Saravanan666/pypi-org huggingface dataset:
Package: oCrypt0r
oCrypt0r - A minimalistic, simple AES encryption library written in python3.oCrypt0r allows you to encrypt and decrypt strings of text via AES. Your encrypted data/strings can only be decrypted using your own custom key and salt you set before encrypting said data. You can use this for a variety of things from securing passwords to securing communication to encrypting HWIDs and directories/folders. Making AES encryption a little bit easier!UpdatesWhat has been updated as of | 7/17/22:Encryption functions now take 3 args instead of 4.Removed the hashing feature that makes a blake2b hash of a key to be used in the encryption. This basically made things less unique as the hash was just all 0-9 and lowercase a-z characters.Installation[Directly from here/this repo.][therealOri~]$pipinstallgit+https://github.com/therealOri/oCrypt0ror[From Pypi.][therealOri~]$pipinstalloCrypt0rCode ExamplesIf you would like to make this look better/more presentable. Please by all means make a pull request xD. I'm not the best with making things look great.It is important to know that all functions will take 3 values. 2 for the making of the encryption key, and 1 for what you want encrypted/decrypted.The encryption takes 2 values to make a key. The key then gets plugged into the AES encryption as a cipher. All of that will be used to encrypt whatever you want as a value. "strings", "files", or "directories/folders". (inclusing sub-directories)You can read more about what the arguments do in the documentation.DocumentationfromocryptorimportoCrypt##---------Strings---------###Encrypting Stringsstring='Hello Wolrd <3'enc_key="abcdefgHIJKLMNOP~!@#$%^&*"enc_salt='qrstuvwxyz1234567890'str_enc=oCrypt().string_encrypt(string,enc_key,enc_salt)print(str_enc)# Output is b64 encoded. => VpqFynzUPOK3dHYaCFO57IGlYrQRyzt2NvmzMEN2+AA=#Decrypting Stringsstring='VpqFynzUPOK3dHYaCFO57IGlYrQRyzt2NvmzMEN2+AA='enc_key="abcdefgHIJKLMNOP~!@#$%^&*"enc_salt='qrstuvwxyz1234567890'str_dcr=oCrypt().string_decrypt(string,enc_key,enc_salt)print(str_dcr)# Output is "Hello Wolrd <3"##---------Strings End---------####---------Files---------###Encrypting Filesfile_path='/home/therealOri/Projects/example.txt'enc_key="abcdefgHIJKLMNOP~!@#$%^&*"enc_salt='qrstuvwxyz1234567890'oCrypt().file_encrypt(file_path,enc_key,enc_salt)#Decrypting Filesfile_path='/home/therealOri/Projects/example.txt.oCrypted'# .oCrypted is what is used to let you know that the file is encrypted.enc_key="abcdefgHIJKLMNOP~!@#$%^&*"enc_salt='qrstuvwxyz1234567890'oCrypt().file_decrypt(file_path,enc_key,enc_salt)##---------Files End---------####---------Directories---------###Encrypting Directorydir_path='/home/therealOri/Projects'#Must be a path to the directory you want to encrypt.enc_key="abcdefgHIJKLMNOP~!@#$%^&*"enc_salt='qrstuvwxyz1234567890'oCrypt().dir_encrypt(dir_path,enc_key,enc_salt)#Decrypting Directorydir_path='/home/therealOri/Projects'enc_key="abcdefgHIJKLMNOP~!@#$%^&*"enc_salt='qrstuvwxyz1234567890'oCrypt().dir_decrypt(dir_path,enc_key,enc_salt)##---------Directories End---------##Support  |  Buy me a coffee <3Donate to me here:Don't have Cashapp?Sign Up
Package: ocs-ingester
Ingester LibraryA library for adding new science data products to an observatory control system'sScience Archive.
The library handles uploading files into aFileStore(S3 recommended), as well as adding records to the Science Archive's database containing
the searchable metadata of all available files. Optionally, it records ingestion metrics in anopenTSDBinstance, which can be disabled by setting the environment variableOPENTSDB_PYTHON_METRICS_TEST_MODE=False.PrerequisitesOptional prerequisites may be skipped for reduced functionality.Python >= 3.7A runningScience ArchiveA configured FileStore (S3 recommended) with write access to store data there(Optional) A runningOpenTSDBfor metrics collectionUsageThis project depends on the OCSArchive Library, so please look through and set all of its environment variables to match your file format header keys and data storage choices. Specifically, theFILESTORE_TYPEenvironment variable must be set for your FileStore backend, since it defaults todummywhich stores no data. The header mapping environment variables should also be set to map to the correct keys in your data products as well. These environment variable values must match the values used in yourScience Archiveinstance as well. Also check out thedata flow documentationfor more details on how to configure and use the ingester.InstallationIt is highly recommended that you install and run your python code inside a dedicated pythonvirtual environment.Add theocs_ingesterpackage to your python environment:(venv)$pipinstallocs_ingesterConfigurationAWS and science archive credentials must be set in order to upload data. Science archive configuration as well as the
AWS Bucket can be either passed explicitly or set as environment variables. The rest of the configuration must be
set as environment variables.Environment VariablesVariableDescriptionDefaultScience ArchiveAPI_ROOTScience Archive URL"http://localhost:8000/"AUTH_TOKENScience Archive Authentication Token. This token must be associated with an admin user.empty stringAWSBUCKETAWS S3 Bucket NameingestertestAWS_ACCESS_KEY_IDAWS Access Key with write access to the S3 bucketempty stringAWS_SECRET_ACCESS_KEYAWS Secret Access Keyempty stringAWS_DEFAULT_REGIONAWS S3 Default Regionempty stringS3_ENDPOINT_URLEndpoint url for connecting to s3. This can be modified to connect to a local instance of s3."http://s3.us-west-2.amazonaws.com"MetricsOPENTSDB_HOSTNAMEOpenTSDB Host to send metrics toempty stringOPENTSDB_PYTHON_METRICS_TEST_MODESet to any value to turn off metrics collectionFalseINGESTER_PROCESS_NAMEA tag set with the collected metrics to identify where the metrics are coming fromingesterSUBMIT_METRICS_ASYNCHRONOUSLYOptionally submit metrics asynchronously. This option does not apply when the command line entrypoint is used, in which case metrics are always submitted synchronously. Note that some metrics may be lost when submitted asynchronously.FalseFor DevelopersRunning the TestsAfter cloning this project, from the project root and inside your virtual environment:(venv)$pipinstall-e.[tests](venv)$pytest
Package: ocsmesh
OCSMeshOCSMesh is a Python package for processing DEM data into georeferenced
unstructured meshes using thejigsaw-pythonlibrary.InstallationTwo ways of installing OCSMesh are described below:UsingcondaThe recommended way to setup the environment for installing OCSMesh is to
usecondawith theenvironment.ymlfile provided in the repo to install
required libraries.The Jigsaw library and its Python wrapper  must be instlled
before OCSMesh can be used. Jigsaw is available onconda-forgechannel.First you need to download theenvironment.ymlfile.wget https://raw.githubusercontent.com/noaa-ocs-modeling/OCSMesh/main/environment.yml

conda env create -f environment.yml -n your-env-name
conda activate your-env-name

conda install -y -c conda-forge jigsawpy
pip install ocsmeshFrom GitHub repoOCSMesh can be installed from the GitHub repository as well.
After downloading the repo, you need to first install Jigsaw using
the script provided in OCSMesh repo by calling:./setup.py install_jigsawin the OCSMesh root directory.
Then OCSMesh can be installed.git clone https://github.com/noaa-ocs-modeling/ocsmesh
cd ocsmesh
python ./setup.py install_jigsaw # To install latest Jigsaw from GitHub
python ./setup.py install # Installs the OCSMesh library to the current Python environment
# OR
python ./setup.py develop # Run this if you are a developer.Requirements3.9 <= PythonCMakeC/C++ compilersHow to CiteTitle : OCSMesh: a data-driven automated unstructured mesh generation software for coastal ocean modelingPersonal Author(s) : Mani, Soroosh;Calzada, Jaime R.;Moghimi, Saeed;Zhang, Y. Joseph;Myers, Edward;Pe’eri, Shachak;Corporate Authors(s) : Coast Survey Development Laboratory (U.S.)Published Date : 2021Series : NOAA Technical Memorandum NOS CS ; 47DOI :https://doi.org/10.25923/csba-m072
Package: ocsort
OcSort-Pip: Packaged version of the OcSort repositoryOverviewThis repo is a packaged version of theOcSortalgorithm.Installationpip install ocsortDetection Model + OcSortfromocsort.ocsortimportOCSorttracker=OCSort(args)forimageinimages:dets=detector(image)online_targets=tracker.update(dets)Citation@article{cao2022observation,title={Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking},author={Cao, Jinkun and Weng, Xinshuo and Khirodkar, Rawal and Pang, Jiangmiao and Kitani, Kris},journal={arXiv preprint arXiv:2203.14360},year={2022}}
Package: ocsp-check
# OCSP CheckUsage Syntax: ocsp_check –POST/–GET -c/-d/-f targetMethod Parameters:-pPerform the OCSP request using an HTTP POST call (–POST works too)-gPerform the OCSP request using an HTTP GET call (–GET works too)Source Parameters:-cUse a crt.sh ID as target-dUse a domain / live website as target-fUse a local file containing a certificate as targetTarget Parameter: In place of target should be a crt.sh ID, domain/website (includinghttps://) or local filenameocsp_check version 0.0.16
Author: Martijn Katerbarg
Package: ocsp-checker
OCSP-CheckerOverviewOCSP-Checker is a python package based on Alban Diquet'snasslwrapper and the Python Cryptographic Authority'scryptographypackage. Relying on a web browser to check the revocation status of a x509 digital certificatehasbeenbrokenfrom the beginning, and validating certificates outside of the web browser is a manual process. OCSP-Checker aims to solve this by providing an automated means to check theOCSPrevocation status for a x509 digital certificate.Pre-requisitesPython- Python 3.7 (64-bit) and above.InstallationIt is strongly recommended to run ocsp-checker in a virtual environment. This will prevent you from impacting your system python when installing its dependencies.venvis a good option, with an example below:python -m venv ocsp-checkercd ocsp-checker && source bin/activateOnce your virtual environment is activated, install ocsp-checker as follows:pip install ocsp-checkerUsage>>> from ocspchecker import ocspchecker
>>> ocsp_request = ocspchecker.get_ocsp_status("github.com")Sample OutputSample output below, let me know if you want to add more fields/information to the output.['Host: github.com:443', 'OCSP URL: http://ocsp.digicert.com', 'OCSP Status: GOOD']PLEASE NOTE: If you run this on a network with a MITM SSL proxy, you may receive unintended results (see below):["Error: Certificate Authority Information Access (AIA) Extension Missing. Possible MITM Proxy."]Command Line UsageOCSP-Checker can now be used at the command line. The format is:usage: ocspchecker [-h] --target target [--port port]

Check the OCSP revocation status for a x509 digital certificate.

optional arguments:
  -h, --help            show this help message and exit
  --target target, -t target
                        The target to test
  --port port, -p port  The port to test (default is 443)For example:ocspchecker -t github.com
Package: ocs-rise-set
Rise-set LibraryWARNING: The API of this library will be updated in the near futureThis library provides Python routines for finding the positions of astronomical bodies to reasonable precision. It is primarily used to calculate target uptime and sunrise, sunset and twilight times, accurate to 30s-1m. It also supports calculating target airmass over time. The library depends on Fortran SLALIB to perform the computations. The rise/set/transit algorithms are implementations of Astronomical Algorithms, Ch. 14 (Jean Meeus). This library was initially authored byEric Saunders.PrerequisitesPython >= 3.7Ability to compile fortran (gfortran installed)InstallationIt is highly recommended that you install and run your python code inside a dedicated pythonvirtual environment.Add theocs_rise_setpackage to your python environment (you may need to install numpy first):(venv)$pipinstallnumpy;pipinstallocs_rise_setFor DevelopersRunning the TestsThe unit tests are currently using nosetests, so there are a few tests dependencies to install. After cloning this project, from the project root and inside your virtual environment (using Poetry):$poetryenvusepython3.10
$poetryinstall
$poetryrunpytest
Package: ocs-sample-library-hub
OSIsoft Cloud Services Python Library SampleVersion:0.1.16_previewThe python OCS library is an introductory language-specific examples of programming against OSISoft Cloud Services (OCS). It is as instructional samples only and are not for production use.They can be obtained by running: pip install ocs_sample_library_previewThe library is not intended to show every endpoint and every option/parameter for endpoints it has. The library is known to be incomplete.Other language libraries and samples are available onGithub.Tests are done by testing the sample apps that use this.Developed against Python 3.7.2.OSI Samplesare licensed under the Apache 2 license.For the main OCS sample libraries page on masterReadMeFor the main OCS samples page on masterReadMeFor the main OSIsoft samples page on masterReadMe
Package: ocs-sample-library-preview
AVEVA Data Hub Python Library Sample:loudspeaker:Notice: This library is being deprecated to be replaced by the AVEVA Data Hub brandedadh_sample_library_previewlibrary. Version 0.7.1_preview of this library installsadh_sample_library_previewas a dependency.Version:0.7.1_previewThis sample library requires Python 3.7+. You can download Pythonhere.NOTE: The library previously required Python 3.9+ to take advantage of type annotations. To provide compatibility with environments that cannot upgrade Python to 3.9,from __future__ import annotationswas added to each necessary file.This provides backwards compatibility down to Python 3.7.About the libraryThe python ADH library is an introductory language-specific example of programming against Aveva Data Hub (ADH). It is intended as instructional samples only and are not for production use.The samples also work on OSIsoft Cloud Services unless otherwise noted.They can be obtained by running:pip install ocs_sample_library_previewThe library is not intended to show every endpoint and every option/parameter for endpoints it has. The library is known to be incomplete.Other language libraries and samples are available onGitHub.Tests are done by testing the sample apps that use this.Developed using Python 3.9.5.AVEVA Samplesare licensed under the Apache 2 license.For the main ADH sample libraries pageReadMeFor the main ADH samples pageReadMeFor the main AVEVA samples pageReadMe
Package: oct2py
Oct2Py allows you to seamlessly call M-files and Octave functions from Python.
It manages the Octave session for you, sharing data behind the scenes using
MAT files.  Usage is as simple as:>>>importoct2py>>>oc=oct2py.Oct2Py()>>>x=oc.zeros(3,3)>>>print(x,x.dtype)[[0.0.0.][0.0.0.][0.0.0.]]float64To run .m function, you need to explicitly add the path to .m file using:>>>fromoct2pyimportoctave>>># to add a folder use:>>>octave.addpath('/path/to/directory')# doctest: +SKIP>>># to add folder with all subfolder in it use:>>>octave.addpath(octave.genpath('/path/to/directory'))# doctest: +SKIP>>># to run the .m file :>>>octave.run('fileName.m')# doctest: +SKIPTo get the output of .m file after setting the path, use:>>>importnumpyasnp>>>fromoct2pyimportoctave>>>x=np.array([[1,2],[3,4]],dtype=float)>>>#use nout='max_nout' to automatically choose max possible nout>>>octave.addpath('./example')# doctest: +SKIP>>>out,oclass=octave.roundtrip(x,nout=2)# doctest: +SKIP>>>importpprint# doctest: +SKIP>>>pprint.pprint([x,x.dtype,out,oclass,out.dtype])# doctest: +SKIP[array([[1.,2.],[3.,4.]]),dtype('float64'),array([[1.,2.],[3.,4.]]),'double',dtype('<f8')]If you want to run legacy m-files, do not have MATLAB®, and do not fully
trust a code translator, this is your library.FeaturesSupports all Octave datatypes and most Python datatypes and Numpy dtypes.ProvidesOctaveMagicfor IPython, including inline plotting in notebooks.Supports cell arrays and structs/struct arrays with arbitrary nesting.Supports sparse matrices.Builds methods on the fly linked to Octave commands (e.g.zerosabove).Thread-safety: each Oct2Py object uses an independent Octave session.Can be used as a context manager.Supports Unicode characters.Supports logging of session commands.Optional timeout command parameter to prevent runaway Octave sessions.InstallationYou must have GNU Octave installed and in yourPATHenvironment variable.
Alternatively, you can set anOCTAVE_EXECUTABLEorOCTAVEenvironment
variable that points tooctaveexecutable itself.You must have the Numpy and Scipy libraries for Python installed.
See the installationinstructionsfor more details.Once the dependencies have been installed, run:$pipinstalloct2pyIf using conda, it is available on conda-forge:$condainstall-cconda-forgeoct2pyDocumentationDocumentation is availableonline.For version information, see theChangelog.
Package: oct4th
oct4thCLI tool to convert CSV/TSV files to Excel spreadsheets, while not converting gene names (e.g. OCT4, DEC1) into dates in the process.For converting small files, you can use theOct4th web application.To learn more about this issue, check outthis article.Installationpip3install-Uoct4thIf you don't have access to a computer where you can runpip, check out thisColab notebook.UsageAs a CLI:# Convert a CSV file to XLSXoct4th--input./data/test.csv--output./data/test.xlsxFrom Python:importoct4th# Convert a CSV file to XLSXoct4th.csv_to_xlsx(file_in="./data/test.csv",file_out="./data/test.xlsx")Developingpython3-mvenvve
.ve/bin/activate
pipinstallsetuptoolswheeltwinepytestxlsxwriterpandasxlrdRun TestsPYTHONPATH=.pytest./tests/Deploy# Clean up and rebuild.ve/bin/activate
rm-rf./build/./dist/
python3setup.pysdistbdist_wheel# Check before deployingtwinecheckdist/*# Upload to testpypipython3-mtwineupload--repositorytestpypidist/*# Test installdeactivate;pip3install-U-ihttps://test.pypi.org/simple/oct4th==1.0.0b9# Deploy to pypi# python3 -m twine upload --repository pypi dist/*
Package: octa
OCTA toolboxThe OCTA Python toolbox was created by Van Geert, Bossens, and Wagemans (2021) as a tool for researchers to create stimuli varying in order and complexity on different dimensions.
It was created in Python 3.8 and is dependent on the following Python libraries: svgwrite, svg.path, svgpathtools, svgutils, jsonpickle, html2image, svglib, reportlab, colour, and IPython.
We thank the developers of each of these libraries and of the Python programming language.A simple example:from octa.Stimulus import Grid
from octa.patterns import GridPattern
from octa.shapes import Ellipse, Rectangle, Triangle

## Create new stimulus
stim = Grid(n_rows = 6, n_cols = 6, background_color = "none",
            row_spacing = 40, col_spacing = 40)

## Determine shape of elements used in the stimulus
stim.shapes = GridPattern.RepeatAcrossColumns([Rectangle, Triangle, Ellipse])

## Determine color of elements used in the stimulus
colors_to_use = ["#1b9fd8", "#6dd6ff", "#006ca1"]
stim.fillcolors = GridPattern.RepeatAcrossColumns(colors_to_use)

## Determine size of elements used in the stimulus
stim.boundingboxes = GridPattern.RepeatAcrossColumns([(30,30)])

stim.Show()OCTA Shiny appA graphical user interface for OCTA is available in the form of aShiny app.Citing OCTAIf you use the OCTA Python toolbox in your (academic) work, please cite:
Van Geert, E., Bossens, C., & Wagemans, J. (2021). The Order & Complexity Toolbox for Aesthetics Python library [Computer software].https://github.com/gestaltrevision/OCTA_toolboxIf you use the OCTA Shiny app in your (academic) work, please cite:
Van Geert, E., Bossens, C., & Wagemans, J. (2021). The Order & Complexity Toolbox for Aesthetics Shiny application [Online application].https://elinevg.shinyapps.io/OCTA_toolbox/DocumentationFind the documentationhereLicenseThe OCTA Python toolbox is licensed under the terms of theGNU Lesser General Public License 3.0.Contacteline.vangeert@kuleuven.be
Package: octadocs
octadocsFeaturesFully typed with annotations and checked with mypy,PEP561 compatibleAdd yours!InstallationpipinstalloctadocsLicenseMITCreditsThis project was generated withwemake-python-package. Current template version is:868260c2d659e455bafc2ed4fe242413ef39e4dc. See what isupdatedsince then.
Package: octal8
octal8Convert all base-10 integers to base-8.installationpipinstalloctal8Usageusage: octal8 [-h] [filename ...]

positional arguments:
filename

options:
-h, --help  show this help message and exitThe script will replace al base-10 integers with base-8 integers in the passed
files.As a pre-commit hookSeepre-commitfor more information.Sample.pre-commit-config.yaml:-repo:https://github.com/samueljsb/octal8rev:"v1.2.1"hooks:-id:octal8
Package: octane
A Python library for Octane’s API.SetupYou can install this package by using the pip tool and installing:$ pip install octaneSetting up a Octane AccountSign up for Octane athttps://cloud.getoctane.io/.Using the Octane APIDocumentation for the python bindings can be found alongside Octane’s other bindings here:https://getoctane.io/docshttps://getoctane.io/docs/api/pythonIn the standard documentation (the first link), most of the reference pages will have examples in Octane’s official bindings (including Python). Just click on the Python tab to get the relevant documentation.In the full API reference for python (the second link), the right half of the page will provide example requests and responses for various API calls.
Package: octant
[![LICENSE](https://anaconda.org/dennissergeev/octant/badges/license.svg)](LICENSE)[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)[![Conda](https://anaconda.org/dennissergeev/octant/badges/version.svg)](https://anaconda.org/dennissergeev/octant)[![Build Status](https://travis-ci.com/dennissergeev/octant.svg?branch=master)](https://travis-ci.com/dennissergeev/octant)[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1313078.svg)](https://doi.org/10.5281/zenodo.1313078)# octantObjective Cyclone Tracking ANalysis Tools## Installation`octant` depends on the following packages:- cython- matplotlib- numpy- pandas- xarray### With conda```bashconda install -c dennissergeev octant```### From source```bashgit clone https://github.com/dennissergeev/octant.gitcd octantpython setup.py install```