Saravanan666/pypi-org huggingface dataset:
Package: tipping
Tipping - Token Interdependency ParsingTipping is a high-performance and flexible log parsing library. It leverages the interdependencies between tokens to cluster them and computes their templates and parameter masks. It is built with speed and efficiency in mind, capable of utilizing all available processor cores to accelerate the parsing process. At its core, Tipping is written in Rust to ensure maximum performance and stability while offering Python bindings for ease of use and integration into Log Analysis research and projects.Features🚀High Performance: Optimized to be fast and memory efficient.🐍Python API: Easy to use, compatible with python 3.8 and newer.🔧Customizable: Many parameters to manipulate and optimize the process.🦀Rust-powered Core: Safe, concurrent, and stable.InstallationTipping could be installed from PyPI:pipinstalltippingUsageLoad your log messages into a list of strings (List[str]) and:importtipping# Example usagemessages=["message1","message2",...]clusters,masks,templates=tipping.parse(messages)print(result)DetailsTipping offers the following parameters to manipulate and optimize the process:tipping.parse(messages:List[str],threshold:float=0.5,special_whites:List[str]=None,special_blacks:List[str]=None,symbols:str="()[]{}=,*",keep_alphabetic:bool=True,keep_numeric:bool=False,keep_impure:bool=False,return_templates:bool=True,return_masks:bool=True,)Citewill be filled upon publication
Package: tippo
OverviewUse the latest type annotation features in older versions of Python.MotivationWhen working with Python development for VFX pipelines we are often stuck with older
Python versions for the runtime.Tippoaims to bridge that gap since it allows us to use features such as static type
checking (which could be performed by newer Python versions with support for MyPy during
the testing phase) even though the code might be designed to run in Python 2.7, for
example.InstallationTippois available throughpip:pip install tippoUsageInstead of importing fromtypingand/ortyping_extensions…>>>try:...fromtypingimportTypeAlias...exceptImportError:...fromtyping_extensionsimportTypeAlias...>>>try:...fromtypingimportfinal...exceptImportError:...fromtyping_extensionsimportfinal...…just import directly fromtippo:>>>fromtippoimportTypeAlias,finalGeneric FixesTippopatchesGenericMetato fix known bugs for the Python 2.7 version oftypingthat were not addressed since it’s not officially supported anymore.Generic class comparison:>>>fromtippoimportMapping>>>assertMapping[str,int]==Mapping[str,int]# passes>>>assertnot(Mapping[str,int]!=Mapping[str,int])# passesSubclassing a generic class with a__weakref__slot:>>>fromweakrefimportref>>>fromtippoimportGeneric,TypeVar>>>T=TypeVar("T")>>>classMyGeneric(Generic[T]):...__slots__=("__weakref__",)...>>>classSubClass(MyGeneric[T]):# does not error out...__slots__=()...>>>instance=SubClass()>>>instance_ref=ref(instance)In order to maintain the same interface,GenericMetapoints totypewhen imported
fromtippoin newer versions of Python.BackportsFeatures from the latest versions of Python, such asTypeAlias,ClassVar,NewType,get_origin, andget_args.>>>fromtippoimportMapping,get_args,get_name>>>mapping_type=Mapping[str,int]>>>[get_name(a)forainget_args(mapping_type)]['str','int']Commonly Used ProtocolsSuch as:tippo.SupportsGetItemtippo.SupportsGetSetItemtippo.SupportsGetSetDeleteItemtippo.SupportsKeysAndGetItem>>>fromtippoimportSupportsGetItem>>>classFoo(object):...def__getitem__(self,item):...# type: (str) -> int...return3...>>>defget_stuff(bar):...# type: (SupportsGetItem[str, int]) -> int...returnbar["stuff"]...>>>assertget_stuff(Foo())==3# passes static type checking>>>assertget_stuff({"stuff":3})==3# passes static type checking
Package: tipranks
TipRanksPython module to interact with TipRanks API.InstallationFrom PyPipip install tipranksFor developmentgit clone https://github.com/visuxls/tipranksFeaturesSupport for the majority of TipRanks API endpoints (create an issue if I missed any)Request based login, Chrome not requiredRequirementsUltimate or Premium account to have access to all methodsTo-DoLogin: Implement request based loginFiltered results: Implement filtered resultsHave a suggestion? Create an issue and I'll add it!UsageSupported Methods.top_analyst_stocks().top_smart_score_stocks().top_insider_stocks().stock_screener().top_online_growth_stocks().trending_stocks().top_experts(expert_type="analyst").anaylst_projection(ticker="TSLA").news_sentiment(ticker="TSLA")
Package: tips
tipsusage: tips [-h] {add,reduce,set,show,graph,stats} …A tips per day tracker and displayer for malnourished underpaid service industry workers.positional arguments:{add,reduce,set,show,graph,stats}add                 increase value under date by amount
reduce              decrease value under date by amount
set                 replace value under date with amount
show                show value(s) under date or range of dates
graph               graph of values in date range
stats               show assorted statsoptional arguments:-h,--helpshow this help message and exitexample usage:add 20                add 20 to today’s value
reduce 15             reduce today’s value by 15
add 12 1d             add 12 to yesterday’s value
set 30 1w             replace the value for the date of 1 week ago with 30
show 2015-12-1        show the value for said date
show 0d 30d           list all the records from the past 30 days
graph 30d 0d          print a graph of the past 30 days
Package: tipsa-api-python
This package create packages to send using TIPSA API.LicenseThe package is released under the New BSD license.Example of usefromtipsaimportapitipsa_api=api.TipsaAPI('agency_code','client_code','client_password')tipsa_api.login()# Web service loginresult=tipsa_api.create({'service_code':'service_code','destination_name':'destination_name','destination_address':'destination_address','destination_postal_code':'destination_postal_code','destination_city':'destination_city'})# Create a shippingprintresult['albaran']printresult['guid']printresult['url']# Url to check status
Package: tipsql
Type Safed SQL Query Builder for Python⚠️⚠️⚠️ This library is currently under consideration and is not ready for use in actual products. ⚠️⚠️⚠️Development NotesDDLThere are no plans for support.DDL is often used infrequently as its syntax varies from database to database.
It is recommended that it be managed by a separate migration tool.For Table RelationIf a PrimaryKey or a join key is included as a constraint, it can be expressed as a NewType
to match the condition.Examplesfromtextwrapimportdedentfromtipsql.core.query.builderimportQueryBuilderfromyour_project.database.publicimportUser,Addressbuilder=(query.chain().from_(lambdac:c(User).left_outer_join(Address,).on(lambdac:c(User.id==Address.user_id).and_(Address.city=="Tokyo"))).select(User.id,User.name,))assert(builder.build()==dedent("""SELECTusers.id,users.nameFROMusersLEFT OUTER JOINaddressesONusers.id = addresses.user_idAND addresses.city = 'Tokyo';""").strip())
Package: tipsy
tipsypython3.10 introduced user-defined TypeGuards. Finally giving users the ability to actually code type narrowing functions themselves and avoid shortfalls of mypy. However, for most builtin basic types automatic TypeGuards are still missing. Writing these TypeGuards yourself for each of your types from scratch can feel redundant and frustrating. tipsy generates these TypeGuards automatically for you based solely on the type annotations.Example 1: TypeGuardsHere's an example of how you can use tipsy to generate TypeGuards for a TypedDict. Let's suppose you have a TypedDict like this:classPerson(TypedDict):uid:intname:strYou might already have observed that you can not useisinstanceto check whether a variable is of that type.isinstance({"uid":5,"name":"jeeves"},Person)# TypeError: TypedDict does not support instance and class checksSo how can you do type narrowing in that case? Well, you need to write a TypeGuard yourself.defis_person(data:Any)->TypeGuard[Person]:return(isinstance(data,dict)andset(data.keys())=={"uid","name"}andisinstance(data["uid"],int)andisinstance(data["name"],str))is_person({"uid":5,"name":"jeeves"})# Trueis_person({"name":"jeeves"})# Falseis_person({"uid":5.0,"name":"jeeves"})# Falseis_person({"uid":5,"name":b"jeeves"})# FalseAs you can see this works perfectly, but these TypeGuards really feel like you are just duplicating the information that is already contained in the type, just to make mypy happy. Well, it's because it is actually duplicated. And even worse, for more complex nested types this gets out of hand quickly. tipsy'sis_typeuses just the information from the type to automatically generate such TypeGuards for you.is_type({"uid":5,"name":"jeeves"},Person)# Trueis_type({"name":"jeeves"},Person)# Falseis_type({"uid":5.0,"name":"jeeves"},Person)# Falseis_type({"uid":5,"name":b"jeeves"},Person)# FalseThat's it, it's literally the same function, but automatically generated for you by tipsy.Example 2: castingAnother use-case is casting, maybe you know that only one type is valid in a certain scenario. Let's say you again have the same TypedDict:classPerson(TypedDict):uid:intname:strwith tipsy, this is a breeze:jeeves=cast_to_type({"uid":5,"name":"jeeves"},Person)
Package: tiptapy
TiptapyLibrary that generates HTML output from JSON export of tiptap editorInstallpipinstalltiptapyTestpython-mpytestUsageimport tiptapy

s = """

{
  "type": "doc",
  "content": [
    {
      "type": "blockquote",
      "content": [
        {
          "type": "paragraph",
          "content": [
            {
              "type": "text",
              "text": "Readability counts."
            }
          ]
        },
        {
          "type": "paragraph",
          "content": [
            {
              "type": "text",
              "marks": [
                {
                  "type": "link",
                  "attrs": { "href": "https://en.wikipedia.org/wiki/Zen_of_Python" }
                }
              ],
              "text": "Zen of Python"
            },
            {
              "type": "text", "text": " By "
            },
            {
              "type": "text",
              "marks": [
                {
                  "type": "bold"
                }
              ],
              "text": "Tom Peters"
            }
          ]
        }
      ]
    }
  ]
}
"""

class config:
    """
    Config class to store constants used by the other nodes.
    """
    DOMAIN = "python.org"


renderer = tiptapy.BaseDoc(config)
out = renderer.render(s)
print(out)Output<blockquote>
  <p>Readability counts.</p>
  <p>
      <a href="https://en.wikipedia.org/wiki/Zen_of_Python">Zen of Python</a> By 
      <strong>Tom Peters</strong>
  </p>
</blockquote>
Package: tiptop
Command-line system monitoring.tiptop is a command-line system monitoring tool in the spirit oftop. It displays various
interesting system stats and graphs them. Works on all operating systems.Install and run withpipinstalltiptop
tiptopFor all options, seetiptop-husage: tiptop [-h] [--version] [--log LOG] [--net NET]

Command-line system monitor.

options:
  -h, --help         show this help message and exit
  --version, -v      display version information
  --log LOG, -l LOG  debug log file
  --net NET, -n NET  network interface to display (default: auto)tiptop usesTextualfor layouting andpsutilfor fetching system data.Other top alternatives in alphabetical order:bashtop,bpytop,btop(which inspired tiptop)bottomGlancesgtophtopSeeherefor a comparison by GitHub stars.
Package: tipy
REQUIREMENTStipy is written for Python 3.On debian: $ sudo apt-get install python3You will also need pip for python3.On debian: $ sudo apt-get install python3-pipIn order to install tipy using the setup.py you will need the setuptools module.On debian: $ sudo apt-get install python3-setuptoolsThe GUI require the Qt library with Python bindings.On debian: $ sudo apt-get install python3-pyqt5INSTALLATIONInstall with pip3:$ sudo pip3 install tipyInstall from sources:$ sudo python3 setup.py installAfter the installation you will need to change the owner of ~/.config/tipy.
The directory is created during the installation, which require root permissions
and therefore set every created file owner to root.
Typing the following should works:$ sudo chown <your_user_name> -R ~/.config/tipy/
Package: ti-python-module
TI-Python-ModuleTexas InstrumentsPython Debugging and Programming SupportInstallation:# Installation:pipinstallti-python-module# Update:pipinstallti-python-module--upgradeHow to install this feature / moduleHow to use these modules properly:Accessing the moduleInstall the package usingpip install ti-python-moduleImport the modules (examples:from ti_python_module.ti_hub import *orfrom ti_python_module import ti_rover as rv)Putting the program on the calculator / roverChange the import so you don't have theti_python_modulepartKnown Problems / IssuesThe modulecmathdon't exists. This is due to a module with the exact same name already exists build in to python. Since I am unable to change build-in classes, I can't add the proper functions. The same issue occurs fortime.The moduleti_imagedoes not exist. This is due to the methodnew_imagerequiring these parameters:width, height, (red, green, blue). Since Python 3.x sub-list arguments (the part in brackets) are not supported (invalid). Due to the majority of people working with Python 3.x, I have decidedNOTto implement the module, because if you can't create an image, you can't work with it later on.Recommended IDEsAs an IDE, I personally recommend you choosing between the following two IDEs depending on your use case.Microsoft Visual Studio CodeFaster UseEasier showing of function or class descriptionIntelliJ IdeaMore Intense and deeper UseEasier coding of complex programsFAQWhy don't theforwardorbackwardmethod work?Make sure, that if you have specified the speed, that you have also specified the speed unit.
There are three usecases of the functions, like listed below. It is not possible to set the speed parameter, but not the speed unit.fromti_python_moduleimportti_roverasrv# import# RIGHT USE# forwardrv.forward(1)rv.forward(1,"m")rv.forward(1,"m",1,"m/s")#backwardrv.backward(1)rv.backward(1,"m")rv.backward(1,"m",1,"m/s")# WRONG USE# forward# rv.forward(1, "m", 1)# backward# rv.backward(1, "m", 1)What are the return values of a function?As you might have guessed, the functions do not actually measure any values, but they rather return calculated or random values.How do I see a functions / class description?When using IntelliJ Idea,Ctrl + Clickthe statement.
When using Visual Studio Code, You will see a dialogue with autocomplete suggestions. Click the>sign to toggle the information.What are the classeserr.pyandfile_handler.pyThese classes are just for simplifying the creation of the functions.DO NOT USE THEM IN YOUR ACTUAL SCRIPTThe function I want to use requires an argument calledself. What does that mean?If a function requires an argument calledself, then it is placed after a class. Some classes need an argument, whilst some just need the brackets()fromti_python_module.ti_hubimportcontinuous_servo,hub_timecontinuous_servo.set_cw(1,1)# WRONGcontinuous_servo("OUT 3").set_cw(1,1)# RIGHThub_time.measurement()# WRONGhub_time().measurement()# RIGHT
Package: tipytool
TipytoolsTipytools is a Python library that simplifies the development of command-line tools by providing a collection of command-line tool templates and utilities. It offers features such as project setup, template-based file generation, logging, and integration with the fire library for creating user-friendly command-line interfaces.FeaturesProject setup made easy: Use thesetupcommand to quickly set up your project by initializing the environment and generating the project structure for your command-line tool.Template-based project structure: Tipytools provides a standardized project structure including essential files like README.md, setup.py, and template files for your tool's implementation.Logging utility: The library includes a logging module that allows easy printing of information, warnings, errors, and success messages with customizable colors.Cross-platform compatibility: Tipytools is designed to work seamlessly on Windows, Linux, and macOS, ensuring compatibility across different platforms.Integration with fire library: Tipytools integrates with the fire library to provide a user-friendly and intuitive command-line interface for your generated tools.Optional virtual environment: If you want to set up the project without a virtual environment, you can use themaketoolcommand to generate only the folder structure without creating a virtual environment.Folder StructureThe folder structure for Tipytools is as follows:Tipytools/
├── package_test/
│ └── test.py
├── [tool_name]/
│ ├── init.py
│ ├── [tool_name].py
│ └── logger.py
├── README.md
└── setup.pyInstallation:pipinstalltipytoolYou can install Tipytools directly from the GitHub repository:pipinstallgit+https://github.com/tipytools/tipytools.gitUsageSet up your project:To create a virtual environment and generate the project structure, run thesetupcommand and specify the tool name and optional virtual environment name.Example:tipy setup tool=[toolname] [optional: env=[venvname]]To generate only the folder structure without a virtual environment, run themaketoolcommand and specify the tool name.Example:tipy maketool [toolname]Implement your tool's logic within the generated files and customize as needed.Run your tool from the command line: Use the tool name followed by the desired command and arguments.Example:[toolname] [command] [arguments]During the project setup, Tipytools will initialize the environment by creating a virtual environment using the specified name (or a default name derived from the tool name). It will then generate the project structure, including the necessary files and directories. After the setup is complete, you can start implementing your tool's functionality within the provided template files.Please refer to thedocumentationavailable in the repository for more detailed information, usage examples, and customization options.Contributions, bug reports, and feature requests are welcome! Feel free to submit issues and pull requests onGitHubto help improve Tipytools.version: 1.0.0author: Mauly dotDev
Package: tiquations
Tiquations 2.0WelcomeTiquations is an Open-Source Python package that is aimed at giving mathematicians and scientists easy access to important equations that they may use often. It was made in python 3.7 and should work on all versions higher than 3.0.DocumentationThere is an official tiquations website now thanks to creme from Discord! Head over to [tiquations.com](https://www.tiquations.com) to check it out!Help commandstiquations.help()tiquations.changelog()EquationsQuadratic equationMathematical sequence equationsCosine Rules for angles and sidesDistance/Speed/TimeForce/Mass/AccelerationWeight/Mass/Gravitational field strengthCircle area/diameter/circumferenceDelta Velocity/Time taken/AccelerationForce/Area/PressureCylinder Volume/Surface AreaTrapezoid Area/Height/Surface AreaPythagoras' TheorumEnergy/Charge/Potential differencePower/Current/Potential differencePower/Energy/TimeOrbital speed/Radius/Time takenCosine rule for sides and anglesEnergy/Mass/Light speedSchwarzschild radiusSphere Mass/Density/Radius/VolumeCube VolumeCone VolumePyramid VolumeWave frequency using timeWave frequency/wave length/ wave speedRefractive Index/Angle of incidence/Angle of refractionVelocity/Kinetic Energy/MassGravitational Potential Energy/Mass/Gravity/HeightFriction coefficient/Friction force/Normal forceFriction coefficient/Gravity/AccelerationCoefficient/Normal/FrictionFocal point/RadiusFocal point/Distance of image/Distance of objectMirror magnification/Height of image/ Distance of objectMirror magnification/Distance of image/Distance of objectPhoton energyMoment/Force/Distance From PivotFringe SpacingWave Period/Frequency/Wavelength/VelocityConversionKelvin/Fahrenheit/Celsiusbits/bytes/kilobytes/megabytes/gigabytes/terabytes/petabytesmiles/kilometers
Package: tira
The TIRA ClientThis is a python client forTIRA.io.Setup REST Client to Access Non-Public EndpointsTo access non-public endpoints, you will need an authentication via an API key to ensure that you have the correct access credentials.
Please generate your API key online attira.io/admin/api/keysand create a credentials file at~/.tira/.tira-settings.jsonwith the following content:{"api_key": "<YOUR-API-KEY>"}Download The results of some SubmissionYou can download runs of published and unblinded submissions via:from tira.rest_api_client import Client

tira = Client()
output = tira.get_run_output('<task>/<team>/<approach>', '<dataset>')As an example, you can download all baseline BM25 runs submitted toTIRExvia:from tira.rest_api_client import Client
from tira.tirex import TIREX_DATASETS

tira = Client()

for dataset in TIREX_DATASETS:
    output = tira.get_run_output('ir-benchmarks/tira-ir-starter/BM25 Re-Rank (tira-ir-starter-pyterrier)', dataset)Overview of public submissionsAs an example, you can see all public software submissions submitted toTIRExvia:from tira.rest_api_client import Client

tira = Client()
submissions = tira.all_softwares("ir-benchmarks")Export datasetsYou can export datasets if you are the owner or if the dataset is public.
Export a dataset via the cli:tira-run --export-dataset '<task>/<tira-dataset>' --output-directory tira-datasetExport a dataset via the python API:from tira.rest_api_client import Client

tira = Client()
tira.download_dataset('<task>', '<tira-dataset>')Running Jupyter Notebooks with TIRAdockerbuild-ttira/submission-base-image:1.0.0-fDockerfile.Testing the model locally can be done using the following command:tira-run\--input-directory${PWD}/input\--output-directory${PWD}/output\--imagetira/submission-base-image:1.0.0\--command'tira-run-notebook --input $inputDataset --output $outputDir /workspace/template-notebook.ipynb'Afterwards you can push the image to TIRAdockerpushtira/submission-base-image:1.0.0and set the command:tira-run-notebook--input$inputDataset--output$outputDir/workspace/template-notebook.ipynbFinally, if the actual processing in notebook is toggled viais_running_as_inference_server()(as seen in thetemplate notebook)
and your notebook defines a function namedpredictin the formatdefpredict(input_list:List)->List:you can start an inference server for your model with:PORT=8001dockerrun--rm-it--init\-v"$PWD/logs:/workspace/logs"\-p$PORT:$PORT\tira/submission-base-image:1.0.0\tira-run-inference-server--notebook/workspace/template-notebook.ipynb--port$PORTExemplary request for a server running onlocalhost:8001are# POST (JSON list as payload)curl-XPOST-H"application/json"\-d"[\"element 1\", \"element 2\", \"element 3\"]"\localhost:8001and# GET (JSON object string(s) passed to the 'payload' parameter)curl"localhost:8001?payload=\"element+1\"&payload=\"element+2\"&payload=\"element+3\""
Package: tiramisu
Due to more and more available options required to set up an operating system,
compiler options or whatever, it became quite annoying to hand the necessary
options to where they are actually used and even more annoying to add new
options. To circumvent these problems the configuration control was
introduced…Tiramisu is an options handler and an options controller, wich aims at
producing flexible and fast options access.This version requires Python 3.5 or later.