Saravanan666/pypi-org huggingface dataset:
Package: individous-wrapper
Individous-WrapperLinksGit:https://edugit.org/pinguin/individous_wrapper/Matrix/Element:https://matrix.to/#/#individous-wrapper:matrix.teckids.orgPyPi:https://pypi.org/project/individous-wrapper/Deutsche VersionDas ist mein Individous-Wrapper.Was kann der Individous-Wrapper?Er kann Daten von YouTube über jegliche Invidious-Plattformen abrufen.
Dazu zählen aktuell allewichtigenDaten von Videos und Kanälen.
Bei Kanälen aber noch nicht:KommentareAlle Videos des KanalsPlaylistsWas ist geplant?Geplant sind folgende Features:Warum heißt der Wrapper falsch?Ich hatte den Name so in Erinnerung, also hab' ich ihn selbstverständlich auch so geschrieben.
Package: indoc
indocDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nindoc--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallindocnbdev# activate conda environment$condaactivateindoc# make sure the indoc package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the indoc package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'$nbdev_conda--mambabuild--build_args'-c conda-forge -c dsm-72'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/indoc.gitor fromconda$condainstall-cdsm-72indocor frompypi$pipinstallindocDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find
package manager specific guidelines oncondaandpypirespectively.indocdecoratordefine (base / mixin) class with a docstring we want to pass to a
subclass@dataclassclassMix:r'''A Mixin classAttributes----------a : stra stringi : int, optionalan intb : bool, optionala boolMethods-------is_b(self) -> boolchecks if b is True'''a:str_:KW_ONLYi:int=0b:bool=False@propertydefprop(self):returnself.a@abstractmethoddefis_b(self)->bool:returnself.bA subclass we want to haveMix’s docstringfoodoc='''A Foo classAttributes----------q : boolMethods-------is_q(self) -> boolchecks if q is True'''@indoc@dataclassclassFoo(Mix):__doc__=foodocq:booldefis_q(self)->bool:returnself.q
Package: indOCRArmy
Indo OCR ArmyThis is a package for OCR Identity card in Indonesia (KTP and SIM). This packages build on top of detectron2 so you should install detectron2 first and some requirements need to install separately before you run this packages, Note that we test it on a device withGPU/CUDAif there is an error please report an issue to our email. After install this package, please follow the tutorial bellow:# if use conda
conda install pytorch torchvision cudatoolkit=10.2 -c pytorch

# if use python
pip install torch==1.5.1
pip install torchvisionpython -m pip install detectron2 -f \ https://dl.fbaipublicfiles.com/detectron2/wheels/cu102/torch1.5/index.htmlfor comprehensive use, you can do this:import os
import cv2
import matplotlib.pyplot as plt

from IndoOCRArmy import defaultConfig, DrawOCR, numericalDetectron2, boundingBoxesDetectron2, alphabeticalDetectron2, easypredict

# load classes
cfg = defaultConfig()

for key in cfg.keys():
    if 'list_cuda' in cfg[key]:
        cfg[key]['list_cuda'] = [0]

drawer_ocr = DrawOCR(cfg['drawOCR'])
bBoxDet = boundingBoxesDetectron2(cfg['boundingBoxesDetectron2'])
numDet = numericalDetectron2(cfg['numericalDetectron2'])
alphaDet = alphabeticalDetectron2(cfg['alphabeticalDetectron2'])

# load image
image_ktp = cv2.imread("assets/ktp_example.jpg")
image_sim = cv2.imread("assets/sim_example.jpg")

# detect boundingboxes
crops, boxes, labels = bBoxDet.predict(image_ktp, input_type='ktp')

# detect number and alphabet
dict_ID = numDet.predict_ensemble(crops[0])
dict_Name = alphaDet.predict_ensemble(crops[1])

# choose `weighted_hardvote_word` for the best result according to our benchmark
ID =  dict_ID.get("weighted_hardvote_word")
Name =  dict_Name.get("weighted_hardvote_word")

# parse NIK to get information about : location, gender, and birthdate
parse_NIK = numDet.parse_nik(ID)

# create listdata and listlabel for visualization later
listdata = [ID, Name]
listlabel = [x for x in list(labels.values()) if x is not None]
for label, data in parse_NIK.items():
    listdata.append(data)
    listlabel.append(label)

print(ID)
print(Name)

drawer_ocr.show_list_images(list_img=crops.values())For visuzlize comprehensive result, use this:drawer_ocr.show_desc(image_ktp, boxes, labels, listdata, listlabel)For quick result, use this:image_ktp = cv2.imread("assets/ktp_example.jpg")
easypredict(image_ktp, bBoxDet, numDet, alphaDet, input_type='ktp')
Package: indodax
IndodaxPyPI version 1.3.1Modul ini untuk trading di indodaxInstallpipinstallindodaxCara PenggunaanMelihat Harga$python
Python3.8.5(default,Jul282020,12:59:40)[GCC9.3.0]onlinux
Type"help","copyright","credits"or"license"formoreinformation.
>>>fromindodaximportindodax
>>>indodax.get_price('btc')#contoh melihat harga BTC{'ticker':{'high':'186608000','low':'173463000','vol_btc':'277.39109788','vol_idr':'49592483275','last':'186306000','buy':'186305000','sell':'186306000','server_time':1603298398}}Melihat Info Saldopertama anda harus mengambil key dan secret di akun anda, jika sudah ada silahkan ikuti instruksi ini sebagai langkah awal:>>>key='YOUR_KEY'>>>secret=b'YOUR_SECRET'>>>a=indodax(key,secret)>>>a.get_info()# anggap saja ini adalah informasi saldo dan alamat qurenncy anda{"succses":'1',
...Melihat History>>>a.history()# Anggap saja history anda sudah ada...Melihat Order Baru/Di Tahanidr_or_btcadalah variable dimana anda membeli/menjual dengan BTC atau IDR pilihannya hanya 2 saja, tetapi default   adalah IDR. jika anda membeli/menjual dengan IDR makaidr_or_btcabaikan saja.>>>a.open_order('btc',idr_or_btc='idr')# Contoh saya membeli BTC, disini anda akn melihat order id anda...Melihat Riwayat Order>>>a.order_history('btc')# Anggap saja semua order terlihat...Trade Buy/SellPemanggilan fungsi trade, fungsi trade ada 2 yaitutrade_buy(coin, diharga, jumlah, idr_or_btc='idr')dantrade_sell(coin, diharga, jumlah, idr_or_btc='idr'). variablecoinadalah jenis qurency, variabledihargaadalah harga qurency-nya, variablejumlahadalah nilai pembelian/penjualan,idr_or_btc='idr'abaikan jika IDRBuy>>>a.trade_buy('btc','186306000','50000')# ini jika anda membeli dengan IDR...Sell>>>a.trade_sell('btc','190000000','0.005')# anggap saja saya menjual BTC di harga 190Juta...Instan Orderinstan_trade(coin, jumlah, type) digunakan untuk order secara instan.
cara penggunaaninstan_trade("trx", 10000, 'buy or sell')Cancel OrderDisini menggunakan 2 fungsi yaitucancel_order_buy(coin, order_id, idr_or_btc='idr')dancancel_order_sell(coin, order_id, idr_or_btc='idr').order_iddariopen_order(...).Buy>>>a.cancel_order_buy('btc','12345')# Kalau order id-nya benar, akan ada result succses = 1...Sell>>>a.cancel_order_sell('btc','12345')# Hampir sama dengan Buy, tapi tergantung type pembelian atau penjualan...Withdrawfungsi withdrawwithdraw(coin, address, amount, memo='', req_id=''). Fungsi ini membutuhkan urlcallback agar dapat bekerja dengan baik.>>>a.withdraw('doge','D7rzpq91xmUVkER6E1ndfinRjRS4jvBkgV','100')# memo hanya untuk address yg menggunakan memo...DonateJika anda suka dengan modul ini anda bisa donasi di bawah iniBTC    : 3BqqfUGaARBBCkMN6w6nV7hYjikvac3dJ4BCHABC : qzdt37fmnftrm8xr50vxza640f48sfnlyqlsfjpyzkDOGE   : D7rzpq91xmUVkER6E1ndfinRjRS4jvBkgVLTC    : M9nQQZXwHQaoNStJrBcr6UfdCqx2RJHz5e
Package: indonesia-earthquake
Latest Indonesia EarthquakeDo you need the latest earthquake from BMKG | Indonesia Meteorological, Climatological, and Geophysical AgencyGuidanceThis package will scrape the latest earthquake data fromBMKG.Install package fromhttps://pypi.org/project/indonesia-earthquake/Install module fromhttps://pypi.org/project/requests/Install module fromhttps://pypi.org/project/beautifulsoup4/Run your main.py with this codeimport last_earthquake

if __name__ == '__main__':
    result = last_earthquake.data_extraction()
    last_earthquake.show_data(result)AuthorArsenius Anom Permadi
Package: indonesian-fishproduction
indomarinefishThis package will give us information about the latest total marine fish production in Indonesia.
The Name of the fish is written in Indonesian. The total production is in Kg.How it work?This package will scrape fromPIPPto get the latest marine fish production in Indonesia.This package will use BeautifulSoup4 and Request, to produce output in the form of JSON.
This package is ready to be used in web or mobile applications.How to useimport produksiikan

if __name__ == '__main__':
    result = produksiikan.data_extraction()
    produksiikan.show_data(result)Authormizan toyyibun
Package: indonlp
indoNLPBahasa |EnglishindoNLP adalah library python sederhana tanpa dependency tambahan yang bertujuan untuk memudahkan proyek NLP anda.InstallasiindoNLP dapat diinstall dengan mudah dengan menggunakanpip:$pipinstallindoNLPQuick StartMengakses Indonesian NLP Open DatasetMengakses Indonesian NLP Open Dataset dengan cepat dan mudah.fromindoNLP.datasetimportDatasethandler=Dataset("twitter-puisi")data=handler.read()# out: Data(name='main', part_of='twitter-puisi')Mengecek kesimetrisan data, jika data bersifat simetrik maka data dapat ditabelisasi menggunakanpandas.DataFrame.importpandasaspdassertdata.is_table(),"Data tidak simetris, tidak dapat ditabulasi!"df=pd.DataFrame(data.data)df.head()# out:#                                                 text# 0  Hanya karena sapa itu.\nKau tikam rasamu.\nSis...# 1  Sedang di antrian panjang\nPada sebuah penanti...# 2  Jika kau bukan tempat awal untuk berlabuh, mak...# 3  Setiap waktu,\nAku masih mendengar getar dawai...# 4  Sebait rindu yang kau bacakan\nMasih terdengar...Preprocessing Data TeksMenerjemahkan emoji dan mengganti kata gaul (slang words).fromindoNLP.preprocessingimportemoji_to_words,replace_slang,pipelinepipe=pipeline([emoji_to_words,replace_slang])pipe("library yg membara 🔥")# out: "library yang membara !api!"DevelopmentSetup local dev environment.indoNLPmenggunakanpython-poetryuntuk packaging dan management dependencies.$makesetup-dev
Package: indoquake
indoquakeA Latest Earthquake Detection Package Taken Based on BMKG | Meteorological, Climatological, and Geophysical AgencyThis package was made using the beautifulsoup4 and request packagesThe data is also taken from theBMKGrequiretment packagebeautifulsoup4
requestsAuthorDanang FirmantoHow to usefromsrc.quakeimportekstrasi_data,tampilkan_dataif__name__=='__main__':print('Earthquake data from BMKG')result=ekstrasi_data()tampilkan_data(result)
Package: indsl
Industrial Data Science LibraryThis is Cognite's collection of data science algorithms and models. Its objective is twofold. First, empower domain
experts to conduct exploratory work, root cause analysis, and analyze data viaCognite Charts.
Second, curate a collection industry relevant data science algorithms to be used as a regular python package.
For more information, consult theCharts documentation page.DocumentationInDSL HomeData Science Developer GuidelinesGallery of Charts - ExamplesPublishing new versions of InDSLContributors ✨Thanks goes to these wonderful people (emoji key):Gustavo📖👀📢⚠️🔣🖋💻🤔Simon Funke💻⚠️🐛Neringa Altanaite💻👀⚠️📖Rhuan Barreto🔧🛡️👀🤔🚇Everton Colling💻🔣📖⚠️redzarosliCognite💻👀🤔📖💡💬📓Morten Grønbech💻💡📖👀💬🤔Cristina Ferrer💻💡🤔👀Håkon V. Treider💻👀🤔🚇Andris Piebalgs💻👀💡kbrattli💻📖🚧⚠️This project follows theall-contributorsspecification. Contributions of any kind welcome!
Package: ind-ticker
🔥 Indian Ticker👨‍💻 CLI Tool for getting data of Indian Stocks and Mutual Funds 📈InstallationMake sure that you are running Python 3.7 or laterpipinstalltermcolorind-tickerTo get Nifty-50 data:ind-tickernifty-50To get the stock data of a single company:ind-tickerstock<comapny_name_without_spaces>Example:ind-tickerstockRelianceTo get the stock data of multiple companies:ind-tickerstocks<comapny_name1_without_spaces><company_name2_without_spaces>Example:ind-tickerstocksBioconCiplaTo get the stock data of a company including the annual analysis:ind-tickerstock<comapny_name_without_spaces>-aaExample:ind-tickerstockAvanti-Feeds-aaTo get the stock data of a company including the quarterly analysis:ind-tickerstock<comapny_name_without_spaces>-qaExample:ind-tickerstockTitan-qaTo get the stock data of a company including both the analysis:ind-tickerstock<comapny_name_without_spaces>-aa-qaExample:ind-tickerstockAdani-Green-aa-qaTo get data of a Mutual Fund Scheme:ind-tickermf<mutual_fund_scheme_name>Example:ind-tickermfmirae-asset-tax-saver
Package: inductance
InductanceThis is a python library to calculate inductance. Mostly for the purposes of calcualting magnetically confined plasmas. It might someday actually contain some plasma physics, but lets not get too carried away.FeaturesSelf-inductance formulasself inductance of circular, circular hollow, and rectangular section by Maxwell's approximationLyle's approximation for thick coil solenoid self inductances to 4th and 6th order.Butterworth's approximation for long solenoidsLorentz's perfect analytic solution for current sheet solenoidsBabic and Akyel's approximation for thin solenoidsMutual-inductance formulasmutual inductance of filaments (Maxwell)Filamentary modelsutility functions to create filament arrays from rectangular definitions of coils and subcoilscalculation for filament array mutual inductancecalculation of filament array self inductanceGreen's functionscalculation of Green's functions for Psi, Br, and Bz from filamented coils to pointswith Numba, calculation of green's functions for arbitrary grids of pointscalculation fo Green's functions for coil forcesArbitrary coil shapesrudimentary support for arbitrary wire filament coil shapesRequirementsInductancerequiresNumPyand usesNumbafor acceleration. It is written in mostly pure python referencing academic articles for calculating inductances by various methods, most of which rely on elliptic functions.InductanceprovidesNumbaaccelerated pure python elliptic functions.It is possible to remove the dependence on Numba and get most of the functionality ofInductance. The plan is to provide different options, including with alternative accelerators, such asJAX. For now, the requirements are:python >= 3.8numpy >= 1.24numba >= 0.57InstallationYou can installinductanceviapipfromPyPI:$pipinstallinductanceReferencePlease see thereferencefor details.ContributingContributions are very welcome.
To learn more, see theContributor Guide.LicenseDistributed under the terms of theMIT license,inductanceis free and open source software.IssuesFor now, this is a very early release. It is likely a new top level API will be
developed as the library matures.If you encounter any problems,
pleasefile an issuealong with a detailed description.CreditsThis project was generated from@cjolowicz'sHypermodern Python Cookiecuttertemplate.
Package: inductiva
Inductiva: a Python package for scaling simulations on the CloudWelcome to the official Python library for the Inductiva API version0.4.4.
The Inductiva API allows running a set of open-source physical
simulators on the cloud, easily parallelizing simulations, each running
on hundreds of CPU cores.Inductiva simplifies the complexities of cloud resource management, and software
configuration, offering a straightforward Python interface for running simulations
on state-of-the-art hardware. This allows scientists and engineers to focus their
time and energy on what matters: running simulations that solve real problems.To find out more, check ourdocumentation.If you have any questions or suggestions about the API pleaseopen an issue on the inductiva’s API Client GitHub repo, or contact us viasupport@inductiva.ai.
Package: industryandcovid
Relationship between coronavirus and Japanese industryThis project will compare amusement park sales with Internet industry sales and the number of people infected with COVID.This is a line chart that uses new_confirmed_cases_daily.xlsx, park_sales.xlsx, and internet_service.xlsx.
The new_confirmed_cases_daily.xlsx, the park_sales.xlsx, the and internet_service.xlsx is downloadable from:https://github.com/ritakei/industryandcovid/blob/main/newly_confirmed_cases_daily.xlsxhttps://github.com/ritakei/industryandcovid/blob/main/internet_service_sales.xlsxhttps://github.com/ritakei/VisitorsandCOVID/blob/main/park_sales.xlsxThe vertical axis is an integer and log display.How to install Visitors-and-Corona-Virus-InfectedYou may need some libraries.$ pip install matplotlib$ pip install pandas$ pip install openpyxlHow to run Visitors-and-Corona-Virus-InfectedThe VandC program allows you to plot the number of visitors to amusement parks in Japan and the number of people infected with COVID from January 2020 to April 2022.$ pip install industryandcovid$ industryandcovidThe following command can display a VisitorsandCOVID line graph with.
There are no options.
Package: industryts
Industry Time Series LibraryTime Series Manipulation for Industry DataThis repository hosts theindustry-ts:Industry Time SeriesLibrary --- a Python library that provides functions to manipulate time series collected from industrial contexts.This project aims to address the necessity for open-source tools developed for solving problems with data collected from industrial process.The modules introduced provide a variety of functions that are particularly tailored to industry data, directed to working with its most common issues, such as discontinuities in process measurements and faulty sensors.Table of ContentsIndustry Time Series LibraryTime Series Manipulation for Industry DataTable of ContentsMain FeaturesHow to use itDocumentationMain FeaturesData Generation: Generate synthetic data from well defined stochastic processes for testing and benchmarking purposes.Modelling: Fit time series models to data.Preprocessing: Preprocess time series with filtering, feature engineering and other techniques.How to use itThe package is available inPyPI, and can be installed with pip:pipinstallindustrytsAlternatively, to use the library, you can clone the repository and install it with pip:gitclonehttps://github.com/Industry-Time-Series/industry-ts.gitcdindustry-ts
gitcheckoutpackaging
pipinstall.DocumentationThe official documentation is hosted onhttps://industry-time-series.github.io/industry-ts/
Package: indxdatalaketools
Data Lake ToolsThis is the repository for the Data Lake tools. This Python package contains command line tools and packages to generate Data Lakes and Funtionality to interact with data lakes.Client PackageThe Client Package is for clients to upload files to the data lake.Package InstallationTo install run:pip install indxdatalaketoolsToolFor help on usage of the tool run:IndxClientDataLakeTools --help
Package: indy-bls
indy-bls-wrapper-pythonA Python wrapper forHyperledger Indy BLS Signatures Rustas used byHyperledger Indy Node.This package implements a version of the BLS signature scheme. The implementation doesn't match up with theBLS signatures specification at the IETF. It uses theBN254 curve defined here(sometimes called BN254N), and should not to be confused with the one used in Ethereum.This package is NOT recommended for new projects. It would be preferable to use a BLS signatures implementation based on the IETF draft, on a curve with a stronger security estimation (such as BLS12-381).InstallationThe package may be installed by using:pipinstallindy_blsNo additional dependencies are required for installation. Python 3.6 and higher are currently supported.BuildingThe primary build dependency is the Rust crate:Hyperledger Indy BLS Signatures Rust, which requires a Rust compiler toolchain. Python packaging requiressetuptoolsandwheel.ContributingPull requests are welcome! Please read ourcontributions guideand submit your PRs. We enforcedeveloper certificate of origin(DCO) commit signing. See guidancehere.We also welcome issues submitted about problems you encounter in usingindy_bls.AcknowledgementsThis code is based on the original Ursa Python wrapper contributed by Cam Parra.LicenseLicensed under the Apache License, Version 2.0. (LICENSE-APACHEorhttp://www.apache.org/licenses/LICENSE-2.0).
Package: indycarpy
IndyCarPyIndyCarPy is a Python package designed to scrape IndyCar session data from
the official IndyCar website. It provides functionalities to retrieve
information about races, practices, qualifications, and warm-up sessions,
as well as the records associated with these sessions.FeaturesSession Data Retrieval: Fetch data about IndyCar sessions including
races, practices, qualifications, and warm-ups.Data Cleaning and Preparation: Clean and prepare the retrieved data
for further analysis or storage.Export to CSV: Option to export the data to CSV format for easy
integration with other tools or databases.InstallationYou can install IndyCarPy using pip:pipinstallindycarpyMake sure you have the required dependencies installed: pandas, requests,
tqdm, and numpy.Usageimportindycarpy# Retrieve session data between specific yearssessions_df=indycarpy.get_sessions_record(from_year=1996,to_year=2024,session_type="R",data_format="df")# Clean session records datacleaned_data=indycarpy.clean_sessions_records(sessions_df)Data FilesThis package includes adata/race_track.csvfile containing information
about the track names for each event, which is utilized during data
retrieval.ContributingContributions to IndyCarPy are welcome! If you encounter any issues or have
suggestions for improvements, feel free to open an issue or submit a pull
request on GitHub.LicenseIndyCarPy is licensed under the GNU General Public License v3.0. See the
LICENSE file for more details.
Package: indy-credx
Indy-CredxA Python wrapper around theindy-credxRust library, this module provides support for Hyperledger Indy "Anoncreds" verifiable credential issuance, presentation, and verification.CreditThe initial implementation ofindy-shared-rswas developed by the Verifiable Organizations Network (VON) team based at the Province of British Columbia, and derives largely from the implementations withinHyperledger Indy-SDK. To learn more about VON and what's happening with decentralized identity in British Columbia, please go tohttps://vonx.io.ContributingPull requests are welcome! Please read ourcontributions guideand submit your PRs. We enforcedeveloper certificate of origin(DCO) commit signing. See guidancehere.We also welcome issues submitted about problems you encounter in usingindy-shared-rs.LicenseApache License Version 2.0
Package: inecocores
INECO Core MethodsThis module contains the core methods of the INECO library.Installationpip install inecocoresUsageform inecocores.core import Service
s = Service()
s.check_report(customerId='1', reportId="123", parameters={"a": 1, "b": 2, "c": 3})
sample_parameter = {
    'js_parameter_name': 'IDS',
    'js_parameter_value': 'sale_order.id = 32069',
}
result = s.call_report(customerId='1', reportId="123", parameters=sample_parameter)
Package: i-need-an-image
i-need-an-imageDownload only one image from web, only one API.从互联网中仅下载一张图片，使用时仅需一个接口。Only support "Bing Image" for now.现在只支持必应图片。Developing...根据自己的项目需求，开发中...确保可以从互联网上获取一张符合条件图片。可以指定图片的以下特征：关键词或一句话里的某个关键词（后续可能会移除提取关键词的功能）图片的版式：横板、竖版、方形我的关注点是尽可能地提高获取图片的成功率，可以通过不同细粒度的重试来达到这一目标：请求图片实际地址失败时进行重试。对同一搜索页面的不同图片进行请求尝试。尝试不同的来源网站（必应、百度、谷歌）。架构愿景：希望可以像Scrapy的流水线一样，不同来源的下载器可随意插拔和扩展。入口点只有一个need_image_from()函数。Installation 安装pip install i-need-an-imageUsage 使用方式>>>fromneed_an_imageimportneed_image_from# Get PIL Image object>>>need_image_from('bing',keyword='Tom')<PIL.JpegImagePlugin.JpegImageFileimagemode=RGBsize=800x1200at0x12594FE0EB0># Save image to disk>>>need_image_from('bing',keyword='Tom',save_to='.')'.\\2f65cbef7b8944cd93d21d434e566bf3.jpg'