Saravanan666/pypi-org huggingface dataset:
Package: pyind
pyindA genetic algorithm library in Python3pyind ONLY supports ndarray (numpy)日本語Installationpip install pyindAbout evaluation functionAn evaluation function has the following formatdefevaluation_function(individual):# individual is an array of genereturnfitness_of_this_individualAboutconfconfhas the following formatconf_format={"eval":{"func":evaluation_function# Required fields and it has not default value.},"sel":{# See "Table Sel" below},"xovr":{# See "Table Xovr" below},"mut":{# See "Table Mut" below},}Value that can be set toconf["sel"]are as shown in the tableIn parentheses is default valueTable Sel"sel" (elitism)"num" (10)elitism0–size of poplationroulette0–size of poplationValue that can be set toconf["xovr"]are as shown in the tableIn parentheses is default valueTable Xovr"xovr" (p2)"pb" (0.875)p20–1uniform0–1ox0–1Value that can be set toconf["mut"]are as shown in the tableIn parentheses is default valueTable Mut"mut" (flip_bit)"pb" (0.0075)"delta" (1)flip_bit0–1boundary0–10–∞swap_idx0–1Future ReleasesFix bugAdd functions of selection, crossover and mutationRun more fasterLicenseMITSample codeOnemax problem# Onemax ProblemimportnumpyasnpfrompyindimportpyindaspifrompyindimportdefaultsasdfIND_LEN=100POP_LEN=100defevl(ind):returnind.sum()if__name__=="__main__":pop=np.random.randint(2,size=(POP_LEN,IND_LEN))conf=df.CONFconf["eval"]["func"]=evlbest=pi.Pyind(pop,conf).run()print("best ind: ")print(best)Traveling salesman problem (TSP)# Traveling salesman problemimportnumpyasnpimportmatplotlib.pyplotaspltfrompyindimportpyindaspifrompyindimportcrossoverasxovrfrompyindimportmutationasmutfrompyindimportdefaultsasdfCITIES_LEN=30POP_LEN=300END_GEN=500cities=np.random.rand(CITIES_LEN*2).reshape((-1,2))defevl(ind):total=0foriinrange(1,len(ind)):total+=np.linalg.norm(cities[ind[i]]-cities[ind[i-1]])return-totaldefsolve(pop):conf=df.CONFconf["eval"]["func"]=evlconf["xovr"]["func"]=xovr.oxconf["mut"]["func"]=mut.swap_idxconf["mut"]["pb"]=0.10returnpi.Pyind(pop,conf).run(END_GEN)if__name__=="__main__":t=cities.T# Create poppop=np.tile(np.arange(CITIES_LEN),(POP_LEN,1))foreinpop:np.random.shuffle(e)# Plot gen 0idx=pop[0]plt.plot(t[0,idx],t[1,idx],label="gen 0",marker="o")best=solve(pop)print("best ind: ")print(best)# Plot gen END_GENidx=bestplt.plot(t[0,idx],t[1,idx],label="gen "+str(END_GEN),marker="o")plt.legend()plt.show()
Package: pyindependentreserve
pyindependentreservePython3 client for Interacting with Independent Reserve API - The Bitcoin and Digital Currency MarketInstall$pipinstallpyindependentreserveUsage REST API$python>>>importindependentreserveasir>>>connection=ir.PublicMethods()>>>connection.get_valid_limit_order_types()[u'LimitBid',u'LimitOffer']>>>api=PrivateMethods("your_api_key","your_api_secret")>>>api.get_open_orders(){'TotalItems':...etcUsage Websocketpyindependentreserve uses python3 asyncio module to implement a producer consumer pattern to consume messages from the websocket.Official websocket documentation can be foundherefromasyncio.queuesimportQueueimportwebsocketsimportasyncioimportsysfromindependentreserveimportwss_subscribeasyncdefconsumer(queue:asyncio.Queue):whileTrue:item=awaitqueue.get()ifitemisNone:breakprint("consuming item:{}".format(item))if__name__=="__main__":try:loop=asyncio.get_event_loop()queue=asyncio.Queue(1000)producer_coroutine=wss_subscribe(queue=queue,channel_name=["ticker-xbt-aud"])consumer_coroutine=consumer(queue=queue)loop.run_until_complete(asyncio.gather(producer_coroutine,consumer_coroutine))loop.close()exceptExceptionaserror:print(error)sys.exit(1)SupportIf you like this project and would want to support it please consider taking a look
at the issues section at:Github Issuesor consider donating toBitcoin:  1B2kZETHm9tjhPKtCCEo6eWhwT5TfXWE6u
Etherium: 0x00912fdef62ab7d9c1cbee712a58105eb1dbd42f
BitCash:  1B2kZETHm9tjhPKtCCEo6eWhwT5TfXWE6u
Package: pyindia
India packageVersion 1.1.5InstallationInstallation Using pippipinstallpyindiaRunning Testspython-munittestdiscover-stestsUsageThis repository makes it easy to access metadata of states and union territories of India.>>>importindia>>>india.states.AROUT:<State:ArunachalPradesh>You can also lookup whether your input is state or not.>>>importindia>>>india.states.lookup('arunachal pradesh')OUT:<State:ArunachalPradesh>New release enables you to access districts/cities across india with several attributes>>>importindia>>>india.cities.KA_BLROUT:<City:Bangalore>Lookup for cities>>>importindia>>>india.cities.lookup('Bangalore')OUT:<City:Bangalore>Check whether the city is capital>>>importindia>>>india.cities.lookup('Bangalore').iscapital()OUT:TrueAttributesAttributes of state objectstate.name# name of the statestate.capital# returns the capital of that statestate.population# returns the population of the statestate.area# returns the area of state in km^2state.density# returns population density per km^2 of statestate.language# primary official language of the stateAttributes of Cities objectcity.name# name of the citycity.state# returns the state of citycity.population# returns the population of the citycity.area# returns the area of the districtcity.density# returns population density per km^2 of the citycity.url# returns official webpage of the cityRelease NotesAdded cities of india with there attributes and states they belong to.Added attributes to state objects including population, area and language.Added cities string access.Added states string access.Added uts string access.Added Jammu and Kashmir and Ladhakh as Union territories.
Package: pyindia-stock
StockAnalysisInstallationAs ususal installation$ pip install pyindia-stockIt uses FBProphet for analysis and prediction.Getting StartedYou can use command-line script.pyindia_stock -hwill give the following.usage: pyindia_stock [-h] --index INDEX --from_date FROM_DATE
                     [--to_date TO_DATE]

Analyzing the Past Behavior of an index from Indian Stock Market

required arguments:
  --index INDEX         NSE index name
  --from_date FROM_DATE
                        starting date to consider for evaluation. Date in
                        d/m/Y,H format, H: should be in 24hrs format

optional arguments:
  --to_date TO_DATE     Specific/present date to consider for evaluation. Date
                        in d/m/Y,H format, H: should be in 24hrs format.
                        Default: Sets to present date and time.You can use it in scripts.# import pyindia_stock
$ from pyindia_stock import StockAnalysis

# run StockAnalysis with index and period_from as arguments.
$ StockAnalysis("SBIN",period_from="01/01/2000,15")

# StockAnalysis has the following arguments:
# - index: Only NSE index name
# - period_from: starting date to consider for evaluation. Date in "%d/%m/%Y,%H" format, H: should be in 24hrs format.
# - period_to: Specific/present date to consider for evaluation. Date in "%d/%m/%Y,%H" format, H: should be in 24hrs 				format.Default: Sets present date and time.
#StockAnalysis has attributes 
# - read_data: Read stock Dataframe
# - fbprophet: Instance of class FBProphet with daily seasonality.
# - is_data_available: if data has loaded to dataframe and has suitable format, then in is trueHow to use it?Colab starter notebook:About FBProphet:Prophet is a forecasting procedure implementation in R and Python. It is fast and provides completely automated forecasts that can be tuned by hand by data scientists and analysts.Prophet follows the sklearn model API. We create an instance of the Prophet class and then call its fit and predict methods.The input to Prophet is always a dataframe with two columns: ds and y. The ds (datestamp) column should be of a format expected by Pandas, ideally YYYY-MM-DD for a date or YYYY-MM-DD HH:MM:SS for a timestamp. The y column must be numeric, and represents the measurement we wish to forecast.
Package: pyindia-zipcode
pyindia_zipcodeFind Post Office Details from PinCode, All India Post Office Pincode DataINSTALLpip3installpyindia-zipcodeIMPORT PKGPython3.6.9(default,Jan262021,15:33:00)[GCC8.4.0]onlinuxType"help","copyright","credits"or"license"formoreinformation.>>>frompyindia_zipcodeimportZipCode>>>>>>obj=ZipCode()>>>ZIP CODE INFOIn this625003zip code infomationPython3.6.9(default,Jan262021,15:33:00)[GCC8.4.0]onlinuxType"help","copyright","credits"or"license"formoreinformation.>>>frompyindia_zipcodeimportZipCode>>>>>>obj=ZipCode()>>>>>>obj.get_zipcode_info(625003)>>>output[{"ID":119891,"officename":"Alagappa Nagar S.O","pincode":"625003","officeType":"S.O","Deliverystatus":"Non-Delivery","divisionname":"Madurai","regionname":"Madurai","circlename":"Tamilnadu","Taluk":"Madurai South","Districtname":"Madurai","statename":"TAMIL NADU","Telephone":"0452-2343894","Related Suboffice":"NA","Related Headoffice":"Madurai H.O","longitude":"NA","latitude":"NA"},{"ID":120019,"officename":"Madakkulam B.O","pincode":"625003","officeType":"B.O","Deliverystatus":"Delivery","divisionname":"Madurai","regionname":"Madurai","circlename":"Tamilnadu","Taluk":"Madurai South","Districtname":"Madurai","statename":"TAMIL NADU","Telephone":"NA","Related Suboffice":"Palanganatham S.O","Related Headoffice":"Madurai H.O","longitude":"NA","latitude":"NA"},{"ID":120073,"officename":"Palanganatham S.O","pincode":"625003","officeType":"S.O","Deliverystatus":"Delivery","divisionname":"Madurai","regionname":"Madurai","circlename":"Tamilnadu","Taluk":"Madurai South","Districtname":"Madurai","statename":"TAMIL NADU","Telephone":"0452-2373669","Related Suboffice":"NA","Related Headoffice":"Madurai H.O","longitude":"NA","latitude":"NA"},{"ID":120185,"officename":"Tvs Nagar S.O","pincode":"625003","officeType":"S.O","Deliverystatus":"Non-Delivery","divisionname":"Madurai","regionname":"Madurai","circlename":"Tamilnadu","Taluk":"Madurai South","Districtname":"Madurai","statename":"TAMIL NADU","Telephone":"0452-2373669","Related Suboffice":"NA","Related Headoffice":"Madurai H.O","longitude":"NA","latitude":"NA"}]The first digit of a PIN indicates the zone, the second indicates the sub-zone, and the third, combined with the first two, indicates the sorting district within that zone. The final three digits are assigned to individual post offices within the sorting district.
Package: pyindi-client
An INDI Client Python API, auto-generated from the official C++ API using SWIG.InstallationUse pip (recommended): pip install pyindi-clientAlternatively download a release, extract it and run: python setup.py installThe file setup.cfg contains configuration options (mainly concerning libindi installation path).
The file setup.py searchs for the libindiclient.a library in some predefined directories.
If not found, the script fails. Locate this library (try locate lindiclient.a from the command line)
and add its path to the libindisearchpaths variable in the setup script.DependenciesFor the above installation to work, you need to have installed from your distribution repositories the following packages: Python setup tools, Python development files, libindi development files and swig.
- On an Ubuntu-like distribution, you may use:
apt-get install python-setuptools python-dev libindi-dev swig
- On a Fedora-like distribution, you may use (dnf or yum):
dnf install python-setuptools python-devel libindi-devel swig
Package: pyindi-client-artak
An INDI Client Python API, auto-generated from the official C++ API using SWIG.InstallationUse pip (recommended): pip install pyindi-clientAlternatively download a release, extract it and run: python setup.py installThe file setup.cfg contains configuration options (mainly concerning libindi installation path).
The file setup.py searchs for the libindiclient.a library in some predefined directories.
If not found, the script fails. Locate this library (try locate lindiclient.a from the command line)
and add its path to the libindisearchpaths variable in the setup script.DependenciesFor the above installation to work, you need to have installed from your distribution repositories the following packages: Python setup tools, Python development files, libindi development files and swig.
- On an Ubuntu-like distribution, you may use:
apt-get install python-setuptools python-dev libindi-dev swig
- On a Fedora-like distribution, you may use (dnf or yum):
dnf install python-setuptools python-devel libindi-devel swig
Package: pyinduct
image::https://img.shields.io/travis/pyinduct/pyinduct.svgtarget:https://travis-ci.org/pyinduct/pyinductPyInduct is a python toolbox for control and observer design for infinite dimensional systems.Documentation:https://pyinduct.readthedocs.org.Bug Reports:https://github.com/pyinduct/pyinduct/issuesPyInduct supports easy simulation of common distributed parameter systems using
ready-to-go FEM implementations or custom modal approximations.
With the included eigenfunctions for parabolic problems up to 2nd order or
case-agnostic Lagrangian polynomials, automated controller and observer
approximation routines are provided.
The included visualization methods help verifying the controllers performance.
Package: pyine
pyineA simple package for the conversion of tradingview's .pine to python script.Currently SupportsVariable Declerationa = 1Dynamic Value Assignmenta = b > cIf statementsAlert functions (will act as a print statement but will have full support in the future)CommentsWarningThe current version (1.1.2) will auto comment any strategy calls so it is advised that a study is used instead.UsagePyine currently supports partial file conversion (good for simple pine script files) and the below indicators (based on their pine script equivelants)IndicatorsSimple Moving AverageExponential Moving AverageConverterfrom pyine import convert
_ = convert(filename)Indicatorsfrom pyine.indicators import *
ema = ema(close, period)
Package: pyinels
PyInelsA Python library that handles communication with proprietary home intelligent system
namediNelsby ElkoEP company.This package is developed against iNels BUS version. It is not tested on older
version CU2 and does not support RF components.RequirementsFor smooth using you need to have Python 3.8 or higher.InstallUse PyPI repositorypip install pyinelsUsageSee the test directory for examples.TestingI usetoxfor testing.$ pip install toxReasonI wrote PyInels library to use it forhome assistantintegration.Watch FeatureIn the future I would like to rewrite the library with better efficiency such assAsyncio.
Package: pyinels-domenix-dev
PyInelsA Python library that handles communication with proprietary home intelligent system
namediNelsby ElkoEP company.This package is developed against iNels BUS version. It is not tested on older
version CU2 and does not support RF components.RequirementsFor smooth using you need to have Python 3.8 or higher.InstallUse PyPI repositorypip install pyinelsUsageSee the test directory for examples.TestingI usetoxfor testing.$ pip install toxReasonI wrote PyInels library to use it forhome assistantintegration.Watch FeatureIn the future I would like to rewrite the library with better efficiency such assAsyncio.
Package: pyInet
pyInetPython module that works to manipulate IPv4/6 addresses, calculate Network/IP addresses.
What you get:ip validation by class or ip versionGenerate IPv4/6, and Mac address bit by bitCalculate IPv4/6Light and fastInstallationPippython -VWindows:python -m pip install pyInetUnix or Mac:pip install pyInetGITWindows, Unix and Mac:git clone https://github.com/LcfherShell/pyInet
   cd pyInet
   python -m pip install . or python setup.pyUsage Examplefrom pyInet import ClassA, ClassB, Topologhy

#manipulate Net
child = ClassA #Public Class
network = ClassB #Private Class

print("Call function using public class")
for i in range(3):
    for ipv4 in child.IPv4(i):
         print("IPv4:", ipv4)
    for ipv6 in child.IPv6(i):
         print("IPv6:", ipv6)
    print("MacAddresss:", child.MacAddresss(),"\n")
i = 0
print("\nCall function using private class")
for i in range(3):
    for ipv4 in network.IPv4(i):
         print("IPv4:", ipv4) 
    for ipv6 in network.IPv6(i):
         print("IPv6:", ipv6)
    print("MacAddresss:", network.MacAddresss(),"\n")

ipv4 = "192.222.02.1"
ipv6 = "f18d:5980:50d1::cf2d"

print("Check Version and Class Ip addresses")
print("IP version:", child.Validate_IP(ipv4))
print("IPv4 Class:",  child.IPv4_Class(ipv4))
print("\nIP version:", child.Validate_IP(ipv6))
print("IPv6 Class:",  child.IPv6_Class(ipv6))
print("\nManipulate IPv4 :")
for x in range(1, 33):
   child.IPv4_Calculator("{}/{}".format(ipv4, x))
   print(child.saving.output)
print("\nManipulate IPv6 :")
for y in range(0, 33):
   ipv6range = "{}/{}".format(ipv6, y)
child.IPv6_Calculator(ipv6range)
print(child.saving.output)

//Net Topologhy
host = Topologhy
//make token
host._token(ipv4, 12)
//set hostrot
host.server
host.server = "Online"//online
//router
host.router()
//make client v1(vuln token)
host.clients_v1(None, host.saving.pinbus)//vuln by access token and custum client
host.clients_v2()//random private token and auto generate

host.switch_s = "192.222.02.1 192.222.02.3"
host.Hypermedia_Host("192.222.02.2")//test connectionIf you find any bugs/problems, please contact email:LCFHERSHELL@TUTANOTA.COMoralfiandecker2@gmail.comHappy coding :). Sorry, my English is very bad
Package: pyinfer
Pyinfer is a model agnostic tool for ML developers and researchers to benchmark the inference statistics for machine learning models or functions.InstallationpipinstallpyinferOverviewInference ReportInferenceReportis for reporting inference statistics on a single model artifact. To create a valid report simply pass it a callable model function or method, valid input(s), and eithern_iterationsorn_secondsto determine what interval the report uses for its run duration. Check out the docs for more information on the optional parameters that can be passed.Multi Inference ReportMultiInferenceReportis for reporting inference statistics on a list of model artifacts. To create a valid multi report pass it a list of callable model functions or methods, a list of valid input(s), and eithern_iterationsorn_secondsto determine what interval the report uses for its run duration. Check out the docs for more information on the optional parameters that can be passed.Example OutputsTable ReportRun PlotStats Currently IncludedSuccess Rate - Number of successful inferences within a specified time range.Failures - Number of inferences above specified time range.Time Taken - Total time taken to run all inferences.Inference Per Second - Estimate of how many inferences per second the selected model can perform.Max Run - The max time taken to perform an inference for a given run.Min Run - The min time taken to perform an inference for a given run.Std - The Standard deviation between runs.Mean - The mean run time.Median - The median run time.IQR - The inter quartile range of the runs.Cores Logical - The number of logical cores on the host machine.Cores Physical - The number of physical Cores on the host machine.Planned Future StatsModel Size - Information relating to the size of the model in bytes.GPU Stat Support - Information about if GPU is available and if it is being utilized.
Package: pyinferno
PyInfernoPython package that renderspyinstrumentprofiles as flamegraphs, using theinfernorust crate.InstallationInstall fromPyPi:pip install pyinfernoUsageContext managerTo profile a specific piece of code, you can use thepyinstrument Profiler class, then render the result using pyinferno'sInfernoRenderer:frompyinstrument.profilerimportProfilerfrompyinfernoimportInfernoRendererimporttimedefslow():time.sleep(0.5)withProfiler()asprofiler:slow()output=profiler.output(InfernoRenderer(title="slow"))withopen("flamegraph.svg","w+")asf:f.write(output)For convenience, the same result can be achieved using theInfernoProfilercontext manager:frompyinfernoimportInfernoProfilerimporttimedefslow():time.sleep(0.5)withInfernoProfiler(file="flamegraph.svg",auto_open=True,title="slow"):slow()Command-lineTo profile a Python script, you can passpyinferno.Rendereras the renderer to thepyinstrumentCLI:pyinstrument-rpyinferno.Renderer-oflamegraph.svgslow.pyFor convenience,pyinfernoincludes its own script which wraps thepyinstrumentCLI:pyinfernoslow.pyIf no output file is specified, the flamegraph will be written to a temporary file and automatically opened using python'swebbrowsermodule. To save the flamegraph to a file, pass the-ooption:pyinferno-oflamegraph.svgslow.pyTo profile a python module, pass the-margument:pyinferno-mpytest-kslow_test
Package: pyinfluxdb
version number: 0.1.3
author: pyinfluxdbOverviewA python package that can be installed with pip.Installation / UsageTo install use pip:$ pip install pyinfluxdbOr clone the repo:$ git clonehttps://github.com/muumlover/pyinfluxdb.git$ python setup.py installContributingTBDExampleTBD
Package: pyinfluxql
AboutA query generator for the SQL dialect of theInflux Query Language (InfluxQL).
Like SQLAlchemy but for InfluxDB. Consider this an experimental WIP.SynopsisfrominfluxdbimportInfluxDBClientfrompyinfluxqlimportEngine,Query,Meanclient=InfluxDBClient('localhost',8086,'root','root','example')engine=Engine(client)query=Query(Mean('value')).from_('cpu_load')\.where(time__gt=datetime.now()-timedelta(1)).group_by(time=timedelta(hours=1))engine.execute(query)TestsHow to invoke the test suite.Using ToxRun InfluxDB within Docker:docker run -it --rm --publish 8086:8086 influxdb:1.8.3Runtox:toxUsing sandboxAlternatively, setup package in development mode:python3 -mvenv .venv
source .venv/bin/activate
pip install --editable=.[test]Runpytest:pytest tests -vvvCreditsThanks a stack to the original authorJeremiah Malinafor his excellent
work as well asMichael Pérezfor adding integration tests, timezone support
and for improving the documentation.
Package: pyinfoepub
PyInfoEpub helps you retrieve specific information from an EPUB file.
Check the documentation to find out how to use it.Free software: GPLv3 licenseDocumentation:https://pyinfoepub.readthedocs.org.Featuresextracts the metainformation from an epub fileuse fully customizable template engine to display this informationHistory0.2 (2015-02-01)Major refactoring release on PyPI.0.1 (2010-12-06)Initial release on PyPI
Package: pyinform
Copyright (c) 2016-2019, Douglas G. MoorePermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the “Software”), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.Description:PyInform is a python wrapper for the Cinformlibrary. You can find live API documentation athttps://elife-asu.github.io/PyInform.So far the python wrapper has been tested underpython2.7,python3.4andpython3.5, and on the following platforms:Debian 8Mac OS X 10.11 (El Capitan)Windows 10Platform: Windows
Platform: OS X
Platform: Linux