Search Results for "ekho-data" - Page 3
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Showing 205 open source projects for "ekho-data"
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1
PyExcelerate
Accelerated Excel XLSX Writing Library for Python 2/3
Accelerated Excel XLSX writing library for Python. PyExcelerate is a Python for writing Excel-compatible XLSX spreadsheet files, with an emphasis on speed. -
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Barfi
A Python visual Flow Based Programming library
...Firstly, each Block has Input and Output interfaces that link to other Blocks. Each Block can carry an executable function, that is specified by the user. This function can access/get data from the Input interface, perform computations or calculations, and set the Output interface. In general, Barfi is an abstraction of Graphical Programming, Flow-Based Programming, or Node programming. Where the Block is synonymous to a Node, and a Link (connection) is synonymous with an Edge. There are many ways to call this, each serving a specific need or a philosophy. -
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Stanza
Stanford NLP Python library for many human languages
...The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. Stanza is built with highly accurate neural network components that also enable efficient training and evaluation with your own annotated data. -
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Python-Spider
Python3 web crawler practice
Python-Spider is a repository intended to teach or provide examples for writing web spiders / crawlers in Python — part of a broader learning and resource collection by its author. The code and documentation are oriented toward beginners or intermediate learners who want to learn how to fetch, parse, and extract data from websites programmatically. As part of the author’s public learning-path repositories, python-spider likely includes examples of HTTP requests, HTML parsing, maybe concurrency or scheduling to crawl multiple pages, and techniques to handle common web-scraping issues. For people wanting to get hands-on with building scrapers, collecting data, or learning how to navigate web programming in Python, this repository acts as a didactic reference or starting point. ... -
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zpdf
Zero-copy PDF text extraction library written in Zig
zpdf is a high-performance PDF text extraction library written in Zig that focuses on speed, low overhead, and modern parsing techniques. It leans heavily on memory-mapped file reading and zero-copy patterns where possible, so it can scan large PDFs without repeatedly copying data around in memory. The library supports streaming extraction using efficient arena allocation, making it well suited for workloads that need to process big documents quickly or in batches. It implements multiple PDF decompression filters and handles common font encoding pathways, which are essential for turning raw PDF content streams into readable text. ... -
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Papis
Powerful and highly extensible command-line based document
...With Papis, you can search your library for books and papers, add documents and notes, import and export to and from other formats, and much much more. Papis uses a human-readable and easily hackable .yaml file to store each entry's bibliographical data. It strives to be easy to use while providing a wide range of features. And for those who still want more, Papis makes it easy to write scripts that extend its features even further. -
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RecBole
A unified, comprehensive and efficient recommendation library
A unified, comprehensive and efficient recommendation library. We design general and extensible data structures to unify the formatting and usage of various recommendation datasets. We implement more than 100 commonly used recommendation algorithms and provide formatted copies of 28 recommendation datasets. We support a series of widely adopted evaluation protocols or settings for testing and comparing recommendation algorithms. -
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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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Comprehensive Python Cheatsheet
Comprehensive Python Cheatsheet
...The project is designed to help developers quickly recall language features without digging through full documentation, making it especially useful for both beginners and experienced programmers. It covers a broad range of topics including data structures, control flow, functions, object-oriented programming, standard library usage, and common patterns. The repository includes both web and printable versions, allowing users to access the material in multiple formats depending on their workflow. Because it is continuously maintained, the cheatsheet reflects modern Python usage and practical conventions. ... -
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Tunix
A JAX-native LLM Post-Training Library
...It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation, letting practitioners swap components without rewriting the whole stack. Examples and reference configs demonstrate end-to-end runs for common model families, helping teams reproduce baselines before customizing. Tunix also leans into research ergonomics: logging, checkpointing, and metrics are built in, and the code is written to be hackable rather than monolithic. ... -
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WTForms
A flexible forms validation and rendering library for Python
...Flask-WTF integrates with the Flask framework. It can automatically load data from the request, uses Flask-Babel to translate based on user-selected locale, provides full-application CSRF, and more. -
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mosdepth
fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing
mosdepth is a fast BAM/CRAM depth calculation tool for genomic data, allowing efficient computation of sequencing coverage. -
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Homemade Machine Learning
Python examples of popular machine learning algorithms
homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. It is well suited for learners who want to move beyond library usage to understand how algorithms operate internally—how cost functions, gradients, updates and predictions work. -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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Albumentations
Fast image augmentation library and an easy-to-use wrapper
...Albumentations supports different computer vision tasks such as classification, semantic segmentation, instance segmentation, object detection, and pose estimation. Albumentations works well with data from different domains: photos, medical images, satellite imagery, manufacturing and industrial applications, Generative Adversarial Networks. Albumentations can work with various deep learning frameworks such as PyTorch and Keras. -
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained inspection and modification after training. ... -
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PyOpenCL
OpenCL integration for Python, plus shiny features
...PyOpenCL also includes convenient features for managing memory, compiling kernels, and interfacing with NumPy, making it a preferred choice in scientific computing, data analysis, and machine learning workflows that demand acceleration. -
18
jlens
Companion code for the global workspace interpretability paper
...Interactive layer-by-position views reveal how token rankings evolve across the network and compare them with the model’s final output. It supports open-weight Hugging Face decoder models, with Qwen used in the included examples. The repository also provides synthetic evaluation data and an end-to-end notebook, but it is not maintained. -
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DeepXDE
A library for scientific machine learning & physics-informed learning
DeepXDE is a library for scientific machine learning and physics-informed learning. DeepXDE includes the following algorithms. Physics-informed neural network (PINN). Solving different problems. Solving forward/inverse ordinary/partial differential equations (ODEs/PDEs) [SIAM Rev.] Solving forward/inverse integro-differential equations (IDEs) [SIAM Rev.] fPINN: solving forward/inverse fractional PDEs (fPDEs) [SIAM J. Sci. Comput.] NN-arbitrary polynomial chaos (NN-aPC): solving... -
20
DGL
Python package built to ease deep learning on graph
...We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks. -
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go1pylib
go1pylib is a Python library designed to control the Go1 robot
go1pylib is a Python library designed to control the Go1 robot by Unitree Robotics. It provides an easy-to-use interface for robot movement, state management, collision avoidance, battery monitoring, and MQTT communication. Ideal for research and robotics development. -
22
segyio
Fast Python library for SEGY files
Segyio is a small LGPL-licensed C library for easy interaction with SEG-Y and Seismic Unix formatted seismic data, with language bindings for Python and Matlab. Segyio is an attempt to create an easy-to-use, embeddable, community-oriented library for seismic applications. Features are added as they are needed; suggestions and contributions of all kinds are very welcome. -
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DeepSeed
Deep learning optimization library making distributed training easy
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. With just a single GPU, ZeRO-Offload of DeepSpeed can train models with over 10B parameters, 10x bigger than the state of arts, democratizing multi-billion-parameter model training such that many deep learning scientists can explore bigger and better models. ... -
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LangExtract
A Python library for extracting structured information
LangExtract is a Python library developed by Google that leverages large language models (LLMs) to extract structured information from unstructured text—such as clinical notes, research papers, or literary works—based on user-defined instructions. It is designed to transform free-form text into reliable, schema-constrained data while maintaining traceability back to the source material. Each extracted entity is precisely grounded in its original context, allowing visual inspection and validation via automatically generated interactive HTML visualizations. LangExtract supports a wide range of models, including Google Gemini, OpenAI GPT, and local LLMs via Ollama, making it adaptable to different deployment environments and compliance needs. ... -
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peepDB
CLI tool and python library to inspect databases fast
peepDB is an open-source command-line tool and Python library designed for developers and database administrators who need a fast and efficient way to inspect their database tables without writing SQL queries. With support for MySQL, PostgreSQL, and MariaDB, peepDB is lightweight, secure, and incredibly easy to use.