Saravanan666/pypi-org huggingface dataset:
Package: tpd-analyse
TPD analysis for first order desorption processDetailsCalculate the adsorption energy, configurational entropy and adsorbate-adsorbate interaction parameter for first order desorption from TPD curves.Equations used to fit are described in the manuscipt: How to Extract Adsorption Energies, Adsorbate-adsorbate Interaction Parameters, and Saturation Coverages from Temperature Programmed Desorption Experiments (link)InstallationThe package can be installed viapip install tpd-analyseUsageAll inputs must be passed to the central classPlotTPD. An example of some possible inputs are shown below.TPDClass = PlotTPD(exp_data=files,
                        order=order,
                        thermo_ads=vibration_energies_ads,
                        thermo_gas=vibration_energies_gas,
                        plot_temperature=np.linspace(100, 500, 50), 
                        T_switch=T_switch_211,
                        T_max=T_max_211,
                        T_rate_min=T_rate_min_211,
                        beta=beta_211)exp_data: list of filenames. Each filename must be of the formatexposure_<some_value>.csvwhere some_value can be the exposure in any units.order: currently only first order desorption reactions are implemented, soorder=1thermo_ads: Here theaseclassHarmonicThermocan be passed with the required inputs for the adsorbate(s) of interest. More information about the class can be foundhere.thermo_gas: Similar to thethermo_ads, only for gas molecules. One option is to useIdealGasThermoplot_temperature: A temperature range that the equibirium coverage can be determined in. An example range would be `np.linspace(100, 500)T_switch: Is there are more than one processes occuring in one TPD plot, supply a list of temperatures to switch from one to another in K.T_max: Maximum temperature to consider forallthe TPDs.T_rate_min: Minimum temperature at which the baseline correction can be done.beta: Heating rate in K/scorrect_background(optional): bool to decide if the background is correctedp(optional): Pressure in the case ofequilibirum, only useful if equilbirum coverages are neededinitial_guess_theta(optional): Initial guess for the coverage in the Newton root solverguess_b(optional): Guess for the ads-ads interaction.calculate_eq_coverage(oprtional): Decide is the equilibrium coverage is computed.
Package: tpdataset
pyctlibIntroductionPackagepyctlibis the fundamental package for projectPyCTLib, a powerful toolkit for python development. This package provides basic functions for fastpython v3.6+programming. It provides easy communication with the inputs and outputs for the operating systems. It provides quick try-catch functiontouch, useful types likevector, timing tools liketimethisandscopeas long as manipulation of file path, reading & writing of text/binary files and command line tools.InstallationThis package can be installed bypip install pyctlibor moving the source code to the directory of python libraries (the source code can be downloaded ongithuborPyPI).pipinstallpyctlibBasic Typesvectorvectoris an improved implement oflistfor python. In addition to original function forlist, it has the following advanced usage:In[1]:frompyctlib.basictypeimportvectorIn[2]:a=vector([1,2,3,4,5,6,7,8,9,10])In[3]:a.map(lambdax:x*2)Out[3]:[2,4,6,8,10,12,14,16,18,20]In[4]:a.filter(lambdax:x%2==0)Out[4]:[2,4,6,8,10]In[5]:a.all(lambdax:x>1)Out[5]:FalseIn[6]:a.any(lambdax:x==2)Out[6]:TrueIn[7]:a[a>7]=7In[8]:aOut[8]:[1,2,3,4,5,6,7,7,7,7]In[9]:a.reduce(lambdax,y:x+y)Out[9]:49In[10]:a.index(lambdax:x%4==0)Out[10]:3File ManagementTiming Toolsscope>>>frompyctlibimportscope,jump>>>withscope("name1"):...print("timed1")...timed1[name1takes0.000048s]>>>withscope("name2"),jump:...print("timed2")...>>>timethis>>>frompyctlibimporttimethis>>>@timethis...deffunc():print('timed')...>>>func()timed[functakes0.000050s]Touch function>>>frompyctlibimporttouch>>>touch(lambda:1/0,'error')'error'>>>touch('a')>>>a=4>>>touch('a')4Acknowledgment@Yiteng Zhang, Yuncheng Zhou: Developers
Package: tpdcclib
Collection of Python modules to write DCC tools in a DCC agnostic way.When working with specific DCCs, tpDccLib will auto import proper modules and will use
DCC specific implementations.InstallationManual1. Clone/Download tpDccLib anywhere in your PC (If you download the repo, you will need to extract
the contents of the .zip file).CopytpDccLibfolder located insidesourcefolder in a path added tosys.pathAutomaticAutomatic installation for tpDccLib is not finished yet.DCC ImplementationsAt this moment following DCCs are supported:3ds Max:https://github.com/tpoveda/tpMaxLibMaya:https://github.com/tpoveda/tpMayaLibHoudini:https://github.com/tpoveda/tpHoudiniLibNuke:https://github.com/tpoveda/tpNukeLibBlender:Work in ProgressDuring tpDccLib initialization, if DCC specific implementation package is found in sys.path, tpDccLib
will automatically detect it and will import it.UsageInitialization CodetpDccLib must be initialized before being used.importtpDccLibtpDccLib.init()ReloadingFor development purposes, you can enable reloading system, so
you can reload tpDccLib sources without the necessity of restarting
your Python session. Useful when working with DCCs.importtpDccLibreload(tpDccLib)tpDccLib.init(True)Enabling debug logBy default, tpDccLib logger only logs warning messages. To enable all log messages
you can set TPDCCLIB_DEV environment variables to ‘True’importosos.environ['TPDCCLIB_DEV']='True'importtpDccLibtpDccLib.init()Deploying new version (only for devs)Update versionMake suresetup.cfgfile version field is updatedInstalling librariesMake sure that you have installed the following packages:wheelpip install wheeltwinepip install twinesetuptoolspip install setuptoolsMake sure to update setuptools to latest available version:pip install setuptools --upgradeGenerate wheelpython setup.py sdist bdist_wheelValidate wheel package generationtwine check dist/*Upload package to PyPitwine upload dist/*
Package: tpdne
Quickstarttpdne is available on PyPI and can be installed withpip.$pipinstalltpdneAfter installing tpdne you can use it like any other Python module.Here is a simple example:importtpdneimage=tpdne.tpdne_base64()Or, if being used within a Jupyter Notebook:importtpdnefromIPython.displayimportImage,MarkdownImage(data=tpdne.tpdne_bytes())Markdown('<img src="data:image/png;base64,{}" />'.format(tpdne.tpdne_base64()))
Package: tpdne-py
tpdne-pya very simple wrapper around requests/aiohttp for thispersondoesnotexist.com (and similar)provides 4 objects, Person, Aioperson, Horse, and AioHorse usage:from tpdne import Person

def main() -> None:
    x = Person()
    with open('test.png', 'wb') as f:
        f.write(x.bytes)

if __name__ == "__main__":
    main()from tpdne import AioPerson
import asyncio

async def main() -> None:
    x = await AioPerson()
    with open('test.png', 'wb') as f:
        f.write(x.bytes)

if __name__ == "__main__":
    asyncio.run(main())optionallyfetch=Falsecan be passed to the constructors so that the image can be fetched at a later time withPerson.fetch()orawait AioPerson.fetch()from tpdne import Person

def main() -> None:
    x = Person(fetch=False)
    # do something
    bytes = x.fetch()
    with open('test.png', 'wb') as f:
        f.write(bytes)

if __name__ == "__main__":
    main()from tpdne import AioPerson
import asyncio

async def main() -> None:
    x = await AioPerson(fetch=False)
    # do something
    bytes = await x.fetch()
    with open('test.png', 'wb') as f:
        f.write(bytes)

if __name__ == "__main__":
    asyncio.run(main())fetch returnsbytesso there is no need to directly access.byteswhen manually fetching (fetch also updates the instance attribute on first invocation)
Package: tpdp
The Pipeline Design Patterntpdpit is the Pipeline Design Pattern realization in Python.QuickstartInstall with pippipinstalltpdpand creating your first pipelinefromtpdpimportPipeline,State,StepclassSimpleState(State):pipeline_name:strstep_1_count:int=0step_2_count:int=0init_state=SimpleState(pipeline_name="simple_pipeline")pipeline=Pipeline(name="simple_pipeline")classStep1(Step):defrun(self,state:SimpleState,**kwargs)->SimpleState:state.step_1_count+=1self.logger.info("step_1_count increased by 1")returnstateclassStep2(Step):defrun(self,state:SimpleState,**kwargs)->SimpleState:state.step_2_count+=1self.logger.info("step_2_count increased by 1")returnstatestep_1=Step1(step_name="step_1")step_2=Step2(step_name="step_2")pipeline.registry_step(step_1)pipeline.registry_step(step_2)pipeline.registry_step(step_1)pipeline.registry_step(step_2)pipeline.registry_step(step_1)pipeline.registry_step(step_2)pipeline.registry_step(step_1)result=pipeline.run(init_state=init_state)final_state=pipeline.get_state()print(f"final_state.step_1_count ={final_state.step_1_count}")print(f"final_state.step_2_count ={final_state.step_2_count}")You will see the following logs[...:INFO]Pipeline:Stepregistered:step_name="step_1"[...:INFO]Pipeline:Stepregistered:step_name="step_2"[...:INFO]Pipeline:Stepregistered:step_name="step_1"[...:INFO]Pipeline:Stepregistered:step_name="step_2"[...:INFO]Pipeline:Stepregistered:step_name="step_1"[...:INFO]Pipeline:Stepregistered:step_name="step_2"[...:INFO]Pipeline:Stepregistered:step_name="step_1"[...:INFO]Pipeline:Pipelinestart:pipeline_name="simple_pipeline",start_at="..."[...:INFO]Pipeline:Stepstart:step_name="step_1"[...:INFO]Step1:step_1_countincreasedby1[...:INFO]Pipeline:Stepfinish:step_name="step_1",step_duration="0.000024"[...:INFO]Pipeline:Stepstart:step_name="step_2"[...:INFO]Step2:step_2_countincreasedby1[...:INFO]Pipeline:Stepfinish:step_name="step_2",step_duration="0.000020"[...:INFO]Pipeline:Stepstart:step_name="step_1"[...:INFO]Step1:step_1_countincreasedby1[...:INFO]Pipeline:Stepfinish:step_name="step_1",step_duration="0.000016"[...:INFO]Pipeline:Stepstart:step_name="step_2"[...:INFO]Step2:step_2_countincreasedby1[...:INFO]Pipeline:Stepfinish:step_name="step_2",step_duration="0.000016"[...:INFO]Pipeline:Stepstart:step_name="step_1"[...:INFO]Step1:step_1_countincreasedby1[...:INFO]Pipeline:Stepfinish:step_name="step_1",step_duration="0.000016"[...:INFO]Pipeline:Stepstart:step_name="step_2"[...:INFO]Step2:step_2_countincreasedby1[...:INFO]Pipeline:Stepfinish:step_name="step_2",step_duration="0.000016"[...:INFO]Pipeline:Stepstart:step_name="step_1"[...:INFO]Step1:step_1_countincreasedby1[...:INFO]Pipeline:Stepfinish:step_name="step_1",step_duration="0.000023"[...:INFO]Pipeline:Pipelinefinish:pipeline_name="simple_pipeline",finish_at="...",duration="0.0005033016204833984"final_state.step_1_count=4final_state.step_2_count=3
Package: tpd-pete
TPD PeteTPD Pete is an AWS Deployment tool for AWS CloudformationConfigureTo setup pete use:pete configureto setup the default profile and region for AWSUsageTo use pete for a project, first set it up using:pete init.
This will generate the nessacary files for pete to function.Then simply use:pete deployto let deploy to your deployment AWS profile.
If you want to deploy to your production environment use:pete deploy --productionIf you have multiple collaborators on a project, and you dont want to share the same development environment.
Then you could also usepete init --localto setup some development override for you locally.
These will be used instead of the project development environment setup, if this has been setup.So if you dont have local overrides, it uses the project config.
If you dont have a project config, it uses the global config which is specific to you.
You can save which account, region or bucket to use for a project in the project config.
This will be saved in the.petefolder in you project folder.
You should add this file to your VCS (like Git or SVN).
But not thelocalfile inside that folder, which hold the local overrides.CIFor CI usage.First set the PETE_CI variable to 1Fill the following variables with the global configuration valuesKeyDescriptionPETE_DEV_PROFILEAWS profile for DevelopmentPETE_PROD_PROFILEAWS profile for ProductionPETE_DEV_BUCKETS3 upload bucket for Development codePETE_PROD_BUCKETS3 upload bucket for Production codePETE_DEV_REGIONRegion to deploy to for DevelopmentPETE_PROD_REGIONRegion to deploy to for ProductionYou can also use the environment keys for AWS access key to override any profile settings.
For more information see:Boto docsKeyDescriptionAWS_ACCESS_KEY_IDAccesskey for AWS CliAWS_SECRET_ACCESS_KEYSecretkey for AWS Cli
Package: tpds-application
# Trust Platform Design Suite - Application[TOC]This application brings various pieces of the Trust Platform Design flow to a single GUI application. This package contains the WebView based GUI. This GUI will serve as a one stop solution for anything Trust Platform related.The Trust Platform for CryptoAuthentication™ is a combination of multiple elements to simplify the addition of security to any embedded design.Microchip Weblink - [Trust Platform](https://www.microchip.com/design-centers/security-ics/trust-platform)After successful installation of the package start menu (windows only) entry for the same will be created. The application can be launched directly from the start menu. The application can also be started through python installation in conda environment. From Anaconda command prompt you can start the application through the following command.## Release Notes### 2.2.0Conversion to modular system### 2.1.1License Agreement window for MCHP packagesOther minor bug fixes and updates### 2.1.0Updates/fixes for Linux supportOther minor bug fixes and updates### 2.0.3MAC OSX Update bug fix### 2.0.2MAC OSX/Windows path updatesUpdate to network check functionProvosioning XML site code updatesUpdates to Webserver to support user messageboxOther minor bug fixes and updates### 2.0.1Updates added to suport OSX### 2.0.0Initial public release of Trust Platform Design Suite V2Integrated Notebooks, HTMLs (WebView) into one GUIInteractive Usecase Notebooks with options to run from transaction diagramAdded update functionality. Now the application can self-updateAbility to generate Secure Exchange packets within the toolMany other improvements from legacy version
Package: tpds-certificate-tools
TPDS Certificate Tools PackageTPDS Certificate Tools contains certificate support and certificate handling scriptsInstructions to generate the Signer certificates from CSRsThis package contains the required scripts and files to perform sign operation of the CSRs provided by Microchip.Installing this package and it's included scriptspython -m pip install tpds-certificate-toolsExtract the CSRs zip file provided by Microchip Provisioning Services. Use this path as --in-pathCreate a folder to store the generated signer certificates. Use this path as --out-pathProvide the signer CA key to sign the CSRs as --cakey.Use the signer.crt available in this package as --cacert.Following is the example command for referencepython sign_csr.py --in-path test_csrs --out-path test_csrs_out --cakey signer_ca.key --cacert signer.crtThis should generate signers signed by signer_ca in --out-path folder. Zip this folder and share to Microchip Provisioning Services along with Provisioning package generated on TPDS Configurator.
Package: tpds-helper
## Package
TPDS Helper has all the required modules for Trust Platform Design Suite Core package## Release Notes### 2.2.1Minor updates to conda dependencies### 2.2.0Convert to use tpds namespacing so packages can locate modules without path manipulation### 2.0.5Updated check for Azure IoT Hub nameOther minor updates### 2.0.4Bug fix for cert validity and signer ID### 2.0.3Updates/fixes for Linux supportOther minor bug fixes and updates### 2.0.2Fixed TrustCustom configuration write errorCanvas/UseCaseDiagram updates and bug fixesOther minor updates and bug fixes### 2.0.1Updates added to suport OSX### 2.0.0Initial version of TPDS-Helper packageSupporting package for TPDS Application and CoreContains various scripts to handle certificates, encryptions and deviceEncryption Utilities for Secure Exchange ProcessUsecase transaction diagrams and User input building blocksMany other improvements from legacy version
Package: tpds-schema
This repo contains the package generation for the secure exchange process
schemasTo generate the models from the schemas:` ./scripts/generate_model.sh <model_package_name> <path_to_xsd> `For example to generate tpds.models.ecc204_1_0 model one would run (from the repo base)` ./scripts/generate_model.sh ecc204_1_0 tpds/schema/data/cryptoauth/ECC204_TA010_Config_1.0.xsd `
Package: tpe-prio
tpe_prioUse like a regularconcurrent.futures.ThreadPoolExecutorexcept there is now abump(fut)method.  During execution, the deque gets rotated and put back, so
it is possible that workers will pick up a non-optimal next choice for a small
window of time.Licensetpe_prio is copyrightTim Hatch, and licensed under
the MIT license.  I am providing code in this repository to you under an open
source license.  This is my personal repository; the license you receive to
my code is from me and not from my employer. See theLICENSEfile for details.
Package: tpfd
TPFDis an easy way to parse strings and execute functions depending on their contents.Inspired byFlaskand usingParseunder the hood, this allows you to decorate functions with grammar rules and if a pattern that matches one of your grammar rules is found, the function will be run with a set of keyword arguments you’ve specified passed to it!  Great for parsing logs and executing macros on what it finds!ExamplesAniamls.txtTurtlesarecoolSlothsarecoolMosquitosaredumb>>>p=tpfd.Parser()>>>@p.on_parse('{Animal}are cool')defmain(animal):print('I like{0}.'.format(animal))>>>p.parse_file('animals.txt')'I like turtles.''I like sloths.'>>>p.parse(['Turtles are cool','Sloths are cool','Mosquitos are dumb'])'I like turtles.''I like sloths.'>>>p.parse('Sloths are cool')'I like sloths.'>>>p.parse('Mosquitos are dumb')None>>>@p.on_find('>{}<')deffind_example(words):print(words)>>>p.find('<p>the <b>bold</b> text</p>')'the bold text'To Install$ pip install tpfdNotesAny format spec supported by parse is supported by this library since it’s all parse under the hood.
Example:{[fieldname]:[formatspec]}Current FeaturesSupport for parsing text filesSupport for accepting generators that output text or intsSupport for parsing unicode stringsSupports parsing strings, ints and interator/generator’s automagically with newparsemethod.TODOExpose custom types functionality thatParsealready offers
Package: tpfi
tpfitpfiis an easy-to-use visualization tool for astronomers to identify and analyze
stars in the Kepler, K2, and TESS missions. The main focus of this project is on
two functions:plot_identificationandplot_season. These functions create
plots to help visualize target stars and their surrounding environments.Plot identification charts for Kepler, K2 and TESS.Theplot_identificationfunction creates identification charts, which are useful
for determining if a target is contaminated by nearby stars. In each chart, the
right panel overlays the Gaia DR3 catalog onto the TESS Target Pixel Files (TPF)
with the target marked by a cross symbol. The circle size represents the relative
brightness of the stars according to Gaia G magnitude. The left panel displays the
same sky coverage but taken from theDSS2 Red survey.This function is revised based ontpfplotter.Plot season charts for Kepler targets.The Kepler Space Telescope was designed to observe a specific field of stars
continuously, but it also needed to ensure its solar panels faced the Sun to power
its operations. As Kepler orbited the Sun, it performed a 90-degree roll every three
months (or every quarter) to keep its solar panels sunward. After four of these
quarterly rolls, amounting to a full year and a complete 360-degree rotation, Kepler
would return to its original orientation. Consequently, every set of quarters
separated by four (e.g., Q1, Q5, Q9) would find Kepler with the same pointing towards
its target field, as the telescope effectively revisited its initial orientation after
its annual orbit.Theplot_seasonfunction creates a plot of the TPF for each season of the Kepler
mission for a given target star. Since the aperture mask may change even in the same
season, the function only plots the aperture mask for the first quarter of each
season. This function is only applicable for Kepler targets.Season 1: Q1, Q5, Q9, Q13, Q17Season 2: Q2, Q6, Q10, Q14Season 3: Q3, Q7, Q11, Q15Season 4: Q4, Q8, Q12, Q16InstallationYou can install this package usingpip:pipinstalltpfiTo upgrade to the latest version, run:pipinstall-UtpfiHow to useSee theexample notebookfor more details.How to citeIf you use this package in your research, please add the following sentence to the footnote
or acknowledgement section of your paper:This work has made use of \texttt{tpfi} (publicly available at \url{https://github.com/keyuxing/tpfi}).and cite our paper:Xing et al., 2023,arXiv linkContributingIf you would like to contribute to this project, feel free to submit a pull request
or open an issue on GitHub. Any suggestion, improvement, or bug report is welcomed.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.
Package: tpfunc
ThingsPro Edge Function SDKThingsPro Edge Function SDK provides several APIs to interact with ThingsPro Edge features.Tag (v1)PubSubDirect AccessHttp Server (v1)GetPostPutDeleteBesides, SDK is tested with Python3.9, theoretically compatible with all other modules which you can refer toPython3.9 official website. Python3.6 is no longer in the support list.Release Note2023-12-21 V1.2.6Changes:chore: upgrade to python3.92023-05-03 V1.2.5Bug Fix:fix: http function missing essential module folder2023-04-26 V1.2.4Features:feat: support unsubscribe all2021-07-26 V1.2.3Bug Fix:fix: can't receive messages after tag_v1 subscribe callback exception2021-07-23 V1.2.2Bug Fix:fix: tag_v1 subscribe init always run into exception
Package: tpg-256a-pressure-monitor
READMETPG - 256A Pressure MonitorThetpg-256a-pressure-monitoris a readout and logging software for the Pfeiffer TPG-256A Pressure Controller. The
package includes a device driver which manages the connection and communication through RS-232 serial port. The
application is run as a command-lineDependenciesThe packagetpg-256a-pressure-monitorhas the following pre-requisites:Python 3.6andpip 10.0are the minimum required versions to build and installtpg-256a-pressure-monitorand its dependencies. It is
recommended to install and runtpg-256a-pressure-monitor(and any other package, for that matter) under avirtual environment.libpq, a C library that implements connections to the PostgreSQL
backend server. It is used by the packagelab-utilsto
connect to the PostgreSQL backend, manage database structure and save new data entries.Getting StartedTODO: pip package available nowUsageTo use a thetpg-256a-pressure-monitorpackage, TODOAuthorsCarlos Vigo-Initial work-GitLabContributingPlease read ourcontributing policyfor details on our code of
conduct, and the process for submitting pull requests to us.VersioningWe useGitfor versioning. For the versions available, see thetags on this repository.LicenseThis project is licensed under theGNU GPLv3 LicenseBuilt WithPyCharm Community Edition- The IDE usedSphinx- DocumentationAcknowledgmentsNobody so far