Saravanan666/pypi-org huggingface dataset:
Package: namu
한글 프로그래밍 언어 "나무""나무"는 코딩 입문자가 쉽게 사용할 수 있는 한글 프로그래밍 언어입니다.도움말시작하기인터프리터 실행하기당연하게도(?) 나무를 실행하기 위해 파이썬을 설치합니다.터미널이나 Shell 창에pip install namu를 입력합니다.파이썬 파일에importnamunamu.interpreter()을 입력하고 실행시키면...!콘솔창에서 나무 인터프리터가 실행됩니다!!문법1. 코드 작성나무는 파이썬처럼 하나의 줄에 한 문장을 입력합니다.줄 구분나무는CRLF와LF,;(세미콜론)으로 줄을 구분합니다.
한 줄에는 하나의 문장만이 들어가지만 (), {}, [] 등의 괄호쌍 내부에서는 줄구분을 하지 않습니다.
따라서 배열 등은 여러 줄에 걸쳐 사용할 수 있습니다.확장자나무는.namu와.나무를 사용하지만 현재는 아무 확장자로 해도 작동됩니다.
나중에 특정 확장자만 쓸 수 있게 할 계획이 있습니다.주석#(샵) 문자 뒤에 있는 코드는 주석으로 처리되어 실행되지 않습니다.
(단, 인터프리터에서 사용하시면 에러가 납니다.)2. 값현재 나무에서는 5가지의 값들을 지원합니다.수정수:1,12,2021실수:0.1,3.14,10.22문자열따옴표나 쌍따옴표로 둘러싸여 있는 값은 문자열로 해석됩니다.'안녕, 세상!',"한글 프로그래밍 언어 나무"논리형아직 논리형은 구현이 안되있고1과0이 대신하고 있습니다.참과거짓내장 변수가 있는데,참은1,거짓은0을 반환합니다.조건문 등에서 사용할 수 있습니다.없음내장 변수없음은 JS에서undefined와null, 파이썬에서None의 역할을 합니다.내장 변수없음은 0을 반환합니다.배열여러개의 값들을 하나로 묶은 값입니다. 대괄호쌍 안에 쉼표로 구별해 입력합니다.[1, "이", [3.1, "배열", 참]]배열 안의 값은 대괄호를 이용해 접근할 수 있습니다.[1, "2", "삼"][1]은 배열의 2번째 원소인"2"입니다.첫번째 원소의 인덱스는0입니다.현재 배열의 원소의 내용을 바꾸는 기능(배열[인덱스] = 값)은 아직 구현되지 않았습니다.객체아직 구현되지 않았습니다.3. 연산자산술 연산자숫자는+ - * / ^로 사칙연산을 할 수 있습니다(^는 거듭제곱입니다.).28+42,10/2*10,2+2*2또 숫자는+ -로 양수와 음수를 나타낼 수 있습니다.+29,-3문자열은+로 문자열을 합치고,*로 문자열을 반복할 수 있습니다."안녕, " + "세상!","그" * 4 + " 뭐더라"배열은+로 항목을 추가하고,-로 항목을 뺄 수 있으며,*로 배열에 배열을 합칠 수 있습니다.배열=[1,"이","three"]배열+"2+2"#[1, "이", "three", "2+2"]배열-2#[1, "이", "2+2"]배열*[5,"六"]#[1, "이", "2+2", 5, "六"]콘솔에_보여주기(배열)#[1, "이", "2+2", 5, "六"]비교 연산자값이 같은지는==로, 값이 다른지는!=로 확인합니다.10 * 10 == 100,"가나다" != "라마바"숫자는< > <= >=로 비교할 수 있습니다.1 < 2,39 > 29논리 연산자AND 연산자&는 왼쪽과 오른쪽 모두가 참(1)인 경우에만 1(참)로 처리합니다.참 & 참,10 == 10 & 38 < 73OR 연산자|은 왼쪽과 오른쪽 중 하나라도 참(1)이면 1(참)로 처리합니다.29>=29 | 87>3,"ㄷㄷ" == "ㄷㄷ" | 28 == 39NOT 연산자!는 1(참)이나 0(거짓)을 반대로 뒤집습니다.!거짓,!27 > 72괄호괄호를 사용하면 계산 순서를 바꿀 수 있습니다.2 + 2 * 2는6,(2 + 2) * 2는8-1 < 2 < 1는0(거짓),-1 < (2 < 1)는1(참)4. 변수변수 선언변수 선언은=을 이용합니다.변수명 = 값형식으로 선언하며, 값을 갱신할 때에도 같은 문법을 사용합니다.변수 이름은 한글, 알파벳, 숫자,_(언더바),$(달러)를 사용할 수 있습니다.
숫자는 변수의 첫 글자에 올 수 없으며, 변수명으로 내장 함수나 내장 변수의 이름을 사용할 수 없습니다.변수 불러오기변수는변수명으로 불러옵니다.예시올해=2021콘솔에_보여주기(올해)#2021내장 변수내장 변수는 나무에서 기본으로 지원하는 변수로, 수정이 불가능합니다.내장 변수 목록은 다음과 같습니다.이름값참1거짓0없음0원주율π(3.14159...)4. 제어문조건문나무에서 조건문을 쓸 때에는만약키워드를 사용합니다.조건문 형식은 다음과 같습니다.만약조건1라면/이라면#조건1이 1(참)일 때 실행될 내용아니면서조건2라면/이라면#조건1이 0(거짓)이면서 조건2가 1(참)일 때 실행될 내용아니면#조건1과 조건2 모두 0(거짓)이면 실행될 내용끝아니면서와아니면은 생략 가능하며,라면과이라면둘 다 사용 가능합니다.반복문나무에서 반복문을 쓸 때에는반복하기키워드를 사용합니다.반복은반복 그만으로 멈춥니다.반복문 형식은 다음과 같습니다.반복하기#반복할 동안 실행될 내용만약조건1이라면반복그만끝끝5. 함수함수 선언하기나무에서는함수키워드로 함수를 선언합니다.다음은 함수 선언 예시입니다.함수함수명(매개변수1,매개변수2,...)#함수 내용리턴리턴값끝매개변수는 생략 가능합니다.
단, 괄호는 꼭 넣어야 합니다.리턴나무의 함수에서는리턴 리턴값으로 리턴을 합니다.함수 불러오기함수는함수명(매개변수1, 매개변수2, ...)로 불러오며, 매개변수는 생략 가능합니다.
단, 괄호는 꼭 넣어야 하며 괄호를 넣지 않으면<함수 함수명>이 반환됩니다.익명 함수나무에서 익명 함수를 선언할 때에도 일반 함수를 선언하는 것처럼함수키워드를 사용합니다.다음은 익명 함수 선언 예시입니다.함수명=함수(매개변수1,매개변수2,...)#함수 내용리턴리턴값마찬가지로 매개 변수는 생략 가능하지만, 괄호는 꼭 넣어야 합니다.내장 함수내장 함수는 나무에서 기본으로 지원하는 함수로, 수정이 불가능합니다.다음은 나무의 내장 함수 목록입니다.이름설명콘솔에_보여주기(내용)내용을 콘솔에 보여줍니다.콘솔_지우기()콘솔의 모든 내용을 지웁니다.숫자인가(값)값이 숫자면1(참), 아니면0(거짓)을 반환합니다.문자열인가(값)값이 문자열이면1(참), 아니면0(거짓)을 반환합니다.배열인가(값)값이 배열이면1(참), 아니면0(거짓)을 반환합니다.함수인가(값)값이 함수면1(참), 아니면0(거짓)을 반환합니다.기다리기(초)초의 값만큼 기다립니다.문자열로(값)값을 문자열로 바꾼 것을 반환합니다.실행하기(파일명)이름이파일명인 파일을 컴파일하고 실행합니다.
Package: nana
Nanakeeps an eye on a directory and reacts when anything changes.UsageNana requires Python 2.6 or better (including 3).Install Nana from PyPI:$ pip install nanaTell Nana what to do when anything changes in the current directory:# Rebuild Sphinx docs on every change in the current directory:
$ nana "sphinx-build -a docs/ docs/_build/html"
^.   .  ^You can specify the directory to monitor with the-doption:# Rebuild Sphinx docs on every change in the "docs" directory:
$ nana "sphinx-build -a docs/ docs/_build/html" -d docs
^.   .  ^You can also tell Nana how many seconds she should wait between the checks with the-toption:# Check the current directory once a minute:
$ nana "echo Updated!" -t 60
^.   .  ^By default, Nana checks the directory every second.To quit Nana, pressCtrl+C:--- Ruff-Ruff! ---ContributeReport a bugFork and improve
Package: nanaimo
NoteNanaimo is alpha software and will remain so until we bump its version to 1.0.0 or greater.
We will not knowingly break compatibility within a minor revision but we will break compatibility
a few more times between minor revisions until beta is declared. Because of this you should depend
on a minor version explicitly. For examplenanaimo ~= 0.1A delicious Python treat that makes on-target testing sweet and satisfying.Nanaimo is a set of utilities and plugins designed to enable integration of hardware test apparatuses
with pytest. This can allow on-target tests to run as part of continuous integration pipelines likeBuildkite,Bamboo, orJenkins.Example of S32K dev boards attached to Raspberry PI CI workers running theBuildkiteagent and using Nanaimo.Nanaimo is designed to enable testing of software-defined, physical components in isolation to
provide pre-integration verification of software interfaces and behavioral contracts. It adapts
asynchronous control and monitoring of these components to fit familiar testing idioms
(e.g. x-unit testing) using the popular python test framework,pytest.Block diagram of Nanaimo’s relationship to other components of a typical software build and test pipeline.Nanaimo isnota simulation framework and is not designed to support the complexity of a full hardware-in-the-loop platform.
Instead it’s focused on testing small integrations with a few hardware components and instruments using concepts, syntax,
and frameworks familiar to software engineers. Examples of these small integrations might include verifying a SPI driver for a
microcontroller or ensuring the upload time for a serial bootloader meets expected Key-Performance-Indicators (KPIs). To do this
Nanaimo abstractions provide async interfaces to hardware either directly using available communication protocols
(e.g. serial or IP networks) or by invoking a CLI provided by the instrument vendor. Because of this latter use case some
instruments will require additional programs be available in a test environment.Example scenario using Nanaimo to test an I2C driver for a microcontroller.This design is an amalgam of theTLYF(Test Like You Fly) methodology and theSwiss cheesemodel of
failure analysis. Specifically; Nanaimo facilitates testing on actual or representative hardware
for the first integration of software into a part or subassembly. Traditionally software engineers were
responsible only for unit-testing and Software-In-the-Loop (SIL) simulation of their code. Nanaimo encourages
software engineers to also provide hardware integration tests by enabling Hardware-In-the-Loopcontinuous-integration(HIL-CI, perhaps?).Hierarchy of system testing. Nanaimo focuses on part and subassembly testing.NoteNanaimo is named afterNanaimo barswhich are about the best things humans have ever invented.
Package: nandboxbotsapi
A Python nandbox Bot APIA Python library to interact with official Nandbox Bot API. A bot token isrequiredand can be obtainedthis way.Build your first botYou can easily build your bot by following the below steps:1.Setup your configuration objectonce you get your bot configuration data from nandbox app , copy it to aconfigobject.If you don't know how to get bot configuration data and token from nandboxOpen your bot in nandbox app then open the top right menu and click toGet token.This process explained in thisvideo.You will get data like this:token:90091783784280234234WBBPmJAnSD5ILIkc6N6QjY3ZzeY
url:wss://<SERVER>:<PORT>/nandbox/api/  
download:https://<SERVER>:<PORT>/nandbox/download/  
upload:https://<SERVER>:<PORT>/nandbox/upload/Add your token and the other data toconfig.jsonfile just like below :{"Token":"<your token>","URI":"wss://<SERVER>:<PORT>/nandbox/api/","DownloadServer":"https://<SERVER>:<PORT>/nandbox/download/","UploadServer":"https://<SERVER>:<PORT>/nandbox/upload/"}2.Implement your main.py file :To do that please follow the next instructions:Make sureconfig.jsonfile is created.Implement theCallBack.on_connectfunction.Implement the rest of the functions as your application requires.importjsonfromnandboxbots.nandboximportNandboxfromnandboxbots.NandboxClientimportNandboxClientfromnandboxbots.util.Utilsimportget_unique_idCONFIG_FILE="./config.json"f=open(CONFIG_FILE)config=json.load(f)f.close()TOKEN=config['Token']client=NandboxClient.get(config)nandbox=Nandbox()napi=nandbox.Api()classCallBack(nandbox.Callback):defon_connect(self,api):globalnapinapi=apiprint("Connected")defon_close(self):print("Closed")defon_error(self):print("Error")defon_receive(self,incoming_msg):print("Message Received")ifincoming_msg.is_text_msg():chatId=incoming_msg.chat.idtext=incoming_msg.textreference=get_unique_id()napi.send_text(chat_id=chatId,text=text,reference=reference)callBack=CallBack()client.connect(config['Token'],callBack)Have a look at thetestfolder, you might find useful examples.LicenseMIT LicenseCopyright (c) 2023 nandboxPermission 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: naneos-devices
naneos-devices (python-toolkit)This repository contains a collection of Python scripts and utilities for ournaneosmeasurement devices. These scripts will provide various functionalities related to data acquisition, analysis, and visualization for your measurement devices.InstallationYou can install thenaneos-devicespackage using pip. Make sure you have Python 3.9 or higher installed. Open a terminal and run the following command:pipinstallnaneos-devicesUsageTo establish a serial connection with the Partector2 device and retrieve data, you can use the following code snippet as a starting point:importtimefromnaneos.partectorimportPartector1,Partector2,scan_for_serial_partectors# Lists all available Partector2 devicesx=scan_for_serial_partectors()# Split dictionary into P1 and P2 devicesp1_devs=x["P1"]p2_devs=x["P2"]iflen(p1_devs)>0:print("Found Partector1 devices:")fork,vinp1_devs.items():print(f"Serial number:{k}, Port:{v}")# Connect to the first devicemyP1=Partector1(list(p1_devs.values())[0],1)time.sleep(2)# Get the data as a pandas DataFramedata=myP1.get_data_pandas()print(data)myP1.close()iflen(p2_devs)>0:print("Found Partector2 devices:")fork,vinp2_devs.items():print(f"Serial number:{k}, Port:{v}")# Connect to the first devicemyP2=Partector2(list(p2_devs.values())[0],1)time.sleep(2)# Get the data as a pandas DataFramedata=myP2.get_data_pandas()print(data)myP2.close()Make sure to modify the code according to your specific requirements. Refer to the documentation and comments within the code for detailed explanations and usage instructions.DocumentationThe documentation for thenaneos-devicespackage can be found in thepackage's documentation page.ProtobufUse this command to create a py and pyi file from the proto fileprotoc-I=.--python_out=.--pyi_out=../protoV1.protoBuilding executablesSometimes you want to build an executable for a customer with you custom script.
The build must happen on the same OS as the target OS.
For example if you want to build an executable for windows you need to build it on Windows.pyinstallerdemo/p1UploadTool.py--console--noconfirm--clean--onefileIdeas for future developmentP2 BLE implementation that integrates into the implementation of the serial P2P2 Bidirectional Implementation that allows to send commands to the P2Automatically activate Bluetooth or ask when BLE is usedContributingContributions are welcome! If you encounter any issues or have suggestions for improvements, please submit an issue on theissue tracker.Please make sure to adhere to the coding style and conventions used in the repository and provide appropriate tests and documentation for your changes.LicenseThis repository is licensed under theMIT License.ContactFor any questions, suggestions, or collaborations, please feel free to contact the project maintainer:Mario HuegiContact:mario.huegi@naneos.chGithub
Package: nangram
NanGramNegative Nancy's expression generator & parser! XDWrite grammars, generate random expressions, parse expressions.InstallationpipinstallnangramUsageFirst write yourself a nice little grammar like this!:grammar.bnf:determiner = "the " | "a " .
noun = "cat " | "dog " | "chair " .
verb = "runs " | "snacks " | "plays " .
adverb = "quickly" | "ferociously" | "sneakily" .

noun_phrase = determiner noun .
verb_phrase = verb adverb .
sentence = noun_phrase verb_phrase .

main = sentence .Then importnangramand load the grammar source:importnangramgrammar=nangram.Grammar.load_bnf('grammar.bnf')Then generate some expressions!:forexpressioningrammar.generate():print(expression)And you get...the cat plays ferociously
the dog plays ferociously
the chair snacks quickly
a cat snacks quickly
a dog runs quickly
a dog snacks ferociously
a dog plays quickly
a chair plays ferociouslyThen try parsing something:forparse_treeingrammar.parse('a cat snacks sneakily'):print(parse_tree)And you get...sentence = 'a cat snacks sneakily'
├ noun_phrase = 'a cat '
│ ├ determiner = 'a '
│ └ noun = 'cat '
└ verb_phrase = 'snacks sneakily'
  ├ verb = 'snacks '
  └ adverb = 'sneakily'(The parser will yield as many parse trees as are valid, so if you have an ambiguous grammar, for example, you can parse all variations. If the expression is not in the language, you won't get any parse trees.)Seeexamples/english.bnfandexamples/english.pyfor another example.
Package: nangs
Welcome to nangsSolving Partial Differential Equations with Neural Networks.Nangs is a Python library built on top of Pytorch to solve Partial Differential Equations.Our objective is to develop a new tool for simulating nature, using Neural Networks as solution approximation to Partial Differential Equations, increasing accuracy and optimization speed while reducing computational cost.Read ourpaperto know more.Installingnangs is on PyPI so you can just run:pip install nangsYou will also need to installPytorch.Getting StartedLearn how to work with nangs with ourtutorials.See nangs in actions with ourexamples.CopyrightCopyright 2020 onwards, SensioIA. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this project's files except in compliance with the License. A copy of the License is provided in the LICENSE file in this repository.
Package: nani
Nani is a Python library that provides an alternative approach to defining and
viewingNumPy’s arrays.Upon getting started with NumPy, the rules to definenumpy.dtypeobjects
tend to quickly becomeconfusing. Not only different syntaxes can create a
same data type, but it also seemsarbitraryand hencedifficultto remember
that sub-array data types can only be defined as tuples while structured data
types exclusively require lists made of field tuples, and so on.To address this point, Nani takes the stance of offering one—and only one—way
of constructingnumpy.dtypeobjects. Although this syntax makes the code
more verbose, it also makes it easier to read and to reason about.Nani’s approach allowstype introspectionwhich brings additional benefits
in the form of dynamically generateddefault valuesandview types.
Default values facilitate the definition of new array elements while view types
are useful to encapsulate interactions with NumPy and to expose a different
public interface to your library users instead of the one provided withnumpy.ndarray.Featuresexplicit syntax for definingnumpy.dtypeobjects.generates default values and view types.allows for type introspection.Usage>>>importnumpy>>>importnani>>>color_type=nani.Array(...element_type=nani.Number(type=numpy.uint8,default=255),...shape=3,...view=None)>>>dtype,default,view=nani.resolve(color_type,name='Color')>>>a=numpy.array([default]*2,dtype=dtype)>>>v=view(a)>>>forcolorinv:...print(color)[255,255,255][255,255,255]Thecolor_typeabove defines an array of 3numpy.uint8elements having
each a default value of255. The resultingdtypeanddefaultobjects are used to initialize a new NumPy array of 10 color elements, while
theviewtype is used to wrap that array into a standard collection
interface.See theTutorialsection from the documentation for more detailed examples
and explanations on how to use Nani.DocumentationRead the documentation online atnani.readthedocs.ioor check its source in
thedocdirectory.AuthorChristopher Crouzet
<christophercrouzet.com>
Package: nani-fighter
# Nani Fighter<img src=”https://user-images.githubusercontent.com/7325483/107784754-04db9500-6d76-11eb-9f21-39dd293ef38d.png”>Nani Fighter is a simple game made with python and pygame. Currently It has two revisions:
* Nani Fighter : The Beginning
* Nani Fighter : The Second VisitThe first one is easier where the latter one is more difficult and has more enemy characters.### Installation
Using pip :`pip installnani-fighter`### Running The Game
Commands to run the revisions`shellnani-fighterthe-beginningnani-fighterthe-second-visit`
Package: nanim
NanimAn animation library designed from the ground up for a intuitive and easy to use interface. Made in python.InstallationUse the package managerpipto install nanim.pipinstallnanimThe dependenices are pycairo and ffmpeg, which pip should install automatically.UsageFirstly make an animation file, in which build your animation,Sample animation files=Scene();rect=s.add(Rectange(x=0,y=0,width=100,height=100,color=Color.RGB(255,0,0)));rect.fadeIn().move_to(x=100,y=100).wait(3).fade_out()s.run_animation();To render your animation:run withnanim <file-name>for examplenanim animation.pywhere file name is the file name of your animation filerunningnanim -hwill give you a list of optionsList of all functions callable on objects"""Fade OutParameters:duration (float): duration of animation in secondsblocking (bool): whether this animation should stop other animations until its done"""deffade_out(duration=0.5,blocking=True):"""Fade InParameters:duration (float): duration of animation in secondsblocking (bool): whether this animation should stop other animations until its done"""deffade_in(duration=0.5,starting_time="not_set",blocking=True):"""RotateParameters:angle (float): the angle to rotate, either in degrees or radians set by pi mode.duration (float): duration of animation in secondsblocking (bool): whether this animation should stop other animations until its donearound (Point): a point to rotate around, default is the center of the objectpi_mode (bool): whetor the angle is in degrees or radians"""defrotate(angle,duration=0.5,blocking=True,around="not_set",pi_mode=False):"""Makes object waitParameters:duration (float): duration of animation in seconds"""defwait(duration=0.5):"""TranslateParameters:duration (float): duration of animation in secondsx (int): how much to translate in the x directiony (int):  how much to translate in the y direction"""deftranslate(self,x=0,y=0,duration=0.5"):"""Set colorParameters:color (color): the color to turn tooduration (float): duration of animation in secondsblocking (bool): whether this animation should stop other animations until its done"""defset_color(self,color,duration=0.5,blocking=True):"""Move toParameters:point (Point): the location to move to (should be a point such as Point(x=0,y=0)duration (float): duration of animation in seconds"""defmove_to(point,duration=0.5):ContributingPull requests are welcome.LicenseMIT
Package: nannernest
nannernestA small package for optimizing banana coverage on peanut butter and banana sandwiches. Seeblog postfor more info.Installationnannernestis generally pip installable. Due to some C dependencies with the nesting library that I usenest2D, along with an outstandingPR, I would recommend the following way to install everything:First, make sure you haveboostandcmakeinstalled. If you are on Linux, then you may havecmakeinstalled, and you can installboostwithsudo apt-get install libboost-all-devI'm on a Mac, and I installedcmakewith conda andboostwith brew:conda install cmake
brew install boostNext, pip install my fork ofnest2D:pip install git+https://github.com/EthanRosenthal/nest2D.git@download-dependenciesFinally, pip installnannernestpip install nannernestUsageTake a top-down picture that contains your banana and at least one slice of bread. Pass the image in via command line:$ nannernest my_image.jpgCLI Details$ nannernest --help
Usage: nannernest [OPTIONS] IMAGE_PATH

Arguments:
  IMAGE_PATH  Image file which contains bread and banana  [required]

Options:
  --num-slices INTEGER            Total number of slices to cut the banana
                                  into. This number defines the slice
                                  thickness.  [default: 22]

  --mask-threshold FLOAT          Threshold of segmentation mask.  [default:
                                  0.6]

  --peel-scaler FLOAT             Fraction of slice that is assumed to belong
                                  to banana insides versus the peel.
                                  [default: 0.8]

  --ellipse-ratio FLOAT           Assumed ratio of minor axis to major axis of
                                  banana slice ellipses  [default: 0.85]

  --plot-segmentation / --no-plot-segmentation
                                  Whether or not to plot the segmentation
                                  masks  [default: False]

  --plot-slicing / --no-plot-slicing
                                  Whether or not to plot the slicing circle
                                  and skeleton  [default: False]

  --output TEXT                   Name of file to output  [default:
                                  perfect_sandwich.jpg]
Package: nannotate
# nannotate
Automate ML dataset labelling[![Build Status](https://travis-ci.org/timkpaine/nannotate.svg?branch=master)](https://travis-ci.org/timkpaine/nannotate)
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Package: nanny-kolenkainc
Helperscripts to ease work with github, jira, jenkinsTODO (currently linux only)Prerequisiteslinuxbashmakepython 3get jira tokenget github token(with scope 'repo')installmake install- installs virtualenv and all dependencies (locally)cp settings_global.py settings_user.pyfill settings_user.pyusagesource login.shpython3 -m create_pr <branch-name> --reviewers user1 user2