Saravanan666/pypi-org huggingface dataset:
Package: lifehacks.colour
lifehacks.colourStructure📦 lifehacks.colour
├── Colour
├── hsla
├── rgba
│
└── 📦 palette
    ├── Apple
    └── MarianaInstallationpipinstalllifehacks.colourUsageColourabstract classhslargbaMarianapaletteColourabstract classAbstract base class, not instantiable.
Can be used in type hinting forhslaandrgbainstancesdefprint_hex(colour:Colour)->None:print(colour.to_hex())print_hex(rgba(15,15,15))#0f0f0fprint_hex(hsla(0,0,6))#0f0f0fhslaoptionalh: hue[0, 359]optionals: saturation[0, 100]or[0.0, 1.0]optionall: lightness[0, 100]or[0.0, 1.0]optionala: alpha (opacity)[0, 100]or[0.0, 1.0]rgbaoptionalr: red[0, 255]optionalg: green[0, 255]optionalb: blue[0, 255]optionala: alpha[0, 100]or[0.0, 1.0]MarianapaletteRemember to import fromlifehacks.colour.palette.
This palette contains the colours from Mariana theme in Sublime Text.fromlifhacks.colour.paletteimportMarianaforname,colourinMariana:content=content.replace(name,colour.to_hex())ContributorsSimon-mightbesimonyou?
Package: lifehacks.metaclasses
lifehacks.metaclassesStructure📦 lifehacks.metaclasses
├── meta
├── enum
└── EnumExceptionInstallationpipinstalllifehacks.metaclassesUsagemetametaclassenummetaclassEnumExceptionmetametaclassThere are a few ways to make anmetaclass.fromlifehacks.metaclassesimportmetaclassmyenum0(metaclass=meta):...@meta# preferred methodclassmyenum1:...@meta()# do not use this methodclassmyenum2:...enummetaclassSame withmetametaclass from above,
there are a few ways to make anenumclass.fromlifehacks.metaclassesimportenum# with typingclassMyPalette0(metaclass=enum[Colour]):...@enum# preferred methodclassMyPalette1:...@enum[Colour]# syntax only allowed python>=3.9classMyPalette2:...@enum()# do not use this methodclassMyPalette3:...usage example:fromlifehacks.metaclassesimportenum@enumclassBasePalette:BLACK=...WHITE=...# extending base palette enumclassSubPalette(BasePalette):RED=...GREEN=...# can be used in type hintingdefprint_colours(palette:enum)->None:forname,valueinpalette:print(name,value)print_colours(BasePalette)# BLACK, WHITEprint_colours(SubPalette)# BLACK, WHITE, RED, GREENprint(BasePalette.BLACKinSubPalette)# Trueenumclasses are not instantiable, more on thatbelow.EnumExceptionenumclasses are not instantiable.
If you try to, you get anEnumException@enumclassPalette:...p=Palette()# illegal, raises EnumExceptionContributorsSimon-mightbesimonyou?
Package: life-in-tkk
Life In Tkk简介用于厦门大学嘉庚学院TKK的综合信息查询的第三方Python3库。如何使用!!注意: 还需安装firefox,geckodriver,tesseract!!1. 直接使用将项目中的life_in_tkk放入所调用的xx.py的同级目录。# 需要importfromlife_in_tkkimportTkk_htmlfromlife_in_tkkimportTkk_schedule# ....importlife_in_tkk2. 基于pip安装使用使用pip3进行下载，之后具体使用方式与直接使用相同。pip3 install life_in_tkk相关依赖版本为开发时使用的版本，未对其他版本进行测试其他应该也没什么问题Python3所需的依赖Python3所需的依赖包，详情可见依赖目录。其余依赖firefox83.0geckodriver0.27.0tesseract4.1.1GNU/LinuxUbuntu/Mint:sudoapt-getinstallfirefoxfirefox-geckodriversudoapt-getinstalltesseracttesseract-ocr-engArch Linux/Marjorn:sudopacman-Stesseracttesseract-data-eng
sudopacman-SfirefoxgeckodriverWindows 10可以在Github仓库的UB-Mannheim/tesseract和mozilla/geckodriver中找到对应的 window32/64 安装包，安装即可。!!注意: 十分重要!!安装完毕后, 需要将软件的安装目录添加到windows 10系统的环境变量（此电脑|属性|高级系统设置|环境变量|Path）中。依赖目录均为开发时所用的版本，仅提供参考。库名版本Pillow8.0.1selenium3.141.0requests2.22.0beautifulsoup44.8.2pytesseract0.3.6tesseract0.1.3numpy1.17.4Plan课表库自动识别验证码调课补课电费查询库LICENSEMIT © Mirasire
Package: lifelib
lifelibis a collection of open-source life actuarial models written in Python.
lifelib includes a variety of models, with sample scripts
and Jupyter notebooks that demonstrate how to use the models.Visithttps://lifelib.iofor more information!What for?lifelib models are highly versatile and transparent.
You can customize lifelib models and utilize them
in various practical areas, such as:Model validation / testingPricing / profit testingResearch / educational projectsValuation / cashflow projectionsAsset-liability modelingRisk and capital modelingActuarial modernization to replace spreadsheet modelsWhy lifelib?By effectively utilizing the models in lifelib,
you can expect the following benefits from both model development and governance perspectives:A more efficient, transparent, and faster model development experienceModel integration with the Python ecosystem (Pandas, Numpy, SciPy, etc.)Elimination of spreadsheet errorsImproved version control and model governanceAutomated model testingSome of the models in lifelib are built usingmodelx, an open-source
Python package for building object-oriented models in Python.
By using lifelib, you can enjoy the following advantages:Models run fast!Formulas are easy to readEasy to trace formula dependency and errorsFormulas are instantly evaluatedPandas and Numpy can be utilizedObject-orientedInput from Excel and CSV filesDocuments can be integratedFormulas are saved in text files
Package: life-line-chart
life_line_chartGenerate ancestor and descendants (genealogy) chart. SVG export is supported.Getting startedInstall the module and the requiredments. Open a gedcom file and generate a ancestor life line chart.PrerequisitesYou will need a gedcom file. You can use the automatically generated one from the tests directory in this repository ([tests/autogenerated.ged]).fromlife_line_chartimportDescendantChart,AncestorChartfromlife_line_chart.GedcomInstanceContainerimportget_gedcom_instance_containerindividual_id='@I249@'chart=AncestorChart(instance_container=get_gedcom_instance_container('tests/autogenerated.ged'),formatting={'total_height':800,'horizontal_step_size':20})chart.set_chart_configuration({'root_individuals':[{'individual_id':individual_id,'generations':8}]})chart.update_chart()chart.paint_and_save('example_1.svg')individual_id='@I2@'chart=DescendantChart(instance_container=get_gedcom_instance_container('tests/autogenerated.ged'),formatting={'total_height':400,'horizontal_step_size':70,'relative_line_thickness':0.2})chart.set_chart_configuration({'root_individuals':[{'individual_id':individual_id,'generations':2}]})chart.update_chart()chart.paint_and_save('example_2.svg')individual_id='@I2@'chart=DescendantChart(instance_container=get_gedcom_instance_container('tests/autogenerated.ged'),positioning={'chart_layout':'cactus'},formatting={'total_height':400,'birth_label_active':False,'death_label_letter_y_offset':-3,'line_weighting':'number_of_descendants','horizontal_step_size':70,'relative_line_thickness':0.2})chart.set_chart_configuration({'root_individuals':[{'individual_id':individual_id,'generations':3}]})chart.update_chart()chart.paint_and_save('example_3.svg')Installingrequirements.txtThen you will need the following modules:svgwrite (i.e. pyparsing)pillow (for tests with photos)pip install -r requirements.txtBuildingpython setup.py bdist_wheelAutomatically generating example gedcom files requires the modulenamesBuilding a wheel requires with setup.py requires:shutilglobsetuptoolsdistutilswheelLicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: lifelines
What is survival analysis and why should I learn it?Survival analysis was originally developed and applied heavily by the actuarial and medical community. Its purpose was to answerwhy do events occur now versus laterunder uncertainty (whereeventsmight refer to deaths, disease remission, etc.). This is great for researchers who are interested in measuring lifetimes: they can answer questions likewhat factors might influence deaths?But outside of medicine and actuarial science, there are many other interesting and exciting applications of survival analysis. For example:SaaS providers are interested in measuring subscriber lifetimes, or time to some first actioninventory stock out is a censoring event for true "demand" of a good.sociologists are interested in measuring political parties' lifetimes, or relationships, or marriagesA/B tests to determine how long it takes different groups to perform an action.lifelinesis a pure Python implementation of the best parts of survival analysis.Documentation and intro to survival analysisIf you are new to survival analysis, wondering why it is useful, or are interested inlifelinesexamples, API, and syntax, please read theDocumentation and Tutorials pageContactStart a conversation in ourDiscussions room.Some users have posted common questions atstats.stackexchange.comcreating an issue in theGithub repository.DevelopmentSee ourContributingguidelines.
Package: lifeomic-chatbot-tools
lifeomic-chatbot-toolsPython utilities for machine learning, web services, and cloud infrastructure.
Includes classes and methods for:ML model serialization/deserializationML model evaluation utilitiesData structures/models related to chatbotsML model artifact persistence and version managementAnd moreThe data structures in this package can all be found in thelifeomic_chatbot_tools.typessub-package, and are allPydanticdata models. For example thelifeomic_chatbot_tools.types.agent.AgentConfigclass represents a chatbot's
configuration and training data.Getting StartedTo begin using the package, use your favorite package manager to install it from PyPi.
For example, using pip:pip install lifeomic-chatbot-toolsSome of the features in this repo require more heavy weight dependencies, like AWS
related utilities, or utilities specific to machine learning. If you try to import
those features, they will tell you if you do not have the correct package extra
installed. For example, many of the features in thelifeomic_chatbot_tools.mlsub-package require themlextra. To installlifeomic-chatbot-toolswith that
extra:pip install lifeomic-chatbot-tools[ml]You can then begin using any package features that require ML dependencies.Developing LocallyBefore making any new commits or pull requests, please complete these steps.Install the Poetry package manager for Python if you do not already have it.
Installation instructions can be foundhere.Clone the project.From the root directory of the repo, install the dependencies, including all dev
dependencies and extras:poetry install --all-extrasTesting LocallyWith Yarn, Docker, and docker-compose installed, run this command from the project
root:poetry run poe ciThis will build the project, lint it, and run the unit tests and integration tests.
All those steps can be run individually as well. See the scripts in thepyproject.tomlfile for the command names.MacOS UsersWhen developing using MacOS, it is recommended to use a dev container. This project supportsVS Code dev containersout of
the box.Releasing The PackageReleasing the package is automatically handled by CI, but three steps must be taken
to trigger a successful release:Use Poetry'sversioncommandto
bump the package's version.Update theCHANGELOGfile with the latest changes added under the new version.Open a PR. When it's merged tomaster, the release will happen automatically.CI will then build and release the package to pypi with that version once the PR is
merged tomaster.
Package: lifeomic-logging
LifeOmic Python LoggingProject StatusGetting StartedDependenciesPython 3version >= 3.6Getting the SourceThis project ishosted on GitHub. You can clone this project directly using this command:gitclonegit@github.com:lifeomic/logging-py.gitDevelopmentPython environments are managed usingvirtualenv.  Be sure to have this installed firstpip install virtualenv.  The makefile will setup the environment for the targets listed below.Running testsmaketestLintingmakelintInstallationpip3installlifeomic_loggingUsagefromlifeomic_loggingimportscoped_loggerwithscoped_logger(__name__,{"bar":"foo"})aslog:log.info("message")Release ProcessReleasesare generally created with each merged PR. Packages for each release are published toPyPi. SeeCHANGELOG.mdfor release notes.VersioningThis project usesSemantic Versioning.ContributingWe encourage public contributions! Please reviewCONTRIBUTING.mdandCODE_OF_CONDUCT.mdfor details on our code of conduct and development process.LicenseThis project is licensed under the MIT License - seeLICENSEfile for details.AuthorsSee the list ofcontributorswho participate in this project.
Package: lifepo4weredPyController
Our intention is to design an oriented object access to the
lifepo4wered-pi3 data module during runtime application.reference:http://lifepo4wered.com/lifepo4wered-pi3.htmlUsing the Raspbery Pi zero in many projects, I found this product
very usefull. So to help my children and python colleagues, we design this.You can find here the documentation of the lifepo4wered product:http://lifepo4wered.com/files/LiFePO4wered-Pi3-Product-Brief.pdf.
Package: lifeproof
lifeproofCreate proofs of life to detect when a program fails.Create a file proof of lifeTo create a file proof of life is very simple. You only need to execute:fromlifeproofimportFileProofOfLifewithFileProofOfLife('file_path'):something_to_do()Where 'file_path' is the file path to the proof of life to check. If this file is removed, then the program has died for
any cause. The something_to_do() represent the commands to check if they are still alive. If something_to_do() breaks
down for some reason, the file automatically will be removed.For example:fromlifeproofimportFileProofOfLifefromtimeimportsleepwithFileProofOfLife('health.txt'):sleep(60)This script will create the file 'health.txt' during 60 seconds. At the end of sleep(60) the 'health.txt' file will be
removed.
Package: lifescale-utils
lifescale_utilsData analysis utilities for lifescale.Programs:lsguilsguistarts the graphical user interface (gui) of lifescale-utils. It provides toe following main features:Read lifescale xlsm filesVisualize the data from the xlsm file and calculate various statisticsAssess the mass distribution of samples by histograms and flag invalid dataWrite the cleand data to csv files (seels2csv)Usage:usage: lsgui [-h]

Starts lifescale utils gui.

optional arguments:
  -h, --help  show this help message and exitls2csvls2csvis a command line program that converts xlsm files written by lifescale units to csv files. The following filesare created:Masses_<run-name>_<guid>.csv: Data series from the sheet AcquisitionIntervals.Metadata_<run-name>_<guid>.csv: Data from the sheet PanelData.SampleSummary_<run-name>_<guid>.csv: Data from the sheet IntervalAnalysis plus sample related data from AcquisitionIntervals.<run-name>and<guid>are the taken from the fieldsNameandGuid(if available) from the settings sheet of the xml file.Usage:usage: ls2csv [-h] -i INPUT_XLSM -o OUT_DIR [-nv] [-s] [-t]

Conversion from lifescale xlsm output to csv files

options:
  -h, --help            show this help message and exit
  -i INPUT_XLSM, --input-xlsm INPUT_XLSM
                        Path and name of the input xlsm file created by
                        lifescale. (default: None)
  -o OUT_DIR, --out-dir OUT_DIR
                        Output directory for the CSV files. (default: None)
  -nv, --not-verbose    Disable command line status messages. (default: False)
  -s, --sample-stats    Calculate sample statistics of masses (median, std.
                        deviation, quartiles, interquartile range) and add
                        them to the SampleSummary output CSV file (columns:
                        Mass_median, Mass_std, Mass_q25, Mass_q75,Mass_iqr).
                        (default: False)
  -t, --sort-masses-by-time
                        Sort data in the Masses CSV file by acquisition time.
                        (default: False)Python package and installationLifescale_utils is available athttps://pypi.org/project/lifescale-utils/Installation:pip install lifescale_utilsLicense and copyrightCopyright (C) 2023  Andreas Hellerschmied (heller182@gmx.at)This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.You should have received a copy of the GNU General Public License
along with this program.  If not, seehttps://www.gnu.org/licenses/.Fundinglifescale_utils was funded by the Centre for Microbiology and Environmental Systems Science (CMES) of the University of
Vienna (https://cmess.univie.ac.at/).
Package: lifesci
Python 3 Life Sciences utilities (pylifesci)This repo contains python3 bioinformatics utilities.InstallationThis package is available on PyPI.pip3 install lifesciAlternatively, the package can be installed from source.git clone https://github.com/bmmalone/pylifesci
cd pylifesci
pip3 install .(The "period" at the end is required.)UsagePlease seethe documentationfor usage details.UninstallationThelifescipackage can be removed with pip.pip3 uninstall lifesci
Package: lifesimpack-AviationSFO
lifesimpackDescriptionLife 'simulation' package for python created as a joke.How to useimport:importlifesimcreate person:person_name=lifesim.Person("First Last",height,weight,age(0isdefault),status(ignorable))InstallationRecomendedCopy and paste the following code into terminal to install via pip. (Recomended method)pipinstalllifesimpack-AviationSFOSource CodeIf you wish to do it the hard way, copy and paste the following code into terminal to install via source code.curlhttps://raw.githubusercontent.com/AviationSFO/lifesimpack/master/install.sh|bash
Package: lifesospy
A Python library to communicate withLifeSOSalarm systems. In some
markets, they may also be labelled under the name of the distributor;
eg. SecurePro in Australia, WeBeHome in northern Europe.It was written for & tested with the LS-30 model, though it should also
work on the LS-10/LS-20 models.The base unit must be connected to your network in order for this
library to communicate with it; serial connections are not currently
supported.Note: This library is intended for developer use. If youâ€™re just looking
to access your LifeSOS alarm system, devices and switches from other
applications, Iâ€™d suggest taking a look atLifeSOSpy_MQTTinstead. It
provides an MQTT Client implementation that easily integrates with
applications that support MQTT (eg. Home Assistant, OpenHAB).When using this library in your app there are three main classes to
choose from:BaseUnitProvides higher level access to the alarm system, managing the Client /
Server connection for you. It will automatically enumerate all attached
devices on connection, monitor the state of the base unit & devices with
notification when they change, and automatically attempt reconnection
(when running as client).This class was created to simplify integration into home automation
software.Client / ServerThese two classes allow you to directly issue commands to the alarm
system, and attach callbacks to handle any events if needed.Simple Client ExamplesDisplay the current modefromlifesospy.clientimportClientfromlifesospy.commandimportGetOpModeCommandclient=Client('192.168.1.100',1680)awaitclient.async_open()response=awaitclient.async_execute(GetOpModeCommand())print("Operation mode is{}".format(str(response.operation_mode)))client.close()Operation mode is DisarmArm the systemfromlifesospy.clientimportClientfromlifesospy.commandimportSetOpModeCommandfromlifesospy.enumsimportOperationModeclient=Client('192.168.1.100',1680)awaitclient.async_open()awaitclient.async_execute(SetOpModeCommand(OperationMode.Away))client.close()
Package: lifesospy-mqtt
This application provides an MQTT client that interfaces withLifeSOSalarm systems, sensors and switches.
It will publish the state of all devices to an MQTT broker, which can
then be consumed by any application that provides MQTT support, such as
Home Assistant or OpenHAB. It will also subscribe to topics on the
broker that allow the control of the alarm system (eg. arm, disarm) and
turn on/off any attached switches.It was written for & tested with the LS-30 model, though it should also
work on the LS-10/LS-20 models. Note that in some markets, they may also
be labelled under the name of the distributor; eg. SecurePro in
Australia, WeBeHome in northern Europe.For a quickstart and configuration help, please refer to theReadTheDocssite.
Package: lifester
lifesterEvery minute of your life. On the command line.lifester is a command line tool to track every miute of your life. Enter your schedule for the day and then analyze how much time you spent on things.Installation|Setup|Usage|Troubleshooting|CreditsInstallationlifester is available onPyPI. This is the easiest way to install it. All dependencies will be installed automatically.pip3installlifesterIf you want to install lifester from source, have a lookhere.SetupNo further setting up needed. The first time you run lifester, it will create a.lifesterdirectory in your home folder (if it does not already exist) and create acategories.txtfile which saves all the categories your time blocks can have.UsageUsage:
    lifester enter
    lifester analyze all
    lifester analyze (year | month | week) <timeframe>
    lifester categories (add)
    lifester help
    lifester version

Timeframe:
    ... start end [year]
    ... single [year]Lifester creates a.lifesterfolder in your home directory (~/) where it saves all entered day data as well as a categories file. If you want to specify a different folder for these files, you need to set theLIFESTERPATHin your.bashrclike so:export LIFESTERPATH=/path/that/you/wantEntering the Data For a DayAnalyzing Previously Entered DataOf course, subsitutingyearwithmonthandweekworks too.Showing / Adding CategoriesTroubleshootingBug Reports and Feature RequestsBug reports and feature requests are very much appreciated. Please contact me on Twitter (@SolviAu) or open an issuehere.CreditsThis project was inspired by Cal Newport and how he organizes and plans his days. This is probably the most crucial blog posts of his:Deep Habits: The Importance of Planning Every Minute of Your Work Daysophieau.github.io– Twitter@SolviAu– © 2018,MIT Licence
Package: life-stream-cli
life-stream-cliOverviewLife is a stream of events, thought noise and ideas are coming every day. The Life Stream service is intended to organize
small notes. Simply save them under the one or more tags. You can find them later easily.
If you want to forget something, simply put it down.How to distributepython -m pep517.build .twine upload dist/*pip install life-stream-cliUseful tips(Development) Switching between profileslst config --set active-profile=default
Package: lifetimefitting
LifetimeFittingToolThis is a quick tool I wrote to take some of my TCSPC fluorescence lifetime fitting tools fromspectraImport.ipynband make them usable for other people. It can read PicoHarp .phd files thanks toadreasnow/picoharp-phdand also reads the plain.txtoutput it can save.The app itself is a basic least squares regression tool but allows you to fit in linear or logarithmic space, supports up to 4 decays, and can export images as well as .csv files of the fitted histogramsInstallingPyPiThe easiest way to get it is to install it directly from pypy, so as too pull all the dependencies:pipinstalllifetimefittingManuallyPython (I'm not sure how old you could go, but I know it runs on >3.9)MatplotlibNumpyPyQt6ScipyThese can be installed pretty easily via pippipinstallmatplotlibnumpyscipypyqt6or condacondainstallmatplotlibnumpyscipypyqt6Then you can clone the module down and install it manuallygitclonehttps://github.com/adreasnow/LifetimeFittingTool.gitcdLifetimeFittingTool
pythonsetup.pyinstallUsageTo run the app, all you need to do is execute the module in python and a QT window should appear :)python-mlifetimefittingThe MathsUses the form of the function:$$
fl(t)=I_0 exp\bigg(-\frac{t}{\tau}\bigg)
$$Where:$t =$ Time$\tau =$ Fluorescence lifetime$I_0 =$ Initial photon concentrationFor the corrected fitting procedure, the convolved function is calculated as:$$
fl=fl(t)_{IRF}\otimes fl(t)
$$$$
fl_{fitted}=\sum_{i=1}^{\text{exponents}} C_i\cdot fl(t)_i
$$Where:$fl(t)_{IRF} =$ Fitted instrument response function$fl(t)_i =$ Fitted function for each decay$C_i =$ Linear coefficient for each decay$\chi^2$ is calculated as perfluortools$$
\chi^2 = \sum_{j=1}^{n} (c_j-\hat{c_j})^2/\hat{c_j}\
\chi^2_{red}=\frac{\chi^2}{n}
$$