukhov (https://github.com/dgpv/)LicenseReleased under MIT license.
Package: bip380
Bitcoin Script Descriptors, with Miniscript extensionAboutIn Bitcoin, outputScripts are used to express the conditions
by which the amount associated with the output may be spent.Output Script Descriptorsare a simple language which can be used to describe such Scripts
generally and precisely.  Bitcoin Output Script Descriptors are defined in a set ofBIPs, the main one beingbip-0380.Miniscriptis a language for writing (a subset of) Bitcoin Scripts in a structured way. It is an
extension to Output Script Descriptors and is currently only defined within P2WSH context.Miniscript permits:To safely extend the Output Descriptor language to many more scripting features thanks to the
typing system (composition).Statical analysis of spending conditions, maximum spending cost of each branch, security
properties, third-party malleability.General satisfaction of any correctly typed ("valid") Miniscript. The satisfaction itself is
also analyzable.To extend the possibilities of external signers, because of all of the above and since it carries
enough metadata.Miniscript guarantees:That for any statically-analyzed as "safe" Script, a witness can be constructed in the bounds of
the consensus and standardness rules (standardness complete).That unless the conditions of the Miniscript are met, no witness can be created for the Script
(consensus sound).Third-party malleability protection for the satisfaction of a sane Miniscript, which is too
complex to summarize here.This library provides an implementation of Segwit-native Output Descriptors and of Miniscript (to be
used withinwsh()descriptors), with a minimal amount of dependencies.WIP: this is not ready for any real use!This library is still a work in progress. It contains known bugs (in the satisfier for instance) and
there are probably many unknown ones.Still, it's ready for hacking around and contributions are welcome. See theissue
trackerfor ideas on where to start.
Package: bip39
BIP39This aims to be a simple and well tested BIP39 implementation in Python, which intentionally only supports the core
properties of thespecificationi.e.,:encode data to mnemonicdecode mnemonic phraseconvert mnemonic phrase to seed value (which than can be further process e.g., inBIP32)Command line usageYou can also used the basic features on the command line::$./bip39.pyencode"00000000000000000000000000000000"abandonabandonabandonabandonabandonabandonabandonabandonabandonabandonabandonabout
$python-mbip39encode"00000000000000000000000000000000"# or like soabandonabandonabandonabandonabandonabandonabandonabandonabandonabandonabandonabout
$./bip39.pydecode"abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon about"00000000000000000000000000000000$./bip39.pytoseed"abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon about""TREZOR"c55257c360c07c72029aebc1b53c05ed0362ada38ead3e3e9efa3708e53495531f09a6987599d18264c1e1c92f2cf141630c7a3c4ab7c81b2f001698e746
Package: bip39gen
bip39gen: wordlist generator for PythonBitcoin BIP39includes wordlists. These wordlists are useful for generating easily-typed but strongly random strings. The wordlists are 2048 words long, so each word carries 11 bits of information; a generated six-word passphrase has 66 bits of entropy, sufficient for most passwords.This module doesnotattempt to encode or decode BIP39 keys; it just manages wordlists, and provides convenience methods for generating strongly random lists of words from them.bip39gencommand[--langlang][--separatorseparator][--countcount][length]Generatecountlines, each withlengthwords, separated byseparator.Only the English (en) wordlist is shipped.
Package: bip39gen-nop
bip39gen: wordlist generator for PythonBitcoin BIP39includes wordlists. These wordlists are useful for generating easily-typed but strongly random strings. The wordlists are 2048 words long, so each word carries 11 bits of information; a generated six-word passphrase has 66 bits of entropy, sufficient for most passwords.This module doesnotattempt to encode or decode BIP39 keys; it just manages wordlists, and provides convenience methods for generating strongly random lists of words from them.bip39gencommand[--langlang][--separatorseparator][--countcount][length]Generatecountlines, each withlengthwords, separated byseparator.Only the English (en) wordlist is shipped.
Package: bip44
python-bip44Simple Pythonbip44implementation.Mnemonic+bip32.Installpip install bip44Quick Start>>>fromcoincurveimportPrivateKey>>>frombip44importWallet>>>frombip44.utilsimportget_eth_addr>>>mnemonic="purity tunnel grid error scout long fruit false embody caught skin gate">>>w=Wallet(mnemonic)>>>sk,pk=w.derive_account("eth",account=0)>>>sk=PrivateKey(sk)>>>sk.public_key.format()==pkTrue>>>get_eth_addr(pk)'0x7aD23D6eD9a1D98E240988BED0d78e8C81Ec296C'Release Notes0.1.1 ~ 0.1.4Support Python 3.10, 3.11, 3.12Bump dependenciesDrop Python 3.6, 3.70.1.0First beta releaseBump dependencies0.0.1 ~ 0.0.7Alpha releases
Package: bip66
Strict DER signature encoding/decoding.Seebip66.This moduleworks only withtwo's complementnumbers.BIP66 doesn't check thatrorsare fully valid.check/decodedoesn't check thatrorsgreat than 33 bytes or that this number represent valid point on elliptic curve.encodedoesn't check thatr/srepresent valid point on elliptic curve.Exampleimportbip66r="29db2d5f4e1dcc04e19266cce3cb135865784c62ab653b307f0e0bb744f5c2aa"s="00a97f5826912cac8b44d9f577a26f169a2f8db781f2ddb7de2bc886e93b6844"encoded=bip66.encode(binascii.unhexlify(r),binascii.unhexlify(s))signature=binascii.hexlify(encoded).decode()# > 00a97f5826912cac8b44d9f577a26f169a2f8db781f2ddb7de2bc886e93b6844DER="3044022029db2d5f4e1dcc04e19266cce3cb135865784c62ab653b307f0e0bb"\"744f5c2aa022000a97f5826912cac8b44d9f577a26f169a2f8db781f2ddb7de2bc886e93b6844"r,s=bip66.decode(binascii.unhexlify(DER))print(binascii.hexlify(r).decode())print(binascii.hexlify(s).decode())# > 29db2d5f4e1dcc04e19266cce3cb135865784c62ab653b307f0e0bb744f5c2aa# > 00a97f5826912cac8b44d9f577a26f169a2f8db781f2ddb7de2bc886e93b6844A catch-all exception regex:/ExpectedDER(integer|sequence)|(R|S)value(excessivelypadded|isnegative)|(R|S|DERsequence)lengthis(zero|tooshort|toolong|invalid)/LICENSEMIT
Package: bipartite-learn
Machine learning estimators tailored to bipartite datasets.In a usual machine learning setting, one is interested in predicting a set of
outputsyfrom a given feature vectorxrepresenting an input instance.
There are tasks, however, that are sometimes better modeled as bipartite
networks, in which two domains of instances are present and only inter-domain
relationships are plausible between pairs of instances. The goal is then to
predict aspects (y) of such interaction between a sample from the first domain
and another from the second domain, respectively represented by feature vectorsx1andx2.  In other words, it is sometimes desirable to model a function
in the format(x1, x2) -> yrather than the usualx -> yformat.Examples of such tasks can be found in the realms of interaction prediction and recommendation systems, and the datasets corresponding to them can be presented
as a pair of design matrices (X1andX2) together with an interaction
matrixYthat describes each relationship between the samplesX1[i]andX2[j]in the positionY[i, j].This package provides:A collection of tools to adapt usual algorithms to bipartite data;Tree-based estimators designed specifically to such
datasets, which yield expressive performance improvements over the naive
adaptations of their monopartite counterparts.A documentation forbipartite_learn, still in its infancy, can be found atbipartite-learn.rtfd.io.
Please refer to theUser Guidefor more information
on how to use this package.Installationbipartite_learnis available on PyPI, and thus can be installed withpip:$pipinstallbipartite_learnInstallation from source can be done by cloning this repository and callingpip installin the root folder.$gitclonehttps://github.com/pedroilidio/bipartite_learn
$cdbipartite_learn
$pipinstall--editable.The optional--editable(or-e) flag links the installed package to the
local cloned repository, so that local changes in it will immediatly be active
without the need for reinstallation.
Package: bipartitepandas
BipartitePandasBipartitePandasis a Python package for handling bipartite labor data.If you want to give it a try, you can start the example notebook here:. This starts a fully interactive notebook with a simple example that generates data and demonstrates some useful functions.BipartitePandas is used inPyTwoWay.The package provides a Python interface. Installation is handled bypiporConda. The source of the package is available on GitHub atBipartitePandas. The online documentation is hostedhere.InstallationTo install via pip, from the command line run:pip install bipartitepandasTo install via Conda, from the command line run:conda install -c tlamadon bipartitepandasAuthorsThibaut Lamadon,
Assistant Professor in Economics, University of Chicago,lamadon@uchicago.eduAdam A. Oppenheimer,
Graduate Student, University of Minnesota - Twin Cities,oppen040@umn.edu
Package: bipbop-microservices
Microserviços BIPBOP - PythonO objetivo desta aplicação é permitir que softwares de Machine Learning funcionem de maneira rápida, discreta e integrada nas aplicações BIPBOP.TL-DRfrombipbop_microservicesimportudp_server,register_serviceregister_service('uppercase',lambdacontent:content.upper(),{type:"string"},{type:"string"})udp_server().serve_forever()