Saravanan666/pypi-org huggingface dataset:
Package: koansys.django.authradius
READMEAllow Django to authenticate against a RADIUS server.IntroductionRADIUS is a protocol commonly used by ISPs for authenticating dial-in
and other remote users; it’s also used by routers and other network
hardware.  Popular servers include FreeRADIUS, GNU RADIUS, and the
delightfully-name Steel Belted RADIUS.MotivationThis little package was developed because my place of work uses RSA
SecurID token authentication, and it can be accessed via RADIUS –
much more easily than their proprietary protocol.All the heavy lifting here is doing by Wichert Akkerman’s “pyrad”
package; this just wraps it up for easy consumption by Django.The code was based on the example athttp://docs.djangoproject.com/en/dev/topics/auth/#other-authentication-sourcesThis code tries hard to catch any error which might throw an exception
so that failure of the backend (misconfigured RADIUS server, bad
import, etc) returns None indicating auth faiure.On successful authentication, the User object is returned. If this
user is new to Django, a new User is created in the Django database.Non-FeaturesTraditionally, upon authentication, the RADIUS server can return
various attribute/value pairs such as allocated IP address and
subnetmask, in addition to the Success code.  ADIUS can also handle
“accounting” the focus here simply on authentication.UsageConfigurationIn your settings.py or local_settings.py, define the following
variables:RADIUS_SERVERThe IP address (or resolvable DNS name) of the server providing the
RADIUS server.  Example: “127.0.0.1”RADIUS_AUTHPORTUDP port that RADIUS is listening on for authentication requests.
The old RFC standard port is 1645, but the more current one
is 1812. Specify it as an integer. Example: 1812RADIUS_SECRETThe shared secret that both the client and server use to encode the
packets.  Example: “The owls are not what they seem.”Auth backendsSpecify this egg in your zc.buildout configuration, or another build
mechanism; you can also just use the bare code.In your settings.py (or local_settings.py) file specify the module and
class path in the authentication stack.  Beware that RADIUS typically
exhibits a 20-second or so timeout if it can’t auth to the server, so
you may want to put it after other authentication backends you may be
using.  Example:AUTHENTICATION_BACKENDS = (
    'django.contrib.auth.backends.ModelBackend',
    'authbackends.authsawsbackend.AuthSawsBackend',
    'koansys.django.authradius.AuthRadius',
  )To DoTests. Sorry.CHANGES1.0.3 2009-02-25Correct usage example, oops.1.0.2 2009-02-25Re-Fix URL info, add address.1.0.1 2009-02-25Fix URL info, upload to googlecode, post to pypi.1.0.0 2009-02-25Creating public egg code from internal private cholesterol-free code.
Package: koansys.recipe.elasticsearch
A brief documentationThis recipe takes a number of options:urlThe URL to download the jar.TestsWe will define a buildout template used by the recipe:>>> buildout_cfg = """
... [buildout]
... parts = elasticsearch
...
... [elasticsearch]
... recipe = koansys.recipe.elasticsearch
... url = http://github.com/downloads/elasticsearch/elasticsearch/elasticsearch-0.13.0.tar.gz
... """We’ll start by creating a buildout:>>> import os.path
>>> write('buildout.cfg', buildout_cfg)Running the buildout gives us:>>> output = system(buildout)
>>> 'koansys.recipe.elasticsearch: downloading elasticsearch distribution...' in output
TrueCheck whether the binaries are copied:>>> set(os.listdir('bin')).issuperset(['elasticsearch'])
TrueA start script with the format ‘start_PART-NAME_mongod.sh’ should be generated.>>> 'start_elasticsearch.sh' in os.listdir('bin')
TrueIt is possible to change the name of this start script with the ‘script_name’
option. Furthermore all options of mongod (version v1.6.0) are supported via
buildout options. A more comprehensive recipe could be for example:>>> buildout_cfg = """
... [buildout]
... parts = elasticsearch.sh
... [elasticsearch]
... recipe = koansys.recipe.elasticsearch
... url = http://github.com/downloads/elasticsearch/elasticsearch/elasticsearch-0.13.0.tar.gz
... script_name = start_es.sh
... quiet=true
... fork=true
... logpath=${buildout:parts-directory}/elasticsearch/log
... dbpath=${buildout:parts-directory}/elasticsearch/data
... """1.0.2 2013-01-17PyPI release1.0.0 2010-11-30Initial release
Package: koansys.recipe.hooks
Supported options=================hooksCustom python script(s) and method(s) that will be executed.The format of the options is::/path/to/the/module.py:name_of_callablewhere the first part is a filesystem path to the python module andthe second part is the name of the callable in the module thatwill be called. The callable will be passed two parameters: the``options`` dictionary from the recipe and the global ``buildout``dictionary. The callable is not expected to return anything.This code was essentially ripped out of plone.recipe.command_and hexagonit.recipe.cmmi_.. _plone.recipe.command  : http://dev.plone.org/collective/browser/buildout/plone.recipe.command.. _hexagonit.recipe.cmmi : http://pypi.python.org/pypi/hexagonit.recipe.cmmiExample usage=============It can be helpful to define in [buildout] a::hooks = ${buildout:directory}/hooksthen invoke like::[your_part_section]hooks = ${buildout:hooks}/hookfile.py:methodnameThe value of 'hooks' can be a whitespace-separated list offiles:methods to specify multiple hooks that are executed inorder.  You can also specify options that can be used in yourhooks.  Example::[your_part_section]hooks = ${buildout:hooks}/hookfile1.py:methodname1${buildout:hooks}/hookfile2.py:methodname2${buildout:hooks}/hookfile2.py:methodname3option1 = xyzzyoption2 = You won't get it up the stairs.
Package: koansys.recipe.pybsddb
.. contents::- Code repository: http://koansys-recipe-pybsddb.googlecode.com/svn/- Report bugs at http://code.google.com/p/koansys-recipe-pybsddb/issues/listDetailed Documentation**********************Supported options=================The recipe supports the following options:Options-------This recipe supports the same options as the pybsddb module insetup2.py. It accepts the names of the environment variables asvariable names and then sets those that are defined so ``pybsddb`` canfind them at build time.berkeleydb_incdirSet the include directoryberkeleydb_libdirSet the lib directoryberkeleydb_dirSet the root of the build. If it is built in the buildout,I.e. ${bdb:location} if the BerkeleyDB section is named bdb.lflagsSet some ``LFLAGS``libsSet some ``LIBS``Example usage=============I don't really understand the testing environment here so the below is broken.We'll start by creating a buildout that uses the recipe::>>> write('buildout.cfg',... """... [buildout]... parts = bsddb3...... [bdb]... location = somdir...... [bsddb3]... recipe = koansys.recipe.pybsddb... berkeleydb_dir = ${bdb:location}... """Running the buildout gives us::>>> print 'start', system(buildout)start...Installing bsbddb.Unused options for test1: 'option2' 'option1'.<BLANKLINE>Contributors************Koansys, LLC, AuthorsReed L. O'BrienChange history**************1.0 (2008-10-18)==================- Created recipe with ZopeSkel [Koansys, LLC].- Initial version working (for me)Download********
Package: koap
KOAP: Modern Konnektor SOAP LibraryConfiguration using environment variablesEnvironment variableCommentKONNEKTOR_BASE_URLBase URL for Konnektor. Theconnector.sdsmust be available at{KONNEKTOR_BASE_URL}/connector.sdsKONNEKTOR_MANDANT_IDContext Mandant ID (Tenant)KONNEKTOR_CLIENT_SYSTEM_IDContext Client System IDKONNEKTOR_WORKPLACE_IDContext Workplace IDKONNEKTOR_USER_IDContext UserID (optional)Basic AuthKONNEKTOR_AUTH_BASIC_USERNAMEUsername for Basic authenticationKONNEKTOR_AUTH_BASIC_PASSWORDPassword for Basic authenticationMutual TLS AuthNot implemented yetexportKONNEKTOR_BASE_URL=https://.../exportKONNEKTOR_MANDANT_ID=m1exportKONNEKTOR_CLIENT_SYSTEM_ID=c1exportKONNEKTOR_WORKPLACE_ID=w1exportKONNEKTOR_USER_ID=user1exportKONNEKTOR_AUTH_BASIC_USERNAME=user1exportKONNEKTOR_AUTH_BASIC_PASSWORD='use strong passwords in production'Once the environmant variables are set, thekoap.config.ConnectorConfigcan be instantiated without parameters. We make use ofPydantic Model Config.fromkoap.configimportConnectorConfigfromkoap.clientimportConnectorClientconfig=ConnectorConfig()client=ConnectorClient(config)event_service=client.create_service_client('EventService','7.2.0')cards=event_service.GetCards(client.context())print(cards)Configuration in codefromkoap.configimportConnectorConfigfromkoap.clientimportConnectorClientconfig=ConnectorConfig(base_url='https://.../',mandant_id='m1',client_system_id='c1',workplace_id='w1',user_id='user1',# Basic Authauth_basic_username='user1',auth_basic_password='use secure passwords in production',)client=ConnectorClient(config)event_service=client.create_service_client('EventService','7.2.0')cards=event_service.GetCards(client.context())print(cards)Developmentgitsubmoduleinit
gitsubmoduleupdate
poetryinstall
Package: kobart-transformers
KoBART-TransformersSKT에서 공개한 KoBART를 편리하게 사용할 수 있게 transformers로 포팅하였습니다.Install (Optional)BartModel과PreTrainedTokenizerFast를 이용하면 설치하실 필요 없습니다.pip install kobart-transformersTokenizerPreTrainedTokenizerFast를 이용하여 구현되었습니다.PreTrainedTokenizerFast.from_pretrained("hyunwoongko/kobart")와 동일합니다.>>>fromkobart_transformersimportget_kobart_tokenizer>>># from transformers import PreTrainedTokenizerFast>>>kobart_tokenizer=get_kobart_tokenizer()>>># kobart_tokenizer = PreTrainedTokenizerFast.from_pretrained("hyunwoongko/kobart")>>>kobart_tokenizer.tokenize("안녕하세요. 한국어 BART 입니다.🤣:)l^o")['▁안녕하','세요.','▁한국어','▁B','A','R','T','▁입','니다.','🤣',':)','l^o']ModelBartModel을 이용하여 구현되었습니다.BartModel.from_pretrained("hyunwoongko/kobart")와 동일합니다.>>>fromkobart_transformersimportget_kobart_model,get_kobart_tokenizer>>># from transformers import BartModel>>>kobart_tokenizer=get_kobart_tokenizer()>>>model=get_kobart_model()>>># model = BartModel.from_pretrained("hyunwoongko/kobart")>>>inputs=kobart_tokenizer(['안녕하세요.'],return_tensors='pt')>>>model(inputs['input_ids'])Seq2SeqModelOutput(last_hidden_state=tensor([[[-0.4488,-4.3651,3.2349,...,5.8916,4.0497,3.5468],[-0.4096,-4.6106,2.7189,...,6.1745,2.9832,3.0930]]],grad_fn=<TransposeBackward0>),past_key_values=None,decoder_hidden_states=None,decoder_attentions=None,cross_attentions=None,encoder_last_hidden_state=tensor([[[0.4624,-0.2475,0.0902,...,0.1127,0.6529,0.2203],[0.4538,-0.2948,0.2556,...,-0.0442,0.6858,0.4372]]],grad_fn=<TransposeBackward0>),encoder_hidden_states=None,encoder_attentions=None)For Seq2Seq Trainingseq2seq 학습시에는 아래와 같이get_kobart_for_conditional_generation()을 이용합니다.BartForConditionalGeneration.from_pretrained("hyunwoongko/kobart")와 동일합니다.>>>fromkobart_transformersimportget_kobart_for_conditional_generation>>># from transformers import BartForConditionalGeneration>>>model=get_kobart_for_conditional_generation()>>># model = BartForConditionalGeneration.from_pretrained("hyunwoongko/kobart")Updates Notesversion 0.1pad토큰이 설정되지 않은 에러를 해결하였습니다.fromkobartimportget_kobart_tokenizerkobart_tokenizer=get_kobart_tokenizer()kobart_tokenizer(["한국어","BART 모델을","소개합니다."],truncation=True,padding=True){'input_ids':[[28324,3,3,3,3],[15085,264,281,283,24224],[15630,20357,3,3,3]],'token_type_ids':[[0,0,0,0,0],[0,0,0,0,0],[0,0,0,0,0]],'attention_mask':[[1,0,0,0,0],[1,1,1,1,1],[1,1,0,0,0]]}version 0.1.3get_kobart_for_conditional_generation()를__init__.py에 등록하였습니다.version 0.1.4누락되었던special_tokens_map.json을 추가하였습니다.이제pip install없이 KoBART를 이용할 수 있습니다.ReferenceSKT KoBARTHuggingface Transformers
Package: kobato
Kobato — Point.im Command Line Interface=============## Description`kobato` is a command-line interface for [Point.im](https://point.im/) microblogging platform. It uses official API, so you can do all the things that are there. But for now you can only do only limited set of things.## Demo![cool gif](http://i.imgur.com/yZjgNy7.gif)## Requirements- Python 3.5 (haven't tested it under anything else, but it should be fine down to 3.3)- requests- decorating- appdirs## Installation- From pipy:* `sudo pip3 install kobato`- Manual* `git clone https://github.com/nico-izo/kobato.git`* `cd kobato`* `virtualenv -p /usr/bin/python2.7 ~/.virtualenvs/kobato`* `source ~/.virtualenvs/kobato/bin/activate`* `pip3 install .`## Dive into Point- Login:* `kobato login`- Post* `kobato post`- Quick post* `kobato post -t tag -t tag2 -m 'message' -f`- Show post* `kobato show -p#da`- Show post with replies* `kobato show -p#vhbne -r | less`- Show user* `kobato show -u@arts`- Aliases* `kobato alias --create anime_art "post -fy -t anime_art -m'{0}' {...}"`- Exit point and remove your login/password from config* `kobato login --reset`## LicenseGPLv3. All hail Stallman!
Package: kobin
Type Hints friendly WSGI Framework for Python3.This library is a pre-release. Expect missing docs and breaking API changes.Kobin has following features.Decorator based Routing System exploited Type Hints.WSGI request and response Wrapper.Provide type annotations from stub files.and other convenient utilities…And Kobin hasNOfollowing features:WSGI Server Adapters: Please useWSGICLIor Gunicorn CLI.Serving static contents: Please usewsgi-static-middlewareor Nginx.Template Engine: But Kobin provides template adapter for Jinja2.RequirementsSupported python versions are python 3.6 or later.
And Kobin has no required dependencies other than the Python Standard Libraries.The following packages are optional:wsgicli - Command Line Interface for developing WSGI application.jinja2 - Jinja2 is a full featured template engine for Python.ResourcesDocumentation (English)Documentation (Japanese)GithubPyPIKobin TodoKobin’s documentation is not yet complete very much.
If you want to know the best practices in Kobin,
Please checkKobin Todo.LicenseThis software is licensed under the MIT License (SeeLICENSE).
Package: kobodata
kobodataA python wrapper forKobo Data Tool KitWhy KobodataThis helps get remote data collected easily via kobo forms via consuming the APIS from*.kobotoolbox.orgsites.There are several accounts , you can signup for one:Humanitarian Organisation AccountsResearchers, Aid Workers & Everyone Else AccountsGetting startedTo get started withkobodata, you have to firstly install the library either directly or usingpip.Installation directlyUse git to clone or you can also manually download the project repository just as shown below;$gitclonehttps://github.com/kalokola/kobodata
$cdkobodata
kobodata$pythonsetup.pyinstallInstalling from pip# For Windowspipinstall--upgradekobodata#For Linux | MACpip3install--upgradekobodataGet Account CredentialsYou have to sign up atKobo ToolBoxand create your first form.To obratinaccount_tokengot to your account settings and you will see an API Token section, view the token and copy it to your cip board. The API Token looks likebd1f68af664306q82d62w1412873d3b76b4321To obtain thedataset_uuidnavigate to your kobo project, select [DATA] to view the table. Inspect the link to your table and copy a section that looks likeagLCVHnDkbXRkEuhtp4oUFSpecify theaccount_domainfor your accountkf.kobotoolbox.orgorkobo.humanitarianresponse.infoOnce you have got the credentials you can proceed as follows.How to Use (Code Exmaple).Here how to fetch real time data>>>fromkobodataimportKoboData>>>account_token="bd1f68af664306q82d62w1412873d3b76b4321">>>dataset_uuid="">>>account_domain="kf.kobotoolbox.org">>>dataset=KoboData(account_subdomain,dataset_uuid,account_token)# get number observations>>>dataset.counts784rows# return a dictionary of results>>>dataset.get_dataAll the creditkalokolaAll other contributors
Package: koboextractor
This Python package provides a wrapper around part of the KoBoToolbox kpi API,
with the main goal being to ease the downloading of survey responses. It
provides methods to download data from the KoBoToolbox kpi API
(e.g.https://kf.kobotoolbox.org/orhttps://kc.humanitarianresponse.info/) and
to rearrange this data into useable structures.InstallationKoboExtractor requires Python 3.6+.Simply install from PyPI with:pip3 install koboextractorExample usageIn this example, response data is downloaded from KoBoToolbox and arranged in a
form that is convenient for further processing, e.g. for storing in a different
database or uploading to Google Sheets.Import and initialise the KoboExtractor:fromkoboextractorimportKoboExtractorkobo=KoboExtractor(KOBO_TOKEN,'https://kf.kobotoolbox.org/api/v2',debug=debug)Get the unique ID of the first asset in your KoBoToolbox account:assets=kobo.list_assets()asset_uid=assets['results'][0]['uid']Information on the questions and choices in your survey can be obtained with:asset=kobo.get_asset(asset_uid)choice_lists=kobo.get_choices(asset)questions=kobo.get_questions(asset=asset,unpack_multiples=True)questionsis a dictionary of the form:{'groups':{GROUP_CODE:{'label':GROUP_LABEL,'sequence':SEQUENCE_NUMBER,'repeat':True/False,'questions':{QUESTION_CODE:{'type':QUESTION_TYPE,'sequence':SEQUENCE_NUMBER,'label':QUESTION_LABEL,'list_name':CHOICE_LIST_NAME,'choices':{CHOICE_CODE:{'label':CHOICE_LABEL,'type':'select_multiple_option','sequence':SEQUENCE_NUMBER}},'other':{'type':'_or_other','label':'Other','sequence':SEQUENCE_NUMBER}}},'groups':{GROUP_CODE:{...}}},'questions':{QUESTION_CODE:{...}}choicesis a dictionary of the form:{LIST_NAME:{'label':CHOICE_LABEL,'sequence':SEQUENCE_NUMBER}}Download all responses submitted after a certain point in time:new_data=kobo.get_data(asset_uid,submitted_after='2020-05-20T17:29:30')The number of downloaded results is available innew_data['count'].new_datawill be an unordered list of form submissions. We can sort this
list by submission time by calling:new_results=kobo.sort_results_by_time(new_data['results'])Each response (list item) is a dict with several metadata keys (such as
‘_submission_time’) and key/value pairs for each answered question in the form
of ‘GROUP_CODE/QUESTION_CODE’: ‘ANSWER_CODE’. Map the question and answer labels
from your survey onto the coded answers in the responses:labeled_results=[]forresultinnew_results:# new_results is a list of list of dicts# Unpack answers to select_multiple questionslabeled_results.append(kobo.label_result(unlabeled_result=result,choice_lists=choice_lists,questions=questions,unpack_multiples=True))DocumentationThe full documentation is available athttps://koboextractor.readthedocs.io.
Package: kobo-md
KoboA hugo-like markdown website/blog builder + serverFeaturesBuilt with FlaskNative support for markdown using katexNo customization -> forced to use the best web theme you've ever seenInstallationRunpython3 -m pip install kobo-mdInstall katex vianpm install katexUsageTo start a new project, simply enter the target directory and runpython3 -m katex new.To compile markdown files into html snippets, runpython3 -m katex compile.To run the server, runpython3 -m katex serverfrom the project directory.
Package: kobra
🐍 KobraWrapper fortwine&python setup.py. The name of this module is not an error but a combination of the words king and cobra.💾 InstallInstalling the project by using pip:pip install kobraIf you have *nix such a system (Android, Mac OS, Free BSD, Linux) you may not have the last python in your terminal, so use:pip3 install kobra⚙️ FunctionsPart of the functionality is copying frompython setup.py.💾 InstallInstalling the module from source code:kobraor:kobra install🧑‍💻 DevelopA command for developers to use the module folder as the main:kobra developIt is desirable to use when changing locales and configs of your module, which are in separate files.📦 PublishWith this command, you can change the version of your module, create a build withpython setup.py sdistand release to pypi.org:kobra publishFor the command to work in your module there must be a file__init__.py, for example the following:__version__="0.2.1"You can also use the version from__init__.pyin yoursetup.py:fromsetuptoolsimportsetupfrom<modulename>import__version__setup(...version=__version__...)
Package: kobukidriver
Kobukidriver|version|Kobukidriver is a python driver for Kobuki quanser qbot2 which helps in control and utilization of the mobile robot.You can build numerous application with the help of the driver.LinksProject:https://github.com/jaxram/kobukiPyPi:https://pypi.org/project/kobukidriver/QuickstartInstall using pip:::pip install kobukidriverkobukidriver works in both windows and linuxFeaturesDevelop any mobile robot applicationsGyro sensor dataDocking IR dataInertial sensor dataCliff sensor datacurrent datageneral purpose input dataBasic sensor dataSet/Clear LEDSet digital output pinControl mobile robot speedPlay inbuilt/custom soundsExamplesGet started by importing theKobukiclass:.. code-block:: python#import the kobuki class
from kobukidriver import Kobuki
#create the instance for the kobuki
kobuki_instance=Kobuki()#raise error if kobuki is not connectedExample code for reading basic sensor data from Kobuki robot.. code-block:: pythonfrom kobukidriver import Kobuki
import time as t
kobuki_instance=Kobuki()

while(1):
    t.sleep(0.2)#delay for fetching data
    basic_sensor_data=kobuki_instance.basic_sensor_data()
    print(basic_sensor_data)#prints the basic sensor data from the robotSteps for building the mobile robot application using the driver.. code-block:: pythonfrom kobukidriver import Kobuki
kobuki_instance=Kobuki()
#Don't change the start function name
def start():
    while(1):
        #your logic
kobuki_instance.kobukistart(start)
Package: kobushi-trackviewer
Kobushi trackviewerBve trainsim 5/6向けのマップファイルから、線路平面図・縦断面図を生成するPythonスクリプトです。動作にはPython 3が必要です。インストールPowershellで次のコマンドを実行してください。pip install kobushi-trackviewerKobushi本体と、動作に必要な下記パッケージが自動でインストールされます。numpymatplotlibscipylarkttkwidgetsアップデートすでに旧バージョンのkobushiをインストール済みの方は、次のコマンドで最新版へアップデートできます。pip install --upgrade kobushi-trackviewer起動Powershellで以下のコマンドを実行します。python -m kobushipython -m kobushi hoge.txtとして、読み込みたいマップファイルを指定して起動することも可能です。リファレンスこちらを参照おことわりバージョン1.10以前のマップファイルには対応していません。マップコンバーターでMap 2.00への変換が必要です。多バイト文字を変数名に使用しているマップには対応していません。変数名に利用できる文字は英字(A-Z, a-z), 数字(0-9), アンダーバー(_)です。その他、BVE本体では読み込み可能なマップファイルがKobushiでは正しく読み込めない場合があります。ご了承ください。LicenseApache License, Version 2.0重要事項本プログラムの著作権はkonawasabi(以下、作者)が有します。本プログラムについて作者はいかなる保証もせず、またプログラムを実行して生じた結果についての責任を負いません。Apache Licence, Version 2.0に従う限り、本ソフトウェアの改変、再配布を自由に行うことができます。ContactAuthor: KonawasabiMail:webmaster@konawasabi.riceball.jpWebsite:https://konawasabi.riceball.jp/