Saravanan666/pypi-org huggingface dataset:
Package: interstat
An HTML formatter for IRC log files.
Currently, only the format used byOmnipresenceis supported; look ininterstat.formatsfor an idea of how to add more.Install it with:$ pip install interstatThen run:$ interstat LOGFILE HTMLFILEIf you want to change the generated HTML or CSS, copy the files in theinterstat/templatesdirectory that you want to override, make your
changes, and run:$ interstat --template-dir my-templates/ LOGFILE HTMLFILEFor more options, try:$ interstat --helpInterstat also provides a Python API, in case that’s more your thing:>>> import interstat
>>> # Convert an entire log file:
>>> interstat.file_as_html(open('irc.log'), 'omnipresence')
>>> # Or just some text with embedded mIRC formatting codes:
>>> interstat.line_as_html('\x02Bold\x02 and \x1Funderlined\x1F, oh my!')Report bugs and make feature requests onInterstat’s GitHub project
page.
Package: interstellar
hyperdrive: Robinhood analytics and algorithmic tradinghyperdriveis a project to obtain stock data, create trading strategies, test against historical data (backtesting), and deploy strategies for algorithmic trading.Getting StartedPrerequisitesYou will need Python 3.8+ and a Robinhood account.Place your credentials in a file named.envin the project root directory.
Follow this structure:RH_USERNAME=...
RH_PASSWORD=...
RH_2FA=...
IEXCLOUD=...InstallationTo install the necessary packages, runpip install -r requirements.txtTestingpython -m pytest -s -v test/test_filename -k function_nameUseMaking ScriptsTo make a script, create a new .py file in thescripts/dir with the following code:import sys
sys.path.append('hyperdrive')
from Algotrader import HyperDrive  # noqa autopep8

drive = HyperDrive()Features:Broker authenticationAutomated data storageBacktesting engineMonte Carlo simulationsPlotting and technical analysisModel trainingStrategy definition (start with buy and hold)Buy and sell functionalityLive tradingDocumentationCheck out theRoadmapfor progress
...AuthUsing Robinhood 2FA, we can simply provide our MFA one-time password in the.envfile to login to Robinhood (viapyotp).DataPrice and VolumeActionsSentimentNews SentimentInvestor SentimentAnalyst RecommendationsCompany / MicroProfile (Sector, # of Employees)EarningsCash FlowCEO CompensationGovernment / MacroReal GDPUS Recession ProbabilitiesMarketGeneral Volatility (VIX)Sector PerformanceStrategyBuy and HoldIndicator/TA basedPortfolio OptimizationTradingBuy and Sell
Package: interva
intervaPython implementation of the InterVA algorithm for assigning causes of death to verbal autopsy dataImporting package and installing dependenciesTo install all package dependencies, run:pipinstallintervaTo import this package's functions:frominterva.interva5importInterVA5Example dataTo access example data from the package:frominterva.interva5importget_example_inputva_data=get_example_input()va_dataIDi004ai004bi019ai019bi022a...i454oi455oi456oi457oi458oi459o0d1..y.y...nnnnnn1d2...yy...nnnnnn2d3..y.....nnnnnn3d4...y....nnnnnn4d5..y.....nnnnnn.........................................195d196...y....nnnnnn196d197..y.y...nnnnnn197d198..y.y...nnnnnn198d199...yy...nnnnnn199d200...yy...nnnnnn[200rowsx354columns]Creating and running an InterVA5 objectTo initialize an InterVA5 object (results will be written toVA_outpt/VA5_results.csv):iv5out=InterVA5(va_data,hiv="h",malaria="l",write=True,directory="VA_output",filename="VA5_result",output="extended",append=False,return_checked_data=True)To run the InterVA5 algorithm on the InterVA5 object:iv5out.run()UsingProbbaseversion:probbasev1920210720..........10%completed..........20%completed..........30%completed..........40%completed..........50%completed..........60%completed..........70%completed..........80%completed..........90%completed..........100%completed100%completedGet cause-specific mortality fractions (CSMFs) for the top 8 causes:iv5out.get_csmf(top=8)HIV/AIDSrelateddeath0.194408Undetermined0.136583Digestiveneoplasms0.083285Otherandunspecifiedinfectdis0.063096Renalfailure0.061253ReproductiveneoplasmsMF0.053655Otherandunspecifiedcardiacdis0.047557Stroke0.045583dtype:float64getters for InterVA5 parameters:iv5out.get_hiv()iv5out.get_malaria()iv5out.get_ids()HIVparameterishMalariaparameterislids0d11d22d33d44d5...195d196196d197197d198198d199199d200Name:ID,Length:200,dtype:objectTo change the parameters, use setters and re-run.iv5out.set_hiv("v")iv5out.set_malaria("v")iv5out.run()
Package: interval-binning
These are some utility functions for working with the interval binning scheme
as used in theUCSC Genome Browser. This scheme can be used to
implement fast overlap-based querying of intervals, essentially mimicking anR-treeindex.Note that some database systems natively support spatial index methods such as
R-trees. See for example thePostGISextension for
PostgreSQL.Although in principle the method can be used for binning any kind of
intervals, be aware that the largest position supported by this implementation
is 2^29 (which covers the longest human chromosome).UsageSee thedocumentation.InstallationTo install the latest release via PyPI using pip:pip install interval-binning
Package: intervalframe
IntervalFrame for interval manipulationThis is a Python package for easy and efficient manipulation
of Next Generation Sequencing reads.InstallIf you dont already have numpy and scipy installed, it is best to downloadAnaconda, a python distribution that has them included.https://continuum.io/downloadsDependencies can be installed by:pip install -r requirements.txtPyPI install, presuming you have all its requirements installed:pip install intervalframeUsagefromintervalframeimportIntervalFrameimportnumpyasnp# Create dataiframe=IntervalFrame()
Package: intervalpy
intervalpyAn interval set utility library.InstallationWithpoetry:poetryaddintervalpyOr with pip:pip3 install intervalpyUsageHave a look at thedocumentation.Basic usage:frominterval_utilimportIntervaldigits=Interval(0,10,end_open=True)ten_and_up=digits.get_gt()positive_numbers=digits.get_gte()assertten_and_up.is_subset_of(positive_numbers)assertpositive_numbers.intersection(Interval.lt(10))==digits
Package: interval-repeat-decorator
Run code asynchronously to the main code executionpipinstallinterval-repeat-decoratorfrominterval_repeat_decoratorimportrepeat_actionfromthreadingimportLocklock=Lock()@repeat_action(print_exception=True,exception_value="FTW",break_on_exceptions=False,interval=.1,threadlock=lock,kill_thread="ctrl+x",number_of_executions=10,)deftestest(number):ifnumber==0:print(number)returnTrueelifnumber==1:print(number/0)returnTrue@repeat_action(print_exception=True,exception_value="FTW",break_on_exceptions=False,interval=.2,threadlock=lock,kill_thread="ctrl+y",number_of_executions=5,)deftestest2(number):ifnumber==0:print(number)returnTrueelifnumber==1:print(number/0)returnTruetestex=testest(number=0)testex2=testest2(number=1)print(f"{testex=}\n{testex2=}")#returns the first result only, but will keep on executing!0divisionbyzerotestex=Truetestex2='FTW'0divisionbyzero00divisionbyzero00divisionbyzero00divisionbyzero00testexOut[3]:Truetestex2Out[4]:'FTW'
Package: interval-search
interval-searchinterval-search provides predicate-based binary and doubling search implementationsFree software: MIT licenseDocumentation:https://interval-search.readthedocs.io.importinterval_searchasinch# inch.binary_searchlist_=[1,10,20,500,5000]inch.binary_search(lambdax:list_[x]>=20,0,len(list_)-1)# -> 2# inch.doubling_searchinch.doubling_search(lambdax:x>=5)# -> 5# with a lower bound to start searching at,inch.doubling_search(lambdax:x>=5,10)# -> 10# inch.interval_search# uses binary search or doubling search# depending on whether upper bound is specifiedinch.interval_search(lambdax:list_[x]>=20,0,len(list_)-1)# -> 2inch.interval_search(lambdax:x>=5,10)# -> 10CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.0.0 (2022-02-22)First release on PyPI.
Package: intervalsicu
Intervals.ICU Python APIThis API provides a basic interface to work with the Intervals.ICU.
You can obtain further documentation for the Intervals.ICU site by
following the instructions fromthis post.API functionality is described in the thread above. This API aims to provide all functionality, but there are gaps. Please open an issue (or a PR) for any missing functionality.Full documentation can be foundhereChangelog0.1.4Added astrictflag to the Intervals library. This flag tells the library
whether it should validate objects received from the server. If object validation
fails, aTypeErroris raised.This flag was added because updates to the backend objects can unintentionally break
client libraries. So you can toggle this flag to stop validating objects.This flag isTrueby default, to preserve backwards compatibility. You must
manually set the flag toFalseto stop validating objects.ExamplesUpdate a field in your wellness documentimportpprintfromdatetimeimportdatefromintervalsicuimportIntervalsdefwellness():svc=Intervals("MY ATHLETE ID","MY API KEY",strict=False)start=date.fromisoformat("2021-03-10")wellness=svc.wellness(start)wellness['restingHR']=57wellness=svc.wellness_put(wellness)pprint.pprint(wellness)if__name__=="__main__":wellness()Write all your activities to a CSV fileimportcsvimportiofromintervalsicuimportIntervalsdefactivities_to_csv():svc=Intervals("MY ATHLETE ID","MY API KEY",strict=False)activities_csv=io.StringIO(svc.activities())withopen('example/activities.csv','w')asw:reader=csv.reader(activities_csv)writer=csv.writer(w)forrowinreader:writer.writerow(row)if__name__=="__main__":activities_to_csv()Download a list of events in JSON.importpprintfromdatetimeimportdatefromintervalsicuimportIntervalsdefevents():svc=Intervals("MY ATHLETE ID","MY API KEY",strict=False)start=date.fromisoformat("2021-03-08")end=date.fromisoformat("2021-03-09")events=svc.events(start,end)pprint.pprint(events)if__name__=="__main__":events()
Package: interval-timer
interval-timerinterval-timeris a Python package that enables iterating over a sequence of regular time intervals with high precision.InstallationInstall fromPyPIvia:pipinstallinterval-timerUsageBasic usage is as follows:frominterval_timerimportIntervalTimerforintervalinIntervalTimer(0.5):print(interval)# Execute code exactly every half second here...Output:Interval(index=0, time=0.000, lag=0.000)
Interval(index=1, time=0.500, lag=0.000)
Interval(index=2, time=1.000, lag=0.000)
...For more usage examples seeexamples/.DescriptionIntervalTimeris an iterator object that returnsIntervalobjects at regular time intervals. Code can then be executed upon each time interval, and the intervals will stay synchronised even when the code execution time is non-zero.IntervalTimeris a more precise replacement for a loop that contains a wait. The following code:fromtimeimportsleep# Iterates approximately every half secondforiinrange(5):print(i)sleep(0.5)can be replaced with:frominterval_timerimportIntervalTimer# Iterates exactly every half secondforintervalinIntervalTimer(0.5,stop=5):print(interval)interval-timerusesperf_counterunder the hood to obtain high precision timing. It will not suffer from drift over long time periods.If an interval iteration is delayed due to slow code execution, then future intervals will still be synchronised to absolute time if they're given time to catch up. The caller can see if synchronisation has been temporarily lost by checking if theIntervalobject'slagattribute returns a non-zero value (see thelag.pyexample).Timing diagramThe above timing diagram shows that each returnedIntervalobject has the following attributes:time: the nominal start time of the interval. Always has equal value to theend_timevalue of the previous interval.buffer: the length of time before the interval start time that the interval was requested. The minimum buffer is zero.lag: The length of time after the interval start time that the interval was requested. The minimum lag is zero. If the lag is non-zero, then the code executed within the previous interval took longer than the interval period, which is generally undesirable.
Package: interval-timer-python
interval-timer-pythonoverviewinterval timer library for pythonon Windows: Waitable Timer wrapperon Linux: timerfd wrapperOSWindows & Linuxinstallationpython-mpipinstallinterval-timer-pythonusageimportinterval_timerINTERVAL_TIME_MS=100itimer=interval_timer.IntervalTimer()itimer.settime(INTERVAL_TIME_MS)whileTrue:print("Hello,World!")itimer.wait()# periodic blocking
Package: interval-tools
Python Tools for Applications of Interval DesignRequirementsPython 3.11+Installationpipinstallinterval-toolsOr if you want to useObjectIdas a unique identifier forEntityorAggregate, runpipinstall"interval-tools[objectid]"Quickstart>>>frominterval.utilsimportbatched>>>forbatchinbatched('ABCDEFG',3):...print(batch)...('A', 'B', 'C')('D', 'E', 'F')('G',)
Package: intervaltree_bio
Convenience classes for loading UCSC genomic annotation records into a set ofinterval treedata structures.InstallationThe easiest way to install most Python packages is viaeasy_installorpip:$ pip install intervaltree-bioThe package requires theintervaltreepackage (which is normally installed automatically when usingpiporeasy_install).UsageOne of the major uses for Interval tree data structures is in bioinformatics, where the
intervals correspond to genes or other features of the genome.As genomes typically consist of a set ofchromosomes, a separate interval tree for each
chromosome has to be maintained. Thus, rather than using an single interval tree, you would typically use
something likedefaultdict(IntervalTree)to index data of genomic features.
The moduleintervaltree_biooffers aGenomeIntervalTreedata structure, which is a similar convenience
data structure. In addition to specific methods for working with genomic intervals it also
provides facilities for reading BED files and the refGene table fromUCSC.The core example is loading the transcription regions of theknownGenetable from the UCSC website:>> from intervaltree_bio import GenomeIntervalTree
>> knownGene = GenomeIntervalTree.from_table()
>> len(knownGene)It is then possible to use the data structure to search known genes within given intervals:>> result = knownGene[b'chr1'].search(100000, 138529)It is possible to load other UCSC tables besidesknownGeneor specify custom URL or file to read the table from.
Consult the docstring of theGenomeIntervalTree.from_tablemethod for more details.CopyrightCopyright (c) Konstantin TretyakovMIT license.Report issues viaGithub.
Package: intervention
interventionis a work in progress for disabling input to my
computer, showing me the current time, and making me ask myself if I’m
being intentional.[STRIKEOUT:It requiressudoNOPASSWD access on OS X to filter
keyboard input. Wrapping it in an application might allow it to be used
with the OS X Accessibility API instead.]Installation$pip3installintervention$crontab-e*/15****/usr/local/bin/intervention# add this lineIt looks like this:screenshot
Package: interview-buddy
Interview BuddyInterview Buddy is designed for beginners who are new to coding which has two ai-models in itcode-llama-7bfor code generation andpython-code-explainerwhich makes it useful for generating code and understanding code for both beginner and intermediate programmersInstallationInstall interview-buddy with cmdpipinstallinterview-buddy==0.4Initialization for Basic Methodsfrominterview.interviewimportInterviewinterview=Interview(data=10)Initialization for Generating Codefrominterview.interviewimportInterviewinterview=Code_Generator("Generate")Initialize the Interview object with necessary dataMethodsa.factorial()This method calculates the factorial of a given number.Parameters:data:Integer, the number for which factorial is to be calculated.Example:result=interview.factorial()print("Factorial:",result)Parameters:User_input:String, Enter the query which want to be generated.Example:result=interview.generate_code("Write me a code for Binary Tree")print("Factorial:",result)Supported MethodsList all the supported methods along with a brief description of what each method does.fibonacci_series():Generates a Fibonacci series.palindrom():Checks if a string is a palindrome.bubble_sort():Sorts a list using the bubble sort algorithm.insertion_sort():Sorts a list using the insertion sort algorithm.anagram():Checks if two strings are anagrams.binary_search():Performs binary search on a sorted list.min_():Finds the minimum value in a list.max_():Finds the maximum value in a list.reverse():Reverses a list.generate_code():Which is used to generate codeInstallationInstall interview-buddy with cmdpipinstallinterview-buddyAuthors@RoboJunior👨‍💻DependenciesTransformersCtransformersTransformers - InstallationpipinstalltransformersCtranformers - Installation#Base ctransformers with no GPU accelerationpipinstallctransformers>=0.2.24#Or with CUDA GPU accelerationpipinstallctransformers[cuda]>=0.2.24#Or with ROCm GPU accelerationCT_HIPBLAS=1pipinstallctransformers>=0.2.24--no-binaryctransformers#Or with Metal GPU acceleration for macOS systemsCT_METAL=1pipinstallctransformers>=0.2.24--no-binaryctransformers
Package: interviewer
interviewer - a little bot helping you to prep your job interviewsWhat it doesintervieweris a little python library that defines a bot to help you
practice your interview skills. It basically prompts interview questions in your
python console and stops the time it takes you to answer those. It is not much,
but it definitely helped me to pick up some confidence.How it worksYou can simply getinterviewerfrom PyPi and run something like:pip install interviewerAdjust this to your local python specs of course. To get the mock interview started,
simply load the class from the library.from interviewer import interviewerNext you can call the class and provide your custom questions as a.txtfile.my_mock_interview = interviewer(questions_file='path_to_my_questions/question_file.txt')Once you did that, you can just start the interview and pressentereach time
you are done with a question. The time it takes you to answer each questions will be recorded.my_mock_interview.start()To get an overview, of how long it took you to answer, you can use the analyze method.my_mock_interview.analyze()Why is the timing important? First of all, you probably learn to get straight to the point
and second, it created a sense of urgency when practicing, which is certainly a good learning.
Package: interviewing
InterviewingInterviewing is a sassy package for shaming unimaginative interviewers.Have you ever walked in to an interview and been asked to calculate the optimal time to buy and sell a stock?Well, gone are the days of remembering interview-only algorithms.
Instead, simply import the question frominterviewing'squestionsmodule and use our code instead.frominterviewing.questionsimportbuy_and_sell_a_stock_onceNo more fizzbuzz! No more is_palindrome! No more lame interview questions!
Package: interview-star-questions
Interview Questions PracticeThis program stores and displays interview questions and corresponding answers, notes, and tips.Description•Features•Future Features•File Descriptions•How To Use•Requirements•Credits•LicenseDescriptionThis is a flash card interface, used for interview questions currently.FeaturesCommand line interface to display random practice questionsOptionally add answers, notes, and tipsKeeps track of what questions you have answeredFuture FeaturesMove program to webpage using flask for better interfaceAdd function to include job descriptionsHow To Usepipinstallinterview-star-questions

interviewRequirementsNo special requirements!Creditsnavdeep-G setup.pyLicenseMIT
Package: interzoid-address-match-key
interzoid_address_match_keyPython package for generating a similarity key from the input data used to match with other similar street address data. Use the generated similarity key, rather than the actual data itself, to match and/or sort street address data by similarity. This avoids the problems of data inconsistency, misspellings, and address element variations when matching within a single dataset, and can also help matching across datasets or for more advanced searching.The key generation is based on a series of tests, algorithms, AI, and an ever-growing body of Machine Learning-based generated knowledge.UsageTo generate the similarity key, you will need the following information:an API License key, available athttps://www.interzoid.coma street address to generate the similarity key forAn API is called by the package to access the Cloud server that generates the similarity key.Begin by importing the package:from interzoid_address_match_key import address_match_keyThen, provide the information into the get_key() method:sim_key, credits, http_code, msg = address_match_key.get_key('YOUR-API-KEY','107 E. Main St.')

#200 is the HTTP status for OK
if http_code == 200:  
    print(sim_key, msg, credits)
else:
    print(sim_key, "error:", http_code, msg, credits)The return values will be the generated similarity key, a code (success or failure), how many remaining credits on your API key, and any error messages. The similarity key can be used to search for other similar street addresses, to sort large datasets by similarity, and perhaps use additional attributes to identify duplicates/redundancy.Examples:100 E. Main St. Suite 101  ->  fS9Xxx-9HoRD4ZGJA43meLBS3tAn5YjdCClGJyXtUrw
100 East Main St. #101  ->  fS9Xxx-9HoRD4ZGJA43meLBS3tAn5YjdCClGJyXtUrw

Park Avenue #500  ->   EP88bx0VFDaIh-cOt86c8pOJ6lNkb_TWiKFpmMKXakY
500 PARK AVE.  ->  EP88bx0VFDaIh-cOt86c8pOJ6lNkb_TWiKFpmMKXakY
Package: interzoid-company-name-match-key
interzoid_company_name_match_keyPython package for generating a similarity key from the input data used to match with other similar company name data. Use the generated similarity key, rather than the actual data itself, to match and/or sort company name data by similarity. This avoids the problems of data inconsistency, misspellings, and name variations when matching within a single dataset, and can also help matching across datasets or for more advanced searching.The key generation is based on a series of tests, algorithms, AI, and an ever-growing body of Machine Learning-based generated knowledge.  As the context of the data is known, in this case organization/company names, it performs far better than generic string comparison algorithms.UsageTo generate the similarity key, you will need the following information:an API License key, available athttps://www.interzoid.coma company name to generate the similarity key forAn API is called by the package to access the Cloud server that generates the similarity key.Begin by importing the package:from interzoid_company_name_match_key import company_name_match_keyThen, provide the information into the get_key() method:sim_key, credits, http_code, msg = company_name_match_key.get_key('YOUR-API-KEY','Bank of America')

#200 is the HTTP status for OK
if http_code == 200:  
    print(sim_key, msg, credits)
else:
    print(sim_key, "error:", http_code, msg, credits)The return values will be the generated similarity key, a code (success or failure), how many remaining credits on your API key, and any error messages. The similarity key can be used to search for other similar company names, to sort large datasets by similarity, and perhaps use additional attributes to identify duplicates/redundancy.Examples:Bank of America  ->  wAR3laPfUVvB784_iH0cw7aQbKhr26sophlZ4z7iqtM
Bank of Amer Corp  ->  wAR3laPfUVvB784_iH0cw7aQbKhr26sophlZ4z7iqtM

AMAZON.COM  ->   EP88bx0VFDaIh-cOt86c8pOJ6lNkb_TWiKFpmMKXakY
Amazon Inc.  ->  EP88bx0VFDaIh-cOt86c8pOJ6lNkb_TWiKFpmMKXakY