Saravanan666/pypi-org huggingface dataset:
Package: hirmeos-clients
HIRMEOS ClientsPython clients for interacting with APIs that were developed as part of the
OPERAS Metrics services - originally developed during the HIRMEOS project.Release Notes:[0.1.8] - 2023-11-16Added:Updated testsChanged:AltmetricsClient.get_token function split between two methods, get_token
and set_tokenAdded token_has_expired optional parameter to AltmetricsClient.set_header()[0.1.7] - 2023-11-15Added:Updated testsadded an authenticated post request method to the Altmetrics client[0.1.6] - 2022-11-04Added:Update tests (minor)Changed:Update PyJWT requirement, as lower versions had security vulnerabilities.[0.1.5] - 2022-05-20Added:Add tag uri schemes to variables list.[0.1.4] - 2021-12-02Changed:Update processing canonical identifiers in the translator client logic to
allow multiple works to be returned whenuri_strict=Trueis used.[0.1.3] - 2021-10-20Changed:Update requirements to be more flexible[0.1.2] - 2021-10-15Added:Allow canonical URIs to be set when creating works in the translator serviceMain identifier will be registered as a canonical identifier when creating a
work[0.1.1] - 2021-10-15Added:Add method to delete URIs from a workAdd method to update/set the canonical flag for a URI[0.1.0] - 2021-02-02Added:Unit Tests for Translator ClientTranslator Client attributes:remove_uri_trailing_slash&use_lower_case_uris. These automatically format URIs for consistency.[0.0.20] - 2021-01-26Changed:TokenClient Bug Fix: Check encoded token type before attempting to decode.[0.0.19] - 2021-01-26Changed:TokenClient Code Change: Separate token encode and decode steps (for
debugging).[0.0.18] - 2020-07-30Changed:TokenClient Bug Fix: Correctly update request header after refreshing token.[0.0.17] - 2020-07-29Changed:TokenClient: update request header after refreshing token, and before
retrying request.[0.0.16] - 2020-07-29Changed:TokenClient: When creating token, convert from bytes to a string.[0.0.15] - 2020-07-29Changed:TranslatorClient.work_exists: Report all content from the translation API
response when this method fails (investigation).[0.0.14] - 2020-07-29Changed:TranslatorClient.work_exists: Report ‘data’ content from the translation API
when this method fails (investigation).[0.0.13] - 2020-07-27AddedToken creation option: The TokenClient can now also be used to create a
token, based on the logic used by the Tokens API.[0.0.12] - 2020-05-20AddedNew client: AltmetricsClient[0.0.11] - 2020-04-15ChangedTranslatorClient.prepare_uri: Now returns the URI as a string in the format
expected by TranslatorClient.get_work_uris.[0.0.10] - 2020-04-15ChangedTranslatorClient.post_new_work: ‘uris’ parameter now assumes the same format
as the output from TranslatorClient.get_work_uris, which was causing errors.
(bug fix)[0.0.9] - 2020-04-06Addedtranslator: Reference variables for work types and URI schemes.translator: Check if a work exists.translator: Fetch all URIs associated with a work.translator: Post new work.[0.0.8] - 2020-03-06ChangedMake requirements for flexible to avoid conflicts with other packages.[0.0.7] - 2020-03-06AddedRelease notesChangedStrip trailing slash from TranslatorClient API base.
Package: hirmeos-crossref-citedby-driver
Library containing logic for the OPERAS crossref-citedby-driver.Allows users to fetch citations from the crossref cited-by API.Release Notes:[0.1.2] - 2023-08-29Changed:Process all citations - not just those for DOIs that match the the
DOI prefix associated with Crossref account.[0.1.1] - 2023-07-28Added:Attempt to fix breaking changes: Temporarily added fetch_citation_xml,
get_crossref_citations and get_citation_data functionsChanged:Bugfix| Timestamp format now uses “YYYY-MM-DD”, not “YYYYMMDD”[0.1.0] - 2023-07-28Changed:Functions are now run as methods, via the CrossrefCitedByClient classRemoved:breaking| All functions removed; replaced with CrossrefCitedByClient[0.0.5] - 2023-07-26Added:Better “best guess” for crossref DOI published dateDetermine the prime-doi for an aliasd DOIChanged:Switched project to using build and toml configuration[0.0.4] - 2023-06-09Added:UnittestsChanged:Setfeatureto “xml” rather than “lxml” when reading XML using BeautifulSoup[0.0.3] - 2022-03-24Changed:Update requirements[0.0.2] - 2022-03-24Changed:Update requirements
Package: hirmeos-google-books
Load csv reports from google books. There are two options:Option 1: Input the google credentials and download the report csv
requested within a date range, it will return a string holding the csv report
content.Option 2: Process a csv uploaded by the user with the option of checking
the expected headers.Note: If the option 1 is required it’s recommended to use the option 2
afterwards to convert the result (string representation of the csv report) to
a list of dict.TroubleshootingFirst of all if the scraping with Selenium is needed,
we have to create a google account only for the purpose of this driver.
Such account has to have a recovery email account to allow the Selenium
download the report freely.It is very important to check the output the first time the driver is run as it
is very likely that Google will block the ‘suspicious’ login attempt. If it
does, you will need to login with the same credentials you have provided the
driver with and review the security settings, Google will ask if you
were prevented from logging in and you must confirm so. Afterwards
re-run the driver and it should work just fine.The alternative to the scraping is uploading the report manually to bypass
the scraping functionality as it could be unreliable because of the frontend
and/or backend changes from google.Release Notes:[0.0.7] - 2024-02-27ChangedCorrections bug account[0.0.6] - 2024-02-27ChangedSmall rename from gb_account to account[0.0.5] - 2024-01-12ChangedSmall correction of the driver interacting with google books[0.0.4] - 2023-10-09AddedAllowed support for chrome and chromium browsersAllow a user to specify browser and user agentChangedAdded driver options to improve report fetching reliability[0.0.1] - 2023-09-22AddedLogic to initialise the webdriverLog in to GoogleFetch a Google Play Books report
Package: hirmeos-irus-uk-driver
Provide functionality to collect and normalise report data from IRUS-UK.Refer tohttps://irus.jisc.ac.uk/r5/oapen/embed/api/#irus_irfor config options.Release Notes:[0.0.2] - 2023-10-19AddedPydantic serializers/models to handle IRUS-UK response dataProvided functionality to return serialized data without explicitly
using the Irus Client.ChangedChanged required options for fetching data[0.0.1] - 2023-09-22AddedLogic to initialise the webdriverLog in to GoogleFetch a Google Play Books report
Package: hirmeos-matomo-driver
This driver allows programmatic retrieval and normalisation of Matomo usage
data, obtained via the Matomo API.The driver code covers the following scenarios:Number of visits to pages on the target website.Number of downloads from different pages on the target website.Number of events, by category, if these have been set up in matomo.Documentation about querying the matomo api can be found here:https://developer.matomo.org/api-reference/reporting-apiRelease Notes:[0.0.2] - 2013-11-03Added:Serializers were added to ingest the response JSON.Specific requests methods to support the functionality provided by
theActions.getPageUrls,Actions.getDownloadsandEvents.getNameFromCategoryIdmethods.Optional Regex processing, to filter URL results by expected patterns.Changed:Response returns serialized data rather than raw JSON response.[0.0.1] - 2013-10-09Added:Make a request to the matomo API, and return the JSON response.
Package: hirmeos-unglue-it-driver
Driver to retrieve metrics from the Unglue.it portal.Refer tohttps://unglue.it/api/helpto get the api key from.Code for the HIRMEOS project is available athttps://github.com/hirmeos/unglueit_driver.For more information about the OPERAS metrics, go tohttps://metrics.operas-eu.org/TroubleshootingAt the moment of testing the plugin, despite doing 3 get requests to the API to get
the needed dataset it wasn’t slow enough to be a concern but an improvement to the
API would be great making less calls and a filter by date would be a preference.Another improvement straight away related to the package would be adding the rest of
identifiers from the dataset returned (‘goog’ and ‘oclc’) if they are needed in the future.Release Notes:[0.0.1] - 2023-10-27AddedLogic to initialise the Unglue.it driver
Package: hirsh
Hirsh📟 Resilient monitoring system that detects utility outages in unreliable environments (e.g. IoT, RaspberryPi, etc).Hirsh is designed and optimized for:💪 residency, robustness and self-healing📟 running in resource-constrained IoT-like unstable environmentsMaturityThe project is in early MVP state.It's being actively tested using my RaspberryPi Zero 2W under the current unstable Ukrainian infrastructure conditions.SetupsHirsh can be executed in any IoT device or board computer that supports Linux-like OS and Python 3.9+.[Only Supported] Basic: The basic setup includes just the device.
The device is plugged into the main electricity circuit/outlet along with a router that provides network connection for the device.UPS: TBUMonitorsIn theory, you can track any utilities your home has (e.g. electricity, network, gas, water, etc.).
However, in practice it's the easiest to track:network connection [Only Supported]electricity supplyHow does it work?TBUNotificationsTelegramThe primary way to notify you about outages is viaTelegram bot.
You need to createa new botand add it to a group or a channel.ReferencesSimilar Projectshttps://github.com/fabytm/Outage-Detectorhttps://github.com/nestukh/rpi-powerfailhttps://www.kc4rcr.com/power-outage-notification/https://homediyelectronics.com/projects/raspberrypi/poweroffdelay/powerfailhttps://projects-raspberry.com/power-outage-sensor/https://raspberrypi.stackexchange.com/questions/13538/raspberry-pi-to-email-when-power-outage-occursPython + RPihttps://medium.com/geekculture/gpio-programming-on-the-raspberry-pi-python-libraries-e12af7e0a812AsyncIO and RPihttps://github.com/PierreRust/apigpiohttps://beenje.github.io/blog/posts/experimenting-with-asyncio-on-a-raspberry-pi/https://www.digikey.bg/en/maker/projects/getting-started-with-asyncio-in-micropython-raspberry-pi-pico/110b4243a2f544b6af60411a85f0437chttps://docs.micropython.org/en/latest/library/uasyncio.htmlDeploymenthttps://github.com/beenje/legomac
Package: hisa
HisaHisa : Python module that translates a number 
    into Malagasy🇲🇬 lettersAuthor : rivo2302 | www.rivo.iteam-s.mgDependencies:Python 2.7+InstallationpipinstallhisaUsagefromhisaimportHisaletters=Hisa(155)print(letters)Responsedimyambydimampoloambyzato
Package: hisak-idtools
Python Identifier Generator ToolsIdentifier generator tools often used privately in Python.Includes the following features:base32support alphabet RFC4648, base32hex, crockford, zbase32base58support alphabet bitcoin, ripple, flickrbase58check encodingxidpython implementation of xiduuid58convert uuid to base58, base58 to uuidconvert uuid to base58check, base58check to uuidInstallInstall and update using pip:pipinstall-Uhisak-idtoolsXid Examplefromhisak.idtools.xidimportnew_xidprint(new_xid())UUID58 Examplefromhisak.idtools.uuid58importuuid4print(uuid4().base58)LinksI used the following code as reference:https://github.com/rs/xidhttps://github.com/graham/python_xidhttps://github.com/keis/base58
Package: hiscanner
HiScanner (High-resolutionSingle cell Allelic copy Number callER)HiScanner is a lightweight python package for high-resolution single-cell copy number analysis.ContentInstallationRequirementsQuick StartOperating SystemDocumentationContributingSupportLICENSEInstallationIt is recommended to install HiScanner in a virtual environment. Here's how to create one using conda:condacreate-nhiscanner_envpython=3.8To install HiScanner, simply use pip:pipinstallhiscannerRequirementsHiScanner requiresbcftools, which must be included inPATH. All other dependencies should be installed automatically with pip.Quick StartTo get started with HiScanner, please refer to ourtutorial. Here's a quick example:importhiscanner# define your json file pathpath="your/dir/to/json"# preprocesshiscanner.pp.preprocess(path)# segmenthiscanner.tl.segment(path)# infer copy numberhiscanner.tl.infer_copy_number(path)# visualizehiscanner.pl.plot_whole_genome_track(path)Command line interfaceFor advanced users interested in multi-sample segmentation (e.g., repurposing for bulk samples), HiScanner provides a command line interface. In bash, simply run:hiscanner-segment-i{input_file}-l{LAMBDA}-o{output_file}For more details, please refer to ourdocumentation.Operating SystemHiScanner was tested in the following operating systems:macOS Ventura 13.5.2CentOS Linux 7.9Windows 11DocumentationFor more detailed information and advanced usage, please refer to ourdocumentation.SupportHiScanner is currently under active development. For support or questions, please open an issue on ourGitHub repository.ContributingContributions to HiScanner are welcome. Please refer to ourcontribution guidelinesfor more information.LICENSEHiScanner is released under the MIT License, and is freely available for non-commercial use.
Package: hiscovid
hiscovidhiscovid is a PyPI tool that calculates time transition scores for individual policies against COVID-19.The goal of hiscovid is for policymakers to understand fatal mistakes by their decisions.
Policymakers must learn their mistakes for possible corrections in the future.The time transition score is calculated by dividing the number of deaths in the time series
due to COVID-19 by the population in millions.Scores monotonically increase so that policymakers can only suppress them, but cannot improve them.
Mistakes by policymakers cannot be corrected and are fatal forever.The lower the score, the better the policy.In other words, the score is equivalent to the accumulation of mistakes made by policymakers.The perfect policy outcome means there are no covid-19 deaths. There is no perfect policy in the world, but
mistakes by policymakers can be corrected.hiscovid scrapes the latest data from the following site over the Internet:https://covid.ourworldindata.org/data/owid-covid-data.csvHow to install hiscovid$ pip install hiscovidHow to run hiscovid$ hiscovid Japan 'South Korea'$ hiscovid Taiwan 'New Zealand'$ hiscovid Taiwan 'United States' 'United Kingdom'
Package: hiscovid-v2
hiscovid_v2hiscovid_v2の目的は政策提案者の失敗を特定することです。hiscovid_v2はcovid-19による各国の死者数の総計をその国の人口で割ったスコアを時系列でグラフにし、そのスコアのグラフの傾きを示したものです。そのスコアのグラフは連続値で単調増加関数です。そのため、急激にグラフが増加しているところで政策提案者が間違いを犯していることとなります。したがって、このグラフの微分(傾き)を取れば、政策提案者の間違いをより明確に表すことができると考えました。グラフの値が高いところほど、政策提案者はより深刻な間違いを犯していると考えることができます。hiscovid_v2 は、インターネットを介して次のサイトから最新のデータをスクレイピングします。https://covid.ourworldindata.org/data/owid-covid-data.csvhiscovid_v2のインストール方法$pip install hiscovid_v2hiscovid_v2の実行方法h iscovid_v2 <国名>$ hiscovid_v2 Japan "South Korea"$ hiscovid_v2 Japan Taiwan$ hiscovid_v2 Taiwan 'United States' 'United Kingdom'
Package: hisel
HISELFeature selection tool based on Hilbert-Schmidt Independence CriterionFeature selection is
the machine learning
task
of selecting from a data set
the features
that are relevant
for the prediction of a given target.
Thehiselpackage
provides feature selection methods
based on
Hilbert-Schmidt Independence Criterion.
In particular,
it provides an implementation of the HSIC Lasso algorithm ofYamada, M. et al. (2012).Why ishiselcool?hiselis accurateHSIC Lasso is an excellent algorihtm for feature selection.
This makeshiselan accurate tool in your machine learning modelling.
Moreover,hiselimplements clever routines
that address common causes of poor accuracy in other feature selection methods.Examples of wherehiseloutperforms the methods insklearn.feature_selectionare given in the notebooksensemble-example.ipynbandnonlinear-transform.ipynb.hiselis fastA crucial step in the HSIC Lasso algorithm
is the computation of
certain Gram matrices.hiselimplemets such computations
in a highly vectorised and performant way.
Moreover,hiselallows you to
accelerate these computations
using a GPU.
The image below shows
the average run time
of the computations
of Gram matrices
viahiselon CPU,
viahiselon GPU,
and
viapyHSICLasso.
The performance has been measured
on the computation
of Gram matrices required
by HSIC Lasso
for the selection
from a dataset of 300 features
with as many samples as reported on the x-axis.hiselhas a friendly user interfaceGetting started withhiselis as straightforward as the following code snippet:>>> import pandas as pd
    >>> import hisel
    >>> df = pd.read_csv('mydata.csv')
    >>> xdf = df.iloc[:, :-1]
    >>> yser = df.iloc[:, -1]
    >>> hisel.feature_selection.select_features(xdf, yser)
    ['d2', 'd7', 'c3', 'c10', 'c12', 'c24', 'c22', 'c21', 'c5']If you are not interested in more details,
please read no further.
If you would like to
explore more about
how to tune the hyper-parameters used byhiselor
how to have more advanced control onhisel's selection,
please browse the examples inexamples/and innotebooks.InstallationInstall viapipThe packagehiselis available fromarti. You can install it viapip.
While on the Wise-VPN, in the environment where you intende to suehisel, just dopip install hisel --index-url=https://arti.tw.ee/artifactory/api/pypi/pypi-virtual/simpleInstall from sourceBasic installation:Checkout the repo and navigate to the root directory. Then,poetry installInstallation with GPU supportYou need to have cuda-toolkit installed and you need to know its version.
To know that, you can donvidia-smiand read the cuda version from the top right corner of the table that is printed out.
Once you know your version ofcuda, dopoetry install -E cudaXXXwherecudaXXXis one of the following:cuda102if you have version 10.2;cuda110if you have version 11.0;cuda111if you have version 11.1;cuda11xif you have version 11.2 - 11.8;cuda12xif you have version 12.x.
This aligns to theinstallation guide of CuPy.
Package: hisensetv
A work-in-progress python API for Hisense televisions based off ofmqtt-hisensetv.InstallationLinuxsudo-Hpython3.8-mpipinstallhisensetvWindowspy-3.8-mpipinstallhisensetvCLI Usageusage: hisensetv [-h] [--authorize] [--get {sources,volume}]
                 [--key {back,down,exit,left,menu,power,right,up}] [--no-ssl] [-v]
                 hostname

Hisense TV control.

positional arguments:
  hostname              Hostname or IP for the TV.

optional arguments:
  -h, --help            show this help message and exit
  --authorize           Authorize this API to access the TV.
  --get {sources,volume}
                        Gets a value from the TV.
  --key {back,down,exit,left,menu,power,right,up}
                        Sends a keypress to the TV.
  --no-ssl              Do not connect with SSL (required for some models).
  -v, --verbose         Logging verbosity.One Time SetupNote:This is not required for all models!hisensetv 10.0.0.128 --authorize
Please enter the 4-digit code: 7815Keypresseshisensetv 10.0.0.28 --key up
[2020-02-29 13:48:52,064] [INFO    ] sending keypress: upGetshisensetv 10.0.0.28 --get volume
[2020-02-29 13:49:00,800] [INFO    ] volume: {
    "volume_type": 0,
    "volume_value": 1
}No SSLSome models do not have self-signed certificates and will fail to connect
without--no-ssl.Please open an issue if yours is not listed here!H43A6250UKLimitationsConcurrencyMultiple instances of this class will conflict with one-another.Not thread-safe.This API reallyshouldbe asyncio in 2020, but asyncio is not yet part of the paho mqtt library (see455).ReliabilityThe concurrency issues contribute to reliability issues in general.Unit tests do not exist yet.SecurityThe self-signed certificates from the TV are completely bypassed.
Package: hishiryo
hishiryoConsciousness beyond thought ^_^Hishiryo is a tool to generate a circular dataviz of any csv dataset.This little experiment aims at trying to quickly represent the content of a dataset and make it funny to discover it's patterns!Each datapoint (like a cell in an excel sheet) is converted into a pixel , and this pixel is diplayed on a circular graph.This version supports the following column data formats : float, integers and text as nominal categories.How to installWith PyPI (Make sure your pip is up to date as it can interfere with CV2 package install)pip install hishiryoDependenciesPandasCV2 (OpenCV)PillowsvgwriteHow to use radial rendering1 - find an appropriate csv. (more than 100 rows will start to overload the result a little)2 - From your code or from a Jupyter notebook :from hishiryo import Hishiryo

HishiryoConverter = Hishiryo.Hishiryo()

input_path = "/home/user/iris.csv"
separator = ','
output_path = "/home/user/iris.png"
radius = 500

HishiryoConverter.convertCSVToRadialBitmap(input_path,separator,output_path,radius,None,"Dot")Arguments :input pathis the path to your csv file (e.g. /home/user/iris.csv)output pathis the path to your target image file (e.g. /home/user/iris.png) The fileformat you want is autodetected thanks to CV2 functionalities.separatoris the character separator in your csv (e.g. ",")radius(in pixel) is the size of the radius of the disk where the pixels will be drawn. The higher it is the bigger and sharper your output image will be. (e.g:  1500)'sort_byis the name of the column or the list of column you want to sort you data. (e.g. "Sepal.Length", or ["Sepal.Length","Sepal.Width"])glyph_typeis the type of representation you want for the pixels. it can be one among the following : "Dot","Square" or "Polygon"input_path = "path/to/your/csv/file.csv"
  output_path = "path/to/your/rendered/image.png"
  separator = ","
  radius = 3000
  sort_by = None
  glyph_type = "Polygon"Colors are assigned based on the variable type.Blue circles represent integer valuesRed circles, float valuesRandom colors are assigned to categorical variables.Black is the default value for value 0 or when there is no dataRadial bitmap rendering examplesSee below an example of a visualisation generated from the train titanic datasetThe 12 columns of the dataset are represented as 12 circular rows. The first column is rendered as the inner circle, and the last as the outer one.Here is an overview of the MNIST train dataset, sort by labelHow to use simple bitmap renderingAnother way is to render your csv as a simple bitmap, without radial representation.from hishiryo import Hishiryo

HishiryoConverter = Hishiryo.Hishiryo()

input_path = "/home/user/iris.csv"
separator = ','
output_path = "/home/user/iris.png"

HishiryoConverter.convertCSVToBitmap(input_path,
                                     output_path,
                                     separator,
                                     )simple bitmap rendering exampleHere is an extract of the MNIST test dataset ()LicenceGNU General Public License v3.0