Saravanan666/pypi-org huggingface dataset:
Package: edrnsite.content
This package,edrnsite.content, provides a framework for deploying content
into theEDRNPublic Portal, implemented withPlone.Normally, you would use Plone’s staging and permissions features to stage new
content and new versions of content on the officialEDRNPublic Portal
directly.However,JPLdoesn’t want to do that.  They’d rather put new content and new
versions of content onanothercopy of theEDRNPublic Portal, and then
somehow migrate that content when we do a new release of the portal software
to theofficialpublic portal.Hence, this package.This package was developed by the Informatics Center (IC), operated byJPL.InstallationUseBuildoutwith the plone.recipe.zope2instance recipe.Addedrnsite.contentto the list of eggs to install, e.g.:[buildout]
...
eggs =
    ...
    edrnsite.contentRe-run buildout, e.g. with:% ./bin/buildoutChangelogWhat follows is a history of changes from release to release.0.0.0 — Happy BirthdayThis is the first release of edrnsite.content.CopyrightCopyright 2012 by the California Institute of Technology.  ALL RIGHTS
RESERVED.The Software is owned by Caltech/JPL and is protected by United States
copyright laws and applicable international treaties and/or conventions.  The
United States Government may have prior rights to use some or all of the
Software as determined under applicable contracts and license agreements with
Caltech/JPL.This software was developed at the Jet Propulsion Laboratory, an operating
division of the California Institute of Technology and is not available for
use by any person, organization, or other entity without prior, specific
written permission.
Package: edrnsite.funding
This product,edrnsite.funding, provides content types forPlone3 (or
later) to announce, search, discover, and manage funding opportunities of the
Early Detection Research Network (EDRN).  Although intended for the EDRN
public portal, it can be installed in any Plone-compatible site.It was developed by the Informatics Center (IC), operated byJPL.InstallationUseBuildoutwith the plone.recipe.zope2instance recipe.Addedrnsite.fundingto the list of eggs to install, e.g.:[buildout]
...
eggs =
    ...
    edrnsite.fundingRe-run buildout, e.g. with:% ./bin/buildoutYou can skip the ZCML slug if you are going to explicitly include the package
from another package’s configure.zcml file.ChangelogWhat follows is a history of changes from release to release.1.0.6 — Plone 4.3.9 UpgradeCA-15921.0.5 — I Had Some Chicken; Pass Me the FLOSSFirst official release as free/libre/open source software.1.0.4 — Let’s TalkCA-1229 - Discussion re-enabled after upgrade1.0.3 — UpgradesThis release includes:Plone 4.3 compatibility.1.0.2 — Test SupportThis release includes:Depending on just Plone the framework instead of Plone the application.Updating to the plone.app.testing fixtures.1.0.1 — Upgrade CleanupThis release includes the following:Upgrades the profile and provides profile upgrade steps.Works around naive timezones by going into the future an extra day.1.0.0 — Plone 4This release makes edrnsite.funding compatible with Plone 4.0.0.0 — UnreleasedInitial release into beta.
Package: edrnsite.vanity
This package allowsEDRNmembers to create their own vanity pages, showing
off their portraits, biomarkers they work on, publications they’ve made, etc.
It was developed by the EDRN Informatics Center (IC) at the Jet Propulsion
Laboratory (JPL).InstallationUse zc.buildout and the plone.recipe.zope2instance recipe to manage your
project, adding this package as an egg.  You don’t need a ZCML slug because it
uses z3c.autoinclude.plugin with the Plone target.ChangelogWhat follows is a log of changes from release to release.  Where issue
identifiers appear, you can find more about them by visiting this project’s
issue tracker athttps://oodt.jpl.nasa.gov/jira/browse/CA.1.0.6 — Plone 4.3.9 UpgradeCA-15921.0.5 — You’re Not That VainCA-1493 - Bespoke pages should show protocols, then biomarkers and datasetsCA-1498 - Disable vanity pages1.0.4 — You’re So VainFinally a functioning bespoke page!1.0.3 — I Had Some Chicken; Pass Me the FLOSSFirst official release as free/libre/open source software.1.0.2 — UpgradesCompatibility with Zope 2.13.20.1.0.1 — More FleshAdditional attributes on bespoke pages: email, phone, EDRN title, specialtyControl panel to enable/disable vanity page creation, naggingMake vanity pages compatible with Members List1.0.0 — FCSFirst customer shipCA-1078 - Access to Vanity Pages0.0.0 — UnreleasedInitial, unreleased release.
Package: edrn.summarizer
Server for the Early Detection Research Network (EDRN) that provides
summary of EDRN’s knowledge using the various summarization methods.edrn.summarizer InstallationUse zc.buildout and the plone.recipe.zope2instance recipe to manage your
project, and do the following:Addedrn.summarizerto the list of eggs to install, e.g.:[buildout]
...
eggs =
    ...
    edrn.summarizerRe-run buildout, e.g. with:$ ./bin/buildoutYou don’t need a ZCML slug because it uses z3c.autoinclude.plugin with the
Plone target.ChangelogWhat follows is a log of changes from release to release.  Where issue
identifiers appear, you can find more about them by visiting this project’s
issue tracker athttps://oodt.jpl.nasa.gov/jira/browse/CA.0.0.7 - You are now mutatedCA-1434CA-14760.0.6 - Ignore, bad version0.0.5 — New content typeCA-1412 - Fetch group too largeCA-1421 - Added dataset to organ summary statistics0.0.4 - ID WebserviceCA-1352CA-13530.0.3 - Tests fixed, naming correctedCA-1340, edrn.summarizer tests fail0.0.2 - JSON Sumarization addedUpdated edrn.summarizer with jsonCA-1329, Create a set of summarization services that summarizes and serves json data for visualizations as well as external data sources0.0.1 - ReleasedFirst releaseGenerates summarized data from dmccCA-1340, edrn.summarizer tests fail0.0.0 - Unreleasedunreleased versionGenerates summarized data from dmcc
Package: e-drone
e-droneInstall> pip install e_drone
> pip --no-cache-dir install e_droneUpgrade> pip install --upgrade e_droneUninstall> pip uninstall e_droneLinkPyPI E-DroneGithub RepositoryDocuments for E-Drone python library.BYROBOT DevBYROBOT ForumDiscord BYROBOTYoutube BYROBOT ChannelFacebook BYROBOTBYROBOT
Package: e-drone-nightly
e_drone_nightlynightly version ofe_drone.Install> pip install e_drone_nightly
> pip --no-cache-dir install e_drone_nightlyUpgrade> pip install --upgrade e_drone_nightlyUninstall> pip uninstall e_drone_nightlyLinkPyPI E-DroneDocuments for E-Drone python library.BYROBOT DevBYROBOT ForumDiscord BYROBOTYoutube BYROBOT ChannelFacebook BYROBOTBYROBOT
Package: edr-pydantic
OGC Environmental Data Retrieval (EDR) API PydanticThis repository contains the edr-pydantic Python package. It providesPydanticmodels
for theOGC Environmental Data Retrieval (EDR) API.
This can, for example, be used to help develop an EDR API using FastAPI.Installpipinstalledr-pydanticOr to install from source:pipinstallgit+https://github.com/KNMI/edr-pydantic.gitUsagefromedr_pydantic.collectionsimportCollectionfromedr_pydantic.data_queriesimportEDRQuery,EDRQueryLink,DataQueriesfromedr_pydantic.extentimportExtent,Spatialfromedr_pydantic.linkimportLinkfromedr_pydantic.observed_propertyimportObservedPropertyfromedr_pydantic.parameterimportParameters,Parameterfromedr_pydantic.unitimportUnitfromedr_pydantic.variablesimportVariablesc=Collection(id="hrly_obs",title="Hourly Site Specific observations",description="Observation data for UK observing sites",extent=Extent(spatial=Spatial(bbox=[[-15.0,48.0,5.0,62.0]],crs="WGS84")),links=[Link(href="https://example.org/uk-hourly-site-specific-observations",rel="service-doc")],data_queries=DataQueries(position=EDRQuery(link=EDRQueryLink(href="https://example.org/edr/collections/hrly_obs/position?coords={coords}",rel="data",variables=Variables(query_type="position",output_formats=["CoverageJSON"])))),parameter_names=Parameters({"Wind Direction":Parameter(unit=Unit(label="degree true"),observedProperty=ObservedProperty(id="https://codes.wmo.int/common/quantity-kind/_windDirection",label="Wind Direction"))}))print(c.model_dump_json(indent=2,exclude_none=True))Will print{"id":"hrly_obs","title":"Hourly Site Specific observations","description":"Observation data for UK observing sites","links":[{"href":"https://example.org/uk-hourly-site-specific-observations","rel":"service-doc"}],"extent":{"spatial":{"bbox":[[-15.0,48.0,5.0,62.0]],"crs":"WGS84"}},"data_queries":{"position":{"link":{"href":"https://example.org/edr/collections/hrly_obs/position?coords={coords}","rel":"data","variables":{"query_type":"position","output_formats":["CoverageJSON"]}}}},"parameter_names":{"Wind Direction":{"type":"Parameter","unit":{"label":"degree true"},"observedProperty":{"id":"https://codes.wmo.int/common/quantity-kind/_windDirection","label":"Wind Direction"}}}}ContributingMake an editable install from within the repository rootpipinstall-e'.[test]'Running testspytesttests/Real world usageThis library is used to build an Environmental Data Retrieval (EDR) API, serving observation data from surface weather data station data from the KNMI. See theKNMI Data Platform.Related projectsCoverageJSON Pydanticgeojson-pydanticTODOsHelp is wanted in the following areas to fully implement the EDR spec:See TODOs in code listing various small inconsistencies in the specIn various places there could be more validation on contentLicenseApache License, Version 2.0
Package: eds4jinja2
eds4jinja2An easy way to reports generation with Jinja2 templates.With Embedded Datasource Specifications inside Jinja2 templates, you can fetch the data you need on the spot.Specify the data sources in your JINJA templates directly.{% set content, error = from_file(path).fetch_tree() %} \n
content:  {{ content }}\n
error: {{ error }}\n{% set content, error =
    from_endpoint(endpoint).with_query(query_string).fetch_tabular() %}
content:  {{ content }} \n
error: {{ error }} \nInstallationpipinstalleds4jinja2UsageRead the docs hereContributingYou are more than welcome to help expand and mature this project. We adhere toApache code of conduct, please follow it in all your interactions on the project.When contributing to this repository, please first discuss the change you wish to make via issue, email, or any other method with the maintainers of this repository before making a change.LicenceThis project is licensed underApache License 2.0.
Powered byMeaningfy.
Package: edsac
NAME----__edsac__ (Electronic Delay Storage Automatic Computer)SYNOPIS-------edsac [ __-h__ ] [ __-v__ ] [ __-f__ __FILE__ ] [ __-r__ __REPRESENTATION__ ]DESCRIPTION-----------__EDSAC__  (Electronic Delay Storage Automatic Computer) is a simulator capable of executing __EDSAC__ I computer's stored-programs.__-f__, __--file__ = _FILE_Specifies the input file.__-r__, __--representation__ = _REPRESENTATION_Representation of memory map/table.+ 1 : values+ 2 : instructions (default)__-h__, __--help__Display help information and exit.__-v__, __--version__Display version information and exit.FILES-----+ `setup.py`  				traditional easy_install or pip+ `setup.cfg` 				for distutils2 installation+ `scripts/edsac`			executable binary+ `edsac/__init__.py` 		a separate library packaged version+ `edsac/EDSACGrammar.py`	edsac grammar+ `edsac/EDSACLexer.py`		edsac lexerEXAMPLES--------There are some programs included under stored-programs directory. Different ways of simulating stored programs are shown below.```bashMrmacHD:~$ edsac -f stored-programs/Hello.txtMrmacHD:~$ python3 edsac -f stored-programs/TypeWriter.txt```STANDARDS---------SEE ALSO--------[The Edsac Simulator](http://www.dcs.warwick.ac.uk/~edsac/), [__EDSAC__](http://www.cs.clemson.edu/~mark/edsac.html)AUTHOR------MrmacHD <mrmachd@gmail.com>BUGS----The EDSAC I kernel is hardcoded at startup, therefore some original EDSAC stored-programs won't simulate flawlessly by default and require rewriting.
Package: eds-api-client
Electronic Disclosure Statement (EDS) API ClientThis driver allows other projects to interact with the City of Chicago's EDS system.SetupDependencieslxmlscrapelibInstallationeds-api-clientis installable via pip.UsageThis driver provides three endpoints. In order to succesfully instantiate theEDSAPIClientclass, provide values forclient_id,client_secret, anddomain. If nodomainis provided, the default value ishttps://apiqa.chicago.govThis driver provides three main functions:Register a usernew_user_response = api_client.register_user(registration_data,
                                             app_username=client_username,
                                             app_password=client_password)Log in a userresponse = api_client._get_access_token(client_username, client_password)Submit an EDSresponse = api_client.submit_eds(submission_data, client_username, client_password)DevelopmentClone this repository, create a virtual environment, then install the package and test requirements.gitclonehttps://github.com/datamade/eds-api-client.git
python3-mvenv~/.virtualenvs/python-eds-clientsource~/.virtualends/python-eds-client
pipinstall-e.
pipinstall-rtest_requirements.txtTo run the tests:pytest-svCopyright and attributionCopyright (c) 2023 DataMade. Released under theMIT License.
Package: edsl
Emeritus Domain-Specific LanguageThe Emeritus Domain-Specific Language (EDSL) package lets you conduct social science and market research with AI. Use it to design surveys and experiments, simulate responses with LLMs, and analyze results.🔗 LinksPyPI:https://pypi.org/project/edsl/Documentation:https://www.goemeritus.com/getting-started/Discord:https://discord.com/invite/mxAYkjfy9m💡 Contributing, Feature Asks, and BugsInterested in contributing? Want us to add a new feature? Found a nasty bug that you would like us to squash? Please send us an email atinfo@goemeritus.comor message us at our discord server.💻 Getting startedOur package is compatible with Python 3.9 - 3.11.pip install edslSeehttps://www.goemeritus.com/getting-started/for examples and tutorials.🔧 DependenciesThe main third-party package requirement isopenai.
Package: edsnlp
EDS-NLPEDS-NLP is a collaborative NLP framework that aims primarily at extracting information from French clinical notes.
At its core, it is a collection of components or pipes, either rule-based functions or
deep learning modules. These components are organized into a novel efficient and modular pipeline system, built for hybrid and multitask models. We usespaCyto represent documents and their annotations, andPytorchas a deep-learning backend for trainable components.EDS-NLP is versatile and can be used on any textual document. The rule-based components are fully compatible with spaCy's components, and vice versa. This library is a product of collaborative effort, and we encourage further contributions to enhance its capabilities.Check out our interactivedemo!FeaturesRule-based componentsfor French clinical notesTrainable components: NER, Span classificationSupport for multitask deep-learning models withweights sharingFast inference, with multi-GPU support out of the boxEasy to use, with a spaCy-like APICompatible with rule-based spaCy componentsSupport for various io formats likeBRAT,JSON,Parquet,PandasorSparkQuick startInstallationYou can install EDS-NLP viapip. We recommend pinning the library version in your projects, or use a strict package manager likePoetry.pipinstalledsnlp==0.10.6or if you want to use the trainable components (using pytorch)pipinstall"edsnlp[ml]==0.10.6"A first pipelineOnce you've installed the library, let's begin with a very simple example that extracts mentions of COVID19 in a text, and detects whether they are negated.importedsnlpnlp=edsnlp.blank("eds")terms=dict(covid=["covid","coronavirus"],)# Split the documents into sentences, this isneeded for negation detectionnlp.add_pipe("eds.sentences")# Matcher componentnlp.add_pipe("eds.matcher",config=dict(terms=terms))# Negation detectionnlp.add_pipe("eds.negation")# Process your text in one call !doc=nlp("Le patient n'est pas atteint de covid")doc.ents# Out: (covid,)doc.ents[0]._.negation# Out: TrueDocumentation & TutorialsGo to thedocumentationfor more information.DisclaimerThe performances of an extraction pipeline may depend on the population and documents that are considered.Contributing to EDS-NLPWe welcome contributions ! Fork the project and propose a pull request.
Take a look at thededicated pagefor detail.CitationIf you use EDS-NLP, please cite us as below.@misc{edsnlp,author={Wajsburt, Perceval and Petit-Jean, Thomas and Dura, Basile and Cohen, Ariel and Jean, Charline and Bey, Romain},doi={10.5281/zenodo.6424993},title={EDS-NLP: efficient information extraction from French clinical notes},url={https://aphp.github.io/edsnlp}}AcknowledgementWe would like to thankAssistance Publique – Hôpitaux de Paris,AP-HP FoundationandInriafor funding this project.
Package: edspdf
EDS-PDFEDS-PDF provides a modular framework to extract text information from PDF documents.You can use it out-of-the-box, or extend it to fit your specific use case. We provide a pipeline system and various utilities for visualizing and processing PDFs, as well as multiple components to build complex models:complex models:📄Extractorsto parse PDFs (based onpdfminer,mupdforpoppler)🎯Classifiersto perform text box classification, in order to segment PDFs🧩Aggregatorsto produce an aggregated output from the detected text boxes🧠 Trainable layers to incorporate machine learning in your pipeline (e.g.,embeddingbuilding blocks or atrainable classifier)Visit the:book: documentationfor more information!Getting startedInstallationInstall the library with pip:pipinstalledspdfExtracting textLet's build a simple PDF extractor that uses a rule-based classifier. There are two
ways to do this, either by using theconfiguration systemor by using
the pipeline API.Create a configuration file:config.cfg[pipeline]pipeline=["extractor", "classifier", "aggregator"][components.extractor]@factory="pdfminer-extractor"[components.classifier]@factory="mask-classifier"x0=0.2x1=0.9y0=0.3y1=0.6threshold=0.1[components.aggregator]@factory="simple-aggregator"and load it from Python:importedspdffrompathlibimportPathmodel=edspdf.load("config.cfg")# (1)Or create a pipeline directly from Python:fromedspdfimportPipelinemodel=Pipeline()model.add_pipe("pdfminer-extractor")model.add_pipe("mask-classifier",config=dict(x0=0.2,x1=0.9,y0=0.3,y1=0.6,threshold=0.1,),)model.add_pipe("simple-aggregator")This pipeline can then be applied (for instance with thisPDF):# Get a PDFpdf=Path("/Users/perceval/Development/edspdf/tests/resources/letter.pdf").read_bytes()pdf=model(pdf)body=pdf.aggregated_texts["body"]text,style=body.text,body.propertiesSee therule-based recipefor a step-by-step explanation of what is happening.CitationIf you use EDS-PDF, please cite us as below.@software{edspdf,author={Dura, Basile and Wajsburt, Perceval and Calliger, Alice and Gérardin, Christel and Bey, Romain},doi={10.5281/zenodo.6902977},license={BSD-3-Clause},title={{EDS-PDF: Smart text extraction from PDF documents}},url={https://github.com/aphp/edspdf}}AcknowledgementWe would like to thankAssistance Publique – Hôpitaux de ParisandAP-HP Foundationfor funding this project.
Package: edspdf-mupdf
edspdf-mupdfedspdf-mupdf provides a MuPdf-based PDF parser component forEDS-PDFBeware, MuPdf isAGPL-licensed: edspdf-mupdf is therefore also AGPL-licensed, and any model depending on this component must be too.Getting startedInstall the library with pip:$pipinstalledspdf-mupdfUsagefrom edspdf import Pipeline

model = Pipeline()
model.add_pipe('mupdf-extractor')

model(pdf_bytes)Visit thedocumentationfor more information!AcknowledgementWe would like to thankAssistance Publique – Hôpitaux de ParisandAP-HP Foundationfor funding this project.
Package: edspdf-poppler
edspdf-poppleredspdf-poppler provides a Poppler-based PDF parser component forEDS-PDF.
We only provide prebuilt binaries for linux and macos. If you are on windows, you will need to build this lib from source.Beware, Poppler isGPL-licensed: edspdf-poppler is therefore also GPL-licensed, and any model depending on this component must be too.Getting startedInstall the library with pip:$pipinstalledspdf-popplerUsagefrom edspdf import Pipeline

model = Pipeline()
model.add_pipe('poppler-extractor')

model(pdf_bytes)Visit thedocumentationfor more information!AcknowledgementWe would like to thankAssistance Publique – Hôpitaux de ParisandAP-HP Foundationfor funding this project.
Package: eds-scikit
eds-scikit is a tool to assist data scientists working on the AP-HP's Clinical Data Warehouse. It is specifically targeted for OMOP-standardized data. It main goals are to:Ease access and analysis of dataAllow a better transfer of knowledge between projectsImprove research reproducibilityDevelopmentThis library is developed and maintained by the core team of AP-HP’s Clinical Data Warehouse (EDS) with the strong support ofInria's SODA team.How to usePlease check theonline documentationfor more informations. You will findDetailed explanation of the project goal and working principlesA complete API documentationVarious Jupyter Notebooks describing how to use various functionnalities of eds-scikitAnd more !Requirementseds-scikit stands on the shoulders ofSpark 2.4which requires:Python ~3.7.1Java 8InstallationYou can install eds-scikit viapip:pipinstall"eds-scikit[aphp]":warning: If you get an an error during installation, please try downgrading pip viapip install -U "pip<23" before installeds-scikit`:warning: If you don't work in AP-HP's ecosystem (EDS), please install via:pipinstalleds-scikitYou can now import the library viaimporteds_scikitContributingYou want to help on the project ?You developped an interesting feature and you think it could benefit other by being integrated in the library ?You found a bug ?You have a question about the library ?...Please check ourcontributing guidelines.CitationIf you useeds-scikit, please cite us as below.@misc{eds-scikit,author={Petit-Jean, Thomas and Remaki, Adam and Maladière, Vincent and Varoquaux, Gaël and Bey, Romain},doi={10.5281/zenodo.7401549},title={eds-scikit: data analysis on OMOP databases},url={https://github.com/aphp/eds-scikit}}AcknowledgmentWe would like to thank the following funders:Assistance Publique – Hôpitaux de ParisAP-HP FoundationInria
Package: edsteva
EDS-TeVaDocumentation:https://aphp.github.io/edsteva/latest/Source Code:https://github.com/aphp/edstevaEDS-TeVa provides a set of tools that aims at modeling the adoption over time and across space of the Electronic Health Records.RequirementsEDS-TeVa stands on the shoulders ofSpark 2.4which requires:Python ~3.7.1Java 8InstallationYou can install EDS-TeVa throughpip:pipinstalledstevaWe recommend pinning the library version in your projects, or use a strict package manager likePoetry.pip install edsteva==0.2.7ExampleA scientific paper is currently being written that describes extensively the use of the library on the study of quality and epidemiological indicators.ContributingContributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.AcknowledgementWe would like to thankAssistance Publique – Hôpitaux de ParisandAP-HP Foundationfor funding this project.
Package: eds-tools
EDSTools -- EvolvedDevelopmentSequenceToolsBEDTools style repository for passing VCF/BED files.Designed to combined variant calls from peaked data with the reference genome. Returns the genomic sequence of the allele most present in the peak.Example Usage:import eds_tools

py_eds_tool = eds_tools.EdsTool("/<path>/analysis_regions.txt")

py_eds_tool = py_eds_tool.sequence(
    fi= "/<path>/genome.fa",
    vcf="/<path>/gatk-snp-indel.vcf.gz"
)
sequences = py_eds_tool.sequencesTo run the unittests please run:cd eds_tools
python -m unittest discover
Package: edsudoku
This is an utility and website for generating solvable sudoku puzzles.UsageThis utility can be used as a Python package, simply usingimport edsudoku.
For example, a regular sudoku board can be generated as follows:import edsudoku
board = edsudoku.generate(3, 3)In addition, edsudoku provides a WSGI web server application.
This application can be used using the following script:from edsudoku.server import app as application.ContactFor any issue, please contact Eli Daian <elidaian@gmail.com>.