Saravanan666/pypi-org huggingface dataset:
Package: acore-server-metadata
Welcome toacore_server_metadataDocumentation背景AzerothCore(acore) 是一个开源的魔兽世界模拟器, 其代码质量以及文档是目前 (2023 年) 我看来所有的开源魔兽世界模拟器中最好的. 根据魔兽世界官服服务器的架构, 每一个 realm (大区下的某个服务器, 例如国服著名的山丘之王, 洛萨等) 一般都对应着一个单体虚拟机和一个单体数据库. 一个大区下有很多这种服务器, 而在生产环境和测试开发环境下又分别有很多这种服务器. 所以我需要开发一个工具对于这些服务器进行管理, 健康检查等.我假设游戏服务器虚拟机和数据库都是在 AWS 上用 EC2 和 RDS 部署的. 所以这个项目只能用于 AWS 环境下的服务器管理.关于本项目本项目是一个简单的 Python 包, 提供了对一个 realm 服务器的抽象.基础用例, 获取服务器状态# 获取服务器的状态>>>importboto3>>>fromacore_server_metadata.apiimportServer>>>server_id="prod">>>server=Server.get_server(server_id,ec2_client,rds_client)>>>serverServer(id='prod-1',ec2_inst=Ec2Instance(id='i-1a2b3c4d',status='running',...tags={'wserver:server_id':'prod'},data=...),rds_inst=RDSDBInstance(id='db-inst-1',status='available',tags={'wserver:server_id':'prod'},data=...),)# 检查服务器的状态>>>server.is_exists()>>>server.is_running()>>>server.is_ec2_exists()>>>server.is_ec2_running()>>>server.is_rds_exists()>>>server.is_rds_running()# 重新获取服务器的状态>>>server.refresh()# 批量获取服务器的状态, 进行了一些优化, 以减少 API 调用次数>>>server_mapper=Server.batch_get_server(...ids=["prod-1","prod-2","dev-1","dev-2"],...ec2_client=ec2_client,...rds_client=rds_client,...)>>>server_mapper{"prod-1":<Serverid="prod-1">,"prod-2":<Serverid="prod-2">,"dev-1":<Serverid="dev-1">,"dev-2":<Serverid="dev-2">,}对服务器进行操作# 创建新的 EC2>>>server.run_ec2(ec2_client,ami_id,instance_type,...)# 创建新的 DB Instance>>>server.run_rds(rds_client,db_snapshot_identifier,db_instance_class,...)# 启动 EC2>>>server.start_ec2(ec2_client)# 启动 RDS>>>server.start_rds(rds_client)# 停止 EC2>>>server.stop_ec2(ec2_client)# 停止 RDS>>>server.stop_rds(rds_client)# 删除 EC2>>>server.delete_ec2(ec2_client)# 删除 RDS>>>server.delete_rds(rds_client)# 更新 DB 的 master password>>>server.update_db_master_password(rds_client,master_password)# 关联 EIP 地址>>>server.associate_eip_address(...)# 创建数据库备份>>>server.create_db_snapshot(...)# 清理数据库备份>>>server.cleanup_db_snapshot(...)Installacore_server_metadatais released on PyPI, so all you need is to:$pipinstallacore-server-metadataTo upgrade to latest version:$pipinstall--upgradeacore-server-metadata
Package: acore-soap-app
Welcome toacore_soap_appDocumentation📔完整文档点这里魔兽世界服务器 worldserver 自带一个交互式的 Console. GM 可以在里面输入命令来创建账号, 修改密码, 封禁账号等. 你如果用 GM 账号登录游戏, 你也可以在游戏内聊天框输入 GM 命令, 本质是一样的. 但是你需要 SSH 到服务器上才能访问这个 Console 界面, 又或是要登录游戏才能输入 GM 命令, 且这些命令必须要人类手动输入. 简而言之, 这套系统是给人类用的. 但是作为服务器维护者, 你会有需要用程序扫描数据库, 日志分析用户行为, 并且进行自动化维护, 例如封号, 发邮件等等. 这些自动化运维的脚本可能是在游戏服务器上运行, 也可能是在其他地方运行, 例如其他 EC2, 容器, Lambda. 这时我们就需要一套机制能安全地 (仅让有权限的人或机器) 远程执行 GM 命令. 这个需求对于长期的正式运营非常重要. 例如你需要玩家能登录你的服务器官网注册账号, 交易物品等等. 那么你就需要你的官网 Web 服务器能远程执行一些 GM 命令.该项目是一个针对这个需求的完整解决方案, 它包含两个组件 Agent 和 SDK.Agent: 提供了一个部署在游戏服务器 EC2 上的命令行程序, 作为外部 API 调用的桥梁. 使得外部有权限的开发者可以通过 AWS SSM Run Command 远程调用这个命令行程序, 从而实现远程执行 GM 命令.SDK: 提供了一套远程运行服务器命令的 SDK, 并提供了很多高级功能例如批量执行, 错误处理等功能. 使得开发者可以很方便的编写出基于 GM 命令的应用程序.在 EC2 上安装完 Agent 之后, 你可以用下面的命令测试./home/ubuntu/git_repos/acore_soap_app-project/.venv/bin/acsoapgm".server info"Installacore_soap_appis released on PyPI, so all you need is to:$pipinstallacore-soap-appTo upgrade to latest version:$pipinstall--upgradeacore-soap-app
Package: acorn
Automatic Computational Research Notebookacornuses the mutability of python objects, together with
decorators, to produce an automatic notebook for computational research.
Common libraries likenumpy,scipy,sklearnandpandasare mutated with decorators that enable logging of calls to important
methods within those libraries.This is really helpful for data science where experimenting with fits,
pipelines and pre-processing transformations can result in hundreds of
fits and predictions a day. At the end of the day, it is hard to
remember which set of parameters produced that one fit, which (of
course) you didn’t realize was important at the time.The library iswell
documented.Basic FlowDepending on the logging level, every time a method/function is
called (whether bound or unbound), we log it into a JSON database.The JSON database is analyzed using javascript by the browser to
produce nice sets of objects, separated by project, task, date and
specific object instances.A nice UI usingbootstrappopulates the HTML dynamically.SynchronizationWe recommend that the JSON database directory be configured on a Dropbox
folder (later we will support Google Drive, etc.). The HTML notebook can
be authorized (per session) to have access to Dropbox so that the JSON
databases can be accessed from anywhere (and any device). Thi HTML and
javascript is completely standalone (i.e., no server backend required
outside of the web service requests).ContributionIf this sparks your interest, please message us. The project is still in
early development, so we can’t say more up front.Special NotesThematplotlibmodule is used frequently, but not in the typical
way. Most of the methods and objects are used internally unless a plot
is being tweaked for some special reason. Thematplotlib.cfgfile
prunes the number of objects that get decorate very aggressively so that
only the common calls are logged. You can adjust your own local config
file if you spend a lot of time actually codingmatplotlibinternals.
Package: aco-routing
Ant Colony OptimizationA Python package to find the shortest path in a graph using Ant Colony Optimization (ACO).The Ant colony Optimization algorithm is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs (source).This implementation of the ACO algorithm uses theNetworkXgraph environment.🏁 Getting StartedTo install the package directly from PyPi:$ pip install aco_routing🎈 UsageCheck out:example.pyImport all the dependencies:fromaco_routingimportACOimportnetworkxasnxCreate aNetworkX.Graphobject with nodes and edges:G=nx.DiGraph()G.add_edge("A","B",cost=2)G.add_edge("B","C",cost=2)G.add_edge("A","H",cost=2)G.add_edge("H","G",cost=2)G.add_edge("C","F",cost=1)G.add_edge("F","G",cost=1)G.add_edge("G","F",cost=1)G.add_edge("F","C",cost=1)G.add_edge("C","D",cost=10)G.add_edge("E","D",cost=2)G.add_edge("G","E",cost=2)Use ACO to find the shortest path and cost between thesourceanddestination:aco=ACO(G,ant_max_steps=100,num_iterations=100,ant_random_spawn=True)aco_path,aco_cost=aco.find_shortest_path(source="A",destination="D",num_ants=100,)Output:ACO path: A -> H -> G -> E -> D
ACO path cost: 8.0📦 ContentsAntaco_routing.AntAnAntthat traverses the graph.ACOaco_routing.ACOThe traditional Ant Colony Optimization algorithm that spawns ants at various nodes in the graph and finds the shortest path between the specified source and destination (pseudo code).ContributingPost any issues and suggestions on the GitHubissuespage.To contribute, fork the project and then create a pull request back to master.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.
Package: acos-client
ACOS ClientTable of ContentsSupported VersionsInstallation for ACOSv4.1.4Installation for ACOSv4.1.1Example usage informationContributing & TestingIssues and InquiriesHelpful LinksSupported Versions| ACOS Version   | AXAPI Version | ACOS Client Version | Status      |
| 2.7.1†         | 2             | >=0.1.0,<0.3.0      | end-of-life |
| 2.7.2          | 2             | >=0.1.0,<0.3.0      | end-of-life |
| 4.0.0          | 3             | >=1.4.6,<1.5.0      | end-of-life |
| 4.1.1          | 3             | >=1.5.0,<2.0.0      | end-of-life |
| 4.1.4 GR1-P2   | 3             | >=2.0.0,<2.4.0      | end-of-life |
| 4.1.4          | 3             | >=2.4.0             | end-of-life |
| 4.1.4 GR1-P5   | 3             | >=2.6.0             | Maintenance |
| 5.2.1          | 3             | >=2.6.0             | Maintenance |
| 5.2.1-p1       | 3             | >=2.7.0             | Maintenance |
| 5.2.1-p2       | 3             | >=2.9.0             | Maintenance |
| 5.2.1-p2       | 3             | >=2.9.1             | Maintenance |
| 5.2.1-p2       | 3             | >=2.10.0            | Maintenance |†Works only when not using partitioningInstallationInstall using pip$pipinstallacos-client>=2.9.0Install from source$gitclonehttps://github.com/a10networks/acos-client.git
$cdacos-client
$gitcheckoutstable/stein
$pipinstall-e.Usagec=acos_client.Client('somehost.example.com',acos_client.AXAPI_30,'admin','password')Example setting up an SLB:importacos_clientasacosc=acos.Client('1.2.3.4',acos.AXAPI_30,'admin','password')c.slb.server.create('s1','1.1.1.1')c.slb.server.create('s2','1.1.1.2')c.slb.service_group.create('pool1',c.slb.service_group.TCP,c.slb.service_group.ROUND_ROBIN)c.slb.virtual_server.create('vip1','1.1.1.3')c.slb.hm.create('hm1',c.slb.hm.HTTP,5,5,5,'GET','/','200',80)c.slb.service_group.update('pool1',health_monitor='hm1')c.slb.service_group.member.create('pool1','s1',80)c.slb.service_group.member.create('pool1','s2',80)ContributingFork itCreate your feature branch (git checkout -b my-new-feature)Commit your changes (git commit -am 'Add some feature')Push to the branch (git push origin my-new-feature)Create new Pull RequestTestingThis project usestoxfor testing. To run
the test suite simply:$sudopipinstalltox# use pip2 if using Arch Linux$cd/path/to/acos_client
$toxIssues and InquiriesFor all issues, please send an email tosupport@a10networks.comHelpful linksImproved speedpypy:http://pypy.org/index.htmlOld python versionsDeadsnakes github:https://github.com/deadsnakesDeadsnakes ppa:https://launchpad.net/~deadsnakes/+archive/ubuntu/ppa
Package: acousondePy
acousondePyTranslate Acousonde MT filesThis software lets you load any Acousonde produced MT files and convert them into easier to use formats.Acoustic data files are converted into wav filesHeader information is stored as csv fileAuxiliary data if present is concatenated into one csv fileFor more information on Acousonde visit theAcousonde websiteCurrently there are 4 functions available:MTread() to read one MT filespec_plot(p,HEADER,INFO) to create a spectrogram plotread_multiple_MT() to read a list of MT filesacousonde() starts a GUI which allows you to convert slected MT filesAcousonde is available onPypiA single Windows executable file of acousonde() which can be used without the need of any programming/scripting and does not require the user to have Python isnstalled can be obtained fromSourceforge.Installationpip install acousondePyIf you have a previous version of acousondePy installed upgrade the package:pip install acousondePy -ULicenceThis software is free to use.MIT License

Copyright (c) 2020 Sven Gastauer

Permission is hereby granted, free of charge, to any person obtaining a copy of this 
software and associated documentation files (the "Software"), to deal in the Software 
without restriction, including without limitation the rights to use, copy, modify, 
merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit 
persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies 
or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, 
INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A 
PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT 
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION 
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE 
OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.ExamplesFor a full example have a look at the Notebooks in the notebook folder.importacousondePyasapimportglob#get example file dirpdir=ap.__path__[0]#get list of example filesfns=glob.glob(pdir+'\\\data\*.MT')#read an acoustic MT filep,HEADER,INFO=ap.MTread(fns[4])#create a spectrogram plot_=ap.spec_plot(p,HEADER,INFO)#read multiple MT filesap.read_multiple_MT(fns)
Package: acoustic-analyser
Acoustic AnalyserAn Open Source package to perform nodal analysis on simple 2D structures using wave based approachAuthorsDhruv BhatiaDr. Abhijit SarkarInstallationPre-requisites:numpysympyscipymatplotlibYou can install tha package through both pip and using the releases present on github.Installing through pip:pipinstallacoustic_analyserInstalling through github:You can find the latest release zip filehereDownload the zip file to a folder and extract its contentsThen run the following command in the terminal from the folder you extracted:pipinstall.Usage:You can find the example problems to get startedhere.
Package: acoustics
python-acousticsThepython-acousticsmodule is a Python module with useful tools for acousticians.InstallationThe latest release can be found on PyPI and installed withpip install acoustics.
Otherwise, you can clone this repository and install withpip installorpip install -ewhen you want an editable install.ExamplesSeveral examples can be found in theexamplesfolder.TestsThe test suite can be run withpytestDocumentationDocumentation can be foundonline.Licensepython-acousticsis distributed under the BSD 3-clause license. SeeLICENSEfor more information.ContributingContributors are always welcome.
Package: acoustics-hardware
This Python package provides a unified interface to serveral hardware platforms used in acoustic measurements, e.g. audio interfaces.
The purpose of this package is twofold, both to enable cross-hardware interactions with a consistent interface, and to simplify scripting of advanced measurement setups.Documentation:http://acoustics-hardware.readthedocs.io/Source code and issue tracker:https://github.com/AppliedAcousticsChalmers/acoustics-hardware
Package: acousticspy
This is a package that I am writing during my time as a graduate student at Brigham Young University. My research is in aeroacoustics, and most of our code is written in MATLAB. Knowing that I may not always have access to MATLAB, and because I enjoy open-source software, I’ve decided to create code in Python that performs many of the same tasks that we regularly perform for research. My dream is that this package can develop to the point where it could realistically be used to do all of the same research that we currently perform in MATLAB.
Package: acpibacklight
A python library and script for changing brightness on Linux via acpi.
Allows for easing animations too!pipinstallacpibacklightYou can use the scriptacpi-ease-backlightto adjust the backlight
with easing via acpi on your device. Seeacpi-ease-backlight--helpfor options.CLI UsageAfter installing via pip, use the scriptacpi-ease-backlight. Here
is how you might use it:$acpi-ease-backlight-h# see help...$acpi-ease-backlightshow# show the current backlight value4000$acpi-ease-backlightmax# show the your display's max backlight value4882$acpi-ease-backlightset2000# set the backlight to 2000, over the default# duration of 0.25 seconds and using the default# easing function 'easeOutCubic'$acpi-ease-backlight-d1-eeaseInOutQuadset3000# set the backlight to 3000 over duration of# 1 second, using the easing function 'easeInOutQuad'$acpi-ease-backlight-d0.5dec1000# decrease the current backlight value by# 1000 over a duration of 0.5 secondsLibrary UsageInstantiatingUse the classacpibacklight.AcpiBacklightControlfor changing the
backlight level in various ways.AcpiBacklightControlis designed to
use pythonwithstatements similarly to file objects and python’sopenbuiltin:fromacpibacklightimportAcpiBacklightControlwithAcpiBacklightControl()asctrl:# set the brightness without animatingctrl.brightness=2000# get max brightness on this devicenew_brightness=ctrl.max# You can also use the animate function on the AcpiBacklightControl.# See the docstring for kwargsctrl.animate(new_brightness,duration=0.75)Alternatively, you can construct, then open, then close theAcpiBacklightControl:ctrl=AcpiBacklightControl()ctrl.open()ctrl.animate(ctrl.brightness-1000)ctrl.close()If you have multiple ACPI backlight devices, specify the name when
constructing theAcpiBacklightControl. Otherwise, the default is the
first device directory found.ctrl=AcpiBacklightControl(device_dir='intel_backlight')Easing FunctionsYou can pass an easing function to be used inanimate()by theeasing_funckeyword arg. This package usesPyTweeningfor its default
animation and the CLI, so you can easily pass one of those:importpytweeningctrl.animate(2345,easing_func=pytweening.easeInOutBounce)Finally, if you want to create and pass your own easing function, it
should take one paramater (time) between 0 and 1, and return a value
between 0 and 1. For instance, a linear easing function would look like:deflinear_easing(t):# t is always in the range [0, 1]returnt# ...ctrl.animate(1234,easing_func=linear_easing)
Package: acpic
acpic - an acpid clientThis little daemon extendsacpidevent handling capabilities. Normally, event handlers are placed by root in/etc/acpi/events/. With acpic, you can place additional handlers in a per-user~/.config/acpi/events/directory.I personally use it to control PulseAudio with hardware volume buttons on my
laptop (seeexamples).InstallationThe easiest way is to installacpicwithpip:$ pip install acpicThen, place your handlers in~/.config/acpi/events/and makeacpicsomehow
start when you log in, for example by creating an XDG-compliant entry in~/.config/autostart/acpic.desktop:[Desktop Entry]
Name=acpic
Comment=acpid event handler
TryExec=acpic
Exec=acpic
Type=ApplicationLicenseCopyright © 2018-2022Piotr ŚliwkaThis work is free. You can redistribute it and/or modify it under the terms of
the Do What The Fuck You Want To Public License, Version 2, as published by Sam
Hocevar. See theCOPYINGfile for more details.
Package: acpipe-acjson
About the acjson project ...This is a python3 library to produce and process acjson objects.Acjson (assay coordinate java script object notation) is
in the big picture a json syntax (http://json.org/) compatible file format,
that was developed to capture the most essential experimental annotations
of a biological wetlab experiment,
how ever simple or complicated the layout may be.In the guts of this file format is each experimental condition described as a single coordinate.Each coordinate is an adaptation of the input-processing-output (IPO) model from software engineering,
which is used to describe the structure of an information processing program.
In the biological experiment use-case, these are represented by (SPE) sample, perturbation, and assay endpoints,
which are represented as three axes.Each of this axis can hold as many sample or reagent records as needed to describe the experimental condition.This library can produce and process such acjson objects.Howto guideHow to install acpipe_acjson?pip3installacpipe_acjsonHow to load the acpipe_acjson library?importacpipe_acjson.acjsonasacHowto get reference information about the implemented constants and functions?importacpipe_acjson.acjsonasac# basic constantsac.ts_ABCac.ts_ACAXISac.ts_NOTCOORac.ts_COORSYSac.d_WELLac.d_RECORDac.d_RECORDLONG# record dictionary add on constantsac.d_SETac.d_EXTERNALIDac.d_SAMPLEac.d_MICROSCOPEac.d_PRIMANTIBODYac.d_SECANTIBODY# leaf constantsac.leafac.es_DATAFRAMELEAF# 96 to 386 well constantesac.dii_96A1ac.dii_96A2ac.dii_96B1ac.dii_96B2# functionhelp(ac.retype)help(ac.escoor)help(ac.icoormax)help(ac.ispotmax)help(ac.ispot)help(ac.xy2icoor)help(ac.acrelabel)help(ac.acbuild)help(ac.acfuseaxisrecord)help(ac.acfusewellrecord)help(ac.acfuserepeat0011)help(ac.acfuserepeat0101)help(ac.acfuseobject)help(ac.acfuse4to1)help(ac.count_record)help(ac.record_in_acjson)help(ac.list_uniq_record)help(ac.max_record)help(ac.pop_record)help(ac.pop_ac)help(ac.xray)help(ac.acjson2layouttsv)help(ac.acjson2dataframetsv)
Package: acpy
# Accounting Center [![Build Status](https://travis-ci.org/uzh/acpy.svg?branch=master)](https://travis-ci.org/uzh/acpy) [![PyPI version fury.io](https://badge.fury.io/py/acpy.svg)](https://pypi.org/project/acpy/)The Accounting Center (API) aims to provide a stable rest interface for accounting resource usage of clusters and private clouds and managing users of a group/tenant.
The idea is that users authenticate on the service using an LDAP compliant account, and can see their own resource usage, and group resource usage.
If users are group administrators, they can add/remove users from the group.In some magical way to be defined (probably with a couple of hacky scripts and cron), cluster controllers and cloud controllers will regularly update resource usage using a service account.
These controllers will also check (and modify) existing group structures within their respective systems.The package is self contained and has a command line interface.
Information regarding the configuration options can be found in the docs.
Details regarding the CLI options can be found in the [docs](https://acpy.readthedocs.io/en/latest/) (and by running acpy –help).
The application is hosted on port 8080 by default.
In production run [nginx](https://www.nginx.com/) in front of it as a reverse proxy, with HTTPS configured (check the [docs](https://acpy.readthedocs.io/en/latest/) for the recommended installation and settings).NOTE: this is all still alpha, only use as a reference for the time being## Installation
Either install the package using pip:`bash pip install acpy `or clone this repo and run:`bash pip install-e. `or simply build and run the docker image:`bash docker build-tacpy . docker run-p8080:8080 acpy start `## Using
Information regarding available commands:`bash acpy--help`To run the tests:`bash python-mpytest tests/ `To start the service:`bash acpy start `
Package: acq4-autopatch
ACQ4-AutopatchAutomated cell patching extension for ACQ4InstallationInstall the package into your environment with e.g.pipinstallacq4_autopatchorgitclonehttps://github.com/sensapex/acq4-autopatch.git
condadevelopacq4-autopatchCustomize the following to suit your hardware and add it to themodules:section of your ACQ4default.cfgfile:Autopatch:module:'acq4_autopatch.module.AutopatchModule'config:imagingDevice:'Camera'patchDevices:PatchPipette1:(0, 0)# bottom-left quadPatchPipette2:(50*mm, 0)# bottom-right quadPatchPipette3:(0, 50*mm)# top-left quadPatchPipette4:(50*mm, 50*mm)# top-right quadplateCenter:(0, 0, 0)wellPositions:[(0,0),(50*mm,0),(0,50*mm),(50*mm,50*mm)]patchStates:cell detect:maxAdvanceDistancePastTarget:1*umseal:autoSealTimeout:60pressureMode:'auto'cell attached:autoBreakInDelay:5.0clean:approachHeight:3*mmcleanSequence:[(-35e3,1.0),(65e3,1.5)]*5rinseSequence:[(-35e3,3.0),(65e3,15.0)]cameraChannels:# Use different (exposure, trigger) DAQ lines for each pipette devicePatchPipette1:('/Dev1/port0/line0', '/Dev1/port0/line1')PatchPipette2:('/Dev2/port0/line0', '/Dev2/port0/line1')PatchPipette3:('/Dev3/port0/line0', '/Dev3/port0/line1')PatchPipette4:('/Dev4/port0/line0', '/Dev4/port0/line1')UsageBriefly:Make sure you have an active Storage directory in the DataManager module.Open the Camera module.The first time through, use this to move each pipette into its home, clean and rinse positions.In the main ACQ4 Manager window, save the home on each Manipulator.In the main ACQ4 Manager window, save the clean and rinse on each PatchPipette.Do any other calibration necessary.For each pipette, open a separate TaskRunner module.Enable the Clamp associated with this pipette.Configure the tasks to be performed after a cell is patched.Open the MultiPatch module. This is useful for monitoring.Open the Autopatch module.Press "Add Points" and add one in the Camera for every cell you'd like to patch. Repeat for each well.Pick your acquisition protocol.Press "Start"Monitor status in the "Pipettes" pane or in the MultiPatch window.Read through results or look at errors in the "Results" pane.TODO create and then link to video explanation.LicensingAll software copyright (c) 2019-2020 Sensapex. All rights reserved. It is offered under multiple different
licenses, depending on your needs:A commercial license is appropriate for development of proprietary/commercial software where you do not want
to share any source code with third parties or otherwise cannot comply with the terms of the GNU GPL
version 3. To purchase a commercial license, contactour sales team.Licensed under the GNU General Public License (GPL) version 3 is appropriate for the development of
open-source applications, provided you can comply with the terms and conditions of the GNU GPL version 3 (or
GNU GPL version 3). SeeGPL-3for details.