Saravanan666/pypi-org huggingface dataset:
Package: investsai
Theinvestsaipackage hosts an Symbolic AI algorithmThe algorithm is interpretable. It can be trained with historic data and predict the companies that are more likely to succeed in the futurePrerequisitesPython >=3.7pip/virtualenv installedInstallingMake sure you have upgraded version of pippython-mpipinstall--upgradepipCreate a virtualenv and install requirements. You can do this by runningvirtualenvvenv
.venv/bin/activateInstall packagepipinstallinvestsai-qExamplefrominvestsai.saiimportSAI
importrandom
importnumpyasnp
importpandasaspd

defsimulate_data()->Union[dict,dict,dict]:"""This function simulates data to demonstrate the moduleReturns:Union[dict, dict, dict]: simulate training and testing data"""# Simulate n securities each with m numeric variables/factorsn=10000# simulate 1000 securitiesm=20# each securities with 20 variables/factors# a pandas DataFrame with training data n x m. n=number of securities and m=number of variables/factorsXTrain=pd.DataFrame(np.random.rand(n,m-1),columns=[f'factor_{i}'foriinrange(m-1)],index=['sec'+str(i)foriinrange(1,n+1)])# add a str factor (i.e. Sector) to test functionality, the dimension of input X is now n x mXTrain.loc[:,'Sector']=['Technology']*\int(n/2)+['Munufacturing']*(n-int(n/2))# Simulate a y varible to represent whether the stocks in training data is successful (can be by any objective or multi-objective)y=[0]*int(n*0.70)+[1]*int(n-int(n*0.70))random.shuffle(y)yTrain=pd.DataFrame(y,columns=['y'])# Simulate a yreal varible to represent the returns from each stocksyreal=pd.DataFrame(np.random.normal(0,0.05,n),columns=['yreal'])# Simulate a test data with n_test securities each with the same m variables/factorn_test=10000# test on 10000 securities, can be different from nXTest=pd.DataFrame(np.random.rand(n_test,m-1),columns=[f'factor_{i}'foriinrange(m-1)],index=['sec'+str(i)foriinrange(1,n_test+1)])# added another variable to represent the sector, the dimension of input XTest is now n x mXTest.loc[:,'Sector']=['Technology']*\int(n_test/2)+['Munufacturing']*(n_test-int(n_test/2))returnXTrain,yTrain,yreal,XTest


defmain()->None:"""Run the invest-sai algorithm and print learned rules and predictions"""XTrain,yTrain,XTest=simulate_data()# Simulate data# Start using Invest-SAI algorithm# Input parametersparams={'q':3,'parallel':True,'nb_workers':2,'verbose':True}invest_sai=SAI(params=params)invest_sai.fit(X=XTrain,y=yTrain,yreal=yreal)# This is the output expected success probilities of the securities in the test datayTest=invest_sai.predict(X=XTest)print(f'\n\nInterpretable rules with conditional probailities to rank securities\n{invest_sai.rules}\n')print(f'\nRanking of securities in XTest\n{yTest}\n')if__name__=='__main__':main()Technical debt
Package: invest-tools
invest-toolsTools to manage portfolio risk analysisInstallationAs a python package this should be installable through:pip install invest-toolsOr:poetry add invest-toolsDependenciesThe dependencies of this project can be seen in thepyproject.tomlfile. However for completeness there is a dependcy onpandas,statsmodelsandmatplotlibas the basics.Data InputsThere are three data inputs which should be present for the package to work as expected.The path strings to the csvs can be passed in.Portfolio price data as a CSVTIDMDateOpenHighLowCloseVolumeAdjustmentEG01/01/2023111111EG201/01/2023111111Currency data as a CSVDateOpenHighLowCloseAdj CloseVolume01/01/2023111111ExampleBuild a portfolio of two securities calledEGandEG2with the weighting split 50:50 between the two. One is denominated in GBP and one in USD.This will output the mean returns of such a portfolio.importnumpyasnpfrominvest_toolsimportportfolioportfolio_definition={"EG":{"weight":0.5,"currency":"gbp"},"EG2":{"weight":0.5,"currency":"usd"}}port=portfolio.Portfolio(portfolio_definition,portfolio.Currency.GBP)port.get_usd_converter("path/to/csv")port.get_prices("path/to/csv")port.build()port.analyse()print(port.analysis)port.plot_correlation_heatmap()port.plot_returns_data()LicenseMITContactJust open an issue I guess?
Package: invest-traker
invest_trackerA class that can be used to track investmentMotivationThis package was a initiative to help me to have a better knowledge about my own investments.
The package is still in a initial development phase containing only a Asset class that can be used
to register and track informations and rentability about investments in investments funds.UsageIt uses investpy package to scrap investment funds historical data. For it to function correctly
the code of the asset must be provided when instantiating the class. The code can be obtained in
the investing.com site by locating the characters in parenthesis after the asset name.
Package: invest-ucm-calibration
InVEST urban cooling model calibrationOverviewAutomated calibration of the InVEST urban cooling model with simulated annealingCitation: Bosch, M., Locatelli, M., Hamel, P., Remme, R. P., Chenal, J., and Joost, S. 2021. "A spatially-explicit approach to simulate urban heat mitigation with InVEST (v3.8.0)".Geoscientific Model Development 14(6), 3521-3537.10.5194/gmd-14-3521-2021Seethe user guidefor more information, orthelausanne-heat-islandsrepositoryfor an example use of this library in an academic article.InstallationThe easiest way to install this library is using conda (or mamba), as in:condainstall-cconda-forgeinvest-ucm-calibrationwhich will install all the required dependencies includingInVEST(minimum version 3.11.0). Otherwise, you can install the library with pip provided that all the dependencies (including GDAL) are installed.TODOAllow a sequence of LULC rasters (although this would require an explicit mapping of each LULC/evapotranspiration/temperature raster or station measurement to a specific date)Support spatio-temporal datasets withxarrayto avoid passing many separate rasters (and map each raster to a date more consistently)Read both station measurements and station locations as a single geo-data frameAcknowledgmentsThe calibration procedure is based simulated annealing implementation ofperrygeo/simannealWith the support of the École Polytechnique Fédérale de Lausanne (EPFL)This package was created with theppwtool. For more information, please visit theproject page.
Package: invesyservertools
invesyservertoolsA small set of useful tools an a server, especially for terminal scripts.Why "invesy"? Invesy (from GermanInhaltsverwaltungssystem == content management system) is a closed source cms I created with Thomas Macher. It's only used in-house, that's why we didn't bother making it open source.What's in the box?interactive_toolswait_for_key: Wait for a pressed key to continue.print_toolsand_list: human-readable list likea, 1, 2 and somethingindent: get an indentation stringprint_: Enhanced print function, specially enhanced for printing in the terminal and into log files.format_filesize: return a human-readable filesize, like31.9 GiB.system_toolsget_username: get the username in the operating systemget_home_dirfind_file_with_path: provide a filename and a start path to begin searching recursively, get the complete path including the filenameHistory0.0.9 (2023-06-10)fixed IndexError inprint_(for line ending in last string)print_checks for terminal (-> no colors, no wrapper)0.0.5 (2022-12-09)fixed import of submodules0.0.4 (2022-12-09)wait_for_keygets a "indent" argumentSphinx documentation0.0.3 (2022-06-16)Added support for line breaks inprint_:can be added as singletons or as part of stringsline break singletons are not counted in the color argument0.0.2 (2022-06-13)splitted modules (now:interactive_tools,print_tools,system_tools)added new functions:system_toolsget_usernameget_home_dirfind_file_pathprint_toolsand_listformat_filesize0.0.1 (2022-06-10)first version
Package: invex
invexAn inventory manager for keeping track of items.How to install1. Install PythonTo install python, go tohttps://python.org/downloadsand download the correct version for you OS.2. Install invexTo install invex, dopy -m pip install invexon Windows orpython3 -m pip install invexon Mac/Linux into any terminal session.3. Go into the correct directoryBefore you launch invex, in the terminal go into the directory you want the data to be stored *Make sure you have read/write access, this is because invex automatically creates a .dat file in the location you are in when you launch it.4. Opening invexTo open invex, typeinvexinto the terminal.If there are any other issues,Click here.
Package: invfinsdk
InvFinSDKAn SDK to interact with InvFin endpointsFree software: MIT licenseDocumentation:https://invfinsdk.readthedocs.io.Support MethodsCompanyExchangeTermIndustrySectorSuperinvestorUser installationThe easiest way to install invfinsdk is usingpip:pip install -U invfinsdkHow to use itfrom invfinsdk import Company

API_KEY = "******"

aapl = Company(API_KEY).get_company_basic_information({"ticker": "AAPL"})Source codeYou can check the latest sources with the command:git clone https://github.com/InvFin/Python-sdk.gitTestingAfter installation, you can launch the test suite from outside the source
directory (you will need to havepytestinstalled):pytest invfinsdkContributingWelcome! Happy to see you willing to make the project better. You can get started by
reading this:Contributing: The basicsChangelogThe log has become rather long. It moved to its own file.SeeCHANGES.AuthorsThe author list is quite long nowadays, so it lives in its own file.SeeAUTHORS.rst=======
History
Package: invg
INVG (INgolstÃ¤dter VerkehrsGesellschaft) api wrapperThis is a reverse engineering of the INVG realtime bus information api.
It is using a mix of api and web crawler to get all its information.Functionsget_station_data(str)this function takes a string of a bus stop's name and returns the Busstation shortcode aswell as the Busstation ID.get_timetable(str, str)this function takes the Busstation shortcode and Busstation ID and returns the timetale as JSON array.get_timtable_by_name(str)this function merges the two above and takes the Name and returns the JSON array.IF you run this from the commandline it will Visualize the requested Station Data.
Package: invian
This repository contains functions for analysis of in vivo electrophysiology data. It is still in early stages of development, but all functions in the main branch should be functional.This goal of this module is to be very flexible, allowing for use with many different file types. To do this, all the functions run using timestamps and values associated to those timestamps. In the future, integration with Neo/NWB would be ideal.Current installation instructions.
-These instructions assumes that user is using the Anaconda python distribution
Clone repository. There are two options:Using git (all branches). In git bash type:git clone https://github.com/AlexLM96/invian.gitDownloading .zip file:In invian repository (https://github.com/AlexLM96/invian/tree/dev) clickcodeand thendownload zipThen open Anaconda prompt and type:pip install INVIAN_LOCATIONwhere INVIAN_LOCATION is the file path of the invian folder. Note that the path should point to the main folder. E.g:pip install C:\Users\alex\Desktop\invian
Package: invidious-parser
invidious-parserInvidious-parser is the library for using invidious api.Not ready for
using in applications.WARNING: TESTED ONLY ON Python3.10AuthorKostiantyn Klochko (c) 2022-2023DonationMonero:
8BPT7PzYeYqLh3iavVeisT8J2yBBfEzBsKoF6j61tqNyZQ5tN81gXLyKLrjUC8eKeaEyk5npkyYRuTZkhXW2uVwe9tDbaPZLicenseUnder GNU GPL v3 license
Package: invidious.py
Invidious.pyA Python wrapper for Invidious APIInstallationpip install invidious.pyGetting Startedfrominvidiousimport*iv=Invidious()searched=iv.search("distrotube")foriteminsearched:iftype(item)==ChannelItem:print(item.author)# Print names of all channels# in first page of result 'distrotube'LinksPyPi:https://pypi.org/project/invidious.py/Git repo:https://codeberg.org/librehub/invidious.pyMatrix:https://matrix.to/#/#librehub:matrix.orgDonatesMonero:47KkgEb3agJJjSpeW1LpVi1M8fsCfREhnBCb1yib5KQgCxwb6j47XBQAamueByrLUceRinJqveZ82UCbrGqrsY9oNuZ97xN
Package: invirtualenv
InVirtualEnvUtilities for deploying applications written in Python.BackgroundThis project is an extensible utility that creates deployment artifacts for Python applications in multiple formats from a single configuration file.  This simplifies the creation of CI Pipelines that support multiple installation methods.ContributePlease refer tothe contributing.md filefor information about how to get involved. We welcome issues, questions, and pull requests. Pull Requests are welcome.LicenseThis project is licensed under the terms o ftheBSDopen source license.  Please refer toLICENSEfor the full terms.
Package: invis
InvisInvis is an invisible framework which purpose is to enforce type checking of both builtins as well as user defined types atruntime.
It is distributed as a single file with no extra dependencies other than the Python Standard Library (>= 3.7).To install:pip install invisA comprehensive tutorial on how to use the framework can be foundhereA discussion about the project, held on reddit's algotrading subforum, can be foundhere
Package: invisible-backdoor-detector
Invisible Backdoor DetectorInvisible Backdoor Detectoris a littlePythonscript that allows you tospotandremoveBidi characters that could lead to aninvisible backdoor. If you don't know what that is you should check the related paragraph.Table of ContentsWhat is an Invisible BackdoorInstallUsageExamplesContributionsCreditsLicenseWhat is an Invisbile BackdoorAn Invisible Backdoor is exactly what you think: a backdoor that you cannot see! It was described byWolfgang EttlingeratCertitudeinthis blog post. It leverages the presence of Unicode characters (Bidi characters) which behaves like normal spaces. In conjunction with the Javascript object destructuring those characters may allow an attacker to introduce a backdoor into an open-source project without anyone noticing it. Check out the blog post for more info.InstallYou can easily install it by running:pip install invisible-backdoor-detectorUsageinvisible-backdoor-detector -hUsage: invisible-backdoor-detector [OPTIONS] PATH                                                                          
                                                                                                                            
╭─ Arguments ──────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ *    path      TEXT  Path of the folder to check [default: None] [required]                                              │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Options ────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --remove  -r        Remove the Bidi characters found                                                                     │
│ --help    -h        Show this message and exit.                                                                          │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ExampleTheexamplefolder provides a working example of an invisible backdoor in Node.js, you may test the script on that folder.
If you want to try out the backdoor you can add the following parameter to the query string:%E3%85%A4=<any command>ContributionsEveryone is invited to contribute!
If you are a user of the tool and have a suggestion for a new feature or a bug to report, please do so through the issue tracker.CreditsDeveloped by Angelo Delicato@SecSILicenseinvisible-backdoor-detectoris released under theMIT LICENSE
Package: invisible-captcha-bypasser
Решение невидимой капчи v3 гугл на запросах(без использования антикапчи, браузера)Google's invisible captcha v3 solution on requests (without using anti-captcha, browser)importasynciofrominvisible_captcha_bypasserimportsolve_captchacaptcha_response:str=asyncio.run(solve_captcha(anchor_url='',proxy='http://user:pass@127.0.0.1:25565'))DONATE (any evm) - 0xDEADf12DE9A24b47Da0a43E1bA70B8972F5296F2DONATE (sol) - 2Fw2wh1pN77ELg6sWnn5cZrTDCK5ibfnKymTuCXL8sPXDONATE (trx) - TEAmkvFXJ6N6wzN4aS3HtgiM7XhnwRrtkW
Package: invisible-ink
This library includes a set of tools for using zero-width unicode characters to
embed human-invisible messages in text.WatermarkingYou can use invisible ink to uniquely identify a piece of text by embedding a
UUID:>>> from invisible_ink import encode_watermark, decode_watermark
>>> encoded_text, uuid = encode_watermark(u'asdf')
>>> print encoded_text
asdf
>>> uuid
UUID('3ca37a37-9c5a-4b9e-a9c0-a50c47c48dba')
>>> decode_watermark(encoded_text)
(u'asdf', UUID('3ca37a37-9c5a-4b9e-a9c0-a50c47c48dba'))encode_watermark(text, watermark_uuid=None, prepend=False)Encodes the given text with a watermark string generated from the given uuid.
Optionally appends or prepends the watermark string.Parameters:text: Unicode string to which the watermark will be addedwatermark_uuid:uuid.UUIDinstance to use as the watermark.
(uuid.uuid4()will be used to generate one if not provided.)prepend: Indicates whether the watermark should be prended totext(defaults toFalse). IfFalse, the watermark will be appended.Returns:A 2-tuple:(encoded_text, watermark_uuid)decode_watermark(encoded_text)Decodes the given text, separating out the original text and the watermark uuid.Paramters:encoded_text: Unicode string which potentially includes a watermarkReturns:A 2-tuple:(text, watermark_uuid). If no watermark is detected,textis the original text andwatermark_uuid is None.Installation$ pip install invisible-ink
Package: invisibleroads
InvisibleRoadsHere is a simple framework for extensible command line scripts.pipinstall-Uinvisibleroadscd~/Documents
gitclonehttps://github.com/invisibleroads/invisibleroadscdinvisibleroads/tests/examples/xyz
pipinstall-e.

xyz
xyza
xyzb
xyzx
xyzxa
xyzxb
xyzy
xyzya
xyzyb

xyzaz
xyzbz
xyzxaz
xyzxbz
xyzyaz
xyzybz0.3Define LoggingScriptSupport nested subparsersSupport ArgumentParser arguments0.2Drop support for Python 2Show available commandsShow script errors0.1Prepare for public release
Package: invisibleroads-macros
Here is a collection of shortcut functions for small tasks.0.9Define link_safely, make_relative_path_safely, make_treeDeprecate define_get_numbers, get_list, parse_settings, set_defaultRename cancel_callback to cancel_shell_callbackResolve links when validating relative or absolute pathsUpdate transform_geometries to support polygons0.8Add cut_and_stripAdd encode_object, define_decode_objectAdd schedule_shell_callback, schedule_curl_callbackAdd define_gather_numbers, parse_second_countAdd format_decimal, format_number0.7Add configuration.load_settings and configuration.save_settingsAdd disk.TemporaryFolder and disk.TemporaryPathAdd math.divide_safelyRemove parse_date_safely thanks to latest dateutilReplace get_interpretation_by_name with gather_settings0.6Add iterable.flatten_dictionaries, iterable.merge_dictionariesAdd log.format_summary, log.print_errorAdd table.normalize_keyFilter keys in parse_nested_dictionary with is_keyMake disk.compress and disk.uncompress compatible with non-Linux0.5Add disk.make_enumerated_folder_for, disk.change_owner_and_group_recursivelyAdd repository.get_github_repository_commit_timestampMove queue.* to invisibleroads-sockets packageMove repository.* to invisibleroads-repositories package0.4Add disk.make_enumerated_folderAdd log.parse_nested_dictionary0.3Add queue.Pusher, queue.Puller, queue.Publisher, queue.SubscriberAdd repository.download_github_repository, repository.get_github_ssh_url0.2Add log.format_pathAdd text.remove_punctuation0.1Add disk.compress, disk.uncompressAdd text.compact_whitespace
Package: invisibleroads-macros-configuration
Shortcut Functions for Configuration OperationsHere are various macros for loading configuration files.Installpip install -U invisibleroads-macros-configurationTestgit clone https://github.com/invisibleroads/invisibleroads-macros-configuration
cd invisibleroads-macros-configuration
pip install -e .[test]
pytest --cov=invisibleroads_macros_configuration --cov-report term-missing tests1.0Add fill_environment_variables, fill_extensions, fill_secretsRestore Settings, set_defaultRestore load_attributes, load_attribute, load_json
Package: invisibleroads-macros-database
Shortcut Functions for Database OperationsInstallpip install invisibleroads-macros-databaseTestgit clone https://github.com/invisibleroads/invisibleroads-macros-database
cd invisibleroads-macros-database
pip install -e .[test]
pytest --cov=invisibleroads_macros_database --cov-report term-missing tests1.0Add load_spatialite_sqlite_extension
Package: invisibleroads-macros-descriptor
Shortcut Functions for Descriptor OperationsInstallpip install invisibleroads-macros-descriptorTestgit clone https://github.com/invisibleroads/invisibleroads-macros-descriptor
cd invisibleroads-macros-descriptor
pip install -e .[test]
pytest --cov=invisibleroads_macros_descriptor --cov-report term-missing tests1.0Restore classproperty, cachedproperty
Package: invisibleroads-macros-disk
Shortcut Functions for Disk OperationsInstallpip install invisibleroads-macros-diskTestgit clone https://github.com/invisibleroads/invisibleroads-macros-disk
cd invisibleroads-macros-disk
pip install -e .[test]
pytest --cov=invisibleroads_macros_disk --cov-report term-missing tests1.3Addcache_downloadUseplatformdirs.user_cache_dirfor OS independent temporary folder1.2Addis_path_in_folder,get_file_hash,get_asset_path1.1Restorearchive_safely,unarchive_safelyRestorecheck_relative_path,get_relative_pathRestorehas_extension,is_matching_paths,walk_paths1.0RestoreTemporaryStorage,make_folder,make_unique_folderRestoreremove_folder,remove_pathRestorecheck_absolute_path,get_absolute_path,get_real_pathRestoremake_enumerated_folder,make_random_folder
Package: invisibleroads-macros-geometry
Shortcut Functions for Geometry OperationsInstallpip install invisibleroads-macros-geometryTestgit clone https://github.com/invisibleroads/invisibleroads-macros-geometry
cd invisibleroads-macros-geometry
pip install -e .[test]
pytest --cov=invisibleroads_macros_geometry --cov-report term-missing:skip-covered --cov-config=tox.ini tests1.0
Package: invisibleroads-macros-log
Shortcut Functions for Log OperationsInstallpip install invisibleroads-macros-logTestgit clone https://github.com/invisibleroads/invisibleroads-macros-log
cd invisibleroads-macros-log
pip install -e .[test]
pytest --cov=invisibleroads_macros_log --cov-report term-missing tests1.0Restore get_log, get_timestampRestore format_path, format_assignmentRestore format_summary, format_nested_dictionary, format_indented_block
Package: invisibleroads-macros-process
Shortcut Functions for Process OperationsInstallpipinstallinvisibleroads-macros-processUseimportloggingfrominvisibleroads_macros_processimportLoggableProcess,StoppableProcesslogging.basicConfig(level=logging.DEBUG)deff():print('whee')process=LoggableProcess(name='MY-LOGGABLE',target=f,daemon=True)process.start()process=StoppableProcess(name='MY-STOPPABLE',target=f,daemon=True)process.start()process.stop()Testgitclonehttps://github.com/invisibleroads/invisibleroads-macros-processcdinvisibleroads-macros-process
pipinstall-e.[test]pytest--cov=invisibleroads_macros_process--cov-reportterm-missingtests0.2Make it possible to specify Process class such as when using a multiprocessing contextReplace SIGTERM with SIGINT0.1Add LoggableProcess, StoppableProcess
Package: invisibleroads-macros-text
Shortcut Functions for Text OperationsInstallpip install invisibleroads-macros-textTestgit clone https://github.com/invisibleroads/invisibleroads-macros-text
cd invisibleroads-macros-text
pip install -e .[test]
pytest --cov=invisibleroads_macros_text --cov-report term-missing tests1.1Add format_name, format_slug, title_conservativelyUpdate normalize_key to treat every non-character as a word separatorUpdate normalize_key to allow custom text processing via process_text1.0Restore compact_whitespace, normalize_key, unicode_safely