Saravanan666/pypi-org huggingface dataset:
Package: uisdata
uisdatalibraryuisdatais a library for easy data access and manipulation of the datasets offered by theUNESCO Institute for Statistics(UIS).Library modulesuisdata.bddsis the first module developed to consume the dataset archives of theBulk Data Download System (BDDS)repository.Access any BDDS zip archive; download the archive from the repo to memory or access the archive on your local driveSubset the datasets based on lists of countries, years and indicatorsMerge a dataset with its metadata (as columns or as a dictionary)Merge a dataset with its country and indicator labelsWrapper to do all the above with a single methodReshape tables from long to wide format (multiple options)Search utility to create lists of indicators and regions... more to come ...Source code and installationThe test version of the source code is currently hosted on PyPi at:https://pypi.org/project/uisdata/Python requirementuisdatarequires a python 64-bit version.
It has not been tested extensively to find the minimal viable version, but it will work on:python>=3.6  (64-bit)Installationpip install -i https://pypi.org/simple/ uisdataModules Dependenciesuisdata.bddshas not been tested extensively to find the minimal viable versions for its dependencies.It requires the following libraries:requests- a standard for making HTTP requests in Python. It abstracts the complexities of making requests behind a simple API.pandas- an open-source Python Library providing high-performance data manipulation and analysis tool using its powerful data structures.numpy- NumPy is a Python library used for working with arrays. It also has functions for working in domain of linear algebra, fourier transform, and matrices.LicenseMIT LicenseBackgroundWork onuisdatastarted in 2021 for facilitating programmatic access to the UIS datasets. It is still under development, and I will be adding features in future iterations.Tutorials / use-case.bddsUse-caseis provided through dataLore.Clone the notebook to your dataLore account (sign-up required).
Note that the library will self-update to the latest version.
Package: uiside
Additional UI components forPySide-based applications.Save File Dialoguiside.dialogs.OpenFileDialogOpen File Dialoguiside.dialogs.SaveFileDialogMessage Boxuiside.dialogs.MessageBoxComponentsFile DialogsFile Dialogs are fast and simple solution to let a user point to a file or files
(Open File Dialog) or enter name for a new file (Save File Dialog). They have
the same look and behaviour for all supported platforms. They are usually faster
than native dialogs as they are designed to do as little as possible when a dialog
pops up.fromuiside.dialogsimportOpenFileDialogfromuiside.dialogsimportSaveFileDialog# multi=True means possibility to select several filesdialog=OpenFileDialog(self,multi=True)# filters are array of tuples (name, list of masks)dialog.setFilters([('Text Files',['*.txt','*.cpp']),('All Files',['*.*'])])# this actually invokes dialogresult=dialog.exec_()# result can be None when user selects Cancel buttonifresult:fullName,directory,files=resultelse:print'nothing was selected'The result ofexec_()method is eitherNonewhen “Cancel” button has been pressed,
or tuple consisting of 3 parts:stringfull absolute path to the first selected filestringfull absolute path to directory containing selected file(s)listof selected file names, for example:(u'/home/rita/test.txt',u'/home/rita',[u'1.txt',u'2.txt'])Message BoxThis is an extension of standard Message Box with a convenient constructor that
allows to specify title, message text and other parameters. It also has possibility
to show a check box. In this case result ofexec_()is tuple consisting ofresult of standardQMessageBoxexec_()eitherTrueorFalserepresenting state of check boxfromuiside.dialogsimportMessageBox# specify appearance of the dialogtitle='Message Box Example'# window titletext='''
Lorem ipsum dolor sit amet, consectetur adipiscing elit,
sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
'''# which buttons are availablebuttons=QtGui.QMessageBox.Yes|QtGui.QMessageBox.No# default buttondefault=QtGui.QMessageBox.Noglyph=QtGui.QMessageBox.Question# we can show a nice glyph in the dialogbox=MessageBox(title,text,'Do not ask next time',buttons,default,glyph,self)printbox.exec_()# tuple is returned# see QMessageBox for details on how to interpret the first partInstallationTheuisidepackage requiresPySideto be installed. The latter is not mentioned
in package dependencies because on most systems PySide is installed as system package.
Should your case not be the same, it is possible to install PySide from PyPI.Theuisidepackage can be installed from PyPI:pipinstalluisideLicenseLicense:MIT.
Package: uisp-crm
UISP CRMOverviewuisp_crmis a Python library for working with UISP Clients.InstallationYou can install the library using pip. Open your terminal and run:pipinstalluisp-crmContributingPull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.Usagefromuisp_crmimportCRMcrm=CRM(hostname="https://YOUR_UISP_CONSOLE",api_key="YOUR_API_KEY")clients=crm.clients.get_clients()LicenseMIT
Package: uistylelang
UI Style Lang (Language)UI Style Lang is a simple CSS-like language which allows for drawing and styling wxPython elements. Many UI Style Lang properties are the same as the normal (not short-hand) CSS3 properties. This provides a familiar syntax, especially for those with experience with CSS3.If you are looking for an easy way to:Draw shapes, text and/or imagesin wxPython without worrying so much about ids, brushes, pens, etc.Style the native wxPython widgetsfrom a stylesheetCreate your own custom widgets in wxPythonthat can be styled with a CSS-like stylesheet...then UI Style Lang is likely the module you're looking for.WIP/ TODOSVG support(?)FeaturesWritten in pure Python with minimal dependancies (just wxPython and the standard library)Drawing APIIncludes theUIStylePDCUI Style Lang class which is a powerful extension of the wxPythonwx.PseudoDCOver 15 stylesheet properties already supportedDraw circles, rectangles, squares, images, & textTranslate & rotate elementsLoad styles from inline styles, string and/or an external stylesheetAuto-handles wxPython IDs, with support for manual-handling of IDsNative Widget Styling APISupports loading from a stylesheet for easy themingSupport for styling app, panels, frames and static text widgets...and more.Usage and ExamplesSee thedocumentationat Read the Docs andfull demo examplesfor information on usage...What does the syntax look like?UI Style Lang (Stylesheet API) example:/* My custom button styles */
@style button {
  background-color: #F4F4F4;
  top: 20px;
  left: 40px;
  width: 115px;
  height: 35px;
  border-color: #D1D1D1;
  border-size: 2px;
}

@style button:hover {
  background-color: #FDFDFD;
  top: 20px;
  left: 40px;
  width: 115px;
  height: 35px;
  border-color: #D1D1D1;
  border-size: 2px;
}Python API example:# Intilizing the element: <div id="button"></div>>>dc.InitElem("button")# Editing the style with inline styles: <div id="button" style="border-color: red; border-width: 4px;"></div>>>dc.UpdateElem('button',styles="border-color: red; border-width: 4px;")# Update the element with the 'hover' styles: <div id="button" class="hover"></div>>>dc.UpdateElem('button:hover')DevelopmentPull requests and/or feature suggestions are welcome!LicenseUI Style Lang is licensed under the BSD 3-Clause license
Package: uitestframework
UI Test FrameworkPackage for Testing Browser User interfaces.Installationpip install uitestframeworkYou must also download the driver for your selected browser and place it in your working directory Drivers can be
downloadedhere.UsageThe UI Test Framework provides a base for creating browser based UI tests by using the Page Object Model and selenium
webdriver. You might find
it most useful for testing web application in development in which the UI is continually being changed. Typical usage
often looks like this:fromunittestimportTestCasefromuitestframeworkimportUITestCaseMixin,PageObjectModelfromuitestframework.pomimportBasePage,BaseElementAPPLICATION_HOST="https://localhost:8080"classMyPage(BasePage):defset_elements(self):# adds a BaseElement instance "Button1" to MyPagebutton1=BaseElement(name="Button1",locator="button_id",locator_type='id',page=self)return[button1]classMyPOM(PageObjectModel):# Maps url paths to BasePage instanceurl_map={'':MyPage,}classMyTestCase(UITestCaseMixin,TestCase):# These are necessary attributes for this classdriver_path="chromedriver.exe"browser='chrome'pom=MyPOM()deftest_foo(self):# tests that button 1 redirects you from the current pageself.driver.get(APPLICATION_HOST)# Using the url map, the pom knows in which page to look for the specified element attribute# Several methods for interacting with UI are implemented in the BaseElement class and its Subclassesself.pom.button1.click()self.assertTrue(self.driver.current_url!=APPLICATION_HOST)To test pages which require user input. The FormPage class can be used. An example of usage is provided below::#!/usr/bin/env pythonfromunittestimportTestCasefromselenium.webdriver.common.byimportByfromuitestframeworkimportUITestCaseMixin,PageObjectModelfromuitestframework.pomimportFormPage,FieldElement,BaseElementAPPLICATION_HOST="https://localhost:8080"classLoginPage(FormPage):defset_elements(self):username=FieldElement(name='username',locator="id_username",locator_type=By.ID,page=self)password=FieldElement(name='password',locator="id_password",locator_type=By.ID,page=self)submit=FieldElement(name='submit',locator="id_submit",locator_type=By.ID,page=self)error_message=BaseElement(name='error_message',locator="id_error",locator_type=By.ID,page=self)return[username,password,submit,error_message]classMyApplicationPOM(PageObjectModel):url_map={'/login':LoginPage,}classMyTestCase(UITestCaseMixin,TestCase):driver_path="chromedriver.exe"browser='chrome'pom=MyApplicationPOM()deftest_login(self):login_url=APPLICATION_HOST+'/login'self.driver.get(login_url)self.pom.autofill(username='username',password='correct password')self.pom.submit.click()self.assertTrue(self.driver.current_url!=login_url)deftest_failed_login(self):login_url=APPLICATION_HOST+'/login'self.driver.get(login_url)self.pom.autofill(username='username',password='wrong password')self.pom.submit.click()self.assertTrue(self.pom.error_message.is_rendered())
Package: ui-test-runner
Translator UI Test RunnerThis testing framework performs UI Pass/Fail analysis on queries it receives from the Translator Test Harness.Installationpip install ui-test-runnerUsagefromui_test_runnerimportrun_ui_testreport=run_ui_test(<env>,<query_type>,<expected_output>,<input_curie>,<output_curie>)Arguements:env: the environment to run the queries against. (dev, ci, test, prod)query_type: type of query to test. (treats(creative), upregulates, downregulates)expected_output: whether the output curie is good or bad. (TopAnswer, Acceptable, BadButForgivable, NeverShow)input_curie: curie used in the initial query.output_curie: curie checked for in the results
Package: uitk
UITK: Dynamic UI Management for Python with PySide2UITK is a comprehensive Python package designed to streamline the creation, management, and interaction of user interfaces (UIs) using Python3|PySide2. With a focus on versatility, UITK leverages a naming convention-based switchboard module to dynamically load UI files, register custom widgets, manage slots, styles, states, and facilitate interaction with widgets. The primary goal of UITK is to simplify the development process of complex UIs and enhance the efficiency of event handling.Key FeaturesDynamic UI file loadingCustom widget registrationUtility properties for MainWindow and child widget subclassingManagement of slot connections and event handlingSupport for UI hierarchy navigation and submenusCustom event behavior through UI tagsUI and slot history storage and retrievalWidget syncing and state management.Module OverviewModuleDescriptionfile_managerAllows for setting multiple locations for dynamic UI files, custom widgets, and slot modules.switchboardHandles dynamic UI loading, assigns convenience properties, manages slot connections, syncs, saves, and restores widget states, etc.eventsManages event handling for dynamic UI widgets.widgetsA source directory for the custom widgets included with this package.Installation:Add theuitkfolder to a directory on your python path, or
install via pip in a command line window using:python-mpipinstalluitkBasic Example:Create an instance of Switchboard to load and connect your dynamic ui.fromuitkimportSwitchboardfromuitkimportexamplesb=Switchboard(ui_location=example,slot_location=example.example_slots)ui=sb.example# Access the UI using its filename.ui.set_attributes(WA_TranslucentBackground=True)# Set properties using keyword arguments.ui.set_flags(FramelessWindowHint=True,WindowStaysOnTopHint=True)ui.set_style(theme="dark",style_class="translucentBgWithBorder")print(repr(ui))ui.show(pos="screen",app_exec=True)Advanced Example:https://github.com/m3trik/tentacle
Package: uitnlp
UITNLP: A Python NLP Library for VietnameseInstallationYou can install this package from PyPI usingpip:$ pip install uitnlpExample#!/usr/bin/python# -*- coding: utf-8 -*-fromuitnlpimportload_word_segmenterword_segmenter=load_word_segmenter(feature_name='base_sep_sfx')word_segmenter.segment(texts=['Chào mừng bạn đến với Trường Đại học Công nghệ Thông tin, ĐHQG-HCM.'],pre_tokenized=False,batch_size=4)NoteCurrently, we have just wrappered the Vietnamese word segmentation method published in the followingour paper:@InProceedings{10.1007/978-981-15-6168-9_33,
  author    = "Nguyen, Duc-Vu and Van Thin, Dang and Van Nguyen, Kiet and Nguyen, Ngan Luu-Thuy",
  editor    = "Nguyen, Le-Minh and Phan, Xuan-Hieu and Hasida, K{\^o}iti and Tojo, Satoshi",
  title     = "Vietnamese Word Segmentation with SVM: Ambiguity Reduction and Suffix Capture",
  booktitle = "Computational Linguistics",
  year      = "2020",
  publisher = "Springer Singapore",
  address   = "Singapore",
  pages     = "400--413",
  abstract  = "In this paper, we approach Vietnamese word segmentation as a binary classification by using the Support Vector Machine classifier. We inherit features from prior works such as n-gram of syllables, n-gram of syllable types, and checking conjunction of adjacent syllables in the dictionary. We propose two novel ways to feature extraction, one to reduce the overlap ambiguity and the other to increase the ability to predict unknown words containing suffixes. Different from UETsegmenter and RDRsegmenter, two state-of-the-art Vietnamese word segmentation methods, we do not employ the longest matching algorithm as an initial processing step or any post-processing technique. According to experimental results on benchmark Vietnamese datasets, our proposed method obtained a better {\$}{\$}{\backslash}text {\{}F{\}}{\_}{\{}1{\}}{\backslash}text {\{}-score{\}}{\$}{\$}F1-scorethan the prior state-of-the-art methods UETsegmenter, and RDRsegmenter.",
  isbn      = "978-981-15-6168-9"
}
Package: uit-tokenizer
UITNLP: A Python NLP Library for VietnameseInstallationYou can install this package from PyPI usingpip:$ pip install uit-tokenizerExample#!/usr/bin/python# -*- coding: utf-8 -*-fromuit_tokenizerimportload_word_segmenterword_segmenter=load_word_segmenter(feature_name='base_sep_sfx')word_segmenter.segment(texts=['Chào mừng bạn đến với Trường Đại học Công nghệ Thông tin, ĐHQG-HCM.'],pre_tokenized=False,batch_size=4)NoteCurrently, we have just wrappered the Vietnamese word segmentation method published in the followingour paper:@InProceedings{10.1007/978-981-15-6168-9_33,
  author    = "Nguyen, Duc-Vu and Van Thin, Dang and Van Nguyen, Kiet and Nguyen, Ngan Luu-Thuy",
  editor    = "Nguyen, Le-Minh and Phan, Xuan-Hieu and Hasida, K{\^o}iti and Tojo, Satoshi",
  title     = "Vietnamese Word Segmentation with SVM: Ambiguity Reduction and Suffix Capture",
  booktitle = "Computational Linguistics",
  year      = "2020",
  publisher = "Springer Singapore",
  address   = "Singapore",
  pages     = "400--413",
  abstract  = "In this paper, we approach Vietnamese word segmentation as a binary classification by using the Support Vector Machine classifier. We inherit features from prior works such as n-gram of syllables, n-gram of syllable types, and checking conjunction of adjacent syllables in the dictionary. We propose two novel ways to feature extraction, one to reduce the overlap ambiguity and the other to increase the ability to predict unknown words containing suffixes. Different from UETsegmenter and RDRsegmenter, two state-of-the-art Vietnamese word segmentation methods, we do not employ the longest matching algorithm as an initial processing step or any post-processing technique. According to experimental results on benchmark Vietnamese datasets, our proposed method obtained a better {\$}{\$}{\backslash}text {\{}F{\}}{\_}{\{}1{\}}{\backslash}text {\{}-score{\}}{\$}{\$}F1-scorethan the prior state-of-the-art methods UETsegmenter, and RDRsegmenter.",
  isbn      = "978-981-15-6168-9"
}
Package: uiuc-490-sp23
ECE490Repo to collaborate within for UIUC's ECE490, Spring 2023InstallationInstallation from PyPIThis should be as simple as:python-mpipinstalluiuc-490-sp23Installation from SourceThis project usesPoetryInstall it viatheir instructionsand run:poetryinstallfrom this directory (preferably from within avenv).ExecutingOnce installed, individual assignments can be ran by:python-muiuc_490_sp23.assignment<n>where<n>is the assignment number. These will have a CLI implemented using argparse; if you're not sure,
just run the above with--helpto get a full list of commands.AssignmentsAssignment 1: Gradient DescentThis solves a simple, randomly generated quadratic minimization problem using Gradient Descent. It does so using
both fixed step size, as well as an adaptive backtracking line search (Armijo's rule).Assignment 2: Newton's Method and Projected Gradient DescentThis assignment does two things:Implements Newton's method to solve a simple 2D cubic polynomial and plots a fractal displaying the resulting solution based on the starting pointImplements Projected gradient descent and uses it to solve a simple box constrained optimization problemAssignment 3: Augmented LagrangianThis assignment implements the augmented Lagrangian to solve an equality constrained quadratic problem.
Package: uiuc-apartments
UIUC Apartment KitA wrapper around a webscraper for popular rental agencies on UIUC campusInstallation:pip install uiuc-apartmentsUsage:fromuiuc_apartmentsimportAllAgenciesforagencyinAllAgencies:print(agency.get_all())fromuiuc_apartmentsimportSmithagency=Smith()print(agency.name)# Smith Apartmentsapartments=agency.get_all()# [<Apartment $1020.0/month 2.0 beds/1.0 baths 8/2/2024 Smith Apartments>, ...print(apartments[0].link)# https://smithapartments-cu.com/property-details/?pid=27Development:Add a new agency to the folderAdd it to the imports ofagencies/__init__.pyand toAllAgencies
Package: uiucapi
UIUC CourseExplorer API=======================.. image:: https://circleci.com/gh/rohits2/UIUC-API/tree/master.svg?style=shieldWhat is this?-------------This is an interface to the UIUC Course Explorer API.  It allows for the easy querying of class statuses from inside Python.This library supports both async and standard queries to the API, as well as querying for specific CRNs.Basic usage-----------The API is very simple to use:::from uiucapi.query import get_coursecourse = get_course("CS 374 FA17")for section in course.sections:print(section.registration_status)Advanced features-----------------If :code:`uiucapi.aioquery` is used instead of query, the :code:`get_course` and :code:`get_section` methods provided will be non-blocking coroutines instead ofblocking methods.
Package: uiuc-api
Aboutuiuc-apiis a simple python package which wraps UIUC's official REST API for querying data about courses. In addition, it deals with some of the annoyances of using the official API by providing some convient structures. Data from the official API is available in XML form, however, it is in an inconvienent-to-parse format. For instance, take the XML data for CS 173:<label>DiscreteStructures</label><description>DiscretemathematicalstructuresfrequentlyencounteredinthestudyofComputerScience.Sets,propositions,Booleanalgebra,induction,recursion,relations,functions,andgraphs.CreditisnotgivenforbothCS173andMATH213.Prerequisite:OneofCS125,ECE220;oneofMATH220,MATH221.</description><creditHours>3hours.</creditHours><courseSectionInformation>CreditisnotgivenforbothCS173andMATH213.Prerequisite:OneofCS125,ECE220;oneofMATH220,MATH221.</courseSectionInformation><classScheduleInformation>Studentsmustregisterforalectureanddiscussionsection.</classScheduleInformation>It is tedious, for example, to accurately parse out the prerequisites in a easy-to-manipulate form.uiuc-apidoes this for the user:>>>importuiuc_apiasua>>>ua.get_course("CS 173").serialize()Output:CS 173:subject:CSnumber:'173'hours:3label:Discrete Structuresdescription:'DiscretemathematicalstructuresfrequentlyencounteredinthestudyofComputerScience.Sets,propositions,Booleanalgebra,induction,recursion,relations,functions,andgraphs.CreditisnotgivenforbothCS173andMATH213.Prerequisite:OneofCS125,ECE220;oneofMATH220,MATH221.'schedule_info:'CreditisnotgivenforbothCS173andMATH213.Prerequisite:OneofCS125,ECE220;oneofMATH220,MATH221.'prereqs:-!!python/object/apply:builtins.frozenset--ECE 220-CS 125-!!python/object/apply:builtins.frozenset--MATH 220-MATH 221coreqs:[]constraints:[]InstallationInstall theuiuc_apimodule via pip (uiuc-apialso works):pipinstalluiuc_apiDocumentationSeehttps://uiuc-api.readthedocs.io/.
Package: uiuc-mas
# Milliarc-second Photon Sieve SimulationsUIUC-SINE Group#### Files- `csbs.py` - clustered SBS algorithm with interchangeable cost modules[paper](https://ieeexplore.ieee.org/document/4429318/)- `psf_generator.py` - functions for generating PSFs at different measurement planes- `random_cost.py` - a simple example cost module for CSBS- `plotting.py` - functions for displaying results from CSBS- `forward_model.py` - functions for simulating observations at measurement planes generated by CSBS algorithm- `examples/` - directory containing python snippets#### Dependencies- Fedora- libtiff-devel- fftw-devel#### Installationcd mas/pythonpip install -e .#### Running testspython tests/tests.py
Package: uium
uiumInstallingInstall and update using pip:$ pip install -U uiumA Simple ExampleimportuiumLinksDocumentation:https://github.com/MarkHoo/uiumPyPI Releases:https://pypi.org/project/uium/Source Code:https://github.com/MarkHoo/uiumIssue Tracker:https://github.com/MarkHoo/uium/issuesWebsite:https://pypi.org/project/uium/
Package: uiwiz
UiWizardUiWizard is a python-based ui-framework for the web. It was inspired by the great frameworkNiceGui. Why create this project that is very similar to NiceGui?The first reason was that NiceGui requires websockets to work and when experimenting with the framework it caused some issues on my hosting platform.Learning. I wanted to figure out how to do something simillar but without using websocketsI wanted to try out HTMXLimited control over the underlaying tech stack but mainly just learningFeaturesTailwind and DaisyUI for the graphics and responsive layoutWebbasedQuite a lot of standard elements, input fields, dropdown, foot, header, tabs...HTMX for interactivityHopefully great defaults!UsageCreate a main.py filefromuiwiz.appimportUiwizAppfromuiwizimportuiimportuvicornapp=UiwizApp()@app.page("/")asyncdefhome_page(request:Request):ui.label("Hello world")if__name__=="__main__":uvicorn.run("main:app",reload=True)Run itpythonmain.pyGeneral infoHTMX works with input fields in HTML and forms. To make it a bit easier to work with the form submit event does not send the data in the normal form format but uses the HTMX extension to convert it to json. This means that endpoints using UiWizard can use pydantic models as the input and have the benefit of validation.