Saravanan666/pypi-org huggingface dataset:
Package: varsity
Varsity helps you define your application’s settings, read them from
environment variables, parse them into native Python types, and validate
them.Load a simple stringAssume the FOO environment variable as been set to ‘3’. After setting up
the loader and calling its .load() method, we get back a dictionary with
a key for each setting we’ve added to the loader.>>> from varsity import Loader
>>> l = Loader()
>>> l.add('FOO')
>>> settings = l.load()
>>> settings.FOO
'3'If you want to use a different name for the setting within Python, you
can provide your own.>>> l.add('FOO', 'foo')
>>> settings = l.load()
>>> settings.foo
'3'The object returned from .load() also provides dictionary-style access
to settings.>>> settings['foo']
'3'You can provide a ‘typ’ callable that will be used to convert the
environment variable string into the type of your choice.>>> l.add('FOO', 'foo', typ=int)
>>> settings = l.load()
>>> settings.foo
3You can provide defaults that will be returned if the environment
variable is not present.>>> l.add('SOME_UNSET_VAR', default=0)
>>> settings = l.load()
>>> settings.SOME_UNSET_VAR
0If you don’t provide a default, and the environment variable is not set,
ValueError will be raised.You can provide your own callable as the ‘typ’ argument. Assume the
‘TODAY’ environment variable is set to ‘2016-05-05’.>>> from varsity import Loader
>>> from iso8601 import parse_date
>>> l = Loader()
>>> l.add('TODAY', 'today', typ=lambda x: parse_date(x).date())
>>> settings = l.load()
>>> settings.today
datetime.date(2016, 5, 5)If you don’t provide a ‘typ’, but you do provide a default, then the
environment variable will be cast to the same type as the default. (Here
we get back an int 3 instead of the string ‘3’, because the default is
an int.)>>> l.add('FOO', 'foo', default=0)
>>> settings = l.load()
>>> settings.foo
3If you access a setting with the attribute-style syntax, then nested
dictionaries can also be accessed with that syntax. In this example, the
FOO environment variable is set to ‘{“bar”: {“baz”: 1.23}}’>>> l.add('FOO', 'foo', typ=json.loads)
>>> settings = l.load()
>>> settings.foo.bar.baz
1.23
Package: varsnap
Varsnap PythonPython Varsnap ClientInstallationInstall from PyPI -pip install varsnapRequirementsThe client depends on three environment variables to be set:VARSNAP- Should be eithertrueorfalse.  Varsnap will be disabled if the variable is anything other thantrue.ENV- If set todevelopment, the client will receive events from production.  If set toproduction, the client will emit events.VARSNAP_PRODUCER_TOKEN- Only clients with this token may emit production snapshots.  Copied fromhttps://www.varsnap.com/user/VARSNAP_CONSUMER_TOKEN- Only clients with this token may emit development snapshots.  Copied fromhttps://www.varsnap.com/user/UsageAdd the varsnap decorator in front of any function you'd like to make better:fromvarsnapimportvarsnap@varsnapdefexample(args,**kwargs):return'output'TestingWith the proper environment variables set, in a test file, add:importunittestfromvarsnapimporttestclassTestIntegration(unittest.TestCase):deftest_varsnap(self):matches,logs=test()ifmatchesisNone:raiseunittest.case.SkipTest('No Snaps found')self.assertTrue(matches,logs)If you're testing a Flask application, set up atest request contextwhen testing:# app = Flask()withapp.test_request_context():matches,logs=test()TroubleshootingDecorators changing function namesUsing decorators may change the name of functions.  In order to not confuse
varsnap, set the decorated function's__qualname__and__signature__to
match the original function:importinspectdefdecorator(func):defdecorated(*args,**kwargs):func(*args,**kwargs)decorated.__qualname__=func.__qualname__wrapper.__signature__=inspect.signature(func)returndecoratedPublishingpipinstallbuildtwine
python-mbuild
twineuploaddist/*
Package: varsom-flood-client
varsom-flood-clientNo description provided (generated by Swagger Codegenhttps://github.com/swagger-api/swagger-codegen)This Python package is automatically generated by theSwagger Codegenproject:API version: v1.0.5Package version: 1.0.0Build package: io.swagger.codegen.v3.generators.python.PythonClientCodegenRequirements.Python 2.7 and 3.4+Installation & Usagepip installIf the python package is hosted on Github, you can install directly from Githubpipinstallgit+https://github.com/GIT_USER_ID/GIT_REPO_ID.git(you may need to runpipwith root permission:sudo pip install git+https://github.com/GIT_USER_ID/GIT_REPO_ID.git)Then import the package:importvarsom_flood_clientSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importvarsom_flood_clientGetting StartedPlease follow theinstallation procedureand then run the following:from__future__importprint_functionimporttimeimportvarsom_flood_clientfromvarsom_flood_client.restimportApiExceptionfrompprintimportpprint# create an instance of the API classapi_instance=varsom_flood_client.CapApi(varsom_flood_client.ApiClient(configuration))startdate='2013-10-20T19:20:30+01:00'# datetime |enddate='2013-10-20T19:20:30+01:00'# datetime |try:api_response=api_instance.cap_feed(startdate,enddate)pprint(api_response)exceptApiExceptionase:print("Exception when calling CapApi->cap_feed:%s\n"%e)# create an instance of the API classapi_instance=varsom_flood_client.CapApi(varsom_flood_client.ApiClient(configuration))id='id_example'# str |try:api_response=api_instance.cap_id(id)pprint(api_response)exceptApiExceptionase:print("Exception when calling CapApi->cap_id:%s\n"%e)Documentation for API EndpointsAll URIs are relative tohttps://api01.nve.no/hydrology/forecast/flood/v1.0.5ClassMethodHTTP requestDescriptionCapApicap_feedGET/api/Cap/Feed/{startdate}/{enddate}CapApicap_idGET/api/Cap/Id/{id}RegionApiregion_getGET/api/Region/{countyId}WarningApiwarning_allGET/api/Warning/All/{langkey}/{startdate}/{enddate}WarningApiwarning_countyGET/api/Warning/County/{county}/{langkey}/{startdate}/{enddate}WarningApiwarning_getGET/api/Warning/{langkey}/{startdate}/{enddate}WarningApiwarning_municipalityGET/api/Warning/Municipality/{municipality}/{langkey}/{startdate}/{enddate}Documentation For ModelsAlertAlertInfoAlertInfoAreaAlertInfoAreaGeocodeAlertInfoEventCodeAlertInfoParameterAlertInfoResourceCauseCodePageDataItemCountyDecoderFallbackEncoderFallbackEncodingFormattedContentResultAlertFormattedContentResultListAlertIRequiredMemberSelectorMediaTypeFormatterMediaTypeHeaderValueMediaTypeMappingMicroBlogPostMunicipalityNameValueHeaderValueStationWarningDocumentation For AuthorizationAll endpoints do not require authorization.Author
Package: varsom-landslide-client
varsom-landslide-clientNo description provided (generated by Swagger Codegenhttps://github.com/swagger-api/swagger-codegen)This Python package is automatically generated by theSwagger Codegenproject:API version: v1.0.6Package version: 1.0.0Build package: io.swagger.codegen.v3.generators.python.PythonClientCodegenRequirements.Python 2.7 and 3.4+Installation & Usagepip installIf the python package is hosted on Github, you can install directly from Githubpipinstallgit+https://github.com/GIT_USER_ID/GIT_REPO_ID.git(you may need to runpipwith root permission:sudo pip install git+https://github.com/GIT_USER_ID/GIT_REPO_ID.git)Then import the package:importvarsom_landslide_clientSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importvarsom_landslide_clientGetting StartedPlease follow theinstallation procedureand then run the following:from__future__importprint_functionimporttimeimportvarsom_landslide_clientfromvarsom_landslide_client.restimportApiExceptionfrompprintimportpprint# create an instance of the API classapi_instance=varsom_landslide_client.CapApi(varsom_landslide_client.ApiClient(configuration))startdate='2013-10-20T19:20:30+01:00'# datetime |enddate='2013-10-20T19:20:30+01:00'# datetime |try:api_response=api_instance.cap_feed(startdate,enddate)pprint(api_response)exceptApiExceptionase:print("Exception when calling CapApi->cap_feed:%s\n"%e)# create an instance of the API classapi_instance=varsom_landslide_client.CapApi(varsom_landslide_client.ApiClient(configuration))id='id_example'# str |try:api_response=api_instance.cap_id(id)pprint(api_response)exceptApiExceptionase:print("Exception when calling CapApi->cap_id:%s\n"%e)Documentation for API EndpointsAll URIs are relative tohttps://api01.nve.no/hydrology/forecast/landslide/v1.0.6ClassMethodHTTP requestDescriptionCapApicap_feedGET/api/Cap/Feed/{startdate}/{enddate}CapApicap_idGET/api/Cap/Id/{id}RegionApiregion_getGET/api/Region/{countyId}WarningApiwarning_allGET/api/Warning/All/{langkey}/{startdate}/{enddate}WarningApiwarning_countyGET/api/Warning/County/{county}/{langkey}/{startdate}/{enddate}WarningApiwarning_getGET/api/Warning/{langkey}/{startdate}/{enddate}WarningApiwarning_municipalityGET/api/Warning/Municipality/{municipality}/{langkey}/{startdate}/{enddate}Documentation For ModelsAlertAlertInfoAlertInfoAreaAlertInfoAreaGeocodeAlertInfoEventCodeAlertInfoParameterAlertInfoResourceCauseCodePageDataItemCountyDecoderFallbackEncoderFallbackEncodingFormattedContentResultAlertFormattedContentResultListAlertIRequiredMemberSelectorMediaTypeFormatterMediaTypeHeaderValueMediaTypeMappingMicroBlogPostMunicipalityNameValueHeaderValueStationWarningDocumentation For AuthorizationAll endpoints do not require authorization.Author
Package: varsom-regobs-client
## Introduction    RegObs is a tool for collecting observations and events   related to natural hazards. It is currently used by the   Norwegian flood, landslide and avalanche warning service in   Norway, but the data is openly available for anyone through this API.    Regobs has been developed by the Norwegian Water resources and   Energy Directorate (NVE), in collaboration with the Norwegian   Meteorological Institute (MET) and the Norwegian Public Roads   Administration (NPRA).    You can check out our representation of the data at [regobs.no](http://regobs.no).    ## Authentication    Some endpoints require an api key.  You can get an API key by sending an email to   [raek@nve.no](mailto:raek@nve.no?subject&#x3D;RegObs%20API%20Key).  To use the api key with the swagger ui, fill in the api_key input above.   It should then be included with every request in the   &#x60;regObs_apptoken&#x60; header.    ## Getting started    Get the last 10 observations using python:    &#x60;&#x60;&#x60;python  import requests  r &#x3D; requests.post(&#x27;https://api.regobs.no/v4/Search&#x27;,       data&#x3D;{&#x27;NumberOfRecords&#x27;: 10},      headers&#x3D;{&#x27;Content-Type&#x27;: &#x27;application/json&#x27;}  )  data &#x3D; r.json()  print(len(data))  # 10  &#x60;&#x60;&#x60;      # noqa: E501
Package: varst
Replace substitutions in rst files with variables.Getting StartedcliSeequickstart documentation.$pipinstallvarst$varst-h# --helpGithub ActionsvarST can be integrated withGithub Actions.
Please refer to thislinkand apply it to your own workflows.ContributingContribution GuidelinePlease read thecontributing guidelinesto learn how to contribute to this project.Reporting IssuesIf you have any questions, suggestions, or bug reports, please feel free to report them to the issue.Code of ConductThis project is governed by theCode of Conduct.LicenseMIT
License
Package: varstardetect
Varstar DetectPython package optimized for variable star detection in TESS Secctor 1
data.Initialization:To install repository from PyPi:from varstardectect import StarLooking for stellar variability:Use theamplitude_test()function, with the following documentation,
to determine objects which are variable. In which you have to determine
the directory of the archive file with the sector info, it must be a csv.amplitude_test(min, max, amp, directory):
"""                
                   amplitude_test DOCUMENTATION
---------------------------------------------------------------------
Detects variable stars with amplitude higher than threshold.
---------------------------------------------------------------------
INPUTS:     - min: lower star search (TESS) range delimiter
            - max: higher star search (TESS) range delimiter
            - amp: amplitude threshold
            - directory: directory with TESS sector 1 files csv. You can
              download from
              https://tess.mit.edu/observations/target-lists/
        -------------------------------------------------------------
OUTPUTS:    - candidates: 1D numpy array with variable candidate 
              target IDs
            - chis: 1D numpy array with the chi^2 parameter of each
              approximation.
            - degree: 1D numpy array with the degree of the optimal
              degree of the approximation.
            - periods: 1D numpy array with the period of each 
              approimating function.
            - period_errors: 1D numpy array with the period 
              uncertainty for each candidate.
            - amplitudes: 1D numpy array with the amplitude of each
              approximation.
            - amplitude_errors: 1D numpy array with the uncertainty 
              of the amplitude of each candidate.
----------------------------------------------------------------------
PROCEDURE:
            1. Calculates amplitude for an observed star.
            2. Calculates if amplitude is bigger than threshold.
            3. Returns candidates and their characteristics.
----------------------------------------------------------------------
"""Background:The function uses several numerical and statistical methods to filter
and interpret the data obtained form TESS, providing the characteristics
of each star through phenomenological analysis of the lightcurve, given
that it has passed the amplitude test.DISCLAIMER:This is a Beta state of the program. It is unstable therefore itcan have
bugs. It has not been optimized correctly yet.
Package: varsubst
Varsubst is a rewrite ofenvsubst.Varsubst render templates from a string with a given resolver.Currently varsubst support shell-like variables.Entry-point has currently been removed. It may be added in the future.Resolvers provided are :EnvResolver: provide value based on environnement variables.DictResolver: provide value based on a given python dictionary.Supported template variablesVarsubst support shell-like variables which are defined as follows:$MY_SIMPLE_VARor${MY_SIMPLE_VAR}: will resolve the variableMY_SIMPLE_VAR${USER-default}: will resolve the variableUSER. If variable is unset thendefaultstring is returned.${USER-$DEFAULT_USER}: will resolve the variableUSER. If variable is unset, resolve the variableDEFAULT_USER.${USER:-default}: will resolve the variableUSER. If variable is unset or empty thendefaultstring is returned.${USER-$DEFAULT_USER}: will resolve the variableUSER. If variable is unset or empty, resolve the variableDEFAULT_USER.Usagefromvarsubstimportvarsubstfromvarsubst.resolversimportDictResolverfromvarsubst.interpolators.jinja_interpolatorimportJinjaInterpolatorprint(varsubst('$USER'))# result : 'tiboun'print(varsubst('$UNDEFINED'))# result : KeyUnresolvedException('UNDEFINED')print(varsubst('$UNDEFINED',fail_on_unresolved=False))# result : ''print(varsubst('$UNDEFINED',fail_on_unresolved=False))# result : ''print(varsubst('$USER',resolver=DictResolver({'USER':'tiboun'})))print(varsubst('{{ USER }}',interpolator=JinjaInterpolator()))ExtrasYou may installvarsubst[jinja2]as well if you intend to interpolate template with Jinja.
If you plan to use jinja2 only, you may install it yourself in your project instead of using this one.
Package: vartests
vartestsis a Python library to perform some statistical tests to evaluate Value at Risk (VaR) Models, such as:T-test: verify if mean of distribution is zero;Kupiec Test (1995): verify if the number of violations is consistent with the violations predicted by the model;Berkowitz Test (2001): verify if conditional distributions of returns "GARCH(1,1)"  used in the VaR Model is adherent to the data. In this specific test, we do not observe the whole data, only the tail;Christoffersen and Pelletier Test (2004): also known as Duration Test. Duration is time between violations of VaR. It tests if VaR Model has quickly response to market movements by consequence the violations do not form volatility clusters. This test verifies if violations has no memory i.e. should be independent.InstallationUsing pipYou can install using the pip package manager by running:pipinstallvartestsAlternatively, you could install the latest version directly from Github:pipinstallhttps://github.com/rafa-rod/vartests/archive/refs/heads/main.zipWhy vartests is important?After VaR calculation, it is necessary to perform statistic tests to evaluate the VaR Models. To select the best model, they should be validated by backtests.ExampleFirst of all, lets read a file with a PnL (distribution of profit and loss) of a portfolio in which also contains the VaR and its violations.importpandasaspddata=pd.read_excel("Example.xlsx",index_col=0)violations=data["Violations"]pnl=data["PnL"]data.sample(5)The dataframe looks like:' |     PnL       |      VaR        |   Violations |
  | -889.003707   | -2554.503872    |            0 |
  | -2554.503872  | -2202.221691    |            1 | 
  | -887.527423   | -2193.692570    |            0 |  
  | -274.344126   | -2160.290746    |            0 | 
  | 1376.018638   | -5719.833100    |            0 |'Not all tests should be applied to the VaR Model. Some of them should be applied when the VaR Model has the assumption of zero mean or follow a specific distribution.importvartestsvartests.zero_mean_test(pnl.values,conf_level=0.95)This assumption is commonly used in parametric VaR like EWMA and GARCH Models. Besides that, is necessary check assumption of the distribution. So you should test with Berkowitz (2001):importvartestsvartests.berkowtiz_tail_test(pnl,volatility_window=252,var_conf_level=0.99,conf_level=0.95)The following tests should be used to any kind of VaR Models.importvartestsvartests.kupiec_test(violations,var_conf_level=0.99,conf_level=0.95)vartests.duration_test(violations,conf_level=0.95)If you want to see the failure ratio of the VaR Model, just type:importvartestsvartests.failure_rate(violations)
Package: vartex
VarTexVarTeX is a command line tool that allows you to generate and compile
multiple LaTeX files from a single template file and a JSON/CSV file containing the variables.UsageTo run the command, use the following command:vartextex_filename<flag>variable_filenameFor example, in theexampledirectory, to use the JSON filevariables.jsonto generate the LaTeX filetemplate.tex:vartexexample/cover_letter.tex--jsonvariables.json
Package: varuploader
Recovery SD Card Uploader ToolInternal tool to help the R&D Software team upload new releases to the FTPReport Bug·Request FeatureAboutThe Variscite Recovery SD Card Uploader tool helps the internal R&D Software
team upload new recovery SD cards releases to theVariscite FTPserver,
automatically updating the changelog file in theYAMLfile format.1.Getting StartedSupported OSOSArchReleaseStatusDebian GNU/Linux 11 (bullseye)x86_641.0.0PassedUbuntu GNU/Linux 22.04 LTSx86_641.0.0PassedMint GNU/Linux 21x86_641.0.0PrerequisitesDebian and UbuntuInstall the following dependencies packages in the host system:aptinstallpython3python3-pippyyamlInstall via Pip Tool (Recommended)To install the Recovery SD Card Uploader tool, use the pip tool:pip3installvaruploaderImportant NotesYou may need to export the following path:export PATH="$HOME/.local/bin:$PATH"Thevaruploaderpackage is hosted on thepypi.orgpage.To manually build the tool, see thisbuildingguide.(back to top)2.UsageTo use the tool, run in the terminal:varuploaderCreate New ReleaseThe following steps automatically updates thechangelogfile and uploads the
recovery SD card to the FTP:Choose the recovery SD card to upload to the Variscite FTP, then press theCreate New Releasebutton.NOTE:The recovery SD card tool automatically renames the recovery SD card image.Fill the fields according, then press theExport Releasebutton:NOTE:Thedate,path,sha224, and thefile sizeare automatically filled.Review the information, then press theOkbutton:Enter the Variscite FTP credentials, then press theOkbutton:NOTE:Theuserandpasswordvalues are the FTP credentials with root
permission that allows thevar-uploadertool to upload and update files in
the FTP server. These credentials are managed by the R&D Software Team.Edit an Existing ReleaseComing soon.Remove an Existing ReleaseComing soon.(back to top)3.Changelog and RoadmapLatest Release1.0.0 - 2022-08-18 - Initial Release of the Variscite Recovery SD Card Uploader ToolSee the full changelog file content athere.Next ReleasesSee the roadmap for the next features:FeatureRelease VersionStatusDateSupport for Yocto Releases1.0.0Passed08/2022Support for Debian Releases09/2022Support for B2Qt Releases09/2022Support to Create New Release1.0.0Passed08/2022Support to Edit an Existing Release10/2022Support to Remove an Existing Release10/2022(back to top)4.Copyright and LicenseCopyright 2022 Variscite LTD. Free use of this software is granted under
the terms of theBSD 3-Clause License.(back to top)
Package: varvamp
variableVirusAMPlicons (varVAMP) is a tool to design primers for highly diverse viruses. The input is an alignment of your viral (full-genome) sequences.varVAMPFor a lot of virus genera it is difficult to design pan-specific primers. varVAMP solves this by introducing ambiguous characters into primers and minimizes mismatches at the 3' end. Primers might not work for some sequences of your input alignment but should recognize the large majority.varVAMP comes in three different flavors:SINGLE: varVAMP searches for the very best primers and reports back non-overlapping amplicons which can be used for PCR-based screening approaches.TILED: varVAMP uses a graph based approach to design overlapping amplicons that tile the entire viral genome. This designs amplicons that are suitable for Oxford Nanopore or Illumina based full-genome sequencing.QPCR: varVAMP searches for small amplicons with an optimized internal probe (TaqMan). It minimizes temperature differences between the primers and checks for amplicon secondary structures.DocumentationInstallationPreparing the dataUsageOutputWet-lab protocolHow it worksFAQAlready established primer schemesWe, in collaboration with specialists for the respective viruses, have already designed and wet-lab evaluated primer schemes for various viral pathogens. All the input data and varVAMP outputs are freely availablehere.If you design primers for a particular pathogen, we will be happy to include them in this repo and make it freely available. Just contribute via an issue or pull request!Citing varVAMP (coming soon)Please cite with the respective DOI of the version you used:varVAMP: automated pan-specific primer design for tiled full genome sequencing and qPCR of highly diverse viral pathogens.(paper currently under preparation)Important disclaimer:For the primer design, varVAMP usesprimer3to check if digested kmers of a sequence are potential primers. Some of the functions for this were adapted fromprimalschemeand I do not claim credit.The remaing code is under the GPLv3 licence. The code is WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.