Saravanan666/pypi-org huggingface dataset:
Package: retailcrm
This is python RetailCRM API client. This library allows to use all
available API versions.Installpip3 install retailcrmUsage# coding utf-8importretailcrmclient=retailcrm.v3('https://demo.retailcrm.pro','uLxXKBwjQteE9NkO3cJAqTXNwvKktaTc')order={'firstName':'John','lastName':'Doe','phone':'+79000000000','email':'john@example.com','orderMethod':'call-request',}result=client.order_create(order)# coding utf-8importretailcrmclient=retailcrm.v4('https://demo.retailcrm.pro','uLxXKBwjQteE9NkO3cJAqTXNwvKktaTc')result=client.customers_history(filter={'sinceId':'1500','startDate':'2018-03-01'})print(result['pagination']['totalCount'])# coding utf-8importretailcrmclient=retailcrm.v5('https://demo.retailcrm.pro','uLxXKBwjQteE9NkO3cJAqTXNwvKktaTc')site='example-com'task={'text':'Product availability problem','commentary':'Take a look ASAP','order':{'externalId':'100500'},'performerId':1}result=client.task_create(task,site)
Package: retail-sales-prediction
retail-sales-predictionPython project to predict the sales of retail stores with machine learning. This project is
based on the data provided in Kaggle Competition.Kaggle Link :https://www.kaggle.com/c/favorita-grocery-sales-forecasting/Free software: MIT licenseDocumentation:https://retail-sales-prediction.readthedocs.io.Project EnvironmentWe create the project environment using below command.conda env create-fenvironment.yml-p./venvUpdate the existing conda environmentconda env update-fenvironment.yml-p./venvActivate the environmentconda activate ./venvFeaturesMachine learning pipeline to predict the sale forecasting. This project is the sand box
and needs a bit of work to complete it.Currently it supports below featuresRunning the Light GBM Model with fixed training, validation and test sets.Two variants of how unit_sales are filled NA. More can be addedNotebooks with Exploratory data analysisNotebooks with Feature engineering and Model TrainingDocumentation using SphnixTODOProject SlidesYou can view the  project slides of my project at using thislinkCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2019-08-29)First release on PyPI.
Package: retail-scraper
Ecommerce Retailer ScraperThe purpose of this project is to create a library of spiders/scraper for major online ecommerce retailer shop such as Amazon, Sephora, Walmart, and many other brands. The app will return product information and review as well in JSON format.The extracted data you can use for market research, product design, consumer buying impulse...The sky is the limit.Instruction:How to install:pipinstallecom-scraperHow to use:fromretail_scraper.spiders.sephoraimportSephora# Sephora spider take either product url or productid Sephora(url=url, productid=product_id)url='https://www.sephora.com/product/huda-beauty-liquid-matte-ultra-comfort-transfer-proof-lipstick-P479843'product_id='P479843'sephora=Sephora(url=url)# Orsephora=Sephora(productid=product_id)sephora.scrap_product_info()# Instantiate the Scrap product functioninfo=sephora.product_info# product info and its variants will be stored in product_infosephora.scrap_product_reviews()# Instantiate The Scrap product reviews functionreviews=sephora.product_reviews# All product reviews will be stored in product_reviewsSupported ScrapersUlta ScraperSephora ScraperAdd a New Spider or FeatureIf you want to add a spider/scraper to the app or even a new feature please use the link bellow or open it as an issue in this github repo. Most upvoted feature will be added to the app.Add new spider or featureUpcoming Scraper/Spidersverishop Scraperuncommongoods ScraperContributionYou are most welcome to contribute to this project and create pull requests.Credit@diemonsterfor all his comments, feedbacks and instruction.Everyone in the#pythoncommunity in thelibera IRCDisclimarThis library is built for educational puposes ONLY, use at your own risk.
Package: retail-stats
Retail StatsThis repository contains code to calculate various values used in retail for
products whose sales and prices are provided.Metrics currently available:Price Elasticity (In Progress)Cross Elasticity (Complete)These simple, almost naive, implementations are taken from the Wikipedia
definitions of the metrics. All performance benefits are from the work of
Numpy. The purpose of this repository is to provide some convenience functions.InstallationInstall from PyPi.pip install retail-statsIf installing outside of a[virtualenv]()then use--userto avoid permission
issues:pip install --user retail-statsDependenciesnumpy~=1.19CalculationsCross ElasticityFromWikipedia,measures the responsiveness of the quantity demanded for a good to a change
in the price of another good,ceteris paribus.This can be seen written using the formula:Percentage Change in Quantity Sold of Product B
-------------------------------------------------
Percentage Change in Price Charged for Product AThe implementation is a direct copy of the formula.fromretail_stats.elasticityimportcalculate_cross_elasticityCalculate Cross Elasticity for a single pair of productsfrommathimportisclosefromretail_statsimportelasticityoriginal_quantity=200new_quantity=400original_price=1000new_price=1050# (200 / 300) / (50 / 1025)expected_ced=13.66666666666666ced=elasticity.calculate_cross_elasticity(original_quantity,new_quantity,original_price,new_price)assertisclose(expected_ced,ced)Calculate All Cross Elasticitiesfrommathimportiscloseimportnumpyasnpfromretail_stats.elasticityimportget_all_cross_elasticitiesskus=np.array(list("ABCD"))# [original, new]qty_a=[200,0]qty_b=[200,400]prc_a=[1000,1050]prc_b=[1000,1000]qty_c=[1000,1050]qty_d=[1000,1100]prc_c=[100,80]prc_d=[80,80]original_quantities=[qty_a[0],qty_b[0],qty_c[0],qty_d[0]]new_quantities=[qty_a[1],qty_b[1],qty_c[1],qty_d[1]]original_prices=[prc_a[0],prc_b[0],prc_c[0],prc_d[0]]new_prices=[prc_a[1],prc_b[1],prc_c[1],prc_d[1]]"""Cross Elasticities between pairs A,B and C,D| A | B | C | DA |   |   |   |B |   |   |   |C |   |   |   |D |   |   |   |"""ceds=get_all_cross_elasticities(original_quantities=original_quantities,new_quantities=new_quantities,original_prices=original_prices,new_prices=new_prices)assertceds.shape==(len(skus),len(skus))assertisclose(ceds[np.argwhere(skus=="A"),np.argwhere(skus=="A")],-41)assertisclose(ceds[np.argwhere(skus=="B"),np.argwhere(skus=="A")],13.66666666666666)assertisclose(ceds[np.argwhere(skus=="D"),np.argwhere(skus=="C")],-0.4285714286)assertisclose(ceds[np.argwhere(skus=="C"),np.argwhere(skus=="A")],1)assertisclose(ceds[np.argwhere(skus=="A"),np.argwhere(skus=="C")],9)PerformanceCore elasticity functionNumber of ProductsTime in Seconds1,0000.06551210,0000.200022100,0001.7272691,000,00026.730988
Package: retailwind
RetailwindReverse obfuscated tailwind classesInstallpipinstallretailwindUsageYou can either use it as a CLI tool, an interactive terminal app or a python library. In all cases, you will need to provide the stylesheet of the website that hides the tailwind classes (-cflag).CLIJust give you r input after the-rflag.retailwind-cstyle.css-ryzInteractiveUse the-iflag, it will start the interactive app.retailwind-cstyle.css-iYou can write (or paste through shift+right-click or your terminal shortcut like ctrl+shift+v) html fragments and see the translated version on the right panel.Libraryfromretailwind.translatorimportTranslator# init the translator with the stylesheettr=Translator("/path/to/styles.css")# run on raw classtr.raw("yz")# run on html fragmenttr.html("<div class='kw lx yz aai'>retailwind</div>")
Package: retaindate
Really simple module to decide wether a a date string is considered “obsolete”
or not.Given a time-string like2010-01-01it will returnTrueif this date
shouldnotbe retained, orFalseif it should.Other time strings can be used by specifying a different format string (seestrftimeandstrptimefor the detailed syntax)Example Usage:from retaindate import is_obsolete
from datetime import datetime, timedelta

for i in range(10*365, -1, -1):
    date = datetime.today() - timedelta(i)
    if not is_obsolete(date):
        print dateSee the module docs (or the source) for more details
Package: retake
Open Source Infrastructure for Vector Data StreamsData pipelines that synchronize vectors with their sources of truthDocumentation•WebsiteInstallationWelcome! If you are not a contributor and just want to use Retake, please
proceed to themain branch.To install the Retake Python SDK:pipinstallretakeFollow thedocumentationfor usage instructions.Key Features:arrows_counterclockwise: Out-of-the-Box Data SyncExisting vector stores are siloes that require complex and sometimes brittle
mechanisms for data synchronization. Retake provides the missing connectors that
allow seamless data synchronization without the need for extensive configuration
or third-party tools.:rocket: True Real-Time UpdatesRetake's connectors achieve sub-10ms end-to-end data latency, excluding variable
model inference times.:link: Extensible Python SDKYou can configure any source, sink, transformation, and embedding model as code.
Joining and filtering tables or adding metadata is easily done from Python
functions.:zap: Scalable and EfficientBuilt on top of Kafka, Retake is designed to handle large volumes of data and
high-throughput workloads.:globe_with_meridians: Deployable AnywhereYou can run Retake anywhere, from your laptop to a distributed cloud system.DevelopmentIf you are a developer who wants to contribute to Retake, follow these instructions to run Retake locally.Python SDKThe Python SDK enables users to define and configure vector data pipelines and
is responsible for all batch ETL jobs. To develop and run the Python SDK
locally:Install Poetrycurl-sSLhttps://install.python-poetry.org|python-Install dependenciespoetryinstallBuild the SDK locallypoetrybuildThis command will build and install theretakeSDK locally. You can nowimport retakefrom a Python environment.Real-Time ServerBuilt on top of Kafka, the real-time server sits between source(s) and
sink(s). It is responsible for all real-time data streams.Ensure that Docker and Docker Compose are installed.Ensure that Poetry and dependencies are installed (see Python SDK
instructions above).Start the development server, which is composed of the Kafka broker, Kafka Connect
and the schema registry. Docker Compose will expose a port for each of the
services (seedocker-compose.ymlfor details).dockercomposeupTo connect to the development server, refer to thedocumentation.ContributingFor more information on how to contribute, please see ourContributing Guide.LicensingRetake isElastic License 2.0 licensed.
Package: retake-pgsync
PostgreSQL to Elasticsearch/OpenSearch syncPGSyncis a middleware for syncing data fromPostgrestoElasticsearch/OpenSearchorOpenSearch.It allows you to keepPostgresas your source of truth data source and
expose structured denormalized documents inElasticsearch/OpenSearch.RequirementsPython3.7+Postgres9.6+Redis3.1.0Elasticsearch6.3.1+ orOpenSearch1.3.7+SQlAlchemy1.3.4+Postgres setupEnablelogical decodingin your
Postgres setting.You also need to set up two parameters in your Postgres config postgresql.confwal_level = logicalmax_replication_slots = 1InstallationYou can install PGSync fromPyPI:$ pip install pgsyncConfigCreate a schema for the application named e.gschema.jsonExample schemaExample spec.. code-block::[
    {
        "database": "[database name]",
        "index": "[Elasticsearch or OpenSearch index]",
        "nodes": {
            "table": "[table A]",
            "schema": "[table A schema]",
            "columns": [
                "column 1 from table A",
                "column 2 from table A",
                ... additional columns
            ],
            "children": [
                {
                    "table": "[table B with relationship to table A]",
                    "schema": "[table B schema]",
                    "columns": [
                      "column 1 from table B",
                      "column 2 from table B",
                      ... additional columns
                    ],
                    "relationship": {
                        "variant": "object",
                        "type": "one_to_many"
                    },
                    ...
                },
                {
                    ... additional children
                }
            ]
        }
    }
]Environment variablesSetup environment variables required for the applicationSCHEMA='/path/to/schema.json'

ELASTICSEARCH_HOST=localhost
ELASTICSEARCH_PORT=9200

PG_HOST=localhost
PG_USER=i-am-root # this must be a postgres superuser or replication user
PG_PORT=5432
PG_PASSWORD=*****

REDIS_HOST=redis
REDIS_PORT=6379
REDIS_DB=0
REDIS_AUTH=*****RunningBootstrap the database (one time only)$ bootstrap --config schema.jsonRun pgsync as a daemon$ pgsync --config schema.json --daemon
Package: retakesearch-py
OpenSearch Python ClientWelcome!User GuideAPI DocCompatibility with OpenSearchProject ResourcesCode of ConductLicenseCopyrightWelcome!opensearch-pyisa community-driven, open source forkof elasticsearch-py licensed under theApache v2.0 License.
For more information, seeopensearch.organd theAPI Doc.User GuideTo get started with the OpenSearch Python Client, seeUser Guide.Compatibility with OpenSearchSeeCompatibility.Project ResourcesProject WebsiteDownloadsDocumentationNeed help? TryForumsProject PrinciplesContributing to OpenSearchMaintainer ResponsibilitiesRelease ManagementAdmin ResponsibilitiesSecurityCode of ConductThis project has adopted theAmazon Open Source Code of Conduct.
For more information see theCode of Conduct FAQ, or contactopensource-codeofconduct@amazon.comwith any additional questions or comments.LicenseThis project is licensed under theApache v2.0 License.CopyrightCopyright OpenSearch Contributors. SeeNOTICEfor details.
Package: retarus-fax
Retarus Python Fax SDKThe official Python Fax SDK provided by Retarus to contact our messaging services.InstallationInstall from PyPi using pip, a package manager for Python. Minimum python version 3.8.pipinstallretarus-faxOr you can download thesource code for the Retarus python SDKand then build it with following command:gitclonehttps://github.com/retarus/retarus-python-faxcdretarus-python-fax
pipinstall.UsageThe Python SDK implements different services that are offered by Retarus. Each service provides a small variety of examples to get a better understanding of how to use their functionality. The examples can be found in the examples directory sorted by each service. Furthermore, you can check out our OpenAPI documents on the interfaces here:https://developers.retarus.comConfiguring the SDKFirst, you need to configure the SDK with your details.fromretarus.commons.configurationimportConfigurationConfiguration.set_auth(your_user_id,your_password)Configuration.set_region(your_region)# if its required for your service (eg. fax)Configuration.customer_number="my_customer_number"Each service implements a client, so simply call "retarus.your_service" and create a client that provides your functionality.fromretarus.fax.clientimportFaxClientsdk=FaxClient(True)Please note thatTruewill use the SDK in an asynchronous way whileFalsewill work in synchronous setup.RegionThe SDK also offers a simple way to select a region where your jobs should be processed. By default the SDK will use the Europe region.To configure your region:fromretarus.commons.configurationimportConfigurationfromretarus.commons.regionimportRegion# if its required for your service (eg. fax)Configuration.set_region(Region.Europe)Send a FaxTo send a fax, first setup the SDK like described above. For your credentials, we recommend to setup an .env file. It should also contain the customer number.Please note:Using the API will only work with valid credentials.After that, you can execute the examples 'send_job_async.py' (for asynchronous processing) or 'send_job_sync.py' (for synchronous processing) with Python. As a result, you should get a message that reports back the ID of the created job.In the fax examples folder, you will also find examples on how to retrieve the status of a fax job ID. The examples contain a little documentation on their own.
Package: retarus-sms
Retarus Python SDKThe official Python SDK provided by Retarus to contact our messaging services.InstallationInstall from PyPi using pip, a package manager for Python. Minimum python version 3.8.pipinstallretarus-smsOr you can download thesource code for the Retarus python SDKand then build it with following command:gitclonehttps://github.com/retarus/retarus-python-smscdretarus-python
pipinstall.UsageThe Python SDK implements different services that are offered by Retarus. Each service provides a small variety of examples to get a better understanding of how to use their functionality. The examples can be found in the examples directory sorted by each service. Furthermore, you can check out our OpenAPI documents on the interfaces here:https://developers.retarus.comConfiguring the SDKFirst, you need to configure the SDK with your details.fromretarus.commons.configurationimportConfigurationConfiguration.set_auth(your_user_id,your_password)Each service implements a client, so simply call "retarus.your_service" and create a client that provides your functionality.fromretarus.sms.clientimportSmsClientsdk=SmsClient(True)Please note thatTruewill use the SDK in an asynchronous way whileFalsewill work in a synchronous setup.Send a SMSTo send a sms, first setup the SDK like described above. For your credentials, we recommend setting up an .env file. It should also contain the customer number.Please note:Using the API will only work with valid credentials.After that, you can execute the examples 'send_jobs_async.py' (for asynchronous processing) or 'send_jobs_sync.py' (for synchronous processing) with Python. As a result, you should get a message that reports back the ID of the created job.In the sms examples folder, you will also find examples on how to retrieve the status of a sms job. The examples contain a little documentation on their own.
Package: retbrown-cdk-ecr-deployment
cdk-ecr-deploymentCDK construct to deploy docker image to Amazon ECRFeaturesCopy an ECR image to anotherCopy docker hub image to ECRCopy an archive tarball image from s3 to ECRExamplesRuntest/integ.ecr-deployment.tsNO_PREBUILT_LAMBDA=1npxcdkdeploy-a"npx ts-node -P tsconfig.dev.json --prefer-ts-exts test/integ.ecr-deployment.ts"Tech Details & ContributionThe core of this project relies onhttps://github.com/containers/imagewhich is used byhttps://github.com/containers/skopeo.
Please take a look at those projects before contribution.To support a new docker image source(like docker tarball in s3), you need to implementimage transport interface. You could take a look atdocker-archivetransport for a good start.To test thelambdafolder,make test.
Package: retdec-python
A Python library and tools providing easy access to theretdec.comdecompilation service through their publicREST API.You can either incorporate the library in your own scripts:fromretdec.decompilerimportDecompilerdecompiler=Decompiler(api_key='YOUR-API-KEY')decompilation=decompiler.start_decompilation(input_file='file.exe')decompilation.wait_until_finished()decompilation.save_hll_code()or you can use the provided script for stand-alone decompilations:$ decompiler -k YOUR-API-KEY file.exe
v23bmYb67R
----------

Waiting for resources (0%)...                    [OK]
Pre-Processing:
  Obtaining file information (5%)...             [OK]
  Unpacking (10%)...                             [OK]
Front-End:
  Initializing (20%)...                          [OK]
[..]
Done (100%)...

Downloading:
 - file.cEither way,file.cthen contains the decompiled C code:$ cat file.c
//
// This file was generated by the Retargetable Decompiler
// Website: https://retdec.com
// Copyright (c) 2016 Retargetable Decompiler <info@retdec.com>
//

#include <stdio.h>
[..]StatusThe library provides support for thedecompilation,fileinfo, andtestservices. For a more detailed list,
see thestatuspage in the documentation.RequirementsPython >= 3.3 (CPython or PyPy)requestsmodule for making HTTPS calls
to theretdec.com APIInstallationThe recommended way of installing is fromPython Package Index(PyPI) withpip:$pipinstallretdec-pythonThis will install the latest stable version, including all dependencies. You
can also install the latest development version directly from GitHub:$pipinstallgit+https://github.com/s3rvac/retdec-pythonDocumentationThe documentation is available onreadthedocs.io:latest (master)stable (0.5.2)Contact and SupportI will be very glad to get your feedback,pull requests,issues, or just a simpleThanks.
Feel free to contact me for any questions you might have!LicenseCopyright (c) 2015-2017 Petr Zemek (s3rvac@gmail.com) and contributors.Distributed under the MIT license. See theLICENSEfile for more
details.Access from Other LanguagesIf you want to access theretdec.comdecompilation
service from other languages, check out the following projects:retdec-rust- A library and tools
for accessing the service from Rust.retdec-cpp- A library and tools
for accessing the service from C++.retdec-sh- Scripts for accessing
the service from shell.
Package: rete
reteContainerized Web Browsing for Added ProtectionInstallpython3-mpipinstallreteNOTE: Install requires$USERto be in the docker group, or sudo permissions.Usage➜rete-husage:reteversion1.0.2[-h][-pPROFILE][-t][--config|--rm|--update][{brave,chromium,firefox,opera,tbb}]positionalarguments:{brave,chromium,firefox,opera,tbb}SupportedBrowsers

optionalarguments:-h,--helpshowthishelpmessageandexit-pPROFILE,--profilePROFILEProfileName-tTemporaryProfile--configOpenConfigforEditing--rmStopandRemoveALLBrowsers--updateCheckforUpatesConfig➜cat~/.config/rete/rete.yml
browser:name:firefox#proxy:#dns:#  ip:#  host:#  doh: falseprofile:default:personallist:[htb,lan,media,personal,shopping,work]#vpn:#  provider:#  user:#  pass:#  config:proxyCurrently the expected value is an HTTP/HTTPS/SOCKS proxy value in the form of: PROTO://IP:PORTProxy also supports BurpSuite by passing the valueburpsuite.dnsip: as the name implies, the ip of the dns server you want to use.host: the appropriate hostname and is the value used when DoH is enableddoh: enabled or disabled DNS over HTTPprofiledefault: the profile to load by default on browser startlist: the list of available profiles to use, feel free to add/remove any of themthe lan profile is a special restricted profile that only has access to RFC1918 IPsvpnSee retenet/tunle for more detailed documentation.provider: one of the supported providersuser: username for loginpass: password for loginconfig: this is used for custom openvpn configs. Itmustbe fullpathTypical args would be provider with user/pass, or simply just a configExample configsStandard Usagebrowser:
  name: firefox
  dns:
    ip: 1.1.1.1
    host: cloudflare-dns.com
    doh: true

profile:
  default: personal
  list: [htb, lan, media, personal, shopping, work]Burpsuitebrowser:
  name: firefox
  proxy: burpsuite

profile:
  default: personal
  list: [htb, lan, media, personal, shopping, work]OpenVPNbrowser:
  name: firefox

profile:
  default: personal
  list: [htb, lan, media, personal, shopping, work]

vpn:
  config: /home/user/ovpn/wh1tf3fox.ovpnTor Transparent Proxybrowser:
  name: firefox

profile:
  default: personal
  list: [htb, lan, media, personal, shopping, work]

vpn:
  provider: torPiabrowser:
  name: firefox

profile:
  default: personal
  list: [htb, lan, media, personal, shopping, work]

vpn:
  provider: pia
  user: abcdef
  pass: abcdefNOTE: if OpenVPN fails to load try adding:pull-filter ignore "ifconfig-ipv6 "
pull-filter ignore "route-ipv6 "to your ovpn config
Package: retenmod
retenmodThis is a python port of the R packageforetell. This projects customer retention rates, see“How to Project Customer Retention” Revisited: The Role of Duration Dependence(Fader et al., 2018)for the original formulation and description of the models.To install, just use pip:pip install retenmodOnly dependencies are scipy and numpy. For a simple example of use for the BdW model:import retenmod
surv = [100, 86.9, 74.3, 65.3, 59.3]
res = retenmod.bdw(surv,6)
print(res.params)
print(res.proj)