Saravanan666/pypi-org huggingface dataset:
Package: bootinfo
BootinfoThis tool detects valid boot signatures on storage devices or debugging boot issues on ARM boards.Supported platformsAllwinner A64 (PinePhone, PineTab, etc...)Rockchip RK3399 (Pinebook Pro, PinePhone Pro, Rockpro64)Generic Amlogic (Should work on all meson platforms)The bootinfo command$sudobootinfoFound 'Sunxi/Allwinner eGON header' on /dev/mmcblk0 offset 8192BFound 'Sunxi/Allwinner eGON header far' on /dev/mmcblk2 offset 131072BFound 'Sunxi/Allwinner eGON header mmcboot' on /dev/mmcblk2boot0 offset 0B/dev/mmcblk2boot0 is not marked bootable!Detected a bootloader on the SD, one on the eMMC which is on another offset because GPT and a bootloader on
the mmc boot hardware partition. The boot0 partition is not marked bootable which on Allwinner platforms will
ignore the boot signature.The wipeboot commandThewipebootcommand is designed to have a similar interface towipefsand allows quickly checking for
a bootloader on a specific block device and also to wipe it.$sudowipeboot/dev/mmcblk2Found 'Sunxi/Allwinner eGON header far' on /dev/mmcblk2 offset 131072BTo clear the bootloader add the-aargument. This will zero out the first few bytes of the bootloader
without touching any of the surrounding partition tables etc.$sudowipeboot-a/dev/mmcblk2Found 'Sunxi/Allwinner eGON header far' on /dev/mmcblk2 offset 131072BDo you want to clean the 1 sectors containing boot signatures?Enter to continue, ctrl+c to abortIf you want to temporarily disable the bootloader there's also the-iflag, this will invert all the
bits of the bootloader signature, which will make it undetectable to the actual hardware but is a nice
and reversible operation.$sudowipeboot--all--invert/dev/mmcblk2Found 'Sunxi/Allwinner eGON header far' on /dev/mmcblk2 offset 131072BDo you want to clean the 1 sectors containing boot signatures?Enter to continue, ctrl+c to abortInverted 8192 (Sunxi/Allwinner eGON header)$sudowipeboot/dev/mmcblk2Found 'Sunxi/Allwinner eGON header' on /dev/mmcblk2 offset 8192B (inverted)$sudowipeboot--all--invert/dev/mmcblk2... the same operation restores the bootloader$sudowipeboot/dev/mmcblk2Found 'Sunxi/Allwinner eGON header' on /dev/mmcblk2 offset 8192B
Package: bootle
Bootle: Half-Index Lists for Python“Should array indices start at 0 or 1? My compromise of 0.5 was rejected
without, I thought, proper consideration.” -- Stan Kelly-BootleInstallationpip3installbootleUsagefrombootleimportListxs=List([1,2,3])assertxs[0.5]==1assertxs[:1.5]==[1]xs[1.5]==2assertxs.index(2)==1.5References"Why numbering should start at zero", Edsger W. Dijkstra, 1982Why Numbering Should Start At Zero, WikiWikiWebWhy Numbering Should Start At One,  WikiWikiWebZero-based numbering, WikipediaLicenseWTFPL
Package: bootlegger
Bootlegger is the command line interface for speakeasy, the paranoid file
storage solution.Installation:pip install bootleggeror clone the repo and runpython setup.py installConfiguration:Create a folder in your home directory called .bootlegger.
In this folder, generate private and public RSA keys called user_private.pem
and user_public.pem, respectively. This can be accomplished using openssl.cd ~/.bootlegger
openssl genrsa -out user_private.pem 2048
# add -des3 if you want a passphrase
openssl rsa -pubout -in user_private.pem -out user_public.pemCreate a file in the .bootlegger folder called bootlegger.conf. Add the
following information[speakeasy]
host = www.example.com
username = testuserReplace the values with your desired host and username.Usage:To add your public key to the server, runbl addkeyTo upload a file, runbl upload file.txtYou can give this subcommand multiple argumentsbl upload file1.txt file2.txt …Giving the prefix option prefixes each filename on the serverbl upload file.txt -p xyz # uploads to xyz_file.txtTo list all the files you have stored on the server, runbl listYou can optionally give the list command a Unix typeglob as a parameter to
list only files that match the pattern. Make sure to properly escape to the
glob so that your shell doesn’t expand it.bl list *.txtTo download a file runbl download file.txtIf the file is prefixed, runbl download file.txt -p xyz # downloads xyz_file.txt to file.txtTo download into a directory other than the current working directory runbl download file.txt -d some/other/directoryTo get detailed information about a file, runbl info file.txtTo share a file with another user, runbl share otheruser file.txtTo see the dates of previous versions of the file, runbl versions file.txtYou can override the username and host in the configuration file by passing
arguments to the –username and –host options on the command line.
Package: bootloader-uassets-validator
Unreal Engine Assets Validator LibraryCommand-line Interface (CLI) responsible for validating Unreal Engine asset files.Auassetfileis an asset file used by Unreal Editor. It contains an asset, such as a level, material, animation, sound, or particle system, used in an Unreal Engine game.  Any piece of content in an Unreal Engine project is an asset.OverviewAs you develop projects in Unreal Engine (UE), the list of Assets in your Content Browser will expand.  This runs the risk of creating redundant variations of assets you're experimenting with, or introducing ambiguity with overly similar names.  For example, it is possible for you to have a folder named "Soldier" with a Blueprint, a texture, and a model that all have the name "Soldier" in them, but no clear way to tell which is which in a simple list.For large projects, Epic Games recommends you establish acommon naming conventionfor individual Assets early in development.  This will make it easier for you and your team to locate files and prevent potential conflicts or ambiguity.[AssetTypePrefix]_[AssetName]_[Descriptor]_[OptionalVariantLetterOrNumber]AssetTypePrefixidentifies the type of Asset, refer to the table below for details.AssetNameis the Asset's name.Descriptorprovides additional context for the Asset, to help identify how it is used. For example, whether a texture is a normal map or an opacity map.OptionalVariantLetterOrNumberis optionally used to differentiate between multiple versions or variations of an asset.Consider using this naming convention for your own project's Assets, as it will provide multiple ways for your team to locate an Asset when searching the Content Browser.Recommended Asset PrefixesThis list is not exhaustive, as new features can require new Asset types.  If you are using an Asset type not listed, use the existing list as a guideline for your naming convention for that Asset.ASSETPREFIXGeneralHigh Dynamic Range Image (HDRI)HDR_MaterialM_Material InstanceMI_Physics AssetPHYS_Physics MaterialPM_Post Process MaterialPPM_Skeletal MeshSK_Static MeshSM_TextureT_OCIO ProfileOCIO_BlueprintsActor ComponentAC_Animation BlueprintABP_Blueprint InterfaceBI_BlueprintBP_Curve TableCT_Data TableDT_EnumE_StructureF_Widget BlueprintWBP_Particle EffectsParticle System (Cascade)PS_Niagara EmitterFXE_Niagara SystemFXS_Niagara FunctionFXF_Skeletal Mesh AnimationsRigRig_SkeletonSKEL_MontagesAM_Animation SequenceAS_Blend SpaceBS_In-Camera VFXNDisplay ConfigurationNDC_AnimationLevel SequenceLS_Sequencer EditsEDIT_MediaMedia SourceMS_Media OutputMO_Media PlayerMP_Media ProfileMPR_OtherLevel SnapshotsSNAP_Remote Control PresetRCP_Installationpoetryinstall
poetryshellExecution./validate.py--path~/path/to/human/trainer/assets/root/folderDistributionpoetryshell
poetrypublish--build--username$PYPI_USERNAME--password$PYPI_PASSWORD
Package: bootmachine
Bootmachine is a bootstrapping tool for securely provisioning
virtual servers up until the point where customized configuration
management begins.The bootmachine’s goal is to allow getting started with, maintenance
of, and exploring new stack options through a simple, pluggable and highly
customizable interface.Configuration Management ToolsCurrently supported:Salthttp://saltstack.orgWrite your ownNext in the queue:Chefhttp://www.opscode.com/chef/Puppethttp://puppetlabs.com/Write your ownProvidersCurrently supported:Rackspace Openstack Compute API v2 via python-novaclientNon-rackspace Openstack Compute via python-novaclientRackspace Openstack Compute API v1 via openstack.compute (deprecated)http://www.rackspace.com/cloud/Write your ownNext in the queue:Amazon EC2 via botohttps://aws.amazon.com/ec2/Virtualbox / Vagranthttp://vagrantup.com/Write your ownDistrosCurrently supported:Arch LinuxUbuntuFedoraDebianWrite your ownNext in the queue:FreeBSDGentooopenSUSECentOSRHELWrite your ownDocumentation about the usage and installation of the bootmachine
can be found at:http://bootmachine.readthedocs.orgThe source code and issue tracker can be found on GitHub:https://github.com/rizumu/bootmachine
Package: bootpeg
> Some people, when confronted with a problem, think “I know, I’ll use regular expressions.” Now they have two problems.bootpegis a PEG parser for creating parsers – including itself.
By default, it supports a modified EBNF with actions akin toPEP 617.>>># recreate the bootpeg parser from itself>>>frombootpeg.apiimportimport_parser,PikaActions>>>frombootpeg.grammarsimportbpeg>>>parse_bpeg=bpeg.parse>>>for_inrange(5):...parse_bpeg=import_parser(...bpeg.__name__,actions=PikaActions,dialect=parse_bpeg...)Unlike most other Python PEG parsers which are top-down parsers,bootpegprovides a bottom-upPika parser:
it handles left-recursive grammars natively,
allows recovering partial parse results,
and is guaranteed to run in linear time.
Like any PEG parser,bootpegautomatically
creates unambiguous grammars,
supports infinite lookahead,
and allows to express grammars comfortably.Native support for left-recursion and left-associativity.Builtin error reporting covering multiple failures.Automatic parser generation from a multitude of meta-grammars.This makes it straightforward to implement your own custom grammars without
worrying about their implementation.
To get started using or contributing tobootpeg,
head straight to thebootpeg documentation.Do I need a bigger boot?> Some people, when confronted with a problem, think “I know, I’ll use self-writing parsers.” Now they have recursive problems.If you need a battle-hardened, production ready parser suite
thenpyparsingshould be your first choice.
If you are the choosy type, make it your second choice as well.Pickbootpegwhen you need safe left-recursion and self-parsing.
It will never bite off your left peg via infinite recursion.
It will take care of itself and all its grammars to make you happy.bootpegis the friend you need when you knowbootpegis the friend you need.Well,eventuallyit will be;bootpegis still a cute little puppy.
Don’t let it lift too heavy.
So far it is only lifting itself.
Package: bootplot
bootplotis a package for black-box uncertainty visualization.
By providing a dataset and a plotting function,bootplotautomatically generates a static image and an animation of your uncertainty.The method works by resampling the original dataset using bootstrap and plotting each bootstrapped sample.
The plots are then combined into a single image or an animation.bootplotis also especially useful when dealing with small datasets, since it
relies on the bootstrap method which robustly estimates uncertainty using resampling.bootplotsupports datasets represented as numpy arrays or pandas dataframes.
Supported image output formats include popular formats such as JPG, PNG, BMP. Supported animation formats include popular formats such as GIF and MP4.Installationbootplotrequires Python version 3.8 or greater. You can install it using:pip install bootplotAlternatively, you can installbootplotusing:git clone https://github.com/davidnabergoj/bootplot
cd bootplot
python setup.py installExampleSuppose we have some data and their corresponding targets. We can model our targets with a regression
line and visualize the uncertainty with the following code:importnumpyasnpfromsklearn.linear_modelimportLinearRegressionfrombootplotimportbootplotdefplot_regression(data_subset,data_full,ax):# Plot full datasetax.scatter(data_full[:,0],data_full[:,1])# Plot regression line trained on the subsetlr=LinearRegression()lr.fit(data_subset[:,0].reshape(-1,1),data_subset[:,1])ax.plot([-10,10],lr.predict([[-10],[10]]),c='r')# Show root mean squared error in a text boxrmse=np.sqrt(np.mean(np.square(data_subset[:,1]-lr.predict(data_subset[:,0].reshape(-1,1)))))bbox_kwargs=dict(facecolor='none',edgecolor='black',pad=10.0)ax.text(x=0,y=-8,s=f'RMSE:{rmse:.4f}',fontsize=12,ha='center',bbox=bbox_kwargs)ax.set_xlim(-10,10)ax.set_ylim(-10,10)if__name__=='__main__':np.random.seed(0)# Dataset to be modeleddataset=np.random.randn(100,2)noise=np.random.randn(len(dataset))*2.5dataset[:,1]=dataset[:,0]*1.5+2+noise# Create image and animation that show uncertaintybootplot(plot_regression,dataset,output_image_path='demo_image.png',output_animation_path='demo_animation.gif',verbose=True)This will generate a static image and an animation, as shown below.
The static image on points shows the full scattered dataset in blue and regression lines that correspond to each
bootstrapped sample of the dataset in red.
The spread of regression lines represents uncertainty according to the bootstrap process.
We can also see the uncertainty in root mean squared error (RMSE).
We see that only the first digit of RMSE is significant, since the decimal part is blurred.
The animation on the right displays uncertainty by iterating over a sequence of plots containing regression lines.See theexamplesfolder for more examples, including bar charts, point plots, polynomial regression models, pie charts, text plots and pandas dataframes.DocumentationRead the documentation and check out tutorials athttps://bootplot.readthedocs.io/en/latest/
Package: boot.py
Install and UseInstall with pip.pip install boot.pyCreate a file and importboot. For example this will install a virtual
environment, install requirements, and create some files.#!/usr/bin/env python3importosimportvenvfrombootimportstep,runfrompathlibimportPathroot_path=Path(__file__).parent.resolve()venv_dir=root_path/'.venv'withstep(f'Creating virtualenv in{venv_dir.name}'):ifnotvenv_dir.exists():venv.create(venv_dir,with_pip=True)withstep('Installing requirements'):run(f'{venv_dir/"bin/pip"}install -r requirements.txt')withstep('Creating directories'):run(f'mkdir -p public/media')run(f'mkdir -p public/static')withstep('Environment file'):envfile=root_path/'.env'ifnotenvfile.exists():withopen(envfile,'w')ashandle:os.chmod(envfile,0o600)handle.write('')This will output.$./script.pyCreating virtualenv in .venv ... [Ok]
Installing requirements ... [Ok]
Installing project ... [Ok]
Creating directories ... [Ok]
Environment file ... [Ok]Simple!You can also compose tasks to decide what to execute and what order.#!/usr/bin/env python3importosimportvenvfrombootimportstep,run,taskfrompathlibimportPathroot_path=Path(__file__).parent.resolve()venv_dir=root_path/'.venv'@taskdefbuild(this)withstep(f'Creating virtualenv in{venv_dir.name}'):ifnotvenv_dir.exists():venv.create(venv_dir,with_pip=True)withstep('Creating directories'):run(f'mkdir -p public/media')run(f'mkdir -p public/static')withstep('Environment file'):envfile=root_path/'.env'ifnotenvfile.exists():withopen(envfile,'w')ashandle:os.chmod(envfile,0o600)handle.write('')@taskdefrequirements(this)withstep('Installing requirements'):run(f'{venv_dir/"bin/pip"}install -r requirements.txt')@taskdefbackup(this)withstep(f'Backup db'):run('pg_dump -d database -f output.sql')if__name__=='__main__':tasks={'default':build>>requirements,'build':build,'requirements':requirements,}iflen(sys.argv)==1:ifsys.argv[0]intasks:tasks[sys.argv[0]]()else:print(f'Unknown task:{sys.argv[0]}')print(f'Available tasks are:{tasks.keys()}')else:default()There are helpers to build scripts with less code, for example
we can replace in the code above the main call with a
a simple task argument parser:fromboot.cliimportActionsCommandif__name__=='__main__':ActionsCommand.main(default=build>>requirements,build=build,requirements=requirements,}This parse–help
Package: boots
🥾 Boots 👢 - A Tiny Bootstrapping LibraryThis is a tiny library for doing bootstrap sampling and estimating. It pulls together various tricks to make the process as fast and painless as possible. The tricks included are:Parallel execution withjoblibThe Bayesian bootstrapwith two-level sampling.TheVose methodfor fast weighted sampling with replacementInstallpipinstallbootsFor development:pipinstallgit+https://github.com/pmbaumgartner/bootsExamplefrombootsimportbootstrapimportnumpyasnpx=np.random.pareto(2,100)samples=bootstrap(data=x,statistic=np.median,n_iterations=1000,seed=1234,n_jobs=-1)# bayesian two-level w/ 4 parallel jobssamples=bootstrap(data=x,statistic=np.median,n_iterations=1000,seed=1234,n_jobs=4,bayesian=True)# do something with itimportpandasaspdposterior=pd.Series(samples)posterior.describe(percentiles=[0.025,0.5,0.975])Paired Statisticsfrombootsimportbootstrapimportnumpyasnp# generate some fake correlated data by sorting two arrays and adding some noisea=np.sort(np.random.normal(0,1,100))+np.random.normal(0,1,100)b=np.sort(np.random.normal(0,1,100))+np.random.normal(0,1,100)pairs=list(zip(a,b))# for paired (or row-wise) metrics you might need to# create a wrapper function that unpacks# each row's values into array arguments for your metric functiondefcorr_unwrap(pairs):a1,a2=zip(*pairs)corr=np.corrcoef(a1,a2)[0,1]returncorrsamples=bootstrap(data=pairs,statistic=corr_unwrap,n_iterations=1000,seed=1234,n_jobs=-1,bayesian=True)importpandasaspdposterior=pd.Series(samples)posterior.describe(percentiles=[0.025,0.5,0.975])
Package: bootstrap3-datetime
This package uses Bootstrap v3 datetimepicker widget version 2 provided by the following project:https://github.com/Eonasdan/bootstrap-datetimepickerThe correct formatting options for dates can be found here:http://momentjs.com/docs/It works only with Bootstrap3. If you are using Bootstrap2 in your
Django project, check out this:https://github.com/zokis/django-bootstrap-datetimepickerInstallRunpip installbootstrap3-datetimeAdd'bootstrap3_datetime'to yourINSTALLED_APPSExampleforms.pyfrom bootstrap3_datetime.widgets import DateTimePicker
from django import forms

class ToDoForm(forms.Form):
    todo = forms.CharField(
        widget=forms.TextInput(attrs={"class": "form-control"}))
    date = forms.DateField(
        widget=DateTimePicker(options={"format": "YYYY-MM-DD",
                                       "pickTime": False}))
    reminder = forms.DateTimeField(
        required=False,
        widget=DateTimePicker(options={"format": "YYYY-MM-DD HH:mm",
                                       "pickSeconds": False}))
Package: bootstrap4-nav
This library was created to make django work with some generic bootstrap4 templates. This library uses the basic
functionality from django-bootstrap4. I use it to match templates with mydjango_materialize_navlibrary.SetupInstall the library.# project/settings.pyINSTALLED_APPS=["bootstrap4_nav",...]Setup Context ProcessorsBootstrap4_nav comes with a context processor to use some settings to change the default base styling.# Context Processor to work with settingsTEMPLATES=[{...'OPTIONS':{'context_processors':[...'bootstrap4_nav.context_processors.get_context',],},},]Alternative way to get the standard context for views# views.pyfrombootstrap4_nav.context_processorsimportget_contextdefshow_page(request):# Get the context with the style settingscontext=get_context(site_name='demo',title='Basic Content')context["object"]="MyObject"returnrender(request,"my_page.html",context)StyleThe base template can be used by extending the materialize base nav.{% extends "bootstrap4_nav/base.html" %}


{% block nav_items %}<liclass="navbar-item{% if title == 'Page1' %} active{% endif %}"><aclass="nav-link"href="/">Page1</a></li><liclass="navbar-item{% if title == 'Page2' %} active{% endif %}"><aclass="nav-link"href="/">Page2</a></li><liclass="navbar-item{% if title == 'Page3' %} active{% endif %}"><aclass="nav-link"href="/">Page3</a></li>{% endblock %}

{% block contents %}<div><p>My Content goes here</p></div>{% endblock %}Styling controlsBootstrap4_nav comes with several style options used in the template context variables listed below.BOOTSTRAP4_SITE_NAMEBOOTSTRAP4_TITLEIf you went through theSetup Context Processorsstep then you can modify several settings to change the default style.
This is an alternative to manually providing all of the template context variables.# settings.pyBOOTSTRAP4_SITE_NAME=None# Display this name in the navbar as the main nameBOOTSTRAP4_TITLE=None# This is the page title displayed as the browser tab name
Package: bootstrap-admin
If you’re looking for a version compatible with Django 1.8 just install0.3.7.1.FeaturesResponsiveSidebar MenuEasy install / setupSupport Django1.11and2.1Bootstrap 3Python 3ScreenshotsMore screenshotsINSTALLfrom pypi (recommended)$ pip install bootstrap-adminAnd don’t forget to addbootstrap_admininINSTALLED_APPSbefore
thedjango.contrib.admin.Example:INSTALLED_APPS=(# ...'bootstrap_admin',# always before django.contrib.admin'django.contrib.admin',# ...)CUSTOMIZESidebar MenuIt is enabled by default. But if you removedjango.template.context_processors.requestfrom yourcontext_processors.Just disable it:BOOTSTRAP_ADMIN_SIDEBAR_MENU=FalseBranding - Overriding logoIf you want to use your own logo, you can achieve this by overriding thelogin.htmlandbase_site.html, just like in Django Admin.First, make sure theTEMPLATESsetting in your settings.py is properly configured:TEMPLATES=[{'BACKEND':'django.template.backends.django.DjangoTemplates','DIRS':[os.path.join(BASE_DIR,'my_django_project/templates')],'APP_DIRS':True,# other stuff},]DIRS: You must set the location of your templates, an absolute path.I’m assumingBASE_DIRis:BASE_DIR=os.path.dirname(os.path.dirname(os.path.abspath(__file__)))This pattern of creating a global templates folder could be useful for you to use for yourbase.htmland other global templates.More info:https://docs.djangoproject.com/en/2.1/ref/templates/api/#configuring-an-engineLet me show you a project structure as an example:├── my_django_project
│   ├── core
│   │   ├── admin.py
│   │   ├── apps.py
│   │   ├── models.py
│   │   ├── tests.py
│   │   └── views.py
│   ├── settings.py
│   ├── templates
│   │   └── admin
│   │       ├── base_site.html
│   │       └── login.html
│   ├── urls.py
│   └── wsgi.py
├── manage.pyYou can see I created a globaltemplates/folder,
with another directory insideadmin/containinglogin.htmlandbase_site.html.Their respective contents are:base_site.html{% extends 'admin/base_site.html' %}
{% load static %}

{% block branding %}<ahref="{% url 'admin:index' %}"class="django-admin-logo"><!-- Django Administration --><imgheight="60"src="{% static "bootstrap_admin/img/logo-140x60.png"%}"alt="{{ site_header|default:_('Django administration') }}"></a>{% endblock branding %}login.html{% extends 'admin/login.html' %}
{% load i18n static %}

{% block branding %}<ahref="{% url 'admin:index' %}"class="django-admin-logo"><!-- Django Administration --><imgheight="60"src="{% static "bootstrap_admin/img/logo-140x60.png"%}"alt="{{ site_header|default:_('Django administration') }}"></a>{% endblock branding %}More info:https://docs.djangoproject.com/en/2.1/ref/contrib/admin/#admin-overriding-templatesContributingFork it!Create your feature branch:git checkout-bmy-new-featureCommit your changes:git commit-am'Add some feature'Push to the branch:git push originmy-new-featureSubmit a pull request =]See thefull listof contributors.Open an issueif you find a bug or want something more.
Package: bootstrap_admin_legacy
django-admin-bootstrap-legacy is a Custom Responsible Skin for Django Admin 1.7 and upper.Featuresa bit of responsivenesssearch directly from the apps listsidebar logs for specific app (on app index)django-mptt custom templatesdjango-reversion and django-reversion-compare custom templatesInstallNOTE:I’m assuming you usepipto
install the Python Packages.$ pip install bootstrap_admin_legacyor from github master branch$ pip install git+https://github.com/alrusdi/django-admin-bootstrap-legacy.gitAnd don’t forget to addbootstrap_admininINSTALLED_APPSbefore
thedjango.contrib.admin.Example:INSTALLED_APPS = (
    # ...
    'bootstrap_admin',
    'django.contrib.admin',
    # ...
 )