Saravanan666/pypi-org huggingface dataset:
Package: enpassreaderlib
A library implementing the decrypting and retrieving secrets from an enpass 6 database.Documentation:https://enpassreaderlib.readthedocs.org/en/latestDevelopment WorkflowThe workflow supports the following stepslinttestbuilddocumentuploadgraphThese actions are supported out of the box by the corresponding scripts under _CI/scripts directory with sane defaults based on best practices.
Sourcing setup_aliases.ps1 for windows powershell or setup_aliases.sh in bash on Mac or Linux will provide with handy aliases for the shell of all those commands prepended with an underscore.The bootstrap script creates a .venv directory inside the project directory hosting the virtual environment. It uses pipenv for that.
It is called by all other scripts before they do anything. So one could simple start by calling _lint and that would set up everything before it tried to actually lint the projectOnce the code is ready to be delivered the _tag script should be called accepting one of three arguments, patch, minor, major following the semantic versioning scheme.
So for the initial delivery one would call$ _tag –minorwhich would bump the version of the project to 0.1.0 tag it in git and do a push and also ask for the change and automagically update HISTORY.rst with the version and the change provided.So the full workflow after git is initialized is:repeat as necessary (of course it could be test - code - lint :) )codelinttestcommit and pushdevelop more through the code-lint-test cycletag (with the appropriate argument)buildupload (if you want to host your package in pypi)document (of course this could be run at any point)Important InformationThis template is based on pipenv. In order to be compatible with requirements.txt so the actual created package can be used by any part of the existing python ecosystem some hacks were needed.
So when building a package out of thisdo notsimple call$ python setup.py sdist bdist_eggas this will produce an unusable artifact with files missing.Instead use the provided build and upload scripts that create all the necessary files in the artifact.Project FeaturesSee USAGE.rst.Can retrieve single entriesCan iterate over all entriesCan do fuzzy matching of entries while searchingHistory0.0.1 (25-03-2021)First code creation0.1.0 (25-03-2021)First release with basic required functionality.0.1.1 (25-03-2021)Loosely pinned dependencies and updated the usage and installation notes a bit.0.1.2 (07-07-2021)Added pipeline.0.2.0 (02-03-2023)Expose totp seeds for passwords that support it.0.2.1 (02-03-2023)Fix linting.0.2.2 (02-03-2023)Fix for entries with no password.0.2.3 (10-08-2023)Update to latest default configured pbkdf2 rounds.0.2.4 (10-08-2023)Fix pipeline with required dependencies for upload.0.2.5 (10-08-2023)Remove debugging logging.
Package: enpraxis.leftskin
IntroductionLeft Skin is a Plone skin that provides a prominent left column in a three column display, as well as provides a rich set of parameters and forms to control the basic settings of your Plone site through the web.Changelog2.5Fixed uneven search button in multiple browsers [blambert555]Added missing default left navigation background image [blambert555]Fixed space under logo [blambert555]2.4Refactored default colors, images [blambert555]Brought up to date with Plone 4.2 [blambert555]Fixed several issues where default Plone theme was showing through [blambert555]2.3Fixed table width issue where left nav gets squished on very
wide tables. [blambert555]Updated .pot file, fixed translations [blambert555]Updated Spanish translation files [blambert555]Updated Brazilian Porteguese translation files [blambert555]2.2Fixed issue with table of contents indents2.1Fixed version numbers and cleaned up docs.2.0Updated to now support Plone 4 and built upon sunburst theme.1.1.0Updated the control panel to use jQuery Color Picker.Additional control panels to expose all base properties.Added theming logic to switch between themes.Back up old themes so that they can be restored.
Package: enpt
EnPT - EnMAP Processing ToolThe EnPT Python package is an automated pre-processing pipeline for the new EnMAP hyperspectral satellite data.
It provides free and open-source features to transform EnMAP Level-1B data to Level-2A. The package has been developed
at the German Research Centre for Geosciences Potsdam (GFZ) as an alternative to the processing chain of the EnMAP
Ground Segment.Please check thedocumentationfor installation and usage instructions and in depth information.Information on how tocite the EnPT Python packagecan be found in theCITATIONfile.LicenseFree software: GNU General Public License v3 or later (GPLv3+)All images contained in any (sub-)directory of this repository are licensed under the CC0 license which can be foundhere.Feature overviewread EnMAP Level-1B input dataradiometric conversion to top-of-atmosphere radiancedead pixel correctionatmospheric correction (based onSICORfor land andACwater PolymerviaPolymerfor water surfaces)optional export of additional results from atmospheric parameter retrievaldetection and correction of geometric misregistrations compared to user provided spatial reference (based onAROSICS)orthorectificationwrite EnMAP Level-2A output dataStatusSee also the latestcoveragereport and thepytestHTML report.History / ChangelogYou can find the protocol of recent changes in the EnPT packagehere.CreditsThis software was developed within the context of the EnMAP project supported by the DLR Space Administration with
funds of the German Federal Ministry of Economic Affairs and Energy (on the basis of a decision by the German
Bundestag: 50 EE 1529) and contributions from DLR, GFZ and OHB System AG.Sentinel-2 spatial reference test data have been provided by ESA.This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.
Package: enpy
EnpyThis is an encryption and decryption program that incorporates One Time Pad to encrypt/decrypt text using a randomly generated key.Usage:An example portraying how the program can encrypt/decrypt text:EncryptionThe encrypt function takes two arguments which are the text to be encrypted and the key. If a key isn't provided as an argument, the program will generate a random key. The function returns the encrypted message and the key.import enpy

enc_msg, msg_key = enpy.encrypt("Hello World!", <key>)DecryptionThe Decrypt function takes in 2 arguments which are the encrypted text and the key respectively. It returns the decrypted message and the key.import enpy

dec_msg, msg_key = enpy.decrypt(<enc_msg>, <key>)Change Log1.0.0 (3/9/21)--First release.
Package: enpyre
EnpyreA Python game engine in React.Write python games that run in React applications 👌Enpyre is an open-source library to render 2D games made with Python in React with graphics byPIXI.jsand the power ofPyodide,WASM, and modern web technologies.Install and UsageEnpyre python engine only works inside Pyodide environment.With Enpyre npm packageJust start a React project and addenpyrepackage.StandaloneStart apyodideenvironment and installenpyrepip package by micropip:awaitpyodide.loadPackage('micropip');awaitpyodide.runPythonAsync(`import micropipawait micropip.install('enpyre')from enpyre import *`);Example gamesSeeexamplesof usage.DevelopmentInstall PoetryOSX/Linux:curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -Windows:(Invoke-WebRequest -Uri https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py -UseBasicParsing).Content | python -Install dependenciespoetry installPre commit installpre-commit installRun server./start.shLocal packageSet you web appliction to install enpyre package fromhttp://localhost:8080/enpyre-0.0.1-py3-none-any.whl
Package: enquire
enquireGoalEnquireis a pet project with no ambitions. However, a bit of history might shed some light on the project goals.It was a cold April morning and the dew on the grass was frozen like a tiny piece of glass.Eric CartmanI needed a modern cli prompt library to add some interactivity to my working projects.PyInquirerturned out to be the most easy-to-use
and convenient among all the libs I could find.Unfortunately, the latest version published on pypi had at least one critical bug: it completely ignored
the default value forlistprompts. The GitHub version does not have that bug, however, it seems to be
abandoned for quite some years.Since I only needed the basic, the radio button, and the checkbox types, these were implemented first.Installationpip install enquireBasic usagefromenquire.promptimportpromptfromenquire.questionimportTextif__name__=="__main__":questions=[Text("name","What's your name?",default="Christian")]answers=prompt(questions)print(answers)Question typesTextTextis the most basic prompt type. It asks you a question and waits for you to type an answer.
If there is a default value it will be pre-typed for you.Paramsname- a unique key in the answers dictmessage- a message to show to uservalidate- an optional function accepting the current answers dict and the current answer being typed by a user.
The function must returnTrueif the answer is valid. There are built-in validation functions in
the library likeis_int,is_numberetc.CheckboxCheckboxprompt generates a list of checkboxes and asks a user to pick 0..n options.
The resulting answer will be an array of picked values.RadioRadioprompt presents a list of options and asks a user to pick exactly one of them.BooleanBooleanis a special prompt which is pre-configuredRadiowith only two options - positive and negative.
You can choose how these are named (the defaults areyesandno)This documentation is a work in progress, check out the examples folder to get some usage tipsTo run an example clone the repo, install the dependencies, and runPYTHONPATH="." python examples/text.py
Package: enquiries
enquiriesaims to provide a straightforward way to get decisions from your users.
It can offer multiple choice, yes/no or free textimportenquiriesoptions=['thing 1','thing 2','thing 3']choice=enquiries.choose('Choose one of these options: ',options)ifenquiries.confirm('Do you want to write something?'):text=enquiries.freetext('Write something interesting: ')print(text)Input for these questions is fully interactive and prevents any incorrect
responses. No more loops checking if the answer matches the question. No more
mapping the text entered to original objects. Let users choose the objects
directly.Multiple choiceAll choices consist of letting users pick one of several items. Forenquiriesthese
can be in any iterable.Users can pick one or many of the options offered to them.Single SelectionFor single choice, use thechoosemethod with the list of choices.>>>options=['Thing 1','Thing 2']>>>response=enquiries.choose('Pick a thing',options)# interactive prompt>>>print('You chose "{}"'.format(response))Youchose"Thing 1">>>The interactive prompt here appears as list of options you can scroll through
and select using the return key:Pick a thing
> Thing 1
  Thing 2
  Thing 3Where up/down arrow keys will scroll through the options moving the>marker. The currently selected option is also in bold typeface (if the terminal
supports it).Multiple SelectionsFor cases where the user can choose multiple options, themultikeyword can
be used.>>>options=['Thing 1','Thing 2','Thing 3']>>>response=enquiries.choose('Pick some things',options,multi=True)# interactive prompt>>>print('You chose "{}"'.format(response))Youchose"['Thing1', 'Thing 3']">>>The interactive prompt for multiple choice is similar to that used for single
choice but the>marker is replaces with ◉ and ◌ to signify chosen or not
chosen. As before, the arrow keys change the selection and the current line is
bold. The space key is used to mark an option as selected.:pick a thing
◉ Thing 1
◌ Thing 2
◌ Thing 3Yes/No ConfirmationUsed to get a simple boolean response from users.>>>ifenquiries.confirm('Do you really want to do the thing')...print('Carrying on')...else:...print('Exiting')...# interactive promptCarryingon>>>Results in the prompt below:Do you really want to do the thing? [y/N]The prompt for confirmation by default acceptsy/nkeys to choose and
return to accept the choice. Return without choosing accepts the default value
(usuallyFalse). The keys used and the default can be changed as required.
By default, the user should choose y/n then hit return butsingle_keymode
can be used to remove the need to hit return.Freetextenquiriesfree text offering is offers a slightly enhanced version of theinputbuiltin function. It adds multi line support as well as basic
readline like controls (Ctrl-a,Ctrl-wetc). The text entry area is also cleared after the text is
accepted keeping terminal history clean.>>>text=enquiries.freetext('Write some stuff')>>>print(text)Thisisthetextyouenteredonmanylines>>>New lines in text can be entered usingAlt-Return.
Package: enrich
enrichEnriched extendsrichlibrary functionality
with a set of changes that were not accepted to rich itself.Console with redirect supportOur Console class adds one additional option to rich.Console in order to
redirectsys.stdoutandsys.stderrstreams using a FileProxy.fromenrich.consoleimportConsoleimportsysconsole=Console(redirect=True,# <-- not supported by rich.cosole.Consolerecord=True)sys.write("foo")# this assert would have passed without redirect=Trueassertconsole.export_text()=="foo"Console with implicit soft wrappingIf you want to produce fluid terminal output, one where the client terminal
decides where to wrap the text instead of the application, you can now
tell the Console constructor the soft_wrap preference.fromenrich.consoleimportConsoleimportsysconsole=Console(soft_wrap=True)console.print(...)# no longer need to pass soft_wrap to each printConsole.print can also deal with ANSI escapesExtends Rich Console to detect if original text already had ANSI escapes and
decodes it before processing it. This solves the case where printing
output captured from other processes that contained ANSI escapes would brake.upstream-404Soft-wrapping loggerRich logger assumes that you always have a fixed width console and it does
wrap logged output according to it. Our alternative logger does exactly the
opposite: it ignores the columns of the current console and prints output
using a Console with soft wrapping enabled.The result are logged lines that can be displayed on any terminal or web
page as they will allow the client to decide when to perform the wrapping.importloggingfromenrich.loggingimportRichHandlerFORMAT="%(message)s"logging.basicConfig(level="NOTSET",format=FORMAT,datefmt="[%X]",handlers=[RichHandler()])log=logging.getLogger("rich")log.info("Text that we do not want pre-wrapped by logger:%s",100*"x")
Package: enrich-omics
Enrich_Omics: A Python wrapper for EnrichR and OpenTargetsTable of ContentsAboutInstallationTutorialDocsAboutPython wrapper for EnrichR and OpenTargets API. Allows for visualisation of enriched pathways or diseases associated to a given targetEnrichRChoose from all EnrichR libraries (Transcription, Pathways, Drugs, etc). Default library is KEGG_pathways_2021Get table with enrichment resultsPlot enrichment results and export itOpenTargetsOpen Target is currently only supporting the search of a single targetTarget endpointConvert Entrez to Ensemble if needed (OpenTargets API accepts only Ensemble IDs)Get description of the function of the targetGet diseases associated to a certain targetPlot diseases associated to a certain targetGet table drugs associated to a certain targetPlot the drugs that work for a given target and the diseases associated to itPlot the drugs associated to a given target and the trial phase they are currently inPlotsExport plots in SVG and PNGInstallationpipinstallenrich-omicsTutorialEnrichR APIimportenrich_omicsfromenrich_omicsimportEnrichRfromenrich_omicsimportOpenTargets# get all available librariesEnrichR.get_libraries()# get enrichment for a list of genes/proteins# default library is 'KEGG_2021_Human' but other libraries can be specified using the 'library_name' argument.# check out available libraries with the command above# library_type, height, width and max_hits arguments are optional. See source code for details or docs for examples.gene_list=['LMNA','MYH7','TNNT2','ACE2']EnrichR.plot_enrichment(gene_list)# specifying a different libraryEnrichR.plot_enrichment(gene_list,library_name='BioPlanet_2019',height=200,width=300,max_hits=None)# get results as table for downstream analysis/ pipeline integrationEnrichR.get_table_enrichment(['LMNA','MYH7','TNNT2','ACE2'],library_name='KEGG_2021_Human')Open Targets API (Open Targets currently only supports single target enrichment. More information on the OpenTargets website)# OpenTargets takes EnsembleIDs by default, but entrez ids can be passed using the argument entrez = True# Export plots easily in png or svgOpenTargets.plot_diseases(target_id='PLG',entrez=True)OpenTargets.get_table_drugs(target_id='PLG',entrez=True)# Plot drugs and diseases associated to a given targetOpenTargets.plot_drugs_disease(target_id='PLG',entrez=True)DocsDocumentation for this package can be foundhereContributions always welcome!
Package: enrich_pvalues
A simple script to compare p-values between a test and comparison dataset at a
variety of p-value cutoffs. By plotting the enrichment score at a variety of
cutoffs, it is possible to pick the optimal cutoff for your data.Version: 1.0-beta2ContentsAlgorithmInstallationRequirementsUsageAlgorithmFor each p-value in the interval betweenmax_pval(default: 0.05) andmin_pval(default: 1e-15), we test at intervals of 1 and 5 for each order of
magnitute, e.g. 0.05, 0.01, 0.005, 0.001, 5e-4, 1e-4, 5e-5, 1e-6, … 1e-15.To test, we simply take all identities with a p-value less than the cutoff and
compare them to all identities in the comparison set with p-values below thecomp_set_pvalue. We simply ask what percentage or the test set are in the
comparison set. We then do exactly the same with the entire set of identities in
the comparison set that have a p-value greater than 0.98.The identities are generally going to be gene or SNP names, but they can be
anything (e.g. coordinates) as long as they overlap in the test and comparison
data.InstallationInstall via PyPI:pipinstallenrich_pvaluesOr install from github:pipinstallhttps://github.com/TheFraserLab/enrich_pvalues/tarball/masterIt should work with python 2 or 3, but python 3 is recommended.RequirementsInrequirements.txt, we use numpy, pandas, matplotlib, seaborn, tabulate,
and tqdm.UsageFirst, dump a configuration file to describe your data:enrich_pvaluesdump-configenrich_atac.jsonThis will also print a help table describing each option. You need to describe
your comparison data and your test data, and pick your p-value thresholds.Next, split your comparison dataset into two tables: significant, and
not-significant:enrich_pvaluessplit-cenrich_atac.json--prefixatac/path/to/comp_data.txt.gzNow, run the enrichment using those two tables and your test data:enrich_pvaluesrun-cenrich_atac.json-oatac_scores.xls-patac/path/to/test_data.txtNote, the second to last argument is the prefix from the second step.Finally, plot the data. This can also be done by passing e.g.--plotmyplot.pngto the run step.enrich_pvaluesplot--prefixcaQTLatac_scores.xlsatac_plot.pdfNote: the scores can be excel format, pickled format, or text format, depending
on the suffix. Also, the prefix in this plot step is different, it is used to
title the plot only, and so can be whatever you want.
Package: enrichr
Enrichr VisionEnrichr is a python framework which sets out to address the security integration problem that vendors and analysts have. While the core functionality of Enrichr is targeted towards security enrichment, plugins are not limited to just enrichment. For example, plugins can push data, dispatch reporting jobs, add indicators to blacklists or other functionality.There are 3 primary audiences for Enrichr:Security analystsData ProvidersSecurity IntegratorsSecurity AnalystsEnrichr has a robust command line interface that can be used in day to day workflows. Enrichr provides a consistent method of interacting with many different vendor enrichments and provides a common workflow.Additionally, since the framework is written in python and has sane defaults, analysts can use enrichr to automate either via bash scripts or simple python scripts.Data ProvidersIf you are a security vendor or provide data products, you no dobut realize how hard it can be to maintain integrations with dozens or hundreds of other products. Enrichr aims to alleviate those issues by providing a sane, tested framework that system integrators such as SIEM, SOAR and MSSP Providers can interface with third party products via a common interface.Additionally, enrichr plugins are extremely flexible, so it is possible to expose advanced features and use enrichr as the primary API client for your customers to interact with your service.Security IntegratorsEnrichr provides a high quality, standardized interface to a number of different security products that are supported by the community. This provides a rich ecosystem that integrators such as SOAR vendors, SIEM products and MSSPs can immediately utilize, so they can focus on their core areas of expertise rather than having to constantly worry about integrations.Official PluginsOfficial plugins have rigorous standards that ensure integrators have a supported interface when interacting with different security products. These standards require that each plugin include things like unit tests, documentation, examples, packaging and continuous integration.Community PluginsPlugins that do not meet the standards or are maintained by third parties are considered community plugins. While they still have standards that they conform to, these plugins might be missing things like unit tests, examples or comprehensive documentation.Repository and Module StructureEnrichr splits each plugin into its own python module and repository. The main reason for this is a practical one, if there are third party dependencies that are required for a module to be supported, for example a yara or fuzzy hashing library that need to have C dependencies, enrichr shouldn't pull those in by default. Additionally, each plugin should be pushed to the Python Package Index through CI.
Package: enrichrpy
enrichrpyA tool for gene set enrichment (GSEA) plots and analysis in Python. Built on top of Enrichr API.Installationenrichrpy is easily installed with the pip package manager.Python>=3.6 required.pipinstallenrichrpyBasic UsageA collab notebook with basic usage examples is availablehere.Note, all plots generated by enrichrpy are created by altair, so they can be easily downloaded as either .svg or .png files from your browser.Enrichr GSEA statisticsimportenrichrpy.enrichraseenimportenrichrpy.plottingaseplgenes=['TYROBP','HLA-DRA','SPP1','LAPTM5','C1QB','FCER1G','GPNMB','FCGR3A','RGS1','HLA-DPA1','ITGB2','C1QC','HLA-DPB1','IFI30','SRGN','APOC1','CD68','HLA-DRB1','C1QA','LYZ','APOE','HLA-DQB1','CTSB','HLA-DQA1','CD74','AIF1','FCGR2A','CD14','S100A9','CTSS']df=een.get_pathway_enrichment(genes,gene_set_library='GO_Biological_Process_2021')dfEnrichment bar plotepl.enrichment_barplot(df,n=20)Enrichment dot plotepl.enrichment_dotplot(df,n=20,hue='Z-score',log=True)