Saravanan666/pypi-org huggingface dataset:
Package: credentials
[![Build Status](https://travis-ci.org/OniOni/credentials.svg?branch=master)](https://travis-ci.org/OniOni/credentials)# Installing```shell$ pip install credentials```# Usage## DefaultUsing default setup, this will try and load credentials first from the processes environement variables and then from `~/.credentials.json````pythonfrom credentials import credentials# load credentials up frontcreds = credentials.require(['cred1', 'cred2'])function_that_needs_creds(creds.cred1)...# load credentials as neededmy_cred = credentials.load('cred_3')function_that_needs_creds(my_cred)...```## Setting up your own loader```python# Only load credentias from environementfrom credentials import Credentials, EnvBackendcreds = Credentials([EnvBackend()])...```# Implementing your own backendA backend is just an object with a `load` method. Method should take a `key` as an argument and return the associated credentials or `None` if it could not be loaded.Example:```pythonclass UniversalCredLoader(object):def load(self, key):return 42...from credentials import Credentialscreds = Credentials([UniversalCredLoader()])cred.load('cred1')>>> 42```
Package: credis
minimal redis client written in cython, 5X faster than redis-py.Tutorialexecute command>>>fromcredisimportConnection>>>conn=Connection(host='127.0.0.1',port=6379)>>>conn.execute('set','test',1)'OK'>>>conn.execute('get','test')'1'execute pipelined commands>>>commands=[('set','test%d'%i,i)foriinrange(3)]>>>conn.execute_pipeline(*commands)('OK','OK','OK')connection pool for gevent>>>fromcredis.geventpoolimportResourcePool>>>pool=ResourcePool(32,Connection,host='127.0.0.1',port=6379)>>>withpool.ctx()asconn:...conn.execute('get','test')'1'>>>pool.execute('get','test')'1'>>>commands=[('get','test%d'%i)foriinrange(3)]>>>pool.execute_pipeline(*commands)('1','2','3')
Package: credisdict
CRedisDictData structure to implement a dictionary whose keys and values can complex data (dict, list...) and are stored in a Redis database. The dictionary is initiated by copying each single (key,value) rather than usinghmset. It takes more time at initialisation but it is faster each time a key is accessed.PrerequisitesPython 3 with the following modules:redisAuthorsJoan HérissonLicenceCRedisDict is released under the MIT licence. See the LICENCE file for details.
Package: credit-agricole
Python Credit AgricoleDISCLAIMER : I AM NOT AFFILIATED TO THE CREDIT AGRICOLE IN ANY WAY, THIS IS AN UNOFFICIAL LIBRARYI'm looking for help to support other countries. I only have access to a french account.This library has been made in a way that it should be easy to add support for other countries.To do so, simply add API endpoints tocreditagricole/__init__.py.Installation$ pip install credit-agricoleUsageThere's a command line tool that will allow you to have a brief summary of your bank
account :$ creditagricole --help
usage: creditagricole [-h] [--country {france,italy,polska,ukraine,maroc,egypt}] [--region REGION]

Welcome to the Credit Agricole utility

options:
  -h, --help            show this help message and exit
  --country {france,italy,polska,ukraine,maroc,egypt}
                        the country you're in
  --region REGION       the region of the Credit Agricole you're affiliated toFor example you can runcreditagricole --country france --region aquitaine.But to be fair, this command line is not really useful.This repo only contains the API to communicate with the Credit Agricole website, if
you want to get valuable insights about your bank accounts, head over to theWork In Progress.The APIfromcreditagricoleimportCreditAgricoleFranceca=CreditAgricoleFrance("aquitaine")# pass the region of your affiliated Credit Agricoleuser_id=input("User ID: ")pin_code=getpass("Pin code: ")ca.login(user_id,pin_code)foraccountinca.accounts:print(account)foroperationinaccount.operations:print(operation)
Package: credit-card-checker
credit_card_checker_pyI published this package on PyPIhttps://pypi.org/project/credit-card-checker/To install the package, please add the package to your Pipfile.or runpip3 install credit_card_checkerValidating a NumberStrings of length 1 or less are not valid. Spaces are allowed in the input,
but they should be stripped before checking. All other non-digit characters
are disallowed.Example 1: valid credit card number4539 1488 0343 6467The first step of the Luhn algorithm is to double every second digit,
starting from the right. We will be doubling4_3_ 1_8_ 0_4_ 6_6_If doubling the number results in a number greater than 9 then subtract 9
from the product. The results of our doubling:8569 2478 0383 3437Then sum all of the digits:8+5+6+9+2+4+7+8+0+3+8+3+3+4+3+7 = 80If the sum is evenly divisible by 10, then the number is valid. This number is valid!Example 2: invalid credit card number8273 1232 7352 0569Double the second digits, starting from the right7253 2262 5312 0539Sum the digits7+2+5+3+2+2+6+2+5+3+1+2+0+5+3+9 = 5757 is not evenly divisible by 10, so this number is not valid.example usage>>> from credit_card_checker import CreditCardChecker
>>> CreditCardChecker('234 567 891 234').valid()
True
>>> CreditCardChecker('8273 1232 7352 0569').valid()
FalsetestTo run the tests, runpytest credit_card_checker_test.pyAlternatively, run the pytest module:python3 -m pytest credit_card_checker_test.py
Package: credit-card-info-generator
💳 Credit Card Info GeneratorThis is a simple, yet powerful Python 🐍 package for generating realistic dummy credit card data. It's a handy tool for developers who need to test payment systems, verify eCommerce applications, or any situation where real credit card data is not necessary or desirable.Check out ourCredit Card Generatorfor more information!🚀 InstallationInstall the package with pip using the following command:pipinstallcredit_card_info_generator⚙️ Usagefromcredit_card_info_generatorimportgenerate_credit_card# Generate a Visa cardcard=generate_credit_card('Visa')# Print the card detailsprint(card)🏦 Supported Card TypesThe package currently supports the generation of the following card types:American ExpressBankcardChina T-UnionChina UnionPayDiners Club enRouteDiners Club InternationalDiners Club United States & CanadaDiscover CardUkrCardRuPayInterPaymentInstaPaymentJCBMastercardLaserMaestro (UK)MaestroDankortMirBORICANPS PridnestrovieSoloSwitchTroyVisaVisa ElectronUATPVerveLankaPayUzCardHumoGPN👥 ContributingPull requests are welcome! 👍 For major changes, please open an issue first to discuss what you would like to change.📜 LicenseThis project is licensed under the MIT License.
Package: creditprice
#Introduction
This package is used to create a suitable plan of credit price for
different borrowers.As historical borrowers'
credit score and loan interests are given, you can train a credit price model
through this package, and this model will allow you to calculate a different, recommended
loan interest for any borrower only based on his or her credit score.#Example:import creditprice as cp
#生成数据
import numpy as np
import pandas as pd
np.random.seed(123)
score = 650 + 100 * np.random.randn(1000)
price = 0.2 + 0.1 * np.random.randn(1000)
flag = np.random.randint(2, size=1000)
flagy = np.random.binomial(1, 0.2, size=flag[flag == 1].shape[0])
data = pd.DataFrame(columns=['score', 'r', 'accept', 'flagy'])
data['score'] = score
data['r'] = price
data['accept'] = flag
data.loc[data.accept == 1, 'flagy'] = flagy
#生成模型
cl = cp.calc(ld=0.5, d = 1, rl = 0.05, rf = 0.04, score='score', interest='r', flag='accept', y = 'flagy')
#计算利率表
r_table = cl.calc_r_table(data = data)
#根据data计算单利率
r = cl.calc_r(p=0.2, data=data)
Package: credit-risk-modelling
.. -- mode: rst --|Travis|_ |PythonVersion|.. |Travis| image::https://api.travis-ci.com/ramonVDAKKER/credit-risk-modelling.svg?branch=main.. _Travis:https://travis-ci.com/ramonVDAKKER/credit-risk-modelling.. |PythonVersion| image::https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9-blue.. _PythonVersion:https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9-blueThecredit-risk-modellingpackage contains several functions that are useful in Credit Risk Modelling.
Package: credit-scoring-toolkit
creditscoringcreditscoring is a Python package built as a credit scoring toolkit.SupportsPython 3.6,3.7Latest ReleasePackage StatusLicenseInstallationRequirementsTo use creditscoring the following packages are required:pandas >= 0.20.1numpy >= 0.7.0matplotlib >= 1.1seaborn >= 0.8.0scipy >= 0.10.0scikit-learn >= 0.18Development and testing additionally require:pytestcoverageflake8twineInstall latest release version via pippipinstallcredit-scoring-toolkitInstall latest development versionpipinstallgit+https://github.com/Keris/creditscoring.gitorgitclonehttps://github.com/Keris/creditscoring.git
pythonsetup.pyinstall
Package: credkeep
credkeepcredkeep is a python package that helps ease the pain of storing sensitive credentials. Credentials that are securely
encrypted using AWS’s Key Management Service (KMS) can be stored in version control systems where they cannot be
decrypted without access to a users encryption key on KMS.Installationpip install credkeepUsagecredkeeprequires you to configure your own KMS master key. This key is used to encrypt/decrypt your data and is
securely stored by AWS. Your KMS master keys can be viewed athttps://console.aws.amazon.com/iam/home#encryptionKeys.
For information about creating new master keys, seehttp://docs.aws.amazon.com/kms/latest/developerguide/create-keys.html.Plaintext api secrets should not be stored in plain text. For exampledeveloper_secrets.json{"SECRET_API_KEY":"thisismysecretkey","ANOTHER_API_KEY":"anotherkey"}By callingcredkeep.encrypt_file{"SECRET_API_KEY":"CiAr4gKwrApZNibuqh1YKjlIGMj4A4GSHArF+0lCqBnqOxKfAQEBAgB4K+ICsKwKWTYm7qodWCo5SBjI+AOBkhwKxftJQqgZ6jsAAAB2MHQGCSqGSIb3DQEHBqBnMGUCAQAwYAYJKoZIhvcNAQcBMB4GCWCGSAFlAwQBLjARBAzGyPmdgqEbxzvnjKICARCAMzOd+DIaI/rUbc8dYQTxGS8aQQNjgXPt6Or0rxo7fFn0rA5/Kf6zpnui0q9XXtUatL4D3Q==","ANOTHER_API_KEY":"CiAr4gKwrApZNibuqh1YKjlIGMj4A4GSHArF+0lCqBnqOxKXAQEBAgB4K+ICsKwKWTYm7qodWCo5SBjI+AOBkhwKxftJQqgZ6jsAAABuMGwGCSqGSIb3DQEHBqBfMF0CAQAwWAYJKoZIhvcNAQcBMB4GCWCGSAFlAwQBLjARBAxgB3p/zbVarLd/5a4CARCAK4w48/dCK7EvwTDELb11bpBe8TpaIhcCalfOqACQzoLoqgciAY8DuczOvRs="}This encrypted json file is safe to distribute via version control as it requires access to the master key on KMS. When
the secrets in the file are required the file can be decrypted usingcredkeep.decrypt_file. This function can optionally
set local environment variables with the decrypted secrets. These environment variables will not persist between shells
or reboots.
Package: credmap
Installation$ pip install credmap && credmapFeaturescredmap, ** The Credential Mapper **How to install ?$ pkg install python -y
$ pip install credmap
$ onexDisclaimerWe are not responsible for your loss.
this tool is made for Education/Learning Purpose.
Dont harm anyone using this tool.Usage$ credmap -h

Author : lightos
PIP module : Parixit Sutariya
Github : github.com/Bhai4You
Blogspot : https://bhai4you.blogspot.comGithub
Package: credmarkutils
Credmark UtilsThe purpose of this project is to create pythonic wrappers and tools for blockchain interaction.InstallationRun the following to install:pipinstallcredmarkutilsUsagefromhelloworldimportsay_hello# Generate "Hello, World!"say_hello()# Generate "Hello, Everybody!"say_hello("Everybody")Developing Credmark UtilsTo install credmarkutils, along with the tools you need to develop and run tests, run the following in your virtualenv:$pipinstall-e.[dev]
Package: credmgr
Client for interacting with Credential Manager APIAPI version: 1.0Package version: 1.6.0RequirementsPython 3.7+Installation & UsagepipinstallcredmgrThen import the package:fromcredmgrimportCredentialManagerGetting Startedcredential_manager=CredentialManager(api_token="api_token")# List all Reddit appsreddit_apps=credential_manager.reddit_apps()forreddit_appinreddit_apps:print(reddit_app.name)# Create a Reddit appredditApp=credential_manager.reddit_app.create(name="reddit_app_name",client_id="client_id",client_secret="client_secret",user_agent="user_agent",redirect_uri="redirect_uri",)# Get the app by idreddit_app=credential_manager.reddit_app(1)# Edit the Reddit appreddit_app.edit(client_id="client_id_2")# Delete the appreddit_app.delete()
Package: credoai-connect
Connect by Credo AI - Utility Module for Connecting to AI Governance PlatformConnect is a utility module that integrates ML assessments with the Credo AI Governance Platform.
Connect definesevidence_containerswhich function as adapters between diverse AI assessment
frameworks (or custom analyses) and Credo AI-compatibleEvidenceobjects.DependenciesCredo AI Connect supports Python 3.8+Sphinx (optional for local docs site)InstallationThe latest stable release (and required dependencies) can be installed from PyPI.pip install credoai-connectDocumentationDocumentation is hosted byreadthedocs.LoggingLogging defaults to stdout. In order to collect all logging information into a specific file,
set the desired location to the environment variableCREDO_CONNECT_LOG_PATH.WarningMake sure the destination has write permissions, otherwise you will get aPermissionErrorat the moment you
attempt library import.
Package: credoai-lens
Lens by Credo AI - Responsible AI Assessment FrameworkLens is a comprehensive assessment framework for AI systems.
Lens standardizes model and data assessment, and acts as a central gateway to assessments
created in the open source community. In short, Lens connects arbitrary AI models and datasets
with Responsible AI tools throughout the ecosystem.Lens can be run in a notebook, a CI/CD pipeline, or anywhere else you do your ML analytics.
It is extensible, and easily customized to your organizations assessments if they are not
supported by default.Though it can be used alone, Lens shows its full value when connected to your organization'sCredo AI App. Credo AI is an end-to-end AI Governance
App that supports multi-stakeholder alignment, AI assessment (via Lens) and AI risk assessment.DependenciesCredo AI Lens supports Python 3.8+Sphinx (optional for local docs site)InstallationThe latest stable release (and required dependencies) can be installed from PyPI.pip install credoai-lensAdditional installation instructions can be found in oursetup documentationGetting StartedTo get started, see thequickstart demo.If you are using the Credo AI Governance App, also check out thegovernance integration demo.DocumentationDocumentation is hosted byreadthedocs.For dev documentation, seelatest.AI GovernanceAs an assessment framework, Lens is an important component of your overallAI Governancestrategy.
But it's not the only component! Credo AI, the developer of Lens, also develops
tools to satisfy your general AI Governance needs, which integrate easily with Lens.To connect toCredo AI's Governance App, see the Governance
tutorial onreadthedocs.For Lens developersRunning testsRunning a testscripts/test.shRunning tests with pytest-watchptw--runner"pytest -s"
Package: credPass
Python library to load credentials or other sensitive data for .json format file.Credentials must be stored under ``~/.credentials.json` in key:value dictionary format.Example::{"device1":{ "username": "federico.olivieri", "password": "p4ssw0rd" },"device2":{ "username": "olivierif", "password": "mys3cr3t" }}If you want change default location of .credentials.json file you need to modify file path under `__init__` methondHow to run it::db = credPass()db.load('device1','password') # 'p4ssw0rd'
Package: creds
CredsCreds is a library that simplifies the management of user accounts and
their credentials on Linux, FreeBSD and OpenBSD.Instead of issuing commands to create, update and delete users and their
ssh keys, supply Creds with details of the users you want and it will
take care of the implementation.The supported inputs are currently YAML, JSON or python dictionaries.User vs System accountsLinux has a default range of user ids to provide to system and user
accounts, found in /etc/login.defs.Creds will attempt to read this file to determine which accounts are
in scope for management and, if unavailable, will default to:UID_MIN = 1000 # User accounts will have an id of 1000 or moreUID_MAX = 60000 # User accounts will not have an id higher than
60000Example UsageRead a list of users from users.yml and create them (if missing) or
update (if existing):from creds.users import Users
from creds.plan import (create_plan, execute_plan)

existing_users = Users.from_passwd()  # Get a list of existing users and their keys
proposed_users = Users.from_yaml('users.yml')  # Read the proposed list of users and their keys

# Generate a list of operations to transition from current to existing
plan = create_plan(existing_users=existing_users, proposed_users=proposed_users)
execute_plan(plan=plan)  # Execute the planDeleting usersIf your input defines all of the user accounts you want to exist, you
can choose to purge any that are undefined by adding a parameter to
create_plan:plan = create_plan(existing_users=existing_users, proposed_users=proposed_users,
                   purge_undefined=True)Protecting usersIf there are users you want to protect from change, e.g. you want to
make sure that certain users are not deleted or updated under any
circumstances, then you can supply a list of usernames for Creds to
ignore:plan = create_plan(existing_users=existing_users, proposed_users=proposed_users,
                   purge_undefined=True, protected_users=['rod', 'jane', 'freddy'])
Package: credsafe
Credentials SafeStore application credentials in keyring with RSA and AES-256.Hierarchycredsafe
|---- Agent()
|   |---- set()
|   |---- get()
|   |---- rm()
|   '---- destroy()
|---- AgentV2()
|   |---- set()
|   |---- get()
|   |---- rm()
|   '---- destroy()
'---- AgentV1()
    |---- set()
    |---- get()
    |---- rm()
    '---- destroy()ExamplepythonSeetest.
Package: credsleuth
Credential SleuthA rule driven library for detecting secrets and credentials within files and strings.Simple UsageFinding secrets in a string:importcredsleuthdata="""Hello, worldPassword=123aws_access_key_id = AKIAIOSFODNN7EXAMPLEGoodbye"""print(credsleuth.check_string(data))Finding secrets in a file:importcredsleuthprint(credsleuth.check_file("filename.txt"))Command line usagecredsleuthfilename.txtAdvanced UsageCustomizing configurationimportcredsleuthconfig=credsleuth.ConfigEngine()config.verbose=Trueconfig.rules_file='custom_rules.json'credsleuth.check_file('filename.txt',config)Installationpip install --user credsleuthWriting RulesSeerules.jsonfor an example in extending rules definitions.TodoAdd some comments to codebaseAdd pretty output options for command line execution.Write a proper read me.Build model to detect credentials based upon entropySearch multiple files
Package: credstash-envvar-helper
Credstash Envvar HelperRetrieves secrets from AWS via credstash, and returns a dictionary.Documentation:https://credstash-envvar-helper.readthedocs.io.FeaturesThis is a magnificent package designed to save you time and bother.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.3 (2020-02-03)Add credstash parsing code to main moduleAdd support for python270.1.2 (2020-01-30)Correct author email address.0.1.1 (2020-01-30)Improve README and tidy up some inconsistencies.0.1.0 (2020-01-30)First release on PyPI.
Package: credstuffer
credstufferFeaturesofcredstuffer:Stuffing social media accounts like comunio, instagram, facebookProvide easily credentials from directories, files or from a database connectionGet Mail or Telegram notifications in success caseLogin requests are only made over proxiesInstallationinstallcredstufferwith pippip3 install credstufferor from sourcesudo python3 setup.py installUsage and ExamplesPrint the available arguments for credstuffercredstuffer --helpUse it with a credential file of your choicecredstuffer instagram --usernames "John, Jane" file --path /home/john/credentials.txtProvide a directory including multiple credential filescredstuffer instagram --usernames "John, Jane" file --dir /home/john/credential_collection/Or fetch credential data from a database connectioncredstuffer instagram --usernames "John, Jane" database --host 192.168.1.2 --port 5432 --user john --password test1234 --dbname postgres --schemas a --tables abcPass Mail Server params to get a notification in success casecredstuffer instagram --usernames "John, Jane" --Nsmtp smtp.web.de --Nport 587 --Nsender sender@web.de --Nreceiver receiver@web.de --Npassword password file --dir /home/john/credential_collection/Logslogs can be found in/var/log/credstufferTroubleshootingadd your current user to groupsyslog, this allows the application/scripts to create a folder in/var/log. Replace<user>with your current usersudo adduser <user> syslogto apply this change, log out and log in again and check with the terminal commandgroupsChangelogAll changes and versioning information can be found in theCHANGELOGLicenseCopyright (c) 2019 Bierschneider Christian. SeeLICENSEfor details
Package: creek
creekSimple streams facade.To install:pip install creekDocumentation hereTheCreekbase class offsers a layer-able wrap of the stream interface.There are three layering methods -- pre_iter, data_to_obj, and post_filt
-- whose use is demonstrated in the iteration code below:for line in self.pre_iter(self.stream):  # pre_iter: prepare and/or filter the stream
    obj = self.data_to_obj(line)  # data_to_obj: Transforms the data that stream yields
    if self.post_filt(obj):  # post_filt: Filters the stream further (but based on object now)
        yield objExamples:>>> from io import StringIO
>>> src = StringIO(
... '''a, b, c
... 1,2, 3
... 4, 5,6
... '''
... )
>>>
>>> from creek import Creek
>>>
>>> class MyCreek(Creek):
...     def data_to_obj(self, line):
...         return [x.strip() for x in line.strip().split(',')]
...
>>> stream = MyCreek(src)
>>>
>>> list(stream)
[['a', 'b', 'c'], ['1', '2', '3'], ['4', '5', '6']]
>>> stream.seek(0)  # oh!... but we consumed the stream already, so let's go back to the beginning
0
>>> list(stream)
[['a', 'b', 'c'], ['1', '2', '3'], ['4', '5', '6']]
>>> stream.seek(0)  # reverse again
0
>>> next(stream)
['a', 'b', 'c']
>>> next(stream)
['1', '2', '3']Let's add a filter! There's two kinds you can use.
One that is applied to the line before the data is transformed by data_to_obj,
and the other that is applied after (to the obj).>>> from creek import Creek
>>> from io import StringIO
>>>
>>> src = StringIO(
...     '''a, b, c
... 1,2, 3
... 4, 5,6
... ''')
>>> class MyFilteredCreek(MyCreek):
...     def post_filt(self, obj):
...         return str.isnumeric(obj[0])
>>>
>>> s = MyFilteredCreek(src)
>>>
>>> list(s)
[['1', '2', '3'], ['4', '5', '6']]
>>> s.seek(0)
0
>>> list(s)
[['1', '2', '3'], ['4', '5', '6']]
>>> s.seek(0)
0
>>> next(s)
['1', '2', '3']Recipes:pre_iter: involving itertools.islice to skip header linespre_iter: involving enumerate to get line indices in stream iteratorpre_iter = functools.partial(map, line_pre_proc_func) to preprocess all lines with line_pre_proc_funcpre_iter: include filter before obj
Package: creeper-adventure
creeper-adventureCreeper adventure is a top down 2d adventure game that I am building with my son using pygame.Table of ContentsInstallationLicenseInstallationpip install creeper-adventureRunning#runthegamecreeper-adventure#runindebugmodecreeper-adventure --debug#seealloptionsavailablecreeper-adventure --helprunning with pipxcreeper-adventurecan also run using pipx if you have pipx installed.pipx run creeper-adventureDownload an exepre-built binaries are available from the websitecreeper-adventure.Licensecreeper-adventureis distributed under the terms of theMITlicense.