Saravanan666/pypi-org huggingface dataset:
Package: aggregate6
[![Build Status](https://travis-ci.org/job/aggregate6.svg?branch=master)](https://travis-ci.org/job/aggregate6)[![Requirements Status](https://requires.io/github/job/aggregate6/requirements.svg?branch=master)](https://requires.io/github/job/aggregate6/requirements/?branch=master)[![Coverage Status](https://coveralls.io/repos/github/job/aggregate6/badge.svg?branch=master)](https://coveralls.io/github/job/aggregate6?branch=master)aggregate6==========aggregate6 will compress an unsorted list of IP prefixes (both IPv4 and IPv6).Description-----------Takes a list of IPv6 prefixes in conventional format on stdin, and performs twooptimisations to attempt to reduce the length of the prefix list. The firstoptimisation is to remove any supplied prefixes which are superfluous becausethey are already included in another supplied prefix. For example,`2001:67c:208c:10::/64` would be removed if `2001:67c:208c::/48` wasalso supplied.The second optimisation identifies adjacent prefixes that can be combined undera single, shorter-length prefix. For example, `2001:67c:208c::/48` and`2001:67c:208d::/48` can be combined into the single prefix`2001:67c:208c::/47`.The above optimalisation steps are often useful in context of compressing firewallrules or BGP prefix-list filters.The following command line options are available:```-4          Only output IPv4 prefixes-6          Only output IPv6 prefixes-h, --help  show help message and exit-m N        Sets the maximum prefix length for entries read, longer prefixes will be discarded prior to processing-t          truncate IP/mask to network/mask-v          Display verbose information about the optimisations-V          Display aggregate6 version```Installation------------OpenBSD 6.3:`$ doas pkg_add aggregate6`Other platforms:`$ pip3 install aggregate6`CLI Usage---------Either provide the list of IPv4 and IPv6 prefixes on STDIN, or give filenamescontaining lists of IPv4 and IPv6 prefixes as arguments.```$ # via STDIN$ cat file_with_list_of_prefixes | aggregate6... output ...$ # with a filename as argument$ aggregate6 file_with_list_of_prefixes [ ... optional_other_prefix_lists ]... output ...$ # Whitespace separated works too$ echo 2001:67c:208c::/48 2000::/3 | aggregate62000::/3$ # You can combine IPv4 and IPv6$ echo 10.0.0.0/16 10.0.0.0/24 2000::/3 | aggregate610.0.0.0/162000::/3```Library Usage-------------Aggregate6 can be used in your own pyp/python2/python3 project as python module.Currently there is just one simple public function: `aggregate()` which takes alist as parameter.```>>> import from aggregate6 import aggregate>>> aggregate(["10.0.0.0/8", "10.0.0.0/24"])['10.0.0.0/8']>>>```Bugs----Please report bugs at https://github.com/job/aggregate6/issuesAuthor------Job Snijders <job@instituut.net>
Package: aggregate-prefixes
aggregate-prefixesFast IPv4 and IPv6 prefix aggregator written in Python.Gets a list of unsorted IPv4 or IPv6 prefixes from argument or SDTIN and returns a sorted list of aggregates to STDOUT
Errors go to STDERR.Installgit clone https://github.com/lamehost/aggregate-prefixes.git
cd aggregate_prefixes
poetry build
pip install dist/aggregate_prefixes-0.7.0-py3-none-any.whlCLI Syntax for executableusage: aggregate-prefixes [-h] [--max-length LENGTH] [--strip-host-mask] [--truncate MASK] [--verbose] [--version] [prefixes]

Aggregates IPv4 or IPv6 prefixes from file or STDIN

positional arguments:
  prefixes              Text file of unsorted list of IPv4 or IPv6 prefixes. Use '-' for STDIN.

options:
  -h, --help            show this help message and exit
  --max-length LENGTH, -m LENGTH
                        Discard longer prefixes prior to processing
  --strip-host-mask, -s
                        Do not print netmask if prefix is a host route (/32 IPv4, /128 IPv6)
  --truncate MASK, -t MASK
                        Truncate IP/mask to network/mask
  --verbose, -v         Display verbose information about the optimisations
  --version, -V         show program's version number and exitUsage as module$ python
Python 3.9.1+ (default, Feb  5 2021, 13:46:56)
[GCC 10.2.1 20210110] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>
>>> from aggregate_prefixes import aggregate_prefixes
>>> list(aggregate_prefixes(['192.0.2.0/32', '192.0.2.1/32', '192.0.2.2/32']))
['192.0.2.0/31', '192.0.2.2/32']
>>>Python version compatibilityTested with:Python 3.9Python 3.10Python 3.11
Package: aggregationslib
MeansMeans, Aggregation functions...Example 1:# example datadata = [0.2, 0.6, 0.7]# configure function parametersfunc1 = A_amn(p=0.5)# use aggregation funcitonprint(func1(data))# Combine two aggregations - arithmetic mean and minimumfunc2 = Combine2Aggregations(A_ar(), min)# use combination of aggregation funcitonprint(func2(data))Example2:To get information about aggregation function you can use__str__()or 'repr()' methods.func1 = A_amn(p=0.5)print(func1)>>>A_amn(0.5)func2 = Combine2Aggregations(A_ar(), A_md())print(func2)>>>A_armdfunc3 = Combine2Aggregations(A_ar(), A_pw(r=3))print(func3.__repr__()) # function parameters are printed in order: func1, func2>>>A_arpw(r=3)exponential(y, r=1)is given by equation$$
A_6^{(r)}(x_1,...,x_n)= \frac{1}{r}\ln
\Big(\frac{1}{n} \sum \limits_{k=1}^{n} e^{rx_k}\Big), where
r \in \mathbb{R}, r \neq 0
$$A_ar - Arithmetic meanA_qd - Quadratic meanA_gm - Geometric meanA_hm - Harmonic meanA_pw - Power meanA_ex, A_ex2, A_ex3 - Exponential meanA_lm - Lehmer meanA_amn - Arithmetic minimum meanA_amx - Arithmetic maximum meanA_md - Median - ordered weighted aggregationA_ol - Olimpic aggregationA_oln - Olimpic aggregationWe can specify how many greatest and smallest records removeCombine2Aggregations - Combine aggregation functionsAmn, Amx, Aar , Aex , Amd,
Aow1, Aow1
Package: agha
Yes, Agha is another GitHub API library for Python 2.x development.Support basic CRUD operations throw the
official REST API v3:http://developer.github.com/v3/Example:fromaghaimportGitHubApiapi=GitHubApi("myuser","mypass")# Create a repositoryapi.create_repo({'name':'mytestrepo1','description':'Github Test 1','auto_init':True}# Edit the repo descriptionapi.edit_myrepo("mytestrepo1",{'description':'Another description for my repo'})# List my repositoriesforrepoinapi.get_myrepos():print"NAME:%(name)s, DESCRIPTION:%(description)s, URL:%(html_url)s"%repo# Delete the repoapi.delete_myrepo("mytestrepo1")# Show my profile informationprint"USER:%(login)s, NAME:%(name)s, EMAIL:%(email)s"%api.get_myprofile()RequirementsPython 2.6+Requests libraryAboutThis source code is available inhttps://github.com/mrsarm/python-aghaDeveloped by Mariano Ruiz <mrsarm@gmail.com>License: LGPL-3 (C) 2014
Package: ag-helper
...SafeExecutorThe SafeExecutor decorator allows you to quickly execute a function or method within a try/except block.
Parameterdefaultallows you to override the return value in case of an error.
Parameterloggertakes aloggerobject and executes thelogger.error(error)method if an error occursExamples:from aghelper.utils import SafeExecutor
from logging import getLogger, StreamHandler, Formatter

logger = getLogger(__name__)
formatter = Formatter("%(asctime)s - %(levelname)s -  %(message)s")

sh = StreamHandler()
sh.setFormatter(formatter)
logger.addHandler(sh)

@SafeExecutor
def foo():
    return 1/0

class FooClass:

    @SafeExecutor
    def foo_method(self):
        return 1/0

    @classmethod
    @SafeExecutor
    def foo_classmethod(cls):
        return 1/0

    @staticmethod
    @SafeExecutor
    def foo_staticmethod():
        return 1/0

    @SafeExecutor(default=0)
    def change_return(self):
        return 1/0

    @SafeExecutor(logger=logger)
    def write_to_log(self):
        return 1/0

print(f"1. Func result: {foo()}")
print(f"2. Method foo result: {FooClass().foo_method()}")
print(f"3. Class method foo result: {FooClass.foo_classmethod()}")
print(f"5. Static method foo result: {FooClass.foo_staticmethod()}")
print(f"6. Set default return: {FooClass().change_return()}")
print(f"7. Write error to log: {FooClass().write_to_log()}")

>>> 1. Func result: None
>>> 2. Method foo result: None
>>> 3. Class method foo result: None
>>> 5. Static method foo result: None
>>> 6. Set default return: 0
>>> 7. Write error to log: None
>>> 2023-01-13 17:06:55,437 - ERROR -  Execute error: division by zero
Package: agi
AGIApparently AGI will be the biggest breakthrough in like forever.Suppose it is true that AGI can be used to solve everything. Then GDP will tend towards infinity if AGI is achieved. AGI will probably be written in Python because network effects and lock-in (sorry Julia and Swift). Therefore the PyPi namespace for AGI will be infinitely valuable.If you wish to acquire this namespace, please send me infinite $$$ (bitcoin not accepted), and we'll see what we can do!Cheers.
Package: agify
Asynchronous Python wrapper for (,,)A simple API for predicting the age, gender, and country of a person by their name.The API is free for up to 1000 names/day. No sign up or API key needed. So go ahead and try it out.Instalationpip install agifyUsage example:async version:fromagifyimportAsyncNameAPIg=AsyncNameAPI(["Igor","Alex"],mode="*")print(asyncio.run(g.get_names_info()))# ->{'Alex':{'age':45,'count':1114390,'country':[{'country_id':'CZ','probability':0.082},{'country_id':'UA','probability':0.045},{'country_id':'RO','probability':0.033},{'country_id':'RU','probability':0.031},{'country_id':'IL','probability':0.028}],'gender':'male','probability':0.96},'Igor':{'age':49,'count':168019,'country':[{'country_id':'UA','probability':0.169},{'country_id':'RS','probability':0.113},{'country_id':'RU','probability':0.093},{'country_id':'HR','probability':0.084},{'country_id':'SK','probability':0.062}],'gender':'male','probability':1.0}}a=AsyncNameAPI(["Ivan"],"gender")print(asyncio.run(a.get_names_info()))# ->{'Ivan':{'count':425630,'gender':'male','probability':1.0}}a=AsyncNameAPI()print(asyncio.run(a.get_limit_remaining()))# ->987usual version:fromagifyimportNameAPIg=NameAPI(["Igor","Alex"],mode="*")print(g.get_names_info())# ->{'Alex':{'age':45,'count':1114390,'country':[{'country_id':'CZ','probability':0.082},{'country_id':'UA','probability':0.045},{'country_id':'RO','probability':0.033},{'country_id':'RU','probability':0.031},{'country_id':'IL','probability':0.028}],'gender':'male','probability':0.96},'Igor':{'age':49,'count':168019,'country':[{'country_id':'UA','probability':0.169},{'country_id':'RS','probability':0.113},{'country_id':'RU','probability':0.093},{'country_id':'HR','probability':0.084},{'country_id':'SK','probability':0.062}],'gender':'male','probability':1.0}}a=NameAPI(["Ivan"],"gender")print(a.get_names_info())# ->{'Ivan':{'count':425630,'gender':'male','probability':1.0}}a=NameAPI()print(a.get_limit_remaining())# ->987
Package: agile-analytics
# jira-agile-extractor[![Build Status](https://travis-ci.org/cmheisel/agile-analytics.svg?branch=master)](https://travis-ci.org/cmheisel/agile-analytics)[![Coverage Status](https://coveralls.io/repos/github/cmheisel/agile-analytics/badge.svg?branch=master)](https://coveralls.io/github/cmheisel/agile-analytics?branch=master)[![Stories in Ready](https://badge.waffle.io/cmheisel/agile-analytics.svg?label=ready&title=Ready)](http://waffle.io/cmheisel/agile-analytics)Extract data about items from JIRA, output raw data and interesting reports## ArchitectureThe agile extractor is composed of several different components. Fetchers gather data, which is fed to one or more analyzer/reporters/writer combos.### Components#### FetchersFetchers are responsible for getting raw data about tickets from agile data sources (JIRA, Trello, etc.)They depend on fetcher specific configuration including things like API end points, credentials and search criteria.They produce a set of AgileTicket objects with a known interface.#### AnalyzersAnalyzers take in a set of AgileTicket objects and an analysis configuration and return a set of AnalyzedTicket objects that contain the original AgileTicket as well as additional data calculated in light of the analysis context.For example, a CycleTime analyzer would look for a start_state and an end_state in the configuration, and calculate the days between those and store it as cycle_time on the AnalyzedTicket object.#### ReportersReporters take in a set of AnalyzedTicket objects and a report configuration and return a Report object. It has two standard attributes:* Table - A representation of the report as a 2 dimensional table, provides column headers, row labels, and values for each row/column combo* Summary - A key/value store of report specific data#### WritersWriters take in a Report and a WriterConfig can write it out a particular source. Examples:* CSV to standout* CSV to a file* Google spreadsheet* Plotly### Diagram```+----------->  Reporter: Distribution|                title=Cycle Time Distribution|                start_date=1/1/2015|                end_date=3/31/2015|                field=cycle_time|+----------->  Reporter: Throughput|                title=Weekly Throughput|                start_date=1/1/2015|                end_date=3/31/2015|                period=weekly|||+----------------->  Analyzer: Cycle Time  +|                      start_state=Backlog|                      end_state=Deployed|                      issue_types=Story|Fetcher          |                                          +-----------> Reporter: Throughputsource=JIRA    +---------------->  Analyzer: Defect       +               title=Escaped Defectsfilter=1111    |                     defect_types=Bug,Incident            start_date=1/1/2015auth=user,pass |                                                          end_date=3/31/2015||+---------------->  Analyzer: Cycle Time   +-----------> Reporter: Throughputstart_state=Analysis                 title=Weekly Analysis Throughputend_state=Dev                        start_date=1/1/2015end_date=3/31/2015period=weekly```
Package: agilecrm
Python library forAgile CRMbased on therest-api documentation.StatusWe use this in production forScreenly, and it works fine. Still a
bit rough around the corners, but it does indeed work.InstallationClone the repo as a sub-module inside your project.Install the Python requirements.$ pip install agilecrmConfigurationIn order to use the module, you need to set the following environment
variables:AGILECRM_APIKEYAGILECRM_EMAILAGILECRM_DOMAINUsageFirst, you need to import the module. This may vary depending on your
paths etc, but something like:import agilecrmCreating a userSimply create a new user. Despite what is claimed in the documentation,
all variables appear to be optional.agilecrm.create_contact(
    first_name='John',
    last_name='Doe',
    email='john@doe.com',
    tags=['signed_up'],
    company='Foobar Inc')You can also use custom fields (must be created in Agile CRM first):agilecrm.create_contact(
    first_name='John',
    custom = {
      'SomeField': 'Foobar'
    }Update a contactUpdate a user object.agilecrm.update_contact(
    first_name='Steve',
    last_name='Smith',
    email='john@doe.com',
    tags=['name_updated'],
    company='Foobar2 Inc')Get a user (by email)This will get the user by email and return the user object as JSON.agilecrm.get_contact_by_email('john@doe.com')Get a user (by UUID)This will get the user by UUID and return the user object as JSON.agilecrm.get_contact_by_uuid(1234)Add a tagThis will add the tag ‘awesome_user’ to the user ‘john@doe.com’. Both
variables are required.agilecrm.add_tag('john@doe.com', 'awesome_user')
Package: agilecrm-python
agilecrm-pythonagilecrm is an API wrapper for Agile CRM written in PythonInstallingpip install agilecrm-pythonUsagefrom agilecrm.client import Client

client = Client('API_KEY', 'EMAIL', 'DOMAIN')Create contactcontact_data = {
    "star_value": "4",
    "lead_score": "92",
    "tags": [
        "Lead",
        "Likely Buyer"
    ],
    "properties": [
        {
            "type": "SYSTEM",
            "name": "first_name",
            "value": "Los "
        },
        {
            "type": "SYSTEM",
            "name": "last_name",
            "value": "Bruikheilmer"
        },
        {
            "type": "SYSTEM",
            "name": "company",
            "value": "steady.inc"
        },
        {
            "type": "SYSTEM",
            "name": "title",
            "value": "VP Sales"
        },
        {
            "type": "SYSTEM",
            "name": "email",
            "subtype": "work",
            "value": "akrambakram@yabba.com"
        },
        {
            "type": "SYSTEM",
            "name": "address",
            "value": "{\"address\":\"225 George Street\",\"city\":\"NSW\",\"state\":\"Sydney\",\"zip\":\"2000\",\"country\":\"Australia\"}"
        },
        {
            "type": "CUSTOM",
            "name": "My Custom Field",
            "value": "Custom value"
        }
    ]
}

response = client.create_contact(contact_data)Get contact by idresponse = client.get_contact_by_id('5685265389584384')Get contact by emailresponse = client.get_contact_by_email('akrambakram@yabba.com')Update contactupdate_contact_data = {
    "id": "5685265389584384",
    "properties": [
        {
            "type": "SYSTEM",
            "name": "last_name",
            "value": "Chan"
        },
        {
            "type": "CUSTOM",
            "name": "My Custom Field",
            "value": "Custom value chane"
        }
    ]
}
response = client.update_contact(update_contact_data)Search contactsimport json

myjson = {
    "rules": [{"LHS": "created_time", "CONDITION": "BETWEEN", "RHS": 1510152185.779954, "RHS_NEW": 1510238585.779877}],
    "contact_type": "PERSON"}
    
response = client.search(
    {'page_size': 25,
    'global_sort_key': '-created_time',
    'filterJson': json.dumps(myjson)
})RequirementsrequestsTestspython tests/test_client.py
Package: agileetc
agileetcExample python 3.9+ project where we can develop best practices and provide teams with a useful template with the following features:Poetry packaged python project with example CLI entry point.Linux and Windows compatible project.Example read/write YML files.Example Unit Tests.Example flake8 linter configuration.Example line operation via click API allowing project to be run from command line of from CICD pipelines.Example use of Fabric API to execute external commands.Example use of Texttable for pretty table output.Example GoCD pipeline.Example GitHub actions.Python package publishing to PiPy.Docker image publishing to docker hub.Example usage of python package.Example usage of docker image.PrerequisitesThis project uses poetry is a tool for dependency management and packaging in Python. It allows you to declare the
libraries your project depends on, it will manage (install/update) them for you.Use the installer rather than pipinstalling-with-the-official-installer.poetryselfaddpoetry-bumpversionpoetry-V
Poetry(version1.2.0)Getting StartedpoetryupdatepoetryinstallRunpoetryrunagileetcLintpoetryrunflake8TestpoetryrunpytestPublishBy default we are usingPYPI packages.Create yourself an access token for PYPI and then follow the instructions.exportPYPI_USERNAME=__token__exportPYPI_PASSWORD=<YourAPIToken>
poetrypublish--build--username$PYPI_USERNAME--password$PYPI_PASSWORDVersioningWe useSemVerfor versioning. For the versions available, see thetags on this repository.ReleasingWe are usingpoetry-bumpversionto manage release versions.poetryversionpatchDependencyOnce the release has been created it is now available for you to use in other python projects via:pipinstallagileetcAnd also for poetry projects via:poetryaddaigleetcContinuous IntegrationThe objects of each of the example CI pipelines here are to:Lint the python code.Run Unit TestsBuild package.Release package, bumping the version.Publishing in new package version.GitHub ActionsThe example GitHub actions CI for this project is located in file .github/workflows/python-ci.yml and is available from
the GitHub dashboard. This CI is setup torun via a local runnerwhich should be configured.JenkinsGoCDContributingPlease readCONTRIBUTING.mdfor details on our code of conduct, and the process for submitting pull requests to us.LicenseThis project is licensed under the Apache License, Version 2.0 - see theLICENSEfile for details
Package: agilent-visa-control
agilent_visa_controlA set of files aimed at facilitating the transfer of data from Agilent Spectrum Analizers through VISA InterfacePrerequisites:You will need PyVisa (and PyVisa's dependencies too obviously).Installation:No need to install, just clone this repository to your working workspace folder and code inside of it.For a good example on how to use the code check Agilent_save_trace.pyFrequency.py is a helper class to help you deal with frequencies and its conversion. You can by using this class just sum or substract frequencies and the units will be taken care of by the script. You can then convert to which ever frequency unit you need. Check Frequency.py for examples on usage (afterif __name__ == __main__:)Usage of Agilent class:Before using this class you will need to know the VISA identifier of the Agilent Spectrum Analyzer you'll want to use.
The identifier is usually found on the IO Librairies Suite of KeySight (https://www.keysight.com/en/pd-1985909/io-libraries-suite) (This suite is usually needed for communication with the Spectrum Analyzer) or in the instrument panel of your VISA package.It is something likeidentifier="GPIB0::8::INSTR"Once you know your identifier you will need to create the Agilent class object:agilent=Agilent(identifier)Then you need to open your connection:agilent.open()Then you could set the mode of the Analyzer, for example you could choose the spectrum analyzer mode. As of today the code only supports setting this mode remotely. You could always set in some other mode using the Frontal Interface on the instrument and then carry on extracting the data with this library.agilent.set_sa()Then you create the frequencies at which you want to center and the span of the analyzer.center_freq = Frequency(80.1, FreqUnit(FreqUnit.MHz))
span = Frequency(50, FreqUnit(FreqUnit.kHz))And we set the x Axis:agilent.set_x(center_freq, span)We set the Y axis now:agilent.set_y(3,10)#in dBm (first argument is the reference Level and the second one is the scale in dBm per Div.You can also set markers:agilent.set_marker(1, center_freq)And in the end we extract the values:values=agilent.get_trace(1)#treat valuesAnd in the end we close the connection.#close connection once you are done with the agilent Spectrum Analyzer
agilent.close()
Package: agilepoint
TODO: Create script to regenerate codeExamplesBasic Usage:from agilepoint import AgilePoint
ap = AgilePoint(host, path, username, password)
db_info = ap.admin.get_database_info()
# Responses in json usually have a primary key indicating what AgilePoint class the response has.
for key, value in db_info['GetDatabaseInfoResult'].items():
    print('{}: {}'.format(key,value))Register Users:users = {'First Last': 'email@domain.tld'}
for name, email in users.items():
    r = ap.admin.register_user(UserName=email, FullName=name)
    print(r)Note: It’s not well defined what arguments are required and what is optional. I’ve made logical conclusions. If you notice that the required/optional arguments is incorrect please submit a PR.
Package: agile-py
AgilePyWhat is it?Agile-py is a Python package to quickly kick off and python project.Main FeaturesInintializeproject withpyproject.toml,.pre-commit-config.yaml,.gitignore, and vscode setting.Where to get itAgile-py can be installed from PyPI usingpip:pipinstallagile-pyInterfaceInitialize python projectapyinit