Saravanan666/pypi-org huggingface dataset:
Package: hcaptcha-challenger
hCaptcha Challenger🚀 Gracefully face hCaptcha challenge with MoE(ONNX) embedded solution.IntroductionDoes not rely on any Tampermonkey script.Does not use any third-party anti-captcha services.Just implement some interfaces to makeAI vs AIpossible.What's featuresChallenge TypePluggable Resourceimage_label_binaryResNet  ONNX classification#challengeimage_label_area_select: pointYOLOv8 ONNX detection#588image_label_area_select: bounding boxYOLOv8 ONNX segmentation#592image_label_multiple_choiceViT ONNX zero-shot motion#917Advanced TaskPluggable ResourceRank.Strategy#nested-model-zooself-supervised challenge#CLIP-ViTWorkflowTasksResourceci: sentinelci: collectordatasets: VCS, annoate#roboflow,#model-factorymodel: ResNet - train / valmodel: YOLOv8 - train / valmodel: upload, upgrade#objects,#modelhubdatasets: public, archive#roboflow-universe,#captcha-datasetsContributorsI would like to express my sincere gratitude to all the contributors.What's nextDislock, the most advanced Discord Browser Generator. Powered by hCaptcha Solving AI.undetected-playwright, stash the fingerprint of playwright-based web agents.epic-awesome-gamer, gracefully claim weekly free games from Epic Store.Referencemicrosoft/playwright-pythonultrafunkamsterdam/undetected-chromedriverhCaptcha challenge template site@maximedrn
Package: hcaptcha-solver
hcaptcha-solvera lightweight Python library for solving hCaptcha challenges with selenium and neural networksNOTE: this package is still in early development.If you encounter any issues or unexpected behaviours, please report them!Installationpipinstallhcaptcha-solverUsagefromhcaptcha_solverimporthcaptcha_solverfromseleniumimportwebdriver# setup chromedriver in english (other languages not supported yet)options=webdriver.ChromeOptions()options.add_experimental_option('prefs',{'intl.accept_languages':'en,en_US'})driver=webdriver.Chrome(options=options)driver.get("https://accounts.hcaptcha.com/demo")# open any url with hCaptcha# create Captcha_Solver object and solve hCaptchacaptcha_solver=hcaptcha_solver.Captcha_Solver(verbose=True)captcha_solver.is_captcha_present(driver)# returns Truecaptcha_solver.solve_captcha(driver)# solves the hCaptchaFunctionalityOnly V1 hCaptchas are supported - any other captcha types will be skipped.The correct images are selected using Convolutional Neural Networks trained on labeled hCaptcha data.The models are chosen by inspecting the captcha header, so the language has to be english in order for the matching to work. (SeeIssue #6)The package features models for a handful of hCaptcha tasks. The currently available models and their labeling accuracies are visualized in the figure below. The accuracy was measured on limited data and is therefore not exact.Functionality for V2 captchasis planned in a similar way to V1 captchas.Current Model Labeling PerformanceCurrent Data AvailabilityContributingIf you encounter any bug, error or unexpected behaviour in general, please report them with an issue giving as much detail as possible - I will try to make this package easy-to-use for everyone.Forks and pull requests are very welcome. You can also create issues to discuss possible changes or improvements.To help collecting captchas, rundev/main.ipynband submit the results. In this notebook you can also explore the data availability and train models.updated 15/08/2023
Package: hccEncoding
Welcome to hccEncoding DocumentationThis is just a example project for demonstration purpose.Quick LinksGitHub HomepageOnline DocumentationPyPI downloadInstallIssue submit and feature requestAPI reference and source codeInstallhccEncodingis released on PyPI, so all you need is:$pipinstallhccEncodingTo upgrade to latest version:$pipinstall--upgradehccEncoding
Package: hcc-topbar-buttons
Workbench custom buttonsLogout Button for JupyterLabRequirementsJupyterLab >= 3.0Installpipinstalljupyterlab-logoutContributingSetup dev environmentmambacreate-njlpm-cconda-forge--yes"python=3.10""nodejs=14""jupyterlab=3""jupyterlab-topbar>=0.6.0""jupyter""notebook""yarn"mambaactivatejlpm

jlpminstallRun lint checks after editing code:jlpmruneslint:checkInstall from dev branchpython3-mpipinstall"git+https://github.com/huntdatacenter/jupyterlab-logout.git@dev"Development installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the jupyterlab-logout directory# Install package in development modepipinstall-e.# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Rebuild extension Typescript source after making changesjlpmrunbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmrunwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm run buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseUninstallpipuninstalljupyterlab-logout
Package: hcdel
Deletes files (hardcore mode - Windows only)Recursive deletion:The function can recursively delete files and directories, ensuring that
all nested files within a given path are removed.Dry run option (enabled by default!!):The dryrun argument allows users to preview the files that would be deleted without actually performing the deletion.
This can help verify the list of files before proceeding
with the actual deletion.Print files option (enabled by default - can't be disabled when running with dryrun):The print_files argument enables users to see the files and directories being deleted.
This can be useful for logging or providing feedback during the deletion process.pendmoves.exe to delete everything:When dealing with stubborn files that cannot be deleted through normal means,
PendMoveshttps://learn.microsoft.com/en-us/sysinternals/downloads/pendmoveshelps in cleaning up such files effectively.
It ensures that unwanted files are eventually removed (next reboot),
preventing them from occupying unnecessary disk space
or causing conflicts in the system.Integration and customization:The function can be easily integrated into existing scripts or applications.
The arguments provide flexibility to customize the deletion process based
on specific requirements. A compiled exe file is also available:https://github.com/hansalemaos/hcdel/raw/main/hcdel.exeIn Python# For security reasons, dryrun is always enabled, and always prints all files that would be deleted!fromhcdel.hcdelimportdelallfilesdelallfiles(path=r'C:\delfiles',dryrun=False,print_files=True)# OutputDeleting:C:\delfiles\xff1fdx.mkvDeleting:C:\delfiles\xfffdx.mkvDeleting:C:\delfiles\xfffxxxxxxxdxxxddddddddd(2).mkvDeleting:C:\delfiles\xfffxxxxxxxdxxxddddddddd.mkvDeleting:C:\delfiles\xffxxxxaaxdx.mkvThefollowingfileswillbedeletedthenextreboot:# i kept this file open in my media playerC:\delfiles\xfffxxxxxxxdxxxddddddddd.mkvCLI# For security reasons, dryrun is always enabled, and always prints all files that would be deleted!
# https://github.com/hansalemaos/hcdel/raw/main/hcdel.exe

hcdel.exe --path "C:\delfiles" --dryrun 0 --print_files 1Argumentsdelallfiles(path:str|None=None,dryrun:int|bool=1,print_files:int|bool=1):r"""Recursively deletes files and directories.Args:path (str | None, optional): The path to the directory or file to be deleted. If None or '', the script exits with code 1. Defaults to None.dryrun (int | bool, optional): If set to 1 or True, performs a dry run and only prints the files that would be deleted without actually deleting them. If set to 0 or False, deletes the files and directories. Defaults to 1.print_files (int | bool, optional): If set to 1 or True, prints the files and directories being deleted. Defaults to 1.Returns:NoneRaises:None
Package: hcdk-eks
Halloumi EKS for the CDKEKS library for the Halloumi modules of the AWS CDKInstallationpip install hcdk_eksUsageHalloumi EKS can be used as a basis to deploy EKS clusters with managed Nodegroups on AWS using the CDK.Passing your own VPCExampleWithin a sample stack, the following example code should be present for minimum functionality.self.eks_cluster_public_subnet_name='eks_public'self.eks_cluster_private_subnet_name='eks_private'self.eks_cluster_name='EksCluster'self.eks_stack_name='eks-cluster-stack'# prerequisites for EKSself.vpc=ec2.Vpc(self,'Vpc',cidr='10.0.0.0/16',max_azs=99,# use all available AZs,subnet_configuration=[{'cidrMask':26,'name':self.eks_cluster_public_subnet_name,'subnetType':ec2.SubnetType.PUBLIC},{'cidrMask':24,'name':self.eks_cluster_private_subnet_name,'subnetType':ec2.SubnetType.PRIVATE}])# Add necessary tags to subnets for the EKS Clusterprivate_eks_subnets=self.vpc.select_subnets(subnet_name=self.eks_cluster_private_subnet_name).subnetsforsubnetinprivate_eks_subnets:core.Tag.add(subnet,key=f'kubernetes.io/cluster/{self.eks_cluster_name}',value='shared')core.Tag.add(subnet,key=f'kubernetes.io/role/internal-elb',value='1')# Add necessary tags to subnets for the EKS Clusterpublic_eks_subnets=self.vpc.select_subnets(subnet_name=self.eks_cluster_public_subnet_name).subnetsforsubnetinpublic_eks_subnets:core.Tag.add(subnet,key=f'kubernetes.io/cluster/{self.eks_cluster_name}',value='shared')core.Tag.add(subnet,key=f'kubernetes.io/role/elb',value='1')EKS ClusterExamplefromhcdk_eksimportHalloumiEksClusterapp=core.App()sample_stack=SampleAppStack(app,"sample-app")__config_eks_cluster={'stack_name':sample_stack.eks_stack_name,'eks_cluster_public_subnet_name':sample_stack.eks_cluster_public_subnet_name,'eks_cluster_private_subnet_name':sample_stack.eks_cluster_private_subnet_name,'eks_cluster_name':sample_stack.eks_cluster_name,'kubernetes_version':'1.14','nodegroups':{'nodegroup1':{'instance_types':['t3.large']},'nodegroup2':{'instance_types':['t3.xlarge']}}}eks_stack=cfn.NestedStack(sample_stack,'eks-stack')HalloumiEksCluster(scope=eks_stack,vpc=sample_stack.vpc,config=__config_eks_cluster)app.synth()Using the VPC from the moduleExamplefromhcdk_eksimportHalloumiEksClusterapp=core.App()sample_stack=SampleAppStack(app,"sample-app")__config_eks_cluster={'nodegroups':{'nodegroup1':{'instance_types':['t3.large']},'nodegroup2':{'instance_types':['t3.xlarge']}}}# EKS Cluster Stackeks_cluster_stack=cfn.NestedStack(sample_stack,'eks-cluster-stack')eks_cluster=HalloumiEksCluster(scope=eks_cluster_stack,config=__config_eks_cluster)synth=app.synth()
Package: hcf-backend
HCF (HubStorage Crawl Frontier) Backend for FronteraWhen used with scrapy, use it with Scrapy Scheduler provided byscrapy-frontera. Scrapy scheduler provided
byFronterais notsupported.scrapy-fronterais a scrapy scheduler which allows to use frontera backends,
like the present one, with scrapy projects.See specific usage instructions at module and class docstrings atbackend.py.
Some examples of usage can be seen in thescrapy-frontera README.A complete tutorial for usinghcf-backendwith ScrapyCloud workflows is available atshub-workflow Tutorial: Managing Hubstorage Crawl Frontiers.shub-workflowis a framework for
defining workflows of spiders and scripts running over ScrapyCloud. This is a strongly recommended lecture, because it documents the integration of different tools
which together provide the best benefit.Package also provides a convenient command line tool for hubstorage frontier handling and manipulation:hcfpal.py. It supports dumping, count, deletion, moving, listing, etc.
See command line help for usage.Another provided tool iscrawlmanager.py. It facilitates the
scheduling of consumer spider jobs. Examples of usage are also available in the already mentionedshub-workflowTutorial.Installationpip install hcf-backendDevelopment environment setupFor hcf-backend developers, Pipfile files are provided for a development environment.Run:$ pipenv install --dev
$ pipenv shell
$ cp .envtemplate .envand edit .env accordingly
Package: hcft
High-Cycle-Fatigue-Tool (HCFT or HcFatFit)A tool with GUI (Graphical User Interface) for processing CSV files obtained from fatigue experiments up to the high-cycle fatigue ranges. Additionally, tests with monotonic loading can be processed.Features:Simple plot functionality for columns of the CSV file.Extracting Max and Min values and filtering the undesired cycles.Extracting and plotting the fatigue creep curve (cycles number vs displacement).Smoothing function for fatigue creep curves.Ability to process file with +20 Gb size.Built-in tool for joining CSV (or TXT) files.Graphical User Interface with all functions and parametersUsage:Option 1 (Installing Python environment with all needed libraries)Install Miniconda(download link).Perform the following commands from Anaconda Command Prompt to install the required libraries:conda install -c anaconda matplotlibconda install -c anaconda scipyconda install -c anaconda pandasconda install -c anaconda traitsconda install -c anaconda traitsuiClone this repository or download its contentsRun the tool using the commandpython PATH_TO_THE_TOOL_REPOSITORY/hcft.pyOption 2 (Direct install of the tool from the exe installer file)You can download and install the tool on Windows using on of these installers:Windows 64bit:hcft_v1.0_64bit.exeWindows 32bit:hcft_v1.0_32bit.exeCite with:The repository can refered to using a unique doi hosted athttps://zenodo.orgScreenshots:
Package: hc-go-plugin-server
hc-go-plugin-serverPython server for HashiCorp's go-plugin (RPCPlugin)DON'T use this yet if you aren't me, trust me.DevelopmentSync/Async variantsThe sync variant of the API is automatically generated from the async one
usingunasync. With dev dependencies
installed, you can regenerate them by runningrun_unasync.pyas a Python
script (e.g. viapoetry run run_unasync.py).
Package: hchacha
hchacha - Human CHromosome Accession CHangeTranslate among the different naming systems used for human chromosomes (of the same assembly)BackgroundThere are a number of different groups that participant in and/or provide reference human sequence
data from theGenome Reference Consortium. However, the same reference
sequence data for each chromosome get accessioned under different identifiers. This script converts
among these identifiers (just within versions-- this is not a crossMap or liftOver), for several
commonly-used file formats, including VCF, SAM, FASTA, chain files...Why? Well, there are several conventions for the naming of human chromosomes. The "ensembl" style
numbers them 1-22 then X and Y. The "ucsc" style (named after the UCSC genome browser, also
used in GATK's reference bundles) prepends these with 'chr'. However, a downside of both of these
is that '11' or 'chr11' do not uniquely identify a sequence (although they may in the context
of a specific assembly version like GRCh38.p13. On the other hand, 'NC_000011.10' is a specific
accessioned sequence (which happens to be the chromosome 11 sequence version used in the
GRCh38 primary assembly. Likewise, the genbank accession rather than the refseq accession could
be used.Exampleshchacha --helpzcat input.vcf.gz | hchacha vcf -a 37 -t ensembl | bgzip -c > output.vcf.gzsamtools view -h input.bam | hchacha sam -a 38 -t refseq | samtools view -b > output.bamSmarter handling for BAM/CRAM filesSince all you are doing is really renaming the sequences in the header (and individual BAM/CRAM records
refer back to those sequence names by an integer index), you can do things much more quickly and with
less CPU usage usingsamtools reheaderif it is available on your system.For example:samtoolsreheader-P-c'hchacha sam -a 38 -t ucsc -s'input.bam>output.bamWith some clever use of theteecommand to output the new bam file and continue the shell pipeline
going, you can even make the new index at the same time:samtoolsreheader-P-c'hchacha sam -a 38 -t ucsc -s'input.bam|teeoutput.bam|samtoolsindex-output.bam.baiData usedNCBI provides a useful file (*.assembly_report.txt) for different GRCh reference versions and patch
levels, for instancehere,
that maps among these names. To get the data included in the repository (for GRCh versions 37 and 38), I
ran the bash scriptget-assembly-reports.bash(requires curl) whichh writes files tosrc/hchacha/data.Mapping for ensembl namesThe mapping to ensEMBL names is not quite as straightforward. It looks
like they use the "short" names (like 1, 2, 3, ... X, Y) for the primary chromosomes, then RefSeq
accessions for the others, so that is what this script does.LicenseMIT license, but I am open to re-licensing this simple to script some other way if you have a good reason.It is my understandig that data derived from RefSeq/NCBI are in the public domain as the work
product of an institution of the governement of the United States of America.Samtools (included as part of the docker image) is MIT/Expat licensed and Copyright (C) 2008-2023 Genome Research Ltd.
Package: hchiam
Hi there! 🔍hchiam.comHere's some GitHub stats:resume.github.io/?hchiamSome fun explorations:Generate form template code without typing code.Get the percent similarity between sentences.Build super-powered Google docs.Make anything draggable and editable (with keyboard accessibility in mind).Get automated code suggestions.Draw without a touchpad/pen.Learn web accessibility.Explore code API with AI.Map out file dependencies.Scan website scripts with URLVoid via a Firefox extension.Get anonymous input while teaching.Learn random JS tidbits.Auto-generate project code/setup.Make a custom VSCode linter.
Andlearn more!Always be
Package: hciexport
Thehciexporttool facilitates the APIs provided byHitachi Content Intelligenc(HCI) to export Workflow bundles
and System configuration packages.The functionality as such is also available through the HCI GUIs,
but sometimes, one want to be able to export them as part of an
automated task (backup), where using the APIs is more appropriate.FeaturesExport a complete Workflow bundleExport the complete System configurationDependenciesYou need to have at least Python 3.7 installed to runhciexport.It depends on thehttpxfor
communication with HCI.DocumentationTo be found atreadthedocs.orgInstallationInstallhciexportby running:$ pip install hciexport-or-get the source fromgitlab.com,
unzip and run:$ python setup.py install-or-Fork atgitlab.comContributeSource Code:https://gitlab.com/simont3/hciexportIssue tracker:https://gitlab.com/simont3/hciexport/issuesSupportIf you’ve found any bugs, please let me know via the Issue Tracker;
if you have comments or suggestions, send an email tomailto:sw@snomis.euLicenseThe MIT License (MIT)Copyright (c) 2020 Thorsten Simons (sw@snomis.eu)Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the “Software”), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: hciplot
HCIplotHCIplot-- High-contrast Imaging Plotting library. The goal of this
library is to be the "Swiss army" solution for plotting and visualizing
multi-dimensional high-contrast imaging datacubes onJupyterLab.
While visualizing FITS files is straightforward with SaoImage DS9 or any
other FITS viewer, exploring the content of an HCI datacube as an
in-memorynumpyarray (for example when running yourJupytersession on a remote machine) is far from easy.HCIplotcontains two functions,plot_framesandplot_cubes,
and relies on thematplotlibandHoloViewslibraries andImageMagick.HCIplotallows to:Plot a single frame (2d array) or create a mosaic of frames.Annotate and save publication ready frames/mosaics.Visualize 2d arrays as surface plots.Create interactive plots when handling 3d or 4d arrays (thanks toHoloViews)Save to disk a 3d array as an animation (gif or mp4).InstallationYou can installHCIplotwithpip:pip install hciplotJupyterLabcan be installed either withpipor withconda:conda install -c conda-forge jupyterlabThePyVizextension must be installed to display theholoviewswidgets onJupyterLab:jupyter labextension install @pyviz/jupyterlab_pyvizIf you want to create animations withplot_cubesyou need to installImageMagickwith your system's package manager (e.g. brew if you are
on MacOS or apt-get if you are on Ubuntu).
Package: hci-protocol
# HCI ProtocolThis is a Python package for parsing and building HCI packets.HCI (Host Controller Interface) is the protocol used for communications between a BT/BLE controller (i.e. USB dongle) and a host computer such as a RPi.Currently **only part of the protocol is implemented in this package**## Usage Examples1. Hci Sniffer (Linux only): `python -m hci_protocol.hci_sniffer --hci 0`2. Building a packet:```pythonfrom hci_protocol import hci_functionshci_functions.create_le_connection_comlete_packet(peer_address='AA:BB:CC:DD:EE:FF', connection_handle=70)# ==> '\x04>\x13\x01\x00F\x00\x00\x01\xff\xee\xdd\xcc\xbb\xaa8\x00\x00\x00*\x00\x00'```3. Parsing a packet:```pythonfrom hci_protocol.hci_protocol import HciPacketprint HciPacket.parse('\x04>\x13\x01\x00F\x00\x00\x01\xff\xee\xdd\xcc\xbb\xaa8\x00\x00\x00*\x00\x00')# ==>#  Container:#      type = EVENT_PACKET (total 12)#      payload = Container:#          event = LE_META_EVENT (total 13)#          length = 19#          payload = Container:#              subevent = LE_CONNECTION_COMPLETED (total 23)#              payload = Container:#                  status = 0#                  handle = 70#                  role = 0#                  peer_bdaddr_type = 1#                  peer_bdaddr = aa:bb:cc:dd:ee:ff (total 17)#                  interval = 56#                  latency = 0#                  supervision_timeout = 42#                  master_clock_accuracy = 0```## ContributeThis package is in a preliminary stage and there is still a lot of work to do. Feel free to fork and submit your pull requests.For more information about the HCI protocol, check out the [Blutooth Core Specifications](https://www.bluetooth.org/DocMan/handlers/DownloadDoc.ashx?doc_id=421043&_ga=2.29692863.121228451.1498147116-1432843607.1484151012)