Search Results for "python code generator" - Page 25

Showing 3816 open source projects for "python code generator"

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  • 1
    dynaconf

    dynaconf

    Configuration Management for Python

    ... Vault and Redis as settings and secrets storage. Built-in extensions for Django and Flask web frameworks. CLI for common operations such as init, list, write, validate, export. On your own code you import and use settings object imported from your config.py file. Dynaconf prioritizes the use of environment variables and you can optionally store settings in Settings Files using any of toml|yaml|json|ini|py extension.
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  • 2
    JS Beautifier

    JS Beautifier

    Beautifier for javascript

    This little beautifier will reformat and re-indent bookmarklets, ugly JavaScript, unpack scripts packed by Dean Edward’s popular packer, as well as partly deobfuscate scripts processed by the npm package javascript-obfuscator. All of the source code is completely free and open, available on GitHub under MIT licence, and we have a command-line version, python library and a node package as well. You may install the NPM package js-beautify. When installed globally, it provides an executable js...
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  • 3
    Bot Framework SDK for .NET

    Bot Framework SDK for .NET

    Welcome to the Bot Framework SDK for .NET repository

    This repository contains code for the .NET version of the Microsoft Bot Framework SDK, which is part of the Microsoft Bot Framework - a comprehensive framework for building enterprise-grade conversational AI experiences. This SDK enables developers to model conversation and build sophisticated bot applications using .NET. SDKs for JavaScript, Python and Java (preview) are also available. To get started building bots using the SDK, see the Azure Bot Service Documentation.
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  • 4
    The Operator Splitting QP Solver

    The Operator Splitting QP Solver

    The Operator Splitting QP Solver

    OSQP uses a specialized ADMM-based first-order method with custom sparse linear algebra routines that exploit structure in problem data. The algorithm is absolutely division-free after the setup and it requires no assumptions on problem data (the problem only needs to be convex). It just works. OSQP has an easy interface to generate customized embeddable C code with no memory manager required. OSQP supports many interfaces including C/C++, Fortran, Matlab, Python, R, Julia, Rust.
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  • 5
    Kompute

    Kompute

    General purpose GPU compute framework built on Vulkan

    General purpose GPU compute framework built on Vulkan to support 1000s of cross-vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous, and optimized for advanced GPU data processing use cases. Backed by the Linux Foundation.
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  • 6
    NeuroMatch Academy (NMA)

    NeuroMatch Academy (NMA)

    NMA Computational Neuroscience course

    ... brush up on your knowledge. The pre-reqs refresher days are asynchronous, so you can go through the material on your own time. You will learn how to code in Python from scratch using a simple neural model, the leaky integrate-and-fire model, as a motivation. Then, you will cover linear algebra, calculus and probability & statistics. The topics covered on these days were carefully chosen based on what you need for the comp neuro course.
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  • 7
    JUDI.jl

    JUDI.jl

    Julia Devito inversion

    JUDI is a framework for large-scale seismic modeling and inversion and is designed to enable rapid translations of algorithms to fast and efficient code that scales to industry-size 3D problems. The focus of the package lies on seismic modeling as well as PDE-constrained optimization such as full-waveform inversion (FWI) and imaging (LS-RTM). Wave equations in JUDI are solved with Devito, a Python domain-specific language for automated finite-difference (FD) computations. JUDI's modeling...
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  • 8
    QuantumOptics.jl

    QuantumOptics.jl

    Library for the numerical simulation of closed as well as open quantum

    QuantumOptics.jl is a numerical framework written in the Julia programming language that makes it easy to simulate various kinds of open quantum systems. It is inspired by the Quantum Optics Toolbox for MATLAB and the Python framework QuTiP. QuantumOptics.jl optimizes processor usage and memory consumption by relying on different ways to store and work with operators. The framework comes with a plethora of pre-defined systems and interactions making it very easy to focus on the physics...
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  • 9
    DifferentialEquations.jl

    DifferentialEquations.jl

    Multi-language suite for high-performance solvers of equations

    This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research which routinely outperform the “standard” C/Fortran methods, and include algorithms optimized...
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  • 10
    k3s in docker

    k3s in docker

    Little helper to run CNCF's k3s in Docker

    k3d is a lightweight wrapper to run k3s (Rancher Lab’s minimal Kubernetes distribution) in docker. k3d makes it very easy to create single- and multi-node k3s clusters in docker, e.g. for local development on Kubernetes. Note: k3d is a community-driven project but it’s not an official Rancher (SUSE) product. Sponsoring: To spend any significant amount of time improving k3d, we rely on sponsorships. k3d creates containerized k3s clusters. This means, that you can spin up a multi-node k3s...
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  • 11
    apiDoc

    apiDoc

    RESTful web API documentation Generator

    apiDoc creates a documentation from API annotations in your source code. apiDoc gives you the ability to attach a version number to an API so you can easily track changes between versions. Creates an apiDoc of all files within dir myapp/, uses template from dir mytemplate/ and put all output to dir apidoc/. Without any parameter, apiDoc generate a documentation from all .cs .dart .erl .go .java .js .php .py .rb .ts files in current dir (incl. subdirs) and writes the output to ./doc/. apiDoc...
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  • 12
    Tarsier

    Tarsier

    Vision utilities for web interaction agents

    At Reworkd, we iterated on all these problems across tens of thousands of real web tasks to build a powerful perception system for web agents... Tarsier! In the video below, we use Tarsier to provide webpage perception for a minimalistic GPT-4 LangChain web agent. Tarsier visually tags interactable elements on a page via brackets + an ID e.g. [23]. In doing this, we provide a mapping between elements and IDs for an LLM to take actions upon (e.g. CLICK [23]). We define interactable elements...
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  • 13
    Digital Earth Australia notebooks

    Digital Earth Australia notebooks

    Repository for Digital Earth Australia Jupyter Notebooks

    The knowledge hub brings together information about Digital Earth Australia’s products and services, allowing you to utilize our free and open-source satellite imagery archive. Browse our catalog of data products to find supporting information and ways to access the data. The Digital Earth Australia notebooks and tools repository (dea-notebooks) hosts Jupyter Notebooks, Python scripts and workflows for analyzing Digital Earth Australia (DEA) satellite data and derived products
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  • 14
    libCEED

    libCEED

    CEED Library: Code for Efficient Extensible Discretizations

    libCEED provides fast algebra for element-based discretizations, designed for performance portability, run-time flexibility, and clean embedding in higher-level libraries and applications. It offers a C99 interface as well as bindings for Fortran, Python, Julia, and Rust. While our focus is on high-order finite elements, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the user manual and API implementation portion
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  • 15
    dbt-re-data

    dbt-re-data

    re_data - fix data issues before your users & CEO would discover them

    re_data is an open-source data reliability framework for the modern data stack. Currently, re_data focuses on observing the dbt project (together with underlaying data warehouse - Postgres, BigQuery, Snowflake, Redshift). Data transformations in re_data are implemented and exposed as models & macros in this dbt package. Gather all relevant outputs about your data in one place using our cloud. Invite your team and debug it easily from there. Go back in time, and see your past metadata. Set up...
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  • 16
    OpenFold

    OpenFold

    Trainable, memory-efficient, and GPU-friendly PyTorch reproduction

    OpenFold carefully reproduces (almost) all of the features of the original open source inference code (v2.0.1). The sole exception is model ensembling, which fared poorly in DeepMind's own ablation testing and is being phased out in future DeepMind experiments. It is omitted here for the sake of reducing clutter. In cases where the Nature paper differs from the source, we always defer to the latter. OpenFold is trainable in full precision, half precision, or bfloat16 with or without DeepSpeed...
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  • 17
    Basaran

    Basaran

    Basaran, an open-source alternative to the OpenAI text completion API

    Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models. The open source community will eventually witness the Stable Diffusion moment for large language models (LLMs), and Basaran allows you to replace OpenAI's service with the latest open-source model to power your application without modifying a single line of code. Stream generation using various decoding strategies...
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  • 18
    Swirl

    Swirl

    Swirl queries any number of data sources with APIs

    Swirl queries any number of data sources with APIs and uses spaCy and NLTK to re-rank the unified results without extracting and indexing anything! Includes zero-code configs for Apache Solr, ChatGPT, Elastic Search, OpenSearch, PostgreSQL, Google BigQuery, RequestsGet, Google PSE, NLResearch.com, Miro & more! SWIRL adapts and distributes queries to anything with a search API - search engines, databases, noSQL engines, cloud/SaaS services etc - and uses AI (Large Language Models) to re-rank...
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  • 19
    git-delete-merged-branches

    git-delete-merged-branches

    Command-line tool to delete merged Git branches

    ... Git hosting. Takes safety seriously. Deletion is a sharp knife that requires care. While git reflog would have your back in most cases, git-delete-merged-branches takes safety seriously. git push is used with --force-with-lease so if the server and you have a different understanding of that branch, it is not deleted. There is no use of os.system or shell code to go wrong.
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  • 20
    LXGW WenKai

    LXGW WenKai

    An open-source Chinese font derived from Fontworks' Klee One

    An open-source Chinese font derived from Fontworks' Klee One. In December 2020, the famous Japanese font manufacturer FONTWORKS released 7 open source Japanese fonts on GitHub , namely Train, Klee, Stick, Rock-n-Roll, Reggae, Rampart and DotGothic16. The seven open-source Japanese fonts have their own characteristics, and among these seven fonts, Klee has the largest number of characters. This is a Japanese textbook style font, which has the characteristics of imitating Song and italics, and...
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  • 21
    Qiling

    Qiling

    Qiling Advanced Binary Emulation Framework

    Cross-platform and multi-arch ultra lightweight emulator. Supported OS: Linux, MacOS, Windows, FreeBSD, DOS and UEFI. Support Arch: x86(16/32/64), ARM(64) MIPS, EVM and WASM. It also support Linux Kernel Module(.ko) , Windows Driver(.sys) and MacOS Kernel(.kext) via Demigod. Binary instrumentation and API are Qiling Framework's main focus and priority. It is designed for reverse engineers - thus there is no need to rebuild another sand boxing tool. Using Qiling Framework saves you time. The...
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  • 22
    Asteroid

    Asteroid

    The PyTorch-based audio source separation toolkit for researchers

    The PyTorch-based audio source separation toolkit for researchers. Pytorch-based audio source separation toolkit that enables fast experimentation on common datasets. It comes with a source code thats supports a large range of datasets and architectures, and a set of recipes to reproduce some important papers. Building blocks are thought and designed to be seamlessly plugged together. Filterbanks, encoders, maskers, decoders and losses are all common building blocks that can be combined...
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  • 23
    Determined

    Determined

    Determined, deep learning training platform

    The fastest and easiest way to build deep learning models. Distributed training without changing your model code. Determined takes care of provisioning machines, networking, data loading, and fault tolerance. Build more accurate models faster with scalable hyperparameter search, seamlessly orchestrated by Determined. Use state-of-the-art algorithms and explore results with our hyperparameter search visualizations. Interpret your experiment results using the Determined UI and TensorBoard...
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  • 24
    Datasets

    Datasets

    Hub of ready-to-use datasets for ML models

    Datasets is a library for easily accessing and sharing datasets, and evaluation metrics for Natural Language Processing (NLP), computer vision, and audio tasks. Load a dataset in a single line of code, and use our powerful data processing methods to quickly get your dataset ready for training in a deep learning model. Backed by the Apache Arrow format, process large datasets with zero-copy reads without any memory constraints for optimal speed and efficiency. We also feature a deep integration...
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  • 25
    PyG

    PyG

    Graph Neural Network Library for PyTorch

    ... graph learning via Quiver, a large number of common benchmark datasets (based on simple interfaces to create your own), the GraphGym experiment manager, and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour).
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