Saravanan666/pypi-org huggingface dataset:
Package: cover-rage-server
Server forCover Rage.Handle checks of test coverage for the last commit / pull request initiated by web-hook on Github / Bitbucket and you CI-server.Keeps your overall coverage percentage for badge.All settings should be defined in environment variables. Available settings are:RAGE_SRV_REDIS_HOST- Redis hostRAGE_SRV_REDIS_PORT- Redis portRAGE_SRV_REDIS_DB- Redis databaseRAGE_SRV_SCHEME- http or httpsRAGE_SRV_HOST- domain name of your Cover Rage serverRAGE_SRV_MIN_GOOD_COVERAGE_PERCENTAGE- min good coverage percentage for badgeTo add a project you should runrun_cliconsole script:./rage_cli.py gh|bb <account> <repo> <access token>where:ghis Github,bbis Bitbucket,accountis your account name on Github / Bitbucketrepois your repo name on Github / Bitbucketaccess tokenis an API access token from Github / BitbucketThis command will create a web-hook on Github / Bitbucket and generate you public and private Cover Rage tokens. Use them when you’ll configuring your CI-server.To run server inside Docker container you can use this command:docker-compose –file docker-compose.yml –project-name cover_rage_server up
Package: covert-ots
covertA secure way to communicate your secretsFind the CLI (wip)hereFind the websitehereBackend Deployed on Google Cloud App EngineWorkingWhen a user saves a secret it is encrypted on the client side using a pass phrase encryption algo.A unique key (url in case of web clients) is generated for every stored secret.A user can then share this key (or url) to someone else, who can then retrieve the secret using the correct pass phraseThe encrypted token is then fetched and decrypted using the pass phrase on the client and displayed to the user (only once)CLI Docscommandscovert new - save a new secretcovert get - get a saved secret
Package: covertree
Cover TreeThis is a Python implementation of cover trees, a data structure for finding
nearest neighbors in a general metric space (e.g., a 3D box with periodic
boundary conditions).Updated for Python 3.7 fromPatrick Varilly's code.The implementation here owes a great deal toPyCoverTree,
by Thomas Kollar, Nil Geisweiller, Emanuele Olivetti.The API follows that of Anne M. Archibald's KD-tree implementation for scipy;
the default metric has been set to euclidean distance, so theCoverTreeclass
can be used exactly as a drop in replacement forscipy.spatial.KDTree.ReferencesCover trees are described in two papers, for which PDF copies are included
in thereferencesdirectory:A. Beygelzimer, S. Kakade, & J. Langford (2006) Cover Trees for Nearest Neighbor,
23rd International Conference on Machine LearningD. R. Karger & M. Ruhl (2002) Finding Nearest Neighbors in Growth-restricted Metrics,
34th Symposium on the Theory of Computing.(both originate fromthispage)
Package: covest
Tool that estimates coverage (and genome size) of dna sequence from
reads.Requirementspython 3.4+python3-devgccInstallationWe suggest to installCovEstin python3 virtual environment.pip install covestFor development:pip install-e.from the project directoryUsagetypecovest--helpfor the usage.Basic Usage:covest histogram-mmodel-kK-rread_lengthYou can specify the read file using-sreads.faparameter for more precise genome size computation.defaultKis 21defaultread lengthis 100currently, the supported models are:basic: for simple genomes without repeatsrepeat: for genomes with repetitive sequencesInput Histogram Specification:The input histogram can be generated from the read data usingjellyfish.jellyfish count-mK-Creads.fa-otable.jfjellyfish histo table.jf-oreads.histThe format of the histogram is just list of lines. Each lines contains an index and value separated by space.Output Specification:CovEst outputs it’s results in simple subset of YAML format for best human readability and possibility of machine processing.The output are lines containingkey: value. The most important keys arecoverageandgenome_size(orgenome_size_readsif reads size was specified).Other included toolsgeset.pytool for estimation genome size from reads size and known
coveragereads_size.pytool for computation of the total reads sizekmer_hist.pycustom khmer histogram computation, it is much slower than other tools, so use it only if you have no other option.read_sampler.pyscript for subsampling reads, useful if you have very high coverage data and want to make it smaller.fasta_length.pyget total length of all sequences in fasta file.Copyright and citationCovEst is licenced underGNU GPLv3license.CovEst is research software, so you should cite us when you use it in scientific publications!Hozza, M., Vinař, T., & Brejová, B. (2015, September). How Big is that Genome? Estimating Genome Size and Coverage from k-mer Abundance Spectra. In String Processing and Information Retrieval (pp. 199-209). Springer International Publishing.
Package: cov-estimator
cov-estimatorSimple estimator module for serializationThis is a simple library to build adapters to construct complex
estimators using sklearn models as well as keras.Basic architecture:from cov_estimator.nodes import Estimator
    from cov_estimator import Pipeline

    img = "path/to/img"

    img = load_img(img, (180, 180))

    img = np.expand_dims(img, axis=0)

    est = Estimator(
        (
            lambda data: {
                "pneumonia": data["pneumonia"],
                "covid": data["pneumonia"] * data["covid"],
                "normal": 1 - data["pneumonia"],
            }
        ),
        "mult_1",
    )

    covid = tf.keras.models.load_model("path/to/model_1")
    covid_est = Estimator(covid, "covid")

    pneumonia = tf.keras.models.load_model("path/to/model_2")
    pneumonia_est = Estimator(pneumonia, "pneumonia")

    est = est(pneumonia_est, covid_est)
    data = {"covid": img, "pneumonia": img}
    model = Pipeline(data, 'Path/to/save')
    result = model(result)

    print("result: {}".format(result)Whats happening?Basically what the library does is create an abstract tree of dependecies which evaluate each node.
For it to properly work, you need to pass a dictionary containing as key each nodes which expects some input.
You can use, lambda funcions to apply some important transformation. it will always get a single dictionary as input,
the dictionary will contain the outputs from each correspondant node.Obs!Each node inside in the graph must have a unique name, it's the developer's responsibility toStack:Python 3.8Virtualenvtensorflow > 2.0numpy > 1.6sklearn
Package: covey-sdk
Getting StartedC++ Build Tools (in case not already on your machine - frequently seen with Windows Users)download hereCreate a project foldermkdir coveyUsing the terminal of your choice, create a virtual python environment withincovey.python3 -m venv envActivate the virtual environment.windowssource env/Scripts/Activatemacsource env/bin/activateOnce the environment is activated (the terminal should have the environment name pop up in front of the user name as(env)), proceed to install the covey-sdk.pip install covey-sdkCreate a new file called test.py or whichever name you would prefer and run the following codeimport covey.covey_trade as ctt = ct.Trade(address = <public wallet key>, address_private = <private_wallet_key>, posting_only = True)t.post_trades_polygon('FB:0.25,ETHUSDT:0.15,AMZN:0.0')Note the post trades string needs to be one string with the format:<target_percent>,:<target_percent>,...If successful, the terminal should write back that your trades have been posted.Please let us know if you have any questions or run into issues, happy coding!FAQstarget_percent is the new percent you want the size to be. If you had a prior target_percent of 0.01 (1%), then you added a new target_percent of 0.03 (3%) that would buy you an additional (0.02) 2%. So the end position is 0.03 (3%)To close a position you need to run target_percent = 0.0
Package: covfee
covfee: continuos video feedback tool.Covfee was created to provide an easily extensible tool for video perception and annotation experiments, especially those requiring continuous feedback from the user.Full documentation:covfee docsQuick startThis document contains instructions for installing covfee locally. We recommend that you work with covfee locally first even if you plan to put it online.SetupInstall version 12.x ofnode.js. Make sure that thenpmcommand is available in your terminal.Clone this repository and install covfee using pip:git clone git@github.com:josedvq/covfee.git
cd covfee
python3 -m pip install -e .Install Javascript dependencies:covfee-installjsGetting startedPlease see thecovfee docsfor an interactive getting started guide.Changing covfeeIf you wish to change the source code of the backend or make changes to the frontend that are not supported by a custom task, see theDevelopment guide.
Package: covgen
Search Based Test Input GenerationA Python implementation of automated test data generation.Currently, it works only for the subset of Python functions satisfying these conditions:takes only integer argumentshad only integer type local variablescontains predicates that only involve relational operators (==, !=, <, >, <=, >=), integer variables, and calls to functions with integer return typeRun from SourceIf directly clone the source and run package, run below command on project root directory.python -m covgen <file>Additional options can be given (you can remain it as default value):--function (-f) <target_function_name> 

--method (-m) <avm or hillclimbing> 

--retry-count (-r) <retry count> 

--int-min <minimum value of initial arguments for heuristic methods> 

--int-max <maximum value of initial arguments for heuristic methods>For example:python -m covgen target/triangle.py -m avm --retry-count 10 --int-min 0 --int-max 1000prints out list of generated inputs that cover detected branches,
from each function defined in the target file.Using pipThis input generator package is available on PyPI of namecovgen.After installing the dependencies:pip install anytree
pip install astorYou can install this package with below command:pip install covgenThen run it anywhere with your python.python -m covgen <target file location>Or, you can build your own program using generated inputs.fromcovgen.run.inputgeneratorimportInputGeneratorgenerator=InputGenerator('target/triangle.py',function_name='triangle')inputs=generator.generate_all_inputs()print(inputs['triangle'])
Package: covid-19
COVID-19 APIcoronavirus-api.netThis API is a wrapper around Johns Hopkins'https://github.com/CSSEGISandData/COVID-19dataset.Please abide by their terms of use with respect to how you use their data via this API.InstallationThis package is hosted onpypiThe recommended method of installation is throughpipx.pipxinstallcovid-19However, covid-19 can also be pip-installed as normal.pipinstallcovid-19WebsiteThecoronavirus api websiteallows several methods of slicing and dicing the data.For example, theget_allendpoint (which returns all data) can be filtered for rows which only contain
data for California and Colorado as of March 22nd in this way:https://coronavirus-api.net/get_all?min_date=2020-03-22&states=["California", "Colorada"]Themain pagewill list the available endpoints and their available parameters.CLI UsageThis package installs a command-line tool,covidIt lets you programmatically access John Hopkins' dataset via terminal commands
or via a rest api that can itself be instantiated locally from the clicovid--help

ThisAPIisawrapperaroundJohnsHopkins'https://github.com/CSSEGISandData/COVID-19dataset.

PleaseabidebytheirtermsofusewithrespecttohowyouusetheirdataviathisAPI.


AvailableCommands:-get_all:FetchalldatafromJohnHopkins.-countries:Returnallcountriesandregionsinthedataset.-states:Returnallstatesandprovincesinthedataset.-for_date:Returnalldataforaspecificdate.-serve:ServeRESTAPIlocally.i.e.covidfor_date2020-03-21[{"Province/State":"Hubei","Country/Region":"China","Last Update":"2020-03-22T09:43:06","Confirmed":67800.0,"Deaths":3144.0,"Recovered":59433.0,"Latitude":30.9756,"Longitude":112.2707
...DockerThis package can also be run as adocker image.dockerrunknowsuchagency/covid-19--help
Package: covid19-api
Covid-19 Tracker API :microbe:Provides up-to-date data about Coronavirus outbreak. Includes numbers about confirmed cases, deaths and recovered.Available data-sources:Currently only 2 data-sources is available to retrieve the data:Epidemic Stats-All statistics data about coronavirus COVID-19 comes from World Health Organization and Johns Hopkins CSSE. Charts includes number of infected, deaths and recovered.Virusncov-All statistics data about coronavirus COVID-19 comes from World Health OrganizationHow it worksThe module emulates the browser actions by sending requests to the site server. The module doesn't load any type of files while sending requests to the site and that makes it faster. The module is scraping the website source code, and returning the final result.FeaturesProvides Fast, and Up-to-Date data about the Coronavirus outbreakA lot of supported countries (up to 100)Installationpip3 install covid19-apiWhen there's new release, you need to update the packagepip3 install covid19-api==1.0 --upgradeSimple Usage# All results is right to today (1/22/2021)# list of supported countries can be printed out | print(instance.countries)importcoroapiinstance=coroapi.Corona()global_stats=instance.global_stats(text=False)print(global_stats)<<['98135997','2101562','70548362','usa']If there's any problem:Email -roeil4939@gmail.comPost issue post on theIssues tab
Package: covid19-big
Covid19-Big PackageA helper pip package for Covid19-BigAssumptions:Assuming python is installed on your system.Installation sets up commandSituation before installation::$ covid19_big
bash: covid19_big: command not foundInstallation right from the source tree (or via pip from PyPI)::$ python setup.py install

$ pip install covid19-bigNow, thecovid19_bigcommand is available::$ covid19_big
Welcome to Covid19 BIG!
serving at port:  1305
serving from directory:  web
open: http://localhost:1305
close your browser and use control-C to stop this server
Package: covid19-cases
Covid19 Cases Tracking For Every Country in Real TimeaboutA small package of Python to access and track the number of cases of confirmed and deaths and  recovered people
from the Coronavirus for any countryInstallationpip install covid19-cases
or in colab google cloud
!pip install covid19-casesUsagefrom covid19_cases import corona19
country_name='any_country' #name of country# to get confirmed count for country in real time
confirmed_count=corona19.confirmed_people(country_name)
#to get deaths count for country in real time 
deaths_count=corona19.deaths_people(country_name)
#to get recoverd count in real time 
recoverd_count=corona19.recoverd_people(country_name)CheckingTo verify the retrieved data within this library
go to worldmeters web site for checking for any coutryhttps://www.worldometers.info/coronavirus
Package: covid19-certificate-pos
This software lets you print your own required Covid 19 certificate to go out on a Point Of Sale printer, that is a little Epson (or compatible) printer used in many stores or other point of sales to print customer receipts.![Epson TM-T20](https://www.epson.fr/files/assets/converted/550m-550m/t/m/t/t/tmtt20ii_left_02.jpg.jpg)All printers supported by the [python-escpos](https://github.com/python-escpos/python-escpos) project are supported.To choose more than one motives, just ctrl + click.
Package: covid19-counter-pkg-richwellum
covid19_counterSimple tool to display information about COVID19 and store and tweet out the
details.Runs on a loop checking the number of Confirmed, Recovered and Deaths and also
the percentage died.All data is pulled from:https://github.com/CSSEGISandData/COVID-19User can specify the interval to check, the type of display (for small
displays), and display the record of any changes. In addition there's a test
option which allows you to enter your own data files, or make modifications.Data on Deaths, Confirmed cases, Recoveries and Percentage Died are calculated
by pulling the CSV files down, and creating pandas df's, summing the data up
ofthe last known column, which is also the latest.Option to Tweet the results - obviously requires a Twitter developer license
and creds populated in an auth.py file.This is currently active:https://twitter.com/alert_covid19In a seperate terminal the user can see a running history of changes:covid19_counter-rTo install on a Mac directly from github clone:Needed: python3 and the packages (pip3 install): pandas, colorama, termcolor,
requests twython:brewinstallpython3#(or sudo apt install python3 etc)pip3installpandascoloramatermcolorrequeststwythonOr install from pypi:pip3installcovid19-counter-pkg-richwellum==<version>covid19_counterExample running:RWELLUM-M-C5JH:covid19rwellum$covid19_counter-i400-husage:covid19.py[-h][-iINTERVAL][-r][-s][-f][-v][-t]GrabandprocessthelatestCOVID-19dataoptionalarguments:-h,--helpshowthishelpmessageandexit-iINTERVAL,--intervalINTERVALintervalinsecondsbetweenretrievingthedataagain,defaultonehour(3600s)-r,--recordviewarecordofallchanges-s,--splitsplitthedisplaytofitsmallerterminals-f,--forcebypasssafetyrails-verydangerous-v,--verboseturnonverbosemessages,commandsandoutputs-t,--testrunwithatestfileE.g.:./covid19.py-i600-s
Package: covid19-counter-richwellum
covid19Simple but somewhat morbid tool to display information about COVID19.Runs on a loop checking the number of Confirmed, Recovered and Deaths and also
the percentage died.All data is pulled from:https://github.com/CSSEGISandData/COVID-19User can specify the interval to check, the type of display (for small
displays), and display the record of any changes. In addition there's a test
option which allows you to enter your own data files, or make modifications.Data on Deaths, Confirmed cases, Recoveries and Percentage Died are calculated
by pulling the CSV files down, and creating pandas df's, summing the data up
ofthe last known column, which is also the latest.To install on a Mac:cdcovid19# cd to the directorybrewinstallpipenvpipenvinstall# Seems temperamental - so use manual steps below if neededOtherwise you need python3 and the packages (pip3 install): pandas, colorama,
termcolor, requests:brewinstallpython3#(or sudo apt install python3 etc)pip3installpandascoloramatermcolorrequestsExample running:RWELLUM-M-C5JH:covid19rwellum$./covid19.py-i400-husage:covid19.py[-h][-iINTERVAL][-r][-s][-f][-v][-t]GrabandprocessthelatestCOVID-19dataoptionalarguments:-h,--helpshowthishelpmessageandexit-iINTERVAL,--intervalINTERVALintervalinsecondsbetweenretrievingthedataagain,defaultonehour(3600s)-r,--recordviewarecordofallchanges-s,--splitsplitthedisplaytofitsmallerterminals-f,--forcebypasssafetyrails-verydangerous-v,--verboseturnonverbosemessages,commandsandoutputs-t,--testrunwithatestfileE.g.:./covid19.py-i600-s
Package: covid19czechia
Web Scraper of COVID-19 data for CzechiaPython packagecovid19czechiaprovides access to COVID-19 data of Czechia.The data is scraped fromMinistry of Health, Czech RepublicCzech Statistical OfficeSetup and usageInstall frompipwithpipinstallcovid19czechiaImporting module is done such asimportcovid19czechiaasCZx=CZ.covid_deaths()Package is regularly updated. Update withpipinstall--upgradecovid19czechiaCOVID-19 CasesGet Covid-19 cases in Czechia.x=CZ.covid_confirmed_cases()Aggregated dataframe countrywise / regionwise / districtwise can be fetched usingx1=CZ.covid_confirmed(level=1)# countryx2=CZ.covid_confirmed(level=2)# regionx3=CZ.covid_confirmed(level=3)# districtThe data contains counts by age, age group and sex and information of week. To aggregate results only over some of the groups (example - per day)x=x\.groupby(['date','week'])\.aggregate({'confirmed':'sum'})\.reset_index()Result of the example contains columns day, week and confirmed.COVID-19 TestsGet Covid-19 tests in Czechia.x1=CZ.covid_tests(level=1)# countryx2=CZ.covid_tests(level=2)# regionx3=CZ.covid_tests(level=3)# districtCOVID-19 DeathsGet Covid-19 deaths in Czechia (weekly counts, by gender and age group)x=CZ.covid_deaths()The function returns Pandas dataframe. It can be stored to csv file withx.to_csv("filename.csv",header=True,index=False)Administrative unit settingOptional parameterlevelsets granularity of administrative units
the deaths are computed in.Defaultly (level = 1) the deaths are taken from the whole Czechia.x=CZ.covid_deaths(level=1)# same as no argument given (above)Settingslevel = 2corresponds with deaths in regions (kraje, NUTS 3).x=CZ.covid_deaths(level=2)Settinglevel = 3means deaths per district (okresy, LAU 1).x=CZ.covid_deaths(level=3)Read more about administrative units of Czech Republichere.Total weekly deathsFor total deaths check my another packageeurostat_deaths.
Package: covid-19-dashboard-pkg-jwh220
COVID-19 DashboardTable of ContentsIntroductionPrerequisitesInstalationGetting StartedTestingDeveloper DocumentationDetailsIntroduction:Creates a locally hosted webpage containing COVID-19 data and news:local last 7 days infection ratenational last 7 days infection ratenational current hospital casesnational total deaths (from COVID-19)PrerequisitesPython 3.10.0 64-bitPython sched modulePython time modulePython json modulePython logging modulePython flask modulePython markupsafe moduleuk_covid19 module (infomationhere)newsapi module (infomationhere)Instalationpip install xGetting StartedIn the file 'config.json', add yourAPI keywhere it says "news API key here"Run the packageThere will be no visual confirmation that it is running successfullyIn a web browser go tohttp://127.0.0.1:5000/Adding updateAdd the time of the update to the top input box (where it says '12:30')Add the name of the update to the second input box (where it says 'Update label')If you want the update to happen every 24-hour, check the 'Repeat update' box; if it is a one-off, leave it uncheckedDepending if you want to update the COVID-19 data or news, check the relevant boxes ('Update Covid data' or 'Update news articles')If neither box is checked, the update will not be setBoth boxes can be checked at once, creating an update for the data and news uder the same nameNew updates can't be set for the same time as scheduled updatesPress the 'Submit' button to create your new update (as the number of visible updates is limited to the next 5, you may not see the update appear instantly)Remove updateClick on the cross on the top right of an update to remove itIf you have a news and data update, like 'example combiation', there is no way to remove just the data or news updateRemove news articleClick on the cross on the top right of a news article to remove itTestingEnter a terminalNavigate to the folder conataining thisRunpytest(infomationhere)Developer Documentationconfig.jsonapi_key : stringadd your newsapi key herenews_search_terms : stringadd any search terms you want headlines for, separated by a space for multiple search termsdefault searches for covid-19 related newslocation : stringlocation_type : stringadd your chosen area heresee valid filtershereupdates : lista list of updates to add when start, formatted like an update (see below)update : dictionarya preset update to be added to the pagename : stringthe name of the updatetime : string in format "HH:MM" or floatthe time of day the update should occur ("HH:MM")ORthe amount of time (in seconds) from startup to the updatetype : stringthe type of update"data" for data update"news" for news update"both" for data and news updaterepeat : stringwhether the update should repeat every 24 hours"False" for single update"True" for repeating updateweb_title : stringthe title of the pagelanguage : stringthe language of articles that should be fetched (see valid optionshere)DetailsMade by Joshua HammondShared under MIT (seeLISENSE)Source code can be foundhere