Saravanan666/pypi-org huggingface dataset:
Package: falibrary
FalibraryFalcon add-on for API specification and validation.Provide OpenAPI document and validation for flask service.Mainly built for Machine Learning Model services.If you're using Flask, check my another Python libraryFlaskerk.AttentionI've created a new library namedSpecTree. It supports all the features of Falibrary, but with a better interface. Give it a try! This library may be archived in the future.FeaturesGenerate API document withRedoc UIorSwagger UI:yum:Less boilerplate code, annotations are really easy-to-use :sparkles:Validate query, JSON data, response data withpydantic:wink:Better HTTP exceptions for API services (default & customized) (JSON instead of HTML) :grimacing:Quick StartInstall withpip install falibrary(Python 3.6+)Basic exampleimportfalconfromwsgirefimportsimple_serverfrompydanticimportBaseModelfromfalibraryimportFalibraryapi=Falibrary(title='Demo Service',version='0.1.2',)classQuery(BaseModel):text:strclassDemo():@api.validate(query=Query)defon_post(self,req,resp):print(req.context.query)passif__name__=='__main__':app=falcon.API()app.add_route('/api/demo',Demo())api.register(app)httpd=simple_server.make_server('localhost',8000,app)httpd.serve_forever()Changes you need to make:create model withpydanticdecorate the route function withFalibrary.validate()specify which part you need invalidatequery(args in url)builtin converters(int, uuid, dt)data(JSON data from request)resp(response) this will be transformed to JSON data after validationx(HTTP Exceptions list)tags(tags for this route)register to Falcon applicationAfter that, this library will help you validate the incoming request and provide API document in/apidoc.Parameters inFalibrary.validateCorresponding parameters infalconqueryreq.context.querydatareq.context.dataresp\x\tags\For more details, check thedocument.More featuresimportfalconfromwsgirefimportsimple_serverfrompydanticimportBaseModel,FieldfromrandomimportrandomfromfalibraryimportFalibraryapi=Falibrary(title='Demo Service',version='0.1.2',)classQuery(BaseModel):text:str=Field(...,max_length=100,)classResponse(BaseModel):label:int=Field(...,ge=0,le=9,)score:float=Field(...,gt=0,lt=1,)classData(BaseModel):uid:strlimit:intvip:boolclassClassification():"""classification demo"""@api.validate(tags=['demo'])defon_get(self,req,resp,source,target):"""API summarydescription here: test information with `source` and `target`"""resp.media={'msg':f'hello from{source}to{target}'}@api.validate(query=Query,data=Data,resp=Response,x=[falcon.HTTP_403])defon_post(self,req,resp,source,target):"""post demodemo for `query`, `data`, `resp`, `x`"""print(f'{source}=>{target}')print(req.context.query)print(req.context.data)ifrandom()<0.5:raisefalcon.HTTPForbidden("Bad luck. You're fobidden.")returnResponse(label=int(10*random()),score=random())if__name__=='__main__':app=falcon.API()app.add_route('/api/{source}/{target}',Classification())api.register(app)httpd=simple_server.make_server('localhost',8000,app)httpd.serve_forever()Try it withhttp POST ':8000/api/zh/en?text=hello' uid=0b01001001 limit=5 vip=true.Open the docs inhttp://127.0.0.1:8000/apidoc.For more examples, checkexamples.
Package: falkolab.ext3.direct
Zope3 Ext.Direct - Server-side Stack for ExtJS 3.How do I use it ?Let’s register api and views:>>> from zope.configuration import xmlconfig
>>> context = xmlconfig.string("""
... <configure
...     xmlns="http://namespaces.zope.org/zope"
...     xmlns:extdirect="http://namespaces.zope.org/extdirect"
...     >
...   <include package="falkolab.ext3.direct" file="meta.zcml" />
...
...   <extdirect:api
...       for="zope.app.folder.interfaces.IFolder"
...       namespace = "my.app"
...       />
...
...   <extdirect:view
...       for="zope.app.folder.interfaces.IFolder"
...       class="falkolab.ext3.direct.testing.AlbumList"
...       permission="zope.ManageContent"
...       name="albumlist"
...       />
...
...   <extdirect:view
...       for="zope.app.folder.interfaces.IFolder"
...       class="falkolab.ext3.direct.testing.Contact"
...       permission="zope.ManageContent"
...       />
... </configure>
... """)Direct API:>>> print http(r"""
... GET /@@directapi HTTP/1.1
... Authorization: Basic bWdyOm1ncnB3
... """)
HTTP/1.1 200 Ok
Cache-Control: no-cache
Content-Length: ...
Content-Type: text/javascript;charset=utf-8
Expires: ...
Pragma: no-cache
<BLANKLINE>
Ext.namespace('my.app');
my.app.REMOTING_API={"url": "http://localhost/@@directrouter", "namespace": "my.app", "type": "remoting", "actions": {"Contact": [{"name": "getInfo", "len": 1}], "albumlist": [{"formHandler": true, "name": "add", "len": 0}, {"name": "getAll", "len": 0}]}};Auto add provider :>>> print http(r"""
... GET /@@directapi?add_provider HTTP/1.1
... Authorization: Basic bWdyOm1ncnB3
... """)
HTTP/1.1 200 Ok
Cache-Control: no-cache
Content-Length: ...
Content-Type: text/javascript;charset=utf-8
Expires: ...
Pragma: no-cache
<BLANKLINE>
Ext.namespace('my.app');
my.app.REMOTING_API={"url": "http://localhost/@@directrouter", "namespace": "my.app", "type": "remoting", "actions": {"Contact": [{"name": "getInfo", "len": 1}], "albumlist": [{"formHandler": true, "name": "add", "len": 0}, {"name": "getAll", "len": 0}]}};
Ext.Direct.addProvider(my.app.REMOTING_API);And Direct Request hanling (for addition see ROUTER.TXT):>>> print http(r"""
... POST /@@directrouter HTTP/1.1
... Authorization: Basic bWdyOm1ncnB3
... Content-Length: 71
... Content-Type: application/json; charset=UTF-8
... Referer: http://localhost/
...
... {"action":"albumlist","method":"getAll","data":[],"type":"rpc","tid":1}""")
HTTP/1.1 200 Ok
Content-Length: 89
Content-Type: text/javascript
<BLANKLINE>
{"action": "albumlist", "tid": 1, "type": "rpc", "method": "getAll", "result": [1, 2, 3]}CHANGES1.1.0 (2010-12-23)Changes to support python 2.61.0.1 (2010-11-10)Removed the dependencies on zope.app.intidChanges to support zope.componetnt>=3.6.0Added skipkeys=True for simplejson encoder to prevent
raising a TypeError1.0.0a (2009-08-20)Initial release.
Package: falkolab.recipe.csstools
Detailed Documentation======================================================CSS Tools recipe for ZC Buildout================================falkolab.recipe.csstools is a zc.buildout recipe for building (validation, compressing)css style sheet sources.  The buildout works to writing concatenatedand compressed files from a declarative config.Buildout Format===============Variables---------* output-dir -- path to where result should be written.* config -- path to builder config file* resource-dir -- not required, used for interpolation of builder config* section -- output concatenated file for only this section of the 'config'* output-name -- (for use with 'section') write file to this name* sourceencoding (optional) -- encoding of the source stylesheet* targetencoding (optional) -- encoding of the combined stylesheet, default 'utf-8'* compress -- defines if the combined sheet should be minified, default FalseConfiguration Format--------------------A config file may have multiple uniquely named output files (iemultiple sections).A section is formatted in the following fashion::[styles.css]root=path/to/where/files/arelicense=path/to/license/for/these/libsinclude =first=styles/color.cssstyles/typography.jsstyles/layout.jslast=core/main.jsexclude=debug/layout-debug.css#...The files listed in the `first` variable will be forced to load*before* all other files (in the order listed). The files in `last`variable will be forced to load *after* all the other files (in theorder listed).The files list in the `exclude` section will not be imported.If you set `include` variable then `first` and `last` variable will be ignored.The configuration allows for the interpolation of variables defined inthe config file.  '%(resource-dir)s'Lines commented using '#' will be ignored.Resolving imports------------------Contained  import directives in style sheets will be resolved and replecedby referenced files or urls content:@import url("color.css");@import "layout.css";Imports can't be controlled by bildout configuration(e.g. first, last, include, exclude lists).Examples--------from file buildout.cfg:...[css-builder]recipe=falkolab.recipe.csstools:builderresource-dir=${buildout:directory}/src/path/to/package/resourcesconfig=css-builder.cfgoutput-dir=${css-builder:resource-dir}/stylescompress=Truetargetencoding=utf-8[css-builder-debug]recipe=falkolab.recipe.csstools:builderconfig=${css-builder:config}resource-dir=${css-builder:resource-dir}output-dir=${css-builder:output-dir}output=${css-builder:output-dir}/ts-debug.csscompress=Falsesection=ts.css...CHANGES=======1.0.2 (2009-06-04)------------------- Some minor changes1.0.1 (2009-03-11)------------------- * BUGFIX: can't add license text1.0.0 (2009-03-05)------------------- First release
Package: fallball
# FallBall Service (backend)[![Build Status](https://travis-ci.org/ingrammicro/fallball-service.svg?branch=master)](https://travis-ci.org/ingrammicro/fallball-service) [![PyPi Status](https://img.shields.io/pypi/v/fallball.svg)](https://pypi.python.org/pypi/fallball) [![codecov](https://codecov.io/gh/ingrammicro/fallball-service/branch/master/graph/badge.svg)](https://codecov.io/gh/ingrammicro/fallball-service)## OverviewFallBall is the best in class file sharing service that offers cloud storage and file synchronization for small and medium businesses (SMBs) worldwide.This dummy service helps developers to learn [APS Connect](http://aps.odin.com) technology## Manual Deploy1. Create application database:```python manage.py migrate```1. In order to run server you need to execute the following command from the root folder of the project:```python manage.py runserver <host_name>:<port>```## Deploy into docker container1. Run docker-compose:```docker-compose up```1. Run kickstart script:```docker exec -it fallballapp bash kickstart.sh```Admin token:```d8cc06c05a6cd5d5b6156fd2eb963a6f1fdd039c```## TestsTo run tests simply execute the following command:```python manage.py test fallballapp.tests```## API ReferenceIn order to explore API description follow to [apiary](http://docs.fallball.apiary.io/) page
Package: fallen
FallenOverviewFallen Financial Tools es una recopilación de herramientas creadas mayormente porSt1tch,Franco Lamasy Marcelo Colom.FuentesSitioDatosCohenHistóricosYahoo FinanceHistóricosRava BursátilHistóricosAmbito FinancieroDolar Blue, Oficial y SolidarioMacrotrendsHistóricos, BalancesMetodosYahoo FinanceEjemplo de data histórica:from Fallen import *

#Fechas en formato Año-Mes-Día como string
yahoo.get_history("GGAL.BA","2020-01-01","2021-12-01")Ambito FinancieroEjemplofrom Fallen import *
  
  #Fechas en formato Año-Mes-Día como string
  ambito.dolar_blue("2016-10-01","2021-01-04")El mismo metodo es valido tamto para dolar_oficial y dolar_solidarioRava BursátilEjemplofrom Fallen import *

#Fechas en formato Año-Mes-Día como string
rava.get_history("GGAL","2020-01-01","2021-12-01")MacrotrendsCohenMetodos disponibles:stocks(Acciones)fixed_income(Renta Fija)options(Opciones)cedears(CEDEARs)Ejemplofrom Fallen import *

#Fechas en formato Año-Mes-Día como string
cohen.stocks("GGAL","2023-09-01","2023-11-01")MacrotrendsEjemplo de data histórica:from Fallen import *

#Trae todo el histórico disponible, no se necesita especificar fecha.
macrotrends.history("SPY")Ejemplo de balances:from Fallen import *

#freq es un parametro opcional, puede ser solo 'Q'(por defecto) o 'A'
macrotrends.incomes("GGAL",freq='A')ColaboradoresPaduelInstallationpip install Fallen==0.6.0

pip install git+https://github.com/franco-lamas/Fallen --upgrade --no-cache-dirDISCLAIMERLa información es mostrada “tal cual es”, puede ser incorrecta o contener errores, eso es responsabilidad de cada sitio. No somos responsables por el uso indebido de los Scripts.
Package: fallible
falliblefallible, an experimental ansiblebuilding$python3src/fallible/_vendor/_build.py--pr72553devel
$python3-mbuild-w-odist
$python3-mbuild-w-odistcompat_entrypointsAlternatively, instead of using--prto enumerate individual PRs, you can use--allto fetch all PRs labeled withfallible.using$python3-mfallibleplaybooksite.yml
$fallible-playbooksite.ymlansible-core compatThecompat_entrypointsdir provides a package forfallible-compatthat will installansible*entrypoints.$pip3installfallible-compat
$ansible-playbooksite.yml
Package: fallible-compat
# fallible-compatThis package is effectively a meta package that providesansible*compatibility entrypoints (CLI commands) forfallible.The goal is to provide an easy compat layer for tooling that expects the ansible CLI utilities to be present for it’s functionality, to allow easily testingfalliblein those environments.This package can be installed explicitly via:`shell $ pip installfallible-compat`or as anextrasfor thefalliblepackage via:`shell $ pip install fallible[compat] `
Package: fallocate
fallocate exposes an interface to fallocate(2), posix_fallocate(3) and
posix_fadvise(3).Under Mac OS X the fallocate() method will use the apple equivalent of
fallocate(2). Note that this might not be exactly the same.When using the wrapper functions around the fallocate(2) call the arguments
given to the function are slightly different then the c call.This module has the arguments like:fallocate(fd, offset, length, mode=0)While in C the function looks like:fallocate(fd, mode, offset, length)The main reason for this is that the mode argument tends not to be used much and
thus having the default as a keyword argument is much easier then having to
specify 0 everytime.UsageFuncation: fallocate(fd, offset, len, [mode=0])Calls fallocate() on the file object or file descriptor. This allows
the caller to directly manipulate the allocated disk space for the file
referred to by fd for the byte range starting at offset and continuing
for len bytes.mode is only available in Linux.It should always be 0 unless one of the following possible flags are
specifiedFALLOC_FL_KEEP_SIZE     - do not grow file, default is extend size
FALLOC_FL_PUNCH_HOLE    - punches a hole in file, de-allocates range
FALLOC_FL_COLLAPSE_SIZE - remove a range of a file without leaving a holeNote:FALLOC_FL_COLLAPSE_SIZEwas introduced in Linux kernel v3.15 and is
only available on certain filesystems (e.g. ext4, xfs, etc). In order to get
access to it, you must build and run on a kernel and filesystem that both
support it.Example:# preallocate using fallocate a 1kb file
with open("/tmp/test.file", "w+b") as f:
    fallocate(f, 0, 1024)
Package: fal-serverless
fal-serverlessLibrary to run, serve or schedule your Python functions in the cloud with any machine type you may need.Check out to thedocsfor more details.Generate OpenAPI client for the REST APIThe recommended way is to use bop. First set theFAL_RESTvariable to the right value and then run:bopopenapiInitial client was generated usingcdprojects/fal_serverless# Notice that you can point to any environmentopenapi-python-clientgenerate--urlhttps://rest.shark.fal.ai/openapi.json--metanone--configopenapi_rest.config.yamlAnd can be manually updated withcdprojects/fal_serverless# Notice that you can point to any environmentopenapi-python-clientupdate--urlhttps://rest.shark.fal.ai/openapi.json--metanone--configopenapi_rest.config.yaml
Package: falsy
# falsyFAL.S.Y### descriptionit's an api framework.using falcon, swagger, yaml together!### licenseMIT and Apache v2### showtime![ScreenShot](https://raw.githubusercontent.com/pingf/falsy/master/demo.gif)### how to install it`pip install falsy`### how to use it0. create the dir for static`mkdir static`1. writting the server code(main.py)```pythonfrom falsy.falsy import FALSYf = FALSY()   #you need create the dir called static before you runf.swagger('test.yml', ui=True, theme='impress') #impress theme is the responsive swagger ui, or you can use 'normal' hereapi = f.api```2. writting the yml file```swagger: '2.0'info:title: FALSY SIMPLE DEMO APIversion: "0.1"consumes:- application/jsonproduces:- application/jsonbasePath: "/v1"paths:'/hello':get:tags: [Method]operationId: demo.get_itsummary: testingparameters:- name: namein: querytype: stringdefault: 'john'responses:200:description: Return response```3. writting the operation handler(demo.py)```pythondef get_it(name):return {'get': name}```4. run it`gunicorn -b 0.0.0.0:8001 main:api --reload -w 1 --threads 1`5. visit the ui page`http://0.0.0.0:8001/v1/ui/`make sure it ends with '/'### video demo![ScreenShot](https://raw.githubusercontent.com/pingf/falsy/master/falsy.gif)### extensionsthere some improvements compare to standard swagger,you can define `operationId` for handler, 'beforeId' and 'afterId' for aop hooks,and 'validationId' for validator, see the files in demo dir for details.
Package: falwa
falwa is a package that contains modules to compute the finite-amplitude
local wave activity (FALWA) and reference state (U_ref) in the following papers:
Huang and Nakamura (2016, JAS): http://dx.doi.org/10.1175/JAS-D-15-0194.1
Huang and Nakamura (2017, GRL): http://onlinelibrary.wiley.com/doi/10.1002/2017GL073760/full
Nakamura and Huang (2018, Science): https://doi.org/10.1126/science.aat0721
Neal et al (2022, GRL): https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021GL097699

The current version of the library handles calculation of FALWA in a spherical barotropic model and QGPV fields on 
isobaric surfaces.

The functions in this library can compute the tracer equivalent-latitude relationship
proposed in Nakamura (1996) (Also, see Allen and Nakamura (2003)) and the (zonal mean)
finite-amplitude wave activity in spherical geometry as in Nakamura and Solomon (2010).

Links:    
- Source code: http://github.com/csyhuang/hn2016_falwa/
Package: famafrench
famafrenchfamafrenchis a Python library package designed to replicate and construct datasets fromKen French's online data libraryvia remote access to thewrds-cloudby queryingCRSP,Compustat Fundamentals Annual, and other datafiles.This module uses theWRDS-Pylibrary package to extract data from CRPS, Compustat Fundamentals Annual, and other datafiles via the cloud
for use with thePandas-Pypackage.famafrench's current efficient performance results from features such as the use of aleast recently used (LRU) cacheimplemented using the Python decoratorfunctools.lru_cache.MetricSupportsPython 3.4+Latest ReleaseCode QualityCitationLicenseDocumentationContributingHitCount!famafrenchis best explored by going through applications and examples provided in the released documentation hosted onGithub Pages.Module ContentsModuleDescriptionfamafrench.pyMain module w/ tools for constructing and replicating datasets from Ken French’s online library via queries to WRDS.utils.pyAuxiliary functions and utilities for use in the main modulefamafrench.py.wrdsconnect.pyEnables remote connection to wrds-cloud largely building on theConnection()class in theWRDS-Pylibrary.version.pyModule w/ package's version number.InstallationThe latest release isRelease 0.1.4as of May 12, 2020 (seedocumentation).Python Package Index (pip)Releases are available viaPyPIand can be installed withpip.pipinstallfamafrenchAnaconda (conda)Conda users will soon be able to install from myAnacondachannel. Stay tuned.Dependenciesfamafrenchrelies on a suite of Python libraries, which include Python's scientific computing stack (e.g.NumPyandPandas). Other dependencies includeNumbaandSQLAlchemy.Please seesetup.pyorrequirements.txtfor specific version threshold requirements.DocumentationReleased documentation is hosted onGithub Pages. Look out for future updated documentation from my master branch hosted on Github.ContributingI welcome recommendations, contributions and/or future collaborations. I am ambitious and plan to expand the module to include construction of additional factor-based datasets relevant for empirical asset pricing. These include the following:AQR Capital Management:Betting Against Beta(BAB)Quality Minus Junk(QMJ)Modified Value - High Minus Low(HMLD)Lettau, Ludvigson, and Ma (2019)Capital Share Factor:Capital Share of Aggregate Income(KS)Pastor and Stambaugh (2003)Liquidity Factors:Non-Traded Liquidity FactorTraded Liquidity FactorSadka (2006)Liquidity Factors:Fixed-Transitory FactorVariable-Permanent FactorStambaugh and Yuan (2017)ClusteredMispricing Factors:Management-related Factor(MGMT)Performance-related Factor(PERF)Mispricing (non-clustered) Factor(UMO)Performance and speed improvements are also appreciated.Please report any bugs or errors tomy github pageor please send me an email atchris.jauregui@berkeley.edu.APIFor in-depth call syntaxes, please see the source code doctrings.DisclaimerThis library and its affiliated content was created withoutany involvementby Kenneth R. French and Eugene F. Fama.
Package: famapy
FamapyFaMaPy is a Python-based AAFM framework that takes into consideration previous AAFM tool designs and enables multi-solver and multi-metamodel support for the integration of AAFM tooling on the Python ecosystem.The main features of the framework are:Easy to extend by enabling the creation of new plugins following a semi-automatic generator approach.Support multiple variability models. Currently, it provides support for cardinality-based feature models. However, it is easy to integrate others such as attributed feature modelsSupport multiple solvers. Currently, it provides support for the PySAT metasolver, which enables more than ten different solvers.Support multiple operations. It is developed, having in mind multi-model operations such as those depicted by Familiar  and single-model operations.Available pluginsfamapy-fmfamapy-satDocumentationAll the proyect related documentation can be found in wiki format atwikiChangelogDetailed changes for each release are documented in therelease notesContributingSeeCONTRIBUTING.md
Package: fa-material
fa-materialfa-material is the easiest way to useFont AwesomeProicons in
yourMaterial for MkDocsproject.An active Font Awesome Pro license is required to use fa-material.InstallationInstall Font Awesome Pro's Python package.Install fa-material.pipinstallfa-materialUsageAdd thefontawesome-proplugin tomkdocs.yml:plugins:-fontawesome-proThat's it. You can now use Font Awesome Pro icons in the same way you already do Font Awesome Free icons (e.g.:fontawesome-thin-user-secret:). They'll work in Markdown files,mkdocs.yml, and anywhere else Material for MkDocs'
icon system is used.Font Awesome 5You can use Font Awesome 5 with fa-material by settingfontawesome-pro'sversionoption to5.plugins:-fontawesome-pro:version:5This option must be either5or6, defaulting to the latter.Licensefa-material is licensed under theMIT License.
Package: fame
Fame is a framework for metamodelling in Python.Entities are described by modelsModels are described by metamodelsModels have fields, derived fields and constraintsEntities can have custom fieldsEntities can be created even if data is invalidThere are functions to validate and get error messagesValidation checks presence and type of fieldsValidation checks all constraintsDerived fields are memoizedExampleclass Experiment(Model):

    @schema
    def metamodel(self, m):
        m.field('name', str)
        m.field('subject', options(
            'user',
            'visitor',
            'email',
            'listing',
            'market'
        ))
        m.field('treatments', array(str))
        m.field('percent_exposed', int, default=100)
        m.field('design', nullable(regexp('^https?')))

    @derived_field
    def is_miscellanous(self):
        return self.subject not in ['user', 'visitor']

    @constraint("expected percent_exposed to not exceed 100, got {}")
    def constraint(self):
        if self.percent_exposed > 100:
            return self.percent_exposedConventionsDefine metamodel function firstThen define derived field functionsThen define all the constraint functionsConstraint functions are all named “constraint”, that is intentionalInstallationTo install this package, runpip install fameContributingBug reports and pull requests are welcome on github at,https://github.com/akuhn/py-fame