Search Results for "240p-test-suite"
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Showing 39 open source projects for "240p-test-suite"
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Skillfully - The future of skills based hiringSkillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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Behaviour Suite Reinforcement Learning
bsuite is a collection of carefully-designed experiments
bsuite is a research framework developed by Google DeepMind that provides a comprehensive collection of experiments for evaluating the core capabilities of reinforcement learning (RL) agents. Its main goal is to identify, measure, and analyze fundamental aspects of learning efficiency and generalization in RL algorithms. The library enables researchers to benchmark their agents on standardized tasks, facilitating reproducible and transparent comparisons across different approaches. Each... -
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
...Pandera provides a simple, flexible, and extensible data-testing framework for validating not only your data but also the functions that produce them. A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness. Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases. Validate the functions that produce your data by automatically generating test cases for them. Integrate seamlessly with the Python ecosystem. Overcome the initial hurdle of defining a schema by inferring one from clean data, then refine it over time. ... -
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urllib3
Python HTTP library with thread-safe connection pooling
...File uploads with multipart encoding. Helpers for retrying requests and dealing with HTTP redirects. Support for gzip, deflate, brotli, and zstd encoding. Proxy support for HTTP and SOCKS. 100% test coverage. Professional support for urllib3 is available as part of the Tidelift Subscription. Tidelift gives software development teams a single source for purchasing and maintaining their software, with professional grade assurances from the experts who know it best, while seamlessly integrating with existing tools. -
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pikepdf
A Python library for reading and writing PDF, powered by QPDF
pikepdf is a Python library allowing the creation, manipulation, and repair of PDFs. It provides a Pythonic wrapper around the C++ PDF content transformation library, QPDF. Python + QPDF = “py” + “qpdf” = “pyqpdf”, which looks like a dyslexia test and is no fun to type. But say “pyqpdf” out loud, and it sounds like “pikepdf”. pikepdf is a library intended for developers who want to create, manipulate, parse, repair, and abuse the PDF format. It supports reading and write PDFs, including creating from scratch. Thanks to QPDF, it supports linearizing PDFs and access to encrypted PDFs. -
The Most Awarded Employee Time Clock SoftwareCloud based time clock solution that pre-populates reports for payroll. Employees can punch in on their desktop or mobile devices. Punching in & out is intuitive for your employees & easy for you to view & export time. Employees can clock in using a browser or our Google, iOS, & Android apps. You can view who's working, their GPS position or even limit where they can punch. We integrate with QuickBooks, ADP, Paychex, & SurePayroll while also offering Excel exports. Advanced features such as PTO Accrual Tracking, Punch Rounding, Job Codes, QR Codes, Automatic Breaks, & SSO are all included in our cloud based time clock.
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ipytest
Pytest in IPython notebooks
ipytest allows you to run Pytest in Jupyter notebooks. ipytest aims to give access to the full pytest experience and to make it easy to transfer tests out of notebooks into separate test files. -
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Hypothesis
The property-based testing library for Python
Hypothesis is a powerful library for property-based testing in Python. Instead of writing specific test cases, users define properties and Hypothesis generates random inputs to uncover edge cases and bugs. It integrates with unittest and pytest, shrinking failing examples to minimal reproducible cases. Widely adopted in production systems, Hypothesis boosts code reliability by exploring input spaces far beyond manually crafted tests. -
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Mistral Inference
Official inference library for Mistral models
Open and portable generative AI for devs and businesses. We release open-weight models for everyone to customize and deploy where they want it. Our super-efficient model Mistral Nemo is available under Apache 2.0, while Mistral Large 2 is available through both a free non-commercial license, and a commercial license. -
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xhtml2pdf
A library for converting HTML into PDFs using ReportLab
xhtml2pdf enables users to generate PDF documents from HTML content easily and with automated flow control such as pagination and keeping text together. The Python module can be used in any Python environment, including Django. The Command line tool is a stand-alone program that can be executed from the command line. -
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Werkzeug
The comprehensive WSGI web application library
Werkzeug is a comprehensive WSGI web application library. It began as a simple collection of various utilities for WSGI applications and has become one of the most advanced WSGI utility libraries. Werkzeug doesn’t enforce any dependencies. It is up to the developer to choose a template engine, database adapter, and even how to handle requests. Includes an interactive debugger that allows inspecting stack traces and source code in the browser with an interactive interpreter for any frame in... -
Diagnose and Resolve IT Issues in Real TimeScreenMeet’s unique combination of video calling, screen share, and remote desktop functionality lets you quickly diagnose hardware and software issues with no frustration.
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MuJoCo Playground
An open source library for GPU-accelerated robot learning
MuJoCo Playground, developed by Google DeepMind, is a GPU-accelerated suite of simulation environments for robot learning and sim-to-real research, built on top of MuJoCo MJX. It unifies a range of control, locomotion, and manipulation tasks into a consistent and scalable framework optimized for JAX and Warp backends. The project includes classic control benchmarks from dm_control, advanced quadruped and bipedal locomotion systems, and dexterous as well as non-prehensile manipulation setups. ... -
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dateutil
Useful extensions to the standard Python datetime features
The dateutil module provides powerful extensions to the standard date time module, available in Python. dateutil can be installed from PyPI using pip (note that the package name is different from the importable name). -
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Helium
Lighter web automation with Python
Helium is a Python library built on top of Selenium to make browser automation more intuitive and human-friendly. It replaces verbose boilerplate code with natural language-like API calls such as click("Login") or write("hello", into="Name"). Helium manages browser setup, waits, and teardown, enabling quick development of scripts for testing, scraping, or task automation without requiring deep Selenium knowledge. -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
...Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before they pass into a neural network (if you use augmentation). The general recommendation is to use suitable augs for your data and as many as possible, then after some time of training disable the most destructive (for image) augs. You can turn on automatic mixed precision with one flag --amp. ... -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and... -
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Strawberry GraphQL
A GraphQL library for Python that leverages type annotations
Python GraphQL library based on dataclasses. Strawberry's friendly API allows to create GraphQL API rather quickly, the debug server makes it easy to quickly test and debug. Django and ASGI support allow having your API deployed in production in a matter of minutes. The quick start method provides a server and CLI to get going quickly. Strawberry comes with a mypy plugin that enables statically type-checking your GraphQL schema. A Django view is provided for adding a GraphQL endpoint to your application. ... -
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Multimodal
TorchMultimodal is a PyTorch library
...The design emphasizes composability: you can mix and match encoder, fusion, and decoder components rather than starting from monolithic models. The repository also includes example scripts and datasets for common multimodal tasks (e.g. retrieval, visual question answering, grounding) so you can test and compare models end to end. Installation supports both CPU and CUDA, and the codebase is versioned, tested, and maintained. -
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Playground Cheatsheet for Python
Playground and cheatsheet for learning Python
learn-python is another repository by Oleksii Trekhleb that serves as both a playground and an interactive cheatsheet for learning Python. It contains numerous Python scripts organized by topic (lists, dictionaries, loops, functions, classes, modules, etc.), each with code examples, explanations, test assertions, and links to further readings. The design supports “learn by doing”: you can modify the code, run the tests, see how behavior changes, and thus internalize Python language features, idioms, and good style practices (including linting and PEP8). Because it is organized in bite-sized chunks, it’s ideal for beginners or people refreshing their Python skills who want to revisit syntax and common patterns before moving into larger frameworks or applications. ... -
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FSP - File Service Protocol Suite
UDP File transfer protocol
FSP - File Service Protocol. FSP is lightweight UDP based protocol for transferring files. It is designed for anonymous transfers over unreliable networks. -
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bidict
The bidirectional mapping library for Python
...Implemented in concise, well-factored, fully type-hinted Python code that is optimized for running efficiently as well as for long-term maintenance and stability. Extensively documented. 100% test coverage running continuously across all supported Python versions. Enterprise-level support for bidict can be obtained via the Tidelift subscription. One of the best things about bidict is that it touches a surprising number of interesting Python corners, especially given its small size and scope. Choose a tier and GitHub handles everything else. ... -
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geometry3d
A Python library for geometric objects in 3 dimentions
...It also can tell if it contains the other object or is it contained by that. Where appropriate, it's easy to check orthogonality and parallelism. Vectors are sub-typed from numpy ndarray class. Extensive unit tests are included. Test coverage exceeds 95%. See documentation of the library internals in section Files ( https://sourceforge.net/projects/geometry3d/files/ ). -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
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Binarytree
Python library for studying Binary Trees
Binarytree is Python library that lets you generate, visualize, inspect and manipulate binary trees. Skip the tedious work of setting up test data, and dive straight into practicing algorithms. Heaps and BSTs (binary search trees) are also supported. Binarytree supports another representation which is more compact but without the indexing properties. Traverse trees using different algorithms. -
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SageMaker Scikit-Learn Extension
A library of additional estimators and SageMaker tools based on scikit
A library of additional estimators and SageMaker tools based on scikit-learn. This project contains standalone scikit-learn estimators and additional tools to support SageMaker Autopilot. Many of the additional estimators are based on existing scikit-learn estimators. SageMaker Scikit-Learn Extension is a Python module for machine learning built on top of scikit-learn. In order to use the I/O functionalies in the sagemaker_sklearn_extension.externals module, you will also need to install the... -
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Big List of Naughty Strings
List of strings which have a high probability of causing issues
The Big List of Naughty Strings is a community-maintained catalog of “gotcha” inputs that commonly break software, from unusual Unicode to SQL and script injection payloads. It exists so developers and QA engineers can easily test edge cases that normal test data would miss, such as zero-width characters, right-to-left marks, emojis, foreign alphabets, and long or malformed strings. By throwing these strings at forms, APIs, databases, and UIs, teams can discover encoding bugs, sanitizer gaps, rendering issues, and security oversights early. The list is language-agnostic and repository-friendly, meaning you can consume it from CI pipelines or local scripts with minimal setup. ... -
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SentEval
A python tool for evaluating the quality of sentence embeddings
...It defines a simple interface—provide an encoder function from sentences to vectors—and then runs consistent training/evaluation loops for tasks like sentiment, entailment, paraphrase, and semantic textual similarity. The suite also contains linguistic probing tasks that illuminate what properties embeddings capture, such as tense, word order, or syntactic structure. Datasets are wrapped with unified preprocessing and metrics so results are comparable across papers and implementations. Because the interface is minimal, researchers can plug in encoders from any framework or language model and obtain a broad evaluation with little glue code. ...
