Saravanan666/pypi-org huggingface dataset:
Package: controlgraph
controlgraphcontrolgraph is a directed graph which can be traversed to enable parallelized Debian package builds.From the available directories with valid Debian packaging, a graph with directories (representing source packages) for nodes and build dependencies for edges is produced. The reverse of this graph can traversed with a breadth-first search to build in dependency order.controlgraphis a program which returns the controlgraph for a directory to build, in linear or dot format.Installationpip3installcontrolgraphLibrary UsageimportsysfrompathlibimportPathimportcontrolgraphimportnetworkxasnx# get all directoriesdirs=[pforpinPath.cwd().iterdir()ifp.is_dir()]# get map of local binary packages to locally-available source build dependenciespkgs=controlgraph.parse_all_controlfiles(dirs)# generate build dependency graph from mapdep_graph=controlgraph.graph(pkgs)# print full dot graphnx.nx_pydot.write_dot(dep_graph,sys.stdout)# print linear order from depth-first searchprint(" ".join(list(nx.dfs_postorder_nodes(dep_graph))))Outputstrict digraph  {
"opx-nas-daemon";
"opx-common-utils";
"opx-cps";
"opx-logging";
"opx-nas-acl";
"opx-sdi-sys";
"opx-nas-daemon" -> "opx-common-utils";
"opx-nas-daemon" -> "opx-cps";
"opx-nas-daemon" -> "opx-logging";
"opx-nas-daemon" -> "opx-nas-acl";
"opx-common-utils" -> "opx-logging";
"opx-cps" -> "opx-common-utils";
"opx-cps" -> "opx-logging";
"opx-nas-acl" -> "opx-common-utils";
"opx-nas-acl" -> "opx-cps";
"opx-nas-acl" -> "opx-logging";
"opx-sdi-sys" -> "opx-common-utils";
"opx-sdi-sys" -> "opx-logging";
}

opx-logging opx-common-utils opx-cps opx-nas-acl opx-nas-daemon opx-sdi-sysCLI UsageWith one or more directories present, runcontrolgraph.$forrinopx-nas-aclopx-nas-daemonopx-alarmopx-loggingopx-common-utils;dogitclone"https://github.com/open-switch/$r"done$controlgraph
opx-alarmopx-loggingopx-common-utilsopx-nas-aclopx-nas-daemon

$controlgraph--graph
strictdigraph{"opx-alarm";"opx-nas-daemon";"opx-common-utils";"opx-logging";"opx-nas-acl";"opx-nas-daemon"->"opx-common-utils";"opx-nas-daemon"->"opx-logging";"opx-nas-daemon"->"opx-nas-acl";"opx-common-utils"->"opx-logging";"opx-nas-acl"->"opx-common-utils";"opx-nas-acl"->"opx-logging";}
Package: controlgym
controlgymDescriptionControlgymprovides 36 safety-critical industrial control environments and 10 infinite-dimensional PDE-based control problems with continuous, unbounded action and observation spaces that are inspired by real-world applications. This project supports the Learning for Dynamics & Control (L4DC) community, focusing on vital issues: convergence of reinforcement learning (RL) algorithms in policy development, stability, safety, and robustness of learning-based controllers, and the scalability of RL algorithms to high and potentially infinite-dimensional systems. We provide a detailed description ofcontrolgyminthis paper.InstallationClone the RepositoryTo get started, clone thecontrolgymrepository and navigate to folder:gitclonehttps://github.com/xiangyuan-zhang/controlgym.gitcdcontrolgymWindows Installation# Step 1: create and activate a virtual environment (Optional)# Example a: using venvpy-3.10-mvenvcontrolgym-env
.\controlgym-env\Scripts\activate.bat# Example b: using condacondacreate-ncontrolgym-envpython=3.10
condaactivatecontrolgym-env# Step 2: install pytorch with cuda (optional)pip3install--upgradepip
pip3installtorch--index-urlhttps://download.pytorch.org/whl/cu121Installtherepository# Step 3: install the controlgym repository# Example a: using pippip3install-e.# Example b: using poetrypoetryinstall# Step 4: deactivate the virtual environment (Optional)# For venv.\controlgym-env\Scripts\deactivate.bat# For condacondadeactivateLinux/MacOS Installation# Step 1: Create and activate a virtual environment (Optional)# Example a: using venvpython3.10-mvenvcontrolgym-envsourcecontrolgym-env/bin/activate# Example b: using condacondacreate-ncontrolgym-envpython=3.10
condaactivatecontrolgym-env# Step 2: Install the controlgym repository# Example a: using pippip3install-e.# Example b: using poetrypoetryinstall# Step 3: Deactivate the virtual environment (Optional)# For venvdeactivate# For condacondadeactivateGetting StartedCheck out our code examples in thisJupyter notebook file.ReferenceZhang, X., Mao, W., Mowlavi, S., Benosman, M., & Başar, T. (2023).Controlgym: Large-Scale Safety-Critical Control Environments for Benchmarking Reinforcement Learning Algorithms.arXiv preprint arXiv:2311.18736.@article{zhang2023controlgym,title={Controlgym: Large-Scale Safety-Critical Control Environments for Benchmarking Reinforcement Learning Algorithms},author={Zhang, Xiangyuan and Mao, Weichao and Mowlavi, Saviz and Benosman, Mouhacine and Ba{\c{s}}ar, Tamer},journal={arXiv preprint arXiv:2311.18736},year={2023}}
Package: controller
ControllerAppNow, it`s possible to use your phone as a controller to develop games and interactive programs in python!ControllerAppis a tool that allows you to catch all sorts of UI events like a simple tap on your mobile's screen or a device's acceleration directly in your Python code.App InstallationThe app is available atPlay Store.Python Package InstallationInstall the controller package usingpip:pip install controllerHow to useThe communication works with a 6-letters code: it`s enought to put the same code in both App and Python code to start using it.
In the app, the code field is ommited: You just need to minimize the square to make it appears!In the Python side, you can test the tap functionality with the following example:fromcontrollerimportControllerc=Controller('a1b2c3')'''room code'''defmyFunction(x,y):print('hello world',x,y)c.mobile.onTap=myFunctionMore functionsExplore all the possibilities in theControllerApp Documentation.
Package: controlM-rest
# Control M REST API packageThis is package for rest service for Control M, if you wanna know more about the Control M, please visithttp://www.bmcsoftware.com.au/it-solutions/control-m.html## Cores
All the api endpoints are managed by core.py sits under /controlm_rest_api/libraryTo initiate the class CoreAPI, you will need theusername,password, andcontrolM server urlmake the tar.gz filepython setup.py sdist bdist_wheelupload the packagetwine upload  –repository-url https://test.pypi.org/legacy/ dist/*twine upload dist/*
Package: controlmyspa
Balboa ControlMySpa™ cloud API for hot tub spa systemsPython API for ControlMySpa.com cloud-controlled of Balboa spa control systems for hot tubs.https://www.balboawatergroup.com/ControlMySpahttps://controlmyspa.comUsagesee example.py for runnable examplefromcontrolmyspaimportControlMySpaAPI=ControlMySpa("user@example.com","myverysecretpassword")pprint.pprint(API._info)ReferencesBased on the JavaScript libraryhttps://gitlab.com/VVlasy/controlmyspajs
Package: controlnet-aux-voltaml
ControlNet auxiliary modelsThis is a PyPi installable package oflllyasviel's ControlNet AnnotatorsThe code is copy-pasted from the respective folders inhttps://github.com/lllyasviel/ControlNet/tree/main/annotatorand connected tothe 🤗 Hub.All credit & copyright goes tohttps://github.com/lllyasviel.Installpip install controlnet-aux==0.0.3UsagefromPILimportImageimportrequestsfromioimportBytesIOfromcontrolnet_auximportHEDdetector,MidasDetector,MLSDdetector,OpenposeDetector,PidiNetDetector,NormalBaeDetector,LineartDetector,LineartAnimeDetector,CannyDetector,ContentShuffleDetector,ZoeDetector,MediapipeFaceDetector# load imageurl="https://huggingface.co/lllyasviel/sd-controlnet-openpose/resolve/main/images/pose.png"response=requests.get(url)img=Image.open(BytesIO(response.content)).convert("RGB").resize((512,512))# load checkpointshed=HEDdetector.from_pretrained("lllyasviel/Annotators")midas=MidasDetector.from_pretrained("lllyasviel/Annotators")mlsd=MLSDdetector.from_pretrained("lllyasviel/Annotators")open_pose=OpenposeDetector.from_pretrained("lllyasviel/Annotators")pidi=PidiNetDetector.from_pretrained("lllyasviel/Annotators")normal_bae=NormalBaeDetector.from_pretrained("lllyasviel/Annotators")lineart=LineartDetector.from_pretrained("lllyasviel/Annotators")lineart_anime=LineartAnimeDetector.from_pretrained("lllyasviel/Annotators")zoe=ZoeDetector.from_pretrained("lllyasviel/Annotators")# instantiatecanny=CannyDetector()content=ContentShuffleDetector()face_detector=MediapipeFaceDetector()# processprocessed_image_hed=hed(img)processed_image_midas=midas(img)processed_image_mlsd=mlsd(img)processed_image_open_pose=open_pose(img,hand_and_face=True)processed_image_pidi=pidi(img,safe=True)processed_image_normal_bae=normal_bae(img)processed_image_lineart=lineart(img,coarse=True)processed_image_lineart_anime=lineart_anime(img)processed_image_zoe=zoe(img)processed_image_canny=canny(img)processed_image_content=content(img)processed_image_mediapipe_face=face_detector(img)
Package: controlplus
controlplusA package for analysis and design of Control Systems in python by Dr. Ahsen Tahir.Installation$pipinstallcontrolplusUsagefrom controlplus.controlplus import find_rlocus, compensated_pole_from_ts, zero_compensator_tf, draw_overlay_rlocusimport control
import matplotlib.pyplot as pltForward path transfer function:s = control.TransferFunction.s;
G = 1 / (s * (s + 4) * (s + 6))Consider second order approximation:damp_ratio = 0.504Draw root locus with overlaying damping ratio lines with intersecting points/poles:plt.figure(figsize=(8,6));
draw_overlay_rlocus(G, damp_ratio);
plt.show()Desired settling time:new_ts = 1.11Find compensator pole for PD controller:desired = compensated_pole_from_ts(new_ts, damp_ratio)Get polynomial for zero compensator:Gc = zero_compensator_tf(desired, G)Final transfer function:final_G = Gc * GFind poles and respective gains for intersection of damping ratio line and root locus:find_rlocus(G, damp_ratio)Draw root locus with overlaying damping ratio lines with intersecting points/poles:plt.figure(figsize=(8,6));
draw_overlay_rlocus(final_G, damp_ratio);
plt.show()ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensecontrolpluswas created by Dr. Ahsen Tahir. It is licensed under the terms of the GNU General Public License v3.0 license.Creditscontrolpluswas created withcookiecutter.
Package: controlpyweb
ControlPyWebA project to facilitate easy read/write to the ControlByWeb line of Automation/SCADA IO products.DescriptionXytronic Research makes a handy line of remote IO products useful for home and industrial
automation. Interacting with these modules generally requires the use
of a url library such as requests, and then requires dissecting the response to be dissected
and processed. While not terribly difficult to do, it is repetitive.This module seeks to abstract out some of that effort in a thought out and tested way.Installationpip install controlpywebUsageThe basis of functionality is the WebIOModule class. It both acts as a container for individual
IO and handles interaction with the hardware.from controlpyweb.webio_module import WebIOModule
from controlpyweb.single_io import DiscreteIn, DiscreteOut, AnalogIn, AnalogOut


class X404DigitalIn(WebIOModule):   # Name the class whatever you like
    StartButton = DiscreteIn("Start Button", "startButton")
    StopButton = DiscreteIn("Stop Button", "stopButton")
    DoorClosed = DiscreteIn("Door Closed", "doorClosed")


class X410DigitalOut(WebIOModule):
    StartLamp = DiscreteOut("Start Lapm", "redLamp")
    MaintLight = DiscreteOut("Maintenance Lamp", "lamp1")


digital_in = X404DigitalIn("192.168.1.1")
relay_out = X410DigitalOut("192.168.1.2")


digital_in.update_from_module()

relay_out.StartLamp = digital_in.StartButton
relay_out.MaintLight = not digital_in.DoorClosed

relay_out.send_changes_to_module()Immediate reads/writes are supportedrelay_out.StartLamp.write_immediate(True)  
is_started = digital_in.read_immediate()(However, immediate reads/writes are costly from a resource perspective and should be avoided.)Overrides are common for typical operationsif discrete_in.StartButton and discrete_in.DoorClosed:
    discrete_out.StartMachine = True
Package: control-scnu
English |简体中文0.control_scnu1.Install control2.Each corresponding file descriptiontemplateinit.pyfile_operation.pygpio.pyjiami.pymachine_learning.pymaths.pyrequirements.txtshijue (shijue0,shijue1,shijue2)unique.pyyuyin.py0.control_scnuThe library was developed for Huaguang AI Education Innovation Team [Case Department]Applicable to artificial intelligence education1.Install controlpip3installcontrol-scnu2.Each corresponding file descriptiontemplateWhere the various model files are savedinit.pyThe init fileThe version information of the software, programming block and library is indicated in this filefile_operation.pyFile manipulation related librariesgpio.pyCar hardware related library
The car forward routine (This item needs to run on the car):from control import gpio
import time

m=gpio.Mecanum_wheel()
m.uart_init()
m.car_go(200)
time.sleep(2)
m.car_stop()jiami.pyA library for encrypted filesmachine_learning.pyLibrary for machine learningIris machine learning routine:from control import machine_learning as ml

datasets=ml.DatasetsNew(ml.data_name["鸢尾花"])
model= ml.ModelNew(ml.model_name['神经网络'])
model.train(datasets.x_train, datasets.y_train,dataName=datasets.data_name)
model.test(datasets.x_test,datasets.y_test)
print(model.test_score,flush=True)
model.predict(datasets.x_test)
print(model.pred,flush=True)
model.save(name='myFirstModel')
model1=ml.ModelNew('myFirstModel.proto')
model1.test(datasets.x_test,datasets.y_test)
print(model.pred,flush=True)maths.pyLibrary related to basic mathematicsrequirements.txtLibrary dependent TXT fileshijue (shijue0,shijue1,shijue2)Visual related librariesThe camera obtains the image and binarizes the display routine:from control import shijue1

a=shijue1.Img()
a.camera(0)
a.name_windows('img')
while  True:
    a.get_img()
    a.BGR2GRAY()
    a.GRAY2BIN()
    a.show_image('img')
    a.delay(1)unique.pyPut something special in ityuyin.pySpeech correlation libraryRoutines for speech recognition and retelling:from control import yuyin

s=yuyin.Yuyin(online=True) 
s.my_record(3,"speech")   
print(s.stt("speech"),flush=True)  
s.play_txt(s.stt("speech"))
Package: controlspeed
# ControlSpeed这项目是用来控制函数调用的频率, 不仅支持本地的同步线程模式, 而且支持分布式模式.[更多开发描述,请点击链接](http://xiaorui.cc)ControlSpeed(本地版)还不兼容多进程多线程的场景, 当然你可以用ControlSpeedNetwork分布式版解决. 缺点是每次访问都会有一次网络io消耗.#Usage:装饰器使用方法```from controlspeed import ControlSpeed@ControlSpeed(max_calls=10, period=1.0)def do_something():pass```with关键词控制上下文```from controlspeed import ControlSpeedrate = ControlSpeed(max_calls=10, period=1.0)for i in range(100):with rate:do_something()```支持回调函数的控速```from controlspeed import ControlSpeedimport timedef limited(until):duration = int(round(until - time.time()))print 'Speed limited, sleeping for %d seconds' % durationrate = ControlSpeed(max_calls=2, period=3, callback=limited)for i in range(3):with rate:print i```在2.1加入了分布式限频, 借助于redis实现.```import redisredis_conn = redis.StrictRedis()key = 'xiaorui.cc'@ControlSpeedNetwork(redis_conn, key, max_calls=10, period=3.0)def do_something(args):print argstime.sleep(0.1)for i in xrange(20):do_something(i)```
Package: control-tmux
control-tmuxThis is a wrapper aroundtmuxthat allows you to quickly
switch between sessions, save sessions while preserving bash history.RequirementsPython 3.6 or higher with PIP. On Ubuntu, runsudo apt install python3-pip.Tmux 3.0a or higher. On Ubuntu, runsudo apt install tmux.Bash 4.0 or higher (probably works with older versions, but not tested)Installationcontrol-tmuxcan be installed using PIP:python3 -m pip install control-tmuxIn order to use the save and restore features, you must set it up in.bashrcfor each
user. Simply run:python3 -m controltmux --setup tThis will installtmux.setup.shandtmux.default.confin your home directory, and add
references to them to.bashrcand.tmux.conf.You can specify one or more aliases to set up forcontrol-tmux. I recommendtbecause
it is short and easy to type, but power users might already have an alias configured. I
usescnas an alias because this project started out many years ago as a wrapper for GNUscreen. Aliases will only apply to terminals opened in the future, but you can runexec bashto reload your aliases in an existing terminal.The installer will also create a default .tmux.conf if you don't have one. This
configuration is not necessary forcontrol-tmuxto run, but includes many bindings that
make tmux easier to use.Simple usageThese usage examples all assume you have aliasedttocontrol-tmuxduring installatinIf run without arguments,torcontrol-tmuxwill list all your current sessions:To start or switch to a session namedblah, just runt blah:This works whether you are running from within tmux or outside of it. If run from outside,
this runs eithertmux attach -t blahortmux new-session -s blah(ifblahdoesn't
exist) . If run from inside tmux, then it doestmux switch-client -t blah, which
switches your current client to the session namedblah.In either case, this will detach any other terminals that are connected toblah, unless
you prefix the session name withn(e.g.t n blah)To save theblahsession to~/.tmuxsave/blah.zip, runt s blah. To restore, runt r blah. Restore only works when the session doesn't already exist. You can save all open
sessions by runningt s all:Restoring a session restores the current working directory and the command history of the
shell running within it. It does not automatically restart any commands that were running.Recovering from a crashThe bash hooks in.tmux.setup.shwrite your history to disk as soon as you launch a
command. In most cases, after a power failure or crash, the session data will be
recoverable. All you need to do is runt s allbefore running tmux.If you forget and try to runt <session>beforet s all, then it will start a new
instance of tmux and runningt s allwill save the sessions from the new index. However,
the data for the old session is still present in~/.tmuxsave. Runls -ld ~/.tmuxsave/tmux-default-*to see all previous sessions. Each directory will have a
timestamp indicating when that particular instance of tmux was started. Once you have that
directory, just runt -s ~/.tmuxsave/tmux-default-2018-XX-XX__XX-XX-XX s alland it will
save the sessions from the previous instance.
Package: control-toolbox
Python Control Systems ToolboxThecontrol-toolboxis a Python Library for implementing and simulating various systems and control strategies.Current Supported Functionality:System modeling with Transfer Functions and State Space Representations.Time Domain Response.Frequency Response.System Representation conversion: State Space model to Transfer Function and vice versa.Block diagram algebra: Series and Parallel.Stability Analysis.Root Locus.Bode Plot.Parameterization of System.Pole-Zero / Eigenvalue plot of systems.Feedback analysis.PID control.Observability and Controllability.Full State Feedback.Full State Observer.Linear Quadratic Regulator(LQR).Linear Quadratic Estimator(LQE) / Kalman Filter.Linearization.System Identification.Future Updates:Linear Quadratic Gaussian Control.Extended Kalman Filter.Unscented Kalman filter.Model Predictive Control.Project LinksProject Homepage:http://control-toolbox.rtfd.io/Documentation:https://control-toolbox.readthedocs.io/InstallationPipTo install using pip, run the following command:pip install control-toolboxDevelopmentTo get the latest unreleased version:git clone https://github.com/rushad7/control-toolbox.git
Package: controme
Controme API Python WrapperDieses Repository enthält einen Python-Wrapper für die Controme-API, der es ermöglicht, auf einfache Weise Abfragen und Befehle an die Controme-Smart-Home-Heizungssteuerung zu senden.FeaturesEinfache Python-Schnittstelle für die Controme-APIAbfrage von Informationen wie Abweichungen, Fußbodenheizungsparametern (FPS) und HeizprogrammenEinstellung von Sollwerten, Zielwerten, Temperaturszenen, Standarddauern, Raum- und Haus-OffsetsInstallationUm dieses Modul zu verwenden, installieren Sie es über pippipinstallcontromeoderpython3-mpipinstallcontromeBeispielEin Beispiel, wie Sie dieses Modul verwenden können:fromcontromeimportContromeAPIbase_url="http://miniserver_ip"haus_id=1user="your.email@example.com"password="your-password"api=ContromeAPI(base_url,haus_id,user,password)deviation=api.get_deviation()print(json.dumps(deviation,indent=2))Bitte ersetzen Sie your.email@example.com und your-password durch Ihre eigenen Zugangsdaten.DokumentationDie Klasse ContromeAPI stellt die folgenden Methoden zur Verfügung:get_deviation(raum_id=None)get_fps(raum_id=None)get_heizprogramm()set_soll(raum_id, soll)set_ziel(raum_id, ziel, duration)set_temperaturszenen(szene_id, duration=None)set_default_duration(duration)set_roomoffset(raum_id, offset, offset_name)set_houseoffset(offset, offset_name)Bitte beachten Sie die Dokumentation in der Klasse für weitere Informationen zu den einzelnen Methoden und ihren Parametern.LizenzDieses Projekt steht unter der MIT-Lizenz. Weitere Informationen finden Sie in der Datei LICENSE.HaftungsausschlussBitte beachten Sie, dass dieses Projekt nicht von Controme oder einem ihrer Partner unterstützt oder offiziell unterstützt wird. Die Nutzung dieses Moduls erfolgt auf eigenes Risiko, und die Autoren übernehmen keine Verantwortung für mögliche Schäden oder Verluste im Zusammenhang mit der Nutzung dieses Codes.BeitragFühlen Sie sich frei, Pull-Requests zu erstellen oder Probleme zu melden, um dieses Projekt zu verbessern.
Package: conttest
# conttestContinuous testing helper, adapted from [1], but which makes noassumption about what tests you might want to run continuously whiledeveloping.  For more information, see [this blog post](http://eigenhombre.com/testing/2012/03/31/ontinuous-testing-in-python-clojure-and-blub/).**Any command supplied to the script will be run once andthen repeated any time the code in the current working directorychanges.**  You may wish to edit the IGNORE_* tuples to suit yourparticular setup.Note that ANY command you supply the script will be run, so becareful.  You have been warned![1] https://github.com/brunobord/tdaemon/blob/master/tdaemon.py### Installation./setup.py install  # from sourceorpip install conttest  # use sudo if installing globally### Usage examplesconttest nosetestsconttest 'nosetests -q && pep8 -r .'Placing a file .conttest-excludes in the current working directorywill exclude subdirectories, e.g.:.svn$.gitbuildvendor/elastic*installwill match files against the listed regular expressions and skip checkingfor changes in those directories.  This can save quite a bit of time and CPUduring normal operation.## Author[John Jacobsen](http://eigenhombre.com)## LicenseEclipse Public LicenseTHE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS ORIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OF THIRD PARTY RIGHTS. INNO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OROTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USEOR OTHER DEALINGS IN THE SOFTWARE.