Saravanan666/pypi-org huggingface dataset:
Package: linkifile
linkifile: Empowering Effortless Data LinkingPackageMetaWhat is linkifile?linkifileis a Python package designed to automate the process of populating one column of data by web scraping information from the internet based on the contents of another column. It simplifies the task of linking data columns and enriching your datasets with desired links.Table of ContentsMain FeaturesWhere to get itInstallationUsageDocumentationContributingLicenseMain FeaturesEffortlessly link data columns, saving time and effort in manual data enrichment tasks.Utilize web scraping to retrieve relevant information from the web and populate your data columns with valuable insights.Tailor your queries to extract specific data from the web, customizing the data enrichment process.Accelerate the data linking process with built-in multithreading support for faster execution, even with large datasets.Designed with user-friendliness in mind, making it accessible to users of all levels of technical expertise.Where to get itThe source code is currently hosted on GitHub at:https://github.com/ar8372/linkifileBinary installers for the latest released version are available at the Python Package Index (PyPI).InstallationYou can install linkifile usingpip:pip install linkifileUsageImport the Linker module from thelinkifilepackage.Create an instance of the Linker class by specifying the source file, column pairs, and optional destination file.Use thepopulatemethod to link data columns based on web scraping queries.Example:fromlinkifileimportLinker# Create a Linker instance with source file, column pairs, and optional destination filel=Linker(source_file="data.csv",coln_pairs=["Company Name","Website Link"])# Populate data columns based on a specific queryl.populate(query="{{x}} official website")BeforeAfterLicenseThis project is licensed under the MIT License
Package: linking
#linkinglinking is easy to use linkifier that converts URLs and emails to HTML hyperlinksCodehttps://github.com/w95/linkingIssue trackerhttps://github.com/w95/linking/issuesLicenseMIT License; see LICENSE file###Installing linkinglinking is available onPyPI, so you can install it withpip::$ pip install linking###Basic useThe simplest way to use linking is:importlinkinglinking.text('some text tesla.com, ...')# -> 'some text <a href="http://tesla.com">tesla.com</a>, ...'linking.text('https://tesla.com',{'rel':'nofollow'})# -> '<a href="https://tesla.com" rel="nofollow">https://tesla.com</a>'linking.text('elon@tesla.com')# -> '<a href="mailto:elon@tesla.com">elon@tesla.com</a>'
Package: linkinglines
Welcome to LinkingLines!1. IntroductionWelcome to the documentation for our Python module that performs the Hough
Transform on line data from a CSV, clusters it using Agglomerative Clustering,
and provides functionality to export the results into a CSV file.
This module also includes custom plotting scripts and feature extraction
methods to help you analyze and visualize your data effectively.This code was used to create the results published inKubo Hutchison et al., 2023.
Initially, it was designed to link together mapped dike segments in Cartesian space
to find their true lengths. This code can be applied to any linear features including
roads, fractures, and other types of linear data.Data Clustering: Apply Agglomerative Clustering to group similar data points, this
can be used for data reduction, analysis, and mapping .Data Visualization: Custom plotting scripts help you visualize and analyze
your data, making it easier to identify patterns and anomalies.Feature Extraction: Extract meaningful features from clustered data to
perform further analysis, such as linear or radial type features.Full documentation can be found onReadTheDocs2. InstallationTo use this module, make sure you have Python installed (preferably Python 3.x).
You can install the required packages using pip:pipinstalllinkinglines3. Quick Startimportpandasaspdimportnumpyasnpimportmatplotlib.pyplotaspltimportlinkinglinesaslldata=pd.read_csv('path/to/data')theta,rho,xc,yc=ll.HoughTransform(data)data['theta']=thetadata['rho']=rhodtheta=2#degreesdrho=500#metersdikeset,Z=ll.AggCluster(data)lines,evaluation=examineCluster(data)fig,ax=DotsLines(lines,ColorBy='AvgTheta')Follow this indepthtutorialto get started!You are now ready to utilize the power of Hough Line Transform, Agglomerative Clustering, and custom plotting in your data analysis projects. If you have any questions or need further assistance, please refer to the detailed documentation or contact our support team.Happy coding!
Package: link.kvstore
link.kvstoreis a database agnostic key/value store API.Seedocumentationfor more informations.Installationpip install link.kvstoreFeaturesdatabase agnosticdict API to access key/value storeExamplesGetting a backend:fromlink.middleware.coreimportMiddleware# Instanciate a K/V store with Riak backendstore=Middleware.get_middleware_by_uri('kvstore+riak://localhost:8087/mybuckettype/mybucket?protocol=pbc')# Instanciate a K/V store with SQL backendstore=Middleware.get_middleware_by_uri('kvstore+sql://localhost:5432/database/table')Accessing data:store['foo']='bar'assertstore['foo']=='bar'assert'foo'instoreforkeyinstore:print(key)delstore['foo']Donating
Package: linklabs-conductor
Welcome to Conductor, Link Labs’ cloud-based data-services platform. Conductor
is a suite of cloud-based services with the purposes of managing the
configuration of and data used bySymphony LinkandLTE Cat M1networks.
This is a python wrapper of Link Labs’s Conductor and Airfinder services. For
more in-depth documenation to Conductor’s services, please check out ourUser Guide.Documentation can be found here:http://devdocs.link-labs.com/conductor_py/InstallationThis package is distributed onPyPIand can be installed withpip:pip install linklabs-conductor --pre
pip install linklabs-conductor --pre --upgrade  # When a previous version is installed.For more information read the full documentation onAccountReporting IssuesTo report issues or make feature requests, please visit ourBitbucketIssues Page.
Package: linklabs-host-interface
This is a python implementation of the Link Labs host interface.To get started, simply instantiate aModuleDriver:import ll_ifc
mod = ll_ifc.ModuleDriver()Then, set up the module with your gateway’s network token and the desired application token:app_token = '12345678901234567890'
net_token = '12345678'
mod.set_up(app_token, net_token)Once that’s finished, you can send uplink messages:mod.send_message_checked(b'hello')And receive downlink messages:mod.set_downlink_mode('always')
mod.wait_for_received_message()
Package: linkm
# LinkM<b>[This project is in active development and not currently recommended for public use.]</b>LinkM is a wrapper around [BamM](http://minillinim.github.io/BamM/) for associating 16S reads with assembled contigs. Emphasis has been placed on linking 16S fragments with contigs binned into putative population genomes. It works as follows:* all pairs where one or both reads derived from a 16S sequence are identified* these <i>16S pairs</i> are mapped onto assembled contigs* report which 16S pairs were mapped to assembled contigs* optionally, a set of population genomes (i.e., bins) can be provided for identifying 16S pairs associated with a specific genomeLinkM was developed as 16S sequence often fail to assemble. As a result, it is common to obtain population genomes either without a 16S sequences or with only a partial 16S sequence. The 16S pairs associated with a population genome can be used to perform a <i>de novo</i> assembly with just these pairs, or used as short fragments and parsimoniously placed in an existing 16S tree. We have also observed that in many cases the 16S pairs will link a contig within a population genome to a partially assembled 16S fragment which was too short to be properly binned.## InstallThe simplest way to install this package is through pip:> sudo pip install linkmLinkM relies on several other software packages which must be on your system path:* [BamM](http://minillinim.github.io/BamM/)* [bwa](http://bio-bwa.sourceforge.net/)* [hmmer](http://hmmer.janelia.org/)## CiteIf you find this package useful, please cite this git repository (https://github.com/dparks1134/LinkM)## CopyrightCopyright © 2015 Donovan Parks. See LICENSE for further details.
Package: linkmanager
LinkManagermanage your link on terminal.Replace bookmark tool present on browser because :Is often heavyDependent of the browser in questionHas a lot of frillsDataBase usage depend on browserFind a local link should not require several hundred MB of Ram and eat your CPUOne software for one thing (Unix Philosophy)KISS for import/exportMany other good reasonsRequirementsLinkmanager depends onredisDatabase and GIT (personal “clint” version).
You must install it like this (on debian/ubuntu) :$sudoapt-getinstallredis-servergitTo enjoy completion, usually you don’t have to do anything extra.
A “sudo pip install” should add it automatically.
Otherwise, just add the run the following command to your ~/.bashrc or ~/.zshrc :$eval"$(register-python-argcompletelinkm)"Examples$linkmaddhttp://stackoverflow.com# add a link on Database$linkmupdatehttp://stackoverflow.com# update properties on a existent link$linkmremovehttp://stackoverflow.com# remove a link on DataBase$linkmsearchpythonlinux# search a link a link on DataBase with tags$linkmdump>|backup.json# serialize a entire Database on a JSON file$linkmloadbackup.json# load a list of links on DataBase$linkmflush# erase all DataBasewhen you add/edit links, the “shell” will ask you for each one to edit tags, priority value and a description.$linkmaddhttp://djangoproject.com"http://djangoproject.com"properties:tags(separatewith","):django,python,frameworkpriorityvalue(integervaluebetween1and10):5giveadescription:Djangoisahigh-levelPythonWebframeworkthatencouragesrapiddevelopmentandclean,pragmaticdesign.Release History0.4.0.14 (2014-10-04)Add features to LinkManager to use it on a production server[Bug] first launch + data requirement with installation0.4.0 (2014-09-16)[cli] : auto-completion[cli] : progress bar on long load[webserver] : add/del/update[webserver] : add a tag-it extension[webserver] : lazyloading and inline on css & jsconf files on /etc/ and ~/.configusage of fakeredis on unit tests[webserver] flatdesignREAD_ONLY option0.3.0 (2014-04-15)some setup.py correction + init redis on launchdebian package + travis/toxadd version optionbetter i18n + change makemessages script + new doc example0.2 (2014-03-14)test it with a Dockerfile (docker.io)setup.py with a dependance not include on pypi : a fork of clint (https://github.com/mothsART/clint)pre-launch redis serverchange script name + README examplesadd requirementsadd HISTORY.rst on MANIFEST.in0.1 (2014-03-09)french translationenglish manpageAUTHORS.rst and HISTORY.rst file
Package: link-migration
Link MigrationA generic tool for schema and data migrations.The primary inspirations for this library came from Alembic, Django, and Hibernate/Liquibase. The ultimate goal is to allow a lightweight migration framework to be deployed into any technology stack. Much of this currently relies on the user to implement, however with time more and more integrations will be added to the default set.Version0.0.12InstallationIf you have pip available on your system, just type::pip install link-migrationIf you’ve already got an old version of link-migration, and want to upgrade, use:pip install --upgrade link-migrationUsage IntroductionThe first thing you’ll need to define is the conf.py file and to specify its location:link_migration -c "path_to_file/conf.py"Below are the minimum requirements for definitions in conf.py. The important step here is to specify where the migrations folder exists so they can be detected, and to specify where to store and fetch the versions for executed migrations.import os
import requests
import json

ROOT_DIR = 'link_migration.example_migrations'
MIGRATIONS_ABS_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__)))
MIGRATIONS_DIR = 'link_migration.example_migrations'


def get_current_version():
    path = "%s/current_version.txt" % MIGRATIONS_ABS_PATH
    with open(path, "r+") as f:
        content = f.read()
    return int(content)


def set_current_version(version):
    path = "%s/current_version.txt" % MIGRATIONS_ABS_PATH
    with open(path, "w") as f:
        content = f.write(f'{version}')
    return int(content)Link Migration uses theversioninformation to track the migrations schema and to
decide the order of execution of the scripts. Link Migration will go through all .py
files in your directory and execute all of themversionorder.Migrating to a specific versionIf you want, you can migrate your database schema to a specific version by
informing the --to (or -t) parameter. The attributeversionof the migration
file will be used as unique identifier:$ link-migration --to=57If you don’t specify any version, using --up or --down, Link Migration will migrate
the schema to the latest version available in the migrations directories
specified in the config file.
Package: linkml
LinkML - Linked Data Modeling LanguageLinkML is a linked data modeling language following object-oriented and ontological principles. LinkML models are typically authored in YAML, and can be converted to other schema representation formats such as JSON or RDF.This repo holds the tools for generating and working with LinkML. For the LinkML schema (metamodel), please seehttps://github.com/linkml/linkml-modelThe complete documentation for LinkML can be found here:linkml.io/linkml
Package: linkml-activitypub
linkml-activitypubLinkML representation of ActivityStreams and ActivityPub schemahttps://pypi.org/projects/linkml-activitypubSource schema:linkml_activitypub/activitystreams.yaml- ActivityStreams2 vocabulary schemalinkml_activitypub/activitypub.yaml- ActivityPub Extensions to ActivityStreams2 (imports ActivityStreams2)Generated models:generated/- All generated schema for both source schemaPydantic 2 Models:linkml_activitypub/activitystreams.pylinkml_activitypub/activitypub.pyDataclasseslinkml_activitypub/dataclass/activitystreams.pylinkml_activitypub/dataclass/activitypub.pyActivityStreamsProcessIntermediate files are in thedatadirectoryactivitystreams2.owl- Initially imported fromactivitystreams2.owlRemoved problematic OrderedCollection definitionsactivitystreams2.ofn- Convert to functional notation withrobotactivitystreams2.yaml- Then to rough linkml usingschema-automatorThen the final schema inlinkml_activitypub/activitystreams.yaml:Reorder to match ActivityStreamsEnsure correctinheritancemultivaluedPrune extra properties and classes to match those inActivityStreams2normative definitionThen re-add the ones that declare a class in their domain, even if the class doesn't list that property in its definitionExcept for those types that seem to be metaclasses:attributedTo(->actor)Added LinkML properties (where needed):Classesdisjoint_withsee_alsowhen references givenPropertiesdescriptiondomainrangeminumum_valuemaximum_valueAdded missing slotsclosedstartIndexHandle special property casesitemsis marked aslist_elements_ordered: trueonOrderedCollectionand false onCollectionMade typesanyURI asxsd:anyURI, did not try and find a validator pattern. The spec alternatingly uses its own anyURI prop andxsd:anyURIdurationas a string that indicates it's axsd:duration, finding a pattern is TODOMade enumsunitEnum- forunitCopied Notes to classdescriptionrather thancommentsAdded schema prefixes:schema:https://schema.org/- for specifying IETF BCP 47 language codesErrataOrderedCollectionPageis not a subclass of, and doesn't mix inCollectionPagesince it would then have an ambiguous
class definition, sinceOrderedCollectioninherits fromCollectionbut asserts that thelist_items_orderedslot istruerather thanfalse. Instead, the slots fromCollectionPageare just duplicated.Accordingly, the domain and range of slots that includeCollectionPagealso include `OrderedCollectionPageNeed to implement somexsd:durationpatternTODOJSON-LD Serialization:https://www.w3.org/TR/activitystreams-core/#syntaxconventionsCollection serialization: "In the JSON serialization, the unordered items of a Collection are represented using the items property while ordered items are represented using the orderedItems property."ShoulditemsandorderedItemsjust be disjoint slots, rather than a slot with a special property modification?ActivityPubProcessErrataTODOEverything!ReferencesStatus of AS OWL vocabulary and etc.https://github.com/w3c/activitystreams/issues/416See Alsohttps://github.com/steve-bate/activitypub-ontology
Package: linkml-arrays
linkml-arraysSupport for N-dimensional arrays in LinkML.Quick reference for common commandscdlinkml-model
poetryrungen-json-schematests/input/examples/schema_definition-array-2.yaml
poetryrungen-pydantictests/input/examples/schema_definition-array-2.yamlAcknowledgementsThiscookiecutterproject was developed from themonarch-project-templatetemplate and will be kept up-to-date usingcruft.
Package: linkml-model
LinkML ModelMetamodel schema, documentation, and specification for the Linked Open Data Modeling Language (LinkML)This documentation is best viewed view the generated web documentationhttps://w3id.org/linkml/Quick LinksGenerated documentationSpecificationSource YAML for metamodelMain LinkML siteAbout LinkMLLinkML is a modeling framework for building datamodels and related applications.The best place to start discovering more about linkml is on the main LinkML website,linkml.io/linkmlLinkML is self-describing, and the underlying datamodel for describing data models is in LinkML. This repository contains that data modelFor DevelopersSee thecontributing docsInstallationThis project uses poetry:>cdlinkml-model
>poetryinstallRunning tests>maketest
Package: linkml-renderer
linkml-rendererGenerating HTML, Markdown, Mermaid, and other rendering artefacts from LinkML data.This applies a configurablegenericmapping between instance data and the target output file.
This is an example of a "no code" approach to generating visual representations of data.In general, writing custom code (e.g. in Jinja) that is specific to your schema may produce
more user-friendly results. LinkML-renderer should only be used in cases where it is harder to
commit developer resources to writing custom code.Status: experimentalCommand Line UsageMinimally, you must pass in a schema (LinkML YAML) and a file of instance data conforming to the schema:linkml-render -s my-schema.yaml my-data.yamlor with a specific output file:linkml-render -s my-schema.yaml my-data.yaml -o output.htmlThe default output type is HTML.To produce other formats:linkml-render -s my-schema.yaml -f markdown my-data.yaml -o output.mdYou can pass in a configuration file using--config(`-c).linkml-render -s my-schema.yaml  my-data.yaml -c my-config.yamlThe YAML file should conform to the style datamodel Configuration object.
(note: autodocumentation for this model will be produced later, for now
consult the LinkML file).Python UsageWhen this library matures, the python documentation will be linked from the main LinkML docs.For now, see the docstrings directly in the source, and the test folder for examples.See minimal sphinx docs:https://linkml.github.io/linkml-rendererOutput typesHTMLMarkdownMermaidNote that the mermaid can be optionally embedded inside the HTML or Markdown.How it worksThe input object is treated as a tree, and nodes in the tree are recursively visited, producing
output in the desired format.For HTML and markdown generation, the following default rules are applied:singular outer objects are translated to Description Listslists of objects are translated to tablesThese rules are contextual:Tables are not nested inside tablesThe rules are also configurable. See the style schema and test cases for details.For example, in the person infoschema, a Container contains a list of persons and a list of organizations.
The default rendering will create two tables, with each row representing an individual or organization.This can lead to wide tables if there are a large number of slots.If thepersonsororganizationsslot is mapped toRenderType.description_list, then instead, each item
gets its own description list, resulting in a longer narrower page.Limitations and Future plansCurrently there are limits to customizability, both in terms of stylesheets and in terms of how schema
elements map to output elements.The HTML generation is currently hardwired to use Bootstrap.It is likely that the functionality here may be subsumed into a future linkml.js library. At this time
the framework may be extended to include interactive form-based data entry.The library has not yet been tested on a wide range of data.
Package: linkml-runtime
linkml-runtimeRuntime support for linkml generated data classesAboutThis python library provides runtime support forLinkMLdatamodels.See theLinkML repofor thePython Dataclass Generatorwhich will convert a schema into a Python object model. That model will have dependencies on functionality in this library.The library also providesloaders: for loading from external formats such as json, yaml, rdf, tsv into LinkML instancesdumpers: the reverse operationSeeworking with datain the documentation for more detailsThis repository also contains the Python dataclass representation of theLinkML metamodel, and various utility functions that are useful for working with LinkML data and schemas.It also includes theSchemaViewclass for working with LinkML schemasNotebooksSee thenotebooksfolder for examples
Package: link-notify
Link_NotifySimple notification creator with button package by progbitsvisit us -https://progbits.xyzFor docs, tutorials and updates visit -https://progbits.xyz/link-notifyInstallation-pip install link-notifySimple code to create a notification-importlink_notifyaslnln.notify("Text for notification under 40 characters","link to open(example.com)",5,#time till notification disappears"text on button")
Package: linkodeit
… lets you send your code tohttp://linkode.orgweb service$ linkodeit -h
usage: linkodeit [-h] [-p PARENT | -g GET] [-i INPUT] [-t TYPE] [-o]
                 [-r REVISION] [-v] [--version]

Paste a text on linkode.org

optional arguments:
  -h, --help            show this help message and exit
  -p PARENT, --parent PARENT
                        linkode id of its parent
  -g GET, --get GET     linkode id to get is parent to this new one
  -i INPUT, --input INPUT
                        text file to be pasted on linkode.org
  -t TYPE, --type TYPE  the type of the content (plain text, Python, diff, C,
                        etc.)
  -o, --open            open the default browser with the link
  -r REVISION, --revision REVISION
                        the revision number of the node that is parent to this
                        new one
  -v, --verbose         show all the debug information
  --version             show the version and exitInstallation$ sudo pip install linkodeitUsage$ echo "Hello world" | linkodeit
http://linkode.org/mqNUYxvinPK9dfHeYa0zF2