Saravanan666/pypi-org huggingface dataset:
Package: pyautocad
pyautoacad - AutoCAD Automation for PythonThis library aimed to simplify writingActiveXAutomationscripts forAutoCADwith PythonRequires:comtypesOptional:xlrd,tablibFeatures:Simplifies work with coordinates (3D points)Efficient objects iteration and searching (with casting to correct type)Excel/csv/json import and export (xlrdandtablibrequired)Simple usage example:from pyautocad import Autocad, APoint


acad = Autocad()
acad.prompt("Hello, Autocad from Python\n")
print acad.doc.Name

p1 = APoint(0, 0)
p2 = APoint(50, 25)
for i in range(5):
    text = acad.model.AddText('Hi %s!' % i, p1, 2.5)
    acad.model.AddLine(p1, p2)
    acad.model.AddCircle(p1, 10)
    p1.y += 10

dp = APoint(10, 0)
for text in acad.iter_objects('Text'):
    print('text: %s at: %s' % (text.TextString, text.InsertionPoint))
    text.InsertionPoint = APoint(text.InsertionPoint) + dp

for obj in acad.iter_objects(['Circle', 'Line']):
    print(obj.ObjectName)See moreexamplesin source distribution.LinksDocumentationatreadthedocs.orgSource code and issue trackingatGitHub.
Package: pyautocast
pyautocastPython library to automatically cast function arguments using decorator.InstallpipinstallpyautocastUsage>>>frompyautocastimportautocast>>>@autocast(x=str)...deffunc(x):...assert(isinstance(x,str))...return"arg 'x' in func() is "+x...>>>func(2)"arg 'x' in func() is 2">>>func([1,2,3])"arg 'x' in func() is [1, 2, 3]">>>frompyautocastimportCustomCast>>>mycast=CustomCast()>>>mycast.add_cast_rule(int,tuple,lambdax:(x,x))>>>@mycast.autocast(x=tuple)...deffunc(x):...print(x)>>>func(2)(2,2)>>>func(-4.5)Traceback(mostrecentcalllast):...TypeError:'float'objectisnotiterable
Package: py-AutoClean
AutoClean - Automated Data Preprocessing & CleaningAutoClean automates data preprocessing & cleaning for your next Data Science project in Python.Read more on the AutoClean algorithm in myMediumarticleAutomated Data Cleaning withÂ Python.View the AutoClean project onGitHub.DescriptionIt is commonly known among Data Scientists that data cleaning and preprocessing make up a major part of a data science project. And, you will probably agree with me that it is not the most exciting part of the project.Wouldn't it be great if this part could be automated?AutoClean helps you exactly with that: it performspreprocessingandcleaningof data in Python in anautomated manner, so that you cansave timewhen working on your next project.AutoClean supports:Handling ofduplicates[ NEW with version v1.1.0 ]Various imputation methods formissing valuesHandling ofoutliersEncodingof categorical data (OneHot, Label)Extractionof datatime valuesand more!Basic UsageAutoClean takes aPandas dataframe as inputand has a built-in logic of how toautomaticallyclean and process your data. You can let your dataset run through the default AutoClean pipeline by using:fromAutoCleanimportAutoCleanpipeline=AutoClean(dataset)The resulting output dataframe can be accessed by using:pipeline.output>Output:col_1col_2...col_n1datadata...data2datadata...data...............Adjustable ParametersIn some cases, the default settings of AutoClean might not optimally fit your data. Therefore it also supportsmanual settingsso that you can adjust it to whatever processing steps you might need.It has the following adjustable parameters, for which the options and descriptions can be found below:AutoClean(dataset,mode='auto',duplicates=False,missing_num=False,missing_categ=False,encode_categ=False,extract_datetime=False,outliers=False,outlier_param=1.5,logfile=True,verbose=False)ParameterTypeDefault ValueOther Valuesmodestr'auto''manual'duplicatesstrFalse'auto',Truemissing_numstrFalse'auto','linreg','knn','mean','median','most_frequent','delete',Falsemissing_categstrFalse'auto','logreg','knn','most_frequent','delete',Falseencode_categlistFalse'auto',['onehot'],['label'],False; to encode only specific columns add a list of column names or indexes:['auto', ['col1', 2]]extract_datetimestrFalse'auto','D','M','Y','h','m','s'outliersstrFalse'auto','winz','delete'outlier_paramint,float1.5any int or float,FalselogfileboolTrueFalseverboseboolFalseTrueBy setting themodeparameter, you can define in which mode AutoClean will run:Automated processing(mode='auto'): the data will be analyzed and cleaned automatically, by being passed through all the steps in the pipeline. All the parameters are set to ='auto'.Manual processing(mode='manual'): you can manually define the processing steps that AutoClean will perform. All the parameters are set toFalse, except the ones that you define individually.For example, you can choose to only handle outliers in your data, and skip all other processing steps by using:pipeline=AutoClean(dataset,mode='manual',outliers='auto')Please see theAutoClean documentation on GitHubfor a detailed usage guide and descriptions of the parameters.
Package: pyautoclicker
Auto-Clickerthis is a very good autoclicker, easy to use.
this is made withpynput.This clicks at 62-100 cps which is more than enough.Usage in MinecraftYou can run this programme in the background and just presss(here 's' is an examle) to start autoclicking for a important pvp situation and stop it by pressingsagain.To end the programme presse(here 'e' is an example) to teriminate the programme.But autoclicking in minecraft can ban you in a server.To implement the autoclickersteps:opencmdand typepip install pyautoclickeropen a python filetype in the followingimportpyautoclickeraspyacpyac.autoclick("s","e")and your done!Click me to see the codeChange log1.0.5(22/6/2021)Added optional parameter 'delay'
Package: pyauto-compl
Pyauto-complPyauto-compl- library for auto complete in Python. It comes with set of standard english words for quick start.Quick startpipinstallpyauto-complfromautocompl.complimportAutoCompletecompl=AutoComplete()# Gonna load minified words, around 274411 wordsprint("Loaded words")completions=compl.get_completions("appl")# Returns list of completionsprint(completions)
Package: pyauto.core
A task running toolWhat is this?PyAuto provides a minimalist project structure for capturing
configuration and orchestrating tasks.What is a Task?A python function.# deployment_tasks.py# this needs to be imported so that the config class will be registeredimportdeployment_configdefdeploy_app(config,app_name):# implement deployment hereprint('deploying{0}...'.format(app_name))app=config.apps.get_tag(app_name)print(app)How is it configured?YAML + Python Class.# config.yml
task_modules:
- deployment_tasks
apps:
- id: my_app
  name: My Application
  source_dir: ./my_app
tasks:
  deploy_my_app:
  - deploy_app,my_app# deployment_config.pyfrompyautoimportconfigimportosclassApp(config.Config):defget_source_dir(self):returnos.path.abspath(self.source_dir)config.set_config_class('apps',App.wrap)How is it used?As a CLI tool.Run the task$python-mpyauto.deploy-cconfig.ymldeploy,my_appOutputs----- deployment_tasks.deploy_app ( my_app  ) -----
deploying my_app...
OrderedDict([('id', 'my_app'), ('name', 'My Application'), ('source_dir', './my_app')])
deploy_app,my_app = NoneThe “,” separates the function from the string arguments. All task
functionsmustaccept string only arguments.Run a sequence of tasks$python-mpyauto.deploy-cconfig.ymldeploy_my_appOutputs----- deployment_tasks.deploy_app ( my_app  ) -----
deploying my_app...
OrderedDict([('id', 'my_app'), ('name', 'My Application'), ('source_dir', './my_app')])
deploy_app,my_app = NoneLine 1 of the output indicates the function invoked, with the arguments
passed to it. Lines 2-3 of the output indicate the standard output of
the function’s execution Last line of the output indicates 1) the
original function invocation string and 2) the return value of the
function.If you wish to suppress output of line 1 and last line, you can pass the-qoption to have PyAuto omit those lines.The task sequencedeploy_my_appis looked up from thetaskssection of the config. A task sequence may list as many tasks or task
sequences as desired. Every item will always be executed when the task
sequence is invoked.Dry-run a sequence of tasks$python-mpyauto.deploy-cconfig.ymldeploy_my_app-iOutputsdeploy_my_app (  )
    deployment_tasks.deploy_app ( my_app )This shows the sequence of tasks that will be run. This is a trivial
example, but you may also invoke other task sequences from a task
sequence, which can lead to a complex order of tasks. This feature
allows you to inspect what a given task sequence will execute before you
execute it.
Package: pyautocorpus
PyAutoCorpusA python interface to the excellentAutoCorpuslibrary.Right now, it only supports the wiki markuptextifyfunction, which strips out
markup. From my benchmarks, this ends up being ~40x faster than methods to strip
markup using other libraries:mwparserfromhell0.208sec/doc
wikitextparser0.215sec/doc
pyautocorpus0.005sec/docwhere:mwparserfromhellismwparserfromhell.parse(x).strip_code()wikitextparseriswikitextparser.parse(x).plain_text()pyautocorpusispyautocorpus.Textifier().textify(x)InstallingFrom pypi:pipinstallpyautocorpusFrom source:Be sure to clone recursively:gitclone--recursivehttps://github.com/seanmacavaney/pyautocorpus.gitYou will first need thepcrelibrary installed.pythonsetup.pyinstallUsageExample:importpyautocorpustextifier=pyautocorpus.Textifier()textifier.textify("==Wiki Marked up text==\n[[Some Page|link text]] example.")'Wiki Marked up text\n\n\nlink text example.'Known issuesWindows is not yet supportedCreditsAutoCorpusContributors to this repository:Sean MacAvaney (University of Glasgow)Thomas Jänich (University of Glasgow)
Package: pyautoeios
pyautoeiosWork in progress port remote_input fromhttps://github.com/Brandon-T/Reflectionto pythonDesign decision was made to implements patches tohttps://github.com/asweigart/pyautogui/and github.com/asweigart/pyscreeze so
that the remote_input so that interface can be used.Planned FeaturesWorks with python 3.8installable via pipWraps well likedpyautoguiinterfaceTransparent Image finding when opencv is installedInjecting into multiple clients (so threads can be used for multi-boxing)no known memory leaks.Backlog Features:More examples?Installs Dependancies for you (for now use thePipfile)integration of color and other methodshttps://github.com/BenLand100/srbot/tree/master/srbotporting modules fromhttps://github.com/SRL/SRLorhttps://github.com/ollydev/SRL-Developmentporting of "reflection" modules fromhttps://github.com/Brandon-T/ReflectionCurrent demo:importrandomimportgetpassfrompyscreezeimportBoximportpyautoeiosaspyautodefmove_to_spot_in_box(box,**kwargs):print(f"box ={box}")if'duration'notinkwargs:kwargs['duration']=random.uniform(0.3,1.1)if'tween'notinkwargs:kwargs['tween']=pyauto.easeOutQuadcx,cy=pyauto.center(box)x=random.randint(int(-1*(box.width/3)),int(box.width/3))+cxy=random.randint(int(-1*(box.height/3)),int(box.height/3))+cyprint(f"x ={x}, y ={y}")pyauto.moveTo(x,y,**kwargs)defclick_on_spot_in_box(box,**kwargs):move_to_spot_in_box(box,**kwargs)pyauto.click(**kwargs)pyauto.inject_clients()forclientinpyauto.clients:pyauto.pair_client(client)click_on_spot_in_box(Box(left=398,top=271,width=148,height=40))click_on_spot_in_box(Box(left=285,top=248,width=235,height=15))pyauto.typewrite(getpass.getpass(),interval=0.3)im=pyauto.screenshot()im.show()click_on_spot_in_box(Box(left=238,top=301,width=148,height=41))
Package: pyautoflow
pyautoflowThis library can control your keyboard and mouse to automate everyday tasks. It can take screenshots and screen recordings for you to check back in on later. Other basic functions include power control and system information.Examples# Import the four base modulesfrompyautoflowimportcontrols,inputs,info,powerfrominfoimport*# CONTROLS# Press the "a" keycontrols.press("a")# Press and hold the "a" key for 5 secondscontrols.press_and_hold("a",5)# Type the string "Hello, world!"controls.type("Hello, world!")# Set the cursor location to 10, 11controls.set_cursor(10,11)# Set the cursor location to the current location plus 10, 11controls.set_cursor_rel(10,11)# Moves the cursor location to 10, 11 over 5 secondscontrols.move_cursor(10,11,5)# Moves the cursor location to the current location plus 10, 11 over 5 secondscontrols.move_cursor_rel(10,11,5)# Clicks at the current locationcontrols.click()# Right clicks at the current locationcontrols.right_click()# Presses and holds the left mouse button until releasedcontrols.press_mouse(0)# Presses and holds the right mouse button until releasedcontrols.press_mouse(1)# Releases the left mouse buttoncontrols.release_mouse(0)# Releases the left mouse buttoncontrols.release_mouse(1)# Drags the cursor from 10, 11 to 100, 101 over 1 secondcontrols.drag(10,11,100,101,1)# Resets timerreset_timer()# Gets the time since the last timer resetdelta=get_timer()# INPUTS# Takes a screenshotscreen=screenshot()# Takes a screenshot of the area 10, 11, 100, 101screen=screenshot_area(10,11,100,101)# Saves the given image as "foo.png"save_img(screen,"foobar.png")# Starts recording the screen as "bar.mp4"start_recording("bar.mp4")# Stops the screen recordingstop_recording()# INFO# Returns the CPU utilisation on each threadutilisation=cpu.percent()# Returns the number of CPU cores and threadscores,threads=cpu.count()# Returns info about the virtual RAM usagevirtual_info=ram.virtual()# Returns info about the swap memory usageswap_info=ram.swap()# Returns info on all partitions detectedpartition_info=disks.partitions()# Returns info the main drive, such as the capacity useddisk_usage=disk.usage()# Returns a list of all processes currently runningpids=pids.pids()# Returns a list of all of the IDs of currently running processesids=pids.ids()# Returns info on the given IDpid_id=pids.lookup(ids[1])# Dumps all of the available info on the currently running processes to the terminalpids.get()# Returns info on the battery chargebattery_info=other.battery()# Returns a list of all users on this device and some infousers=other.users()# Returns the timestamp of the systems clocktimestamp=other.time()# POWER# Shutdown the computerpower.shutdown()# Reboot the computerpower.reboot()TODO:Text recognitionMicrophone and camera inputMore advanced power controls
Package: pyautogan
AutoGan介绍AutoGan 是一个 agent frame，它为大规模 agent 群组和超长工作流而设计。
通过 AutoGan 可以将 agent 和真人员工结合，形成一系列独立的数字部门。
这些部门可以独立运作，同时又能在需要的时候，让 agent、真人员工、数字部门之间互相协作，以完成各种任务。
我们的目标是创造一个环境，能够充分发掘和利用 LLM 的最大潜力。
随着 LLM 的不断发展和进步，相信越来越多的人工任务将被接替。每个 agent 可以自主选择需要交流的对象。除了依赖于 LLM 本身的能力，agent 还可以借助工具函数实现更多功能，例如：代码执行、数据查询、文件读取、邮件发送等。通过构建组织架构，可以将 agent 和真人员工组成数字部门，并定义各数字部门的上下级关系。在默认情况下，agent 的协作对象只限于当前部门的其他 agent 或真人员工，以及子数字部门的 leader。agent 在执行任务时，可根据需要向其他 agent、真人员工或数字部门的 leader 发布子任务。agent 的对话域仅聚焦于当前任务，不会受到其他任务对话内容的影响。如果一个任务的执行过程较长，那么远期的会话记录将被压缩，但任务的原始内容将始终保持不变。QuickstartinstallAutoGan requires Python version >= 3.8. It can be installed from pip:pipinstallpyautogannotebook在 jupyter 中运行已创建的示例下载本仓库gitclonecdautogan/notebook打开 ./notebook 中的 LLM_CONFIG 文件，然后设置正确的配置开始运行 notebook如需要 agent 执行代码，请使用 docker 环境特性Agent在本框架中，agent 可以是以 LLM 为核心的智能体，也可以是仅使用工具函数的自动化程序，或者是真人员工的数字化身。所有 agent 都是在 UniversalAgent 基类之上构建的，其主要属性如下：name:该属性相当于 agent 的地址，用于 agent 之间的相互识别与沟通，因此该属性的值应当是全局唯一的。duty:用于向其他 agent 介绍自身职责及能力。work_flow:用于定义 agent 自身的工作流程。use_tool用于定义 agent 使用工具函数的方式。框架本身已构建了一些基础的 agent，实现了网络查询、编程、邮件发送等功能，以便于用户可以快速上手。关于 agent 的详细介绍和创建方法，可参考 notebook工具使用如想要为 agent 添加定制化功能，可以通过重写 UniversalAgent 类的 tool_function 方法来实现。agent 的 use_tool 属性，与 tool_function 方法的调用关系：use_tooltool_functionNone不调用工具函数only不使用 LLM，仅调用工具函数生成结果。joinLLM 生成的内容将作为工具函数的输入参数关于 agent 工具使用的详细介绍，可参考 notebook组织架构考虑到并非所有 agent 之间都需要建立协作关系，且过多无用的协作关系会影响到 agent 决策的准确性。
因此本框架引入了组织架构的概念，让需要相互协作的 agent 组成独立的数字部门，以更加专注于解决特定领域的问题。创建组织架构的方式非常简单，只需要定义一个存储 agent 对象的多维列表，例如：org_structure=[customer,customer_manager,[project_manager,product_manager[coder,code_execution_agent]]]数字部门支持上下级关系，各部门的第一个 agent 为部门的 leader，其负责与上级部门的 agent 进行沟通。
因此 leader 的 duty 属性应当概述整个部门的职测与能力。会话域agent 之间的协作，是以任务为基础的，一个任务通常会被 agent 查分成多个子任务后，再分派给其他 agent。
每轮对话中 agent 仅会专注于当前任务内，有其参与的会话内容。
任何 agent 不会受到上级任务或子任务执行过程的影响。Switch所有 agent 的回复消息，都会先被推送到 Switch，Switch 本身不会决定消息的接收方，
而是通过消息内的 @ 符号来判断将消息转发给谁。除此之外，Switch 还负责任务的创建和任务间所属关系的维护。
Package: pyautogecko
pyautogeckoFork ofgeckodriver-autoinstallerwhich is no longer mantained.
Automatically download and installgeckodriverthat supports the currently installed version of firefox. This installer supports Linux, MacOS and Windows operating systems.InstallationpipinstallpyautogeckoUsageJust typeimport pyautogeckoin the module you want to use geckodriver.Examplefrom selenium import webdriver
import pyautogecko


pyautogecko.install()  # Check if the current version of geckodriver exists
                                     # and if it doesn't exist, download it automatically,
                                     # then add geckodriver to path

driver = webdriver.Firefox()
driver.get("http://www.python.org")
assert "Python" in driver.title
Package: pyautogit
pyautogitA command line interface for working with git written in python with the help ofpy_cui.InstallationAn obvious prerequisit to installingpyautogitis to havegitinstalled and in your system path. You will also require python 3.4+, andpython3andpythonmust be reachable on your systemPATHfor operations that require git credentials.
Once this is done, you may install the module.To installpyautogit, it is recommended to usepip:pip install pyautogitThis will also installpy_cui, the Command Line UI builder library upon which the project is based, andwindows-cursesif running on windows, which is acursesemulator for the win32 platform.Alternatively, you can install from source. Clone this repository and usepipto install:git clone https://github.com/jwlodek/pyautogit
cd pyautogit
pip install .Ifpyautogitis already installed and you would like to update it, use:pip install --upgrade pyautogitorcd pyautogit
git pull
pip install --upgrade .if updating a local version.Note that you may require root access for installing withpipdepending on your system's python configuration.DemoBelow is a quick demo of usingpyautogitto do some common git actions.UsageOncepyautogitis installed, open a command line client (note that Windows Terminal is not yet supported), then navigate to a directory and type:pyautogitYou can also specify an external directory:pyautogit -w /home/jwlodek/reposIf you openpyautogitin a directory that contains a.gitfolder, it will treat it as a repository, while if it cannot find said folder, the target location will be treated as a workspace.Use the keyboard shortcut descriptions listed in the status bar at the bottom of the window to navigate the interface and menus.LicenseBSD 3-Clause LicenseCopyright (c) 2020, Jakub Wlodek
All rights reserved.
Package: pyautogui-cli
pyautogui-cliUsagePutting the function name ofpyautoguias the first argument, and all the arguments (anything inside the parentheses) as the second.Examplepyautogui.moveTo():>>> pyautogui.moveTo(100, 200)  # moves mouse to X of 100, Y of 200.should be translated as:$ pyautogui moveTo "100, 200"
Package: pyautogui-simplified-edition
PyAutoGUI Simplified EditionThis is a simplified edition of the PyAutoGUI library that provides easy-to-use functions for screen automation.PyAutoGUI is a cross-platform GUI automation Python module that can perform many functions, including mouse and keyboard control, taking screenshots, and locating images on the screen.However, the library can be complex and difficult to use for beginners. The PyAutoGUI Simplified Edition provides simpler functions that are easier to use, but can still accomplish many of the same tasks as the original library.InstallationThe package can be installed using pip:pipinstallpyautogui_simplified_editionUsageHere are some available functions in this package:importpyautogui_simplified_edition.screenasscreen# Wait until an image is found on the screenpyse.wait_until_found('example.png')# Find an image in a specific regionlocation=pyse.find_in('example.png',region=(100,100,500,500))# Find any of a list of images on the screenimage,location=pyse.find_any(['example1.png','example2.png'])# Take a screenshot and save it to a filepyse.take('screenshot.png')For detailed information on the usage of each function, please refer to the docstrings in the code.AcknowledgementsThis package is based on the PyAutoGUI library, which can be found athttps://pypi.org/project/PyAutoGUI/.License...
Package: pyautoinstall
PyAutoInstallMagically install modules just by importing them!!📝 DescriptionThis is aWork-In-ProgressLibrary which willchangeyour way of installing packagesforever.🤯 Disclaimer(This project is still in unstable planning stage)🔥 Getting Started⬇️ InstallationWhile it would be nice to installpyautoinstalljust by importing it,
that just isn't the case.Via pippip install pyautoinstall⚡ UsageWithout pyautoinstall>>>importrequestsTraceback(mostrecentcalllast):File"<stdin>",line1,in<module>ModuleNotFoundError:Nomodulenamed'requests'With it>>>importpyautoinstall>>>importrequestsShouldIinstallrequests?(y/n)-ySuccessfullyinstalledrequests!!>>>requests.get('https://pypi.org/project/pyautoinstall/')<Response[200]>
Package: pyautokakao
pyautokakaoKakaoTalk automation tool for WindowsInstallationpip install pyautokakaoUsageYou should start kakaotalk before.Chat room nameshould be exactly the same. (Unexpected behavior)importpyautokakao# Read Chatlog=pyautokakao.read("Chat room name")print(log)# Send Chatpyautokakao.send("Chat room name","message")# Add to friendspyautokakao.add_friend("friend name(you determine)","phone number")# Invite friend to existing roompyautokakao.invite("Chat room name",["friend name 1","friend name 2",])# Make new chat roompyautokakao.make_room("Chat room name",["friend name 1","friend name 2",])
Package: pyautomagic
pyautomagicA Python3 version of the automagic EEG processing pipeline. Development in progress. This is all temporary.ReferencesPaper:https://www.biorxiv.org/content/10.1101/460469v1Paper:https://www.ncbi.nlm.nih.gov/pubmed/31233907Matlab github repo:https://github.com/methlabUZH/automagicProject Organization├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── pyautomagic
|   ├── src            <- Src/ from automagic (matlab)
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── base           <- Scripts that are configuration files, or other code used by the entire pyautomagic repo.
│   │
│   ├── gui             <- Scripts for the gui
│   │
│   ├── preprocessing   <- Scripts for running EEG preprocessing
│   │
│   └── visualization  <- Scripts to visualize results, etc.
│
└── tox.ini            <- tox file with settings for running tox; see tox.testrun.orgIntended Users / UsageResearchers dealing with EEG data. The main (default) workflow is summarized in:Installation GuideFor installation instructions, seeinstallation guide.Setup Jupyter Kernel To TestYou need to install ipykernel to expose your conda environment to jupyter notebooks.conda install ipykernel
python -m ipykernel install --name pyautomagic --user
# now you can run jupyter lab and select a kernel
jupyter labTesting and DocumentationFor contributing, please seecontribution guide.For running tests, please seetesting guide.