Search Results for "operator"
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Showing 31 open source projects for "operator"
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Kubernetes Operator Pythonic Framework
A Python framework to write Kubernetes operators in just a few lines
Kopf —Kubernetes Operator Pythonic Framework— is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). -
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Apache Airflow Provider
Great Expectations Airflow operator
...If your Airflow version is 2.1.0, and you want to install this provider version, first upgrade Airflow to at least version 2.1.0. Otherwise, your Airflow package version will be upgraded automatically, and you will have to manually run airflow upgrade db to complete the migration. This operator currently works with the Great Expectations V3 Batch Request API only. If you would like to use the operator in conjunction with the V2 Batch Kwargs API, you must use a version below 0.1.0. This operator uses Great Expectations Checkpoints instead of the former ValidationOperators. Because of the above, this operator requires Great Expectations >=v0.13.9, which is pinned in the requirements.txt starting with release 0.0.5. -
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BigMac
An open-source toolkit for BigMac-style pipeline-parallel training
...Profiling tools also expose per-operator traces for diagnosing pipeline performance before or during experiments. -
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Telegram-MedicalBot
User support system in Telegram
...The system can assist operators with answers drawn from a local knowledge base and optional AI-generated suggestions. Aiogram provides the Telegram integration, while a local database stores users, roles, documents, and operational state. Administrator and operator roles are synchronized at startup, and middleware records activity while enforcing user-consent rules. The project is structured as a modular support platform rather than a fully autonomous medical adviser, keeping human operators involved in the response process. -
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The Reactive Extensions for Python
Reactive extensions for Python
RxPY is a library for composing asynchronous and event-based programs using observable collections and pipable query operators in Python. A library for composing asynchronous and event-based programs using observable collections and query operator functions in Python. Reactive Extensions for Python (RxPY) is a set of libraries for composing asynchronous and event-based programs using observable sequences and pipable query operators in Python. Using Rx, developers represent asynchronous data streams with Observables, query asynchronous data streams using operators, and parameterize concurrency in data/event streams using Schedulers. ... -
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glom
Python's nested data operator
glom is a Python library and command-line tool for accessing, restructuring, and transforming nested data. It is designed for real-world data structures where dictionaries, objects, and lists are deeply nested and difficult to handle cleanly. Developers can use path-based access to retrieve values without writing long chains of fragile indexing code. The library also provides readable error messages, which makes debugging broken paths much easier. Its declarative specification style lets... -
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Claude-Red
claude-red is a curated library of offensive security skills
...Users can install the complete collection or select individual categories. The project is intended for legitimate red-team engagements, bug-bounty triage, CTF practice, operator training, and security research. Its modular structure makes the collection expandable as new methodologies and categories are added. -
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Transcrypt
Python 3.7 to JavaScript compiler
Python in the browser, precompiled for speed. Transcrypt started out as a personal repo, owned by Jacques de Hooge. As the project caught on and the number of people contributing issues, ideas and code grew, the repo was transferred to the QQuick organization, to be able to form a developer team on GitHub. There's a simple parallel between the Python and the JavaScript code. In combination with the use of source maps, this enables efficient debugging. Also, code can be tested from the... -
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xFormers
Hackable and optimized Transformers building blocks
...One of its key goals is efficient attention: it supports dense, sparse, low-rank, and approximate attention mechanisms (e.g. FlashAttention, Linformer, Performer) via interchangeable modules. The library includes memory-efficient operator implementations in both Python and optimized C++/CUDA, ensuring that performance isn’t sacrificed for modularity. It also integrates with PyTorch seamlessly so you can drop in its blocks to existing models, replace default attention layers, or build new architectures from scratch. xformers includes training, deployment, and memory profiling tools. -
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gusty
Making DAG construction easier
gusty allows you to control your Airflow DAGs, Task Groups, and Tasks with greater ease. gusty manages collections of tasks, represented as any number of YAML, Python, SQL, Jupyter Notebook, or R Markdown files. A directory of task files is instantly rendered into a DAG by passing a file path to gusty's create_dag function. gusty also manages dependencies (within one DAG) and external dependencies (dependencies on tasks in other DAGs) for each task file you define. All you have to do is... -
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fvcore
Collection of common code shared among different research projects
...Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. A standout capability is FLOP and activation counting, which analyzes arbitrary PyTorch graphs to report cost by operator and by module for precise profiling. The file I/O layer (PathManager) abstracts local/remote storage so the same code can read from disks, cloud buckets, or HTTP endpoints. Because it is small, stable, and well-tested, fvcore is frequently imported by projects like Detectron2 and PyTorchVideo to avoid duplicating infrastructure and to keep research repos. -
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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... -
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Thinc
A refreshing functional take on deep learning
Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy. We wrote the new version to let users compose,... -
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AAD-50
Zero-trust storage erasure. Hardware-verified data destruction.
AAD-50 is an open-source NVMe sanitization framework that closes a 15-year verification gap in Linux nvme-cli. The standard nvme sanitize command returns immediately after acceptance without confirming the drive actually completed the background erasure. AAD-50 fixes this by polling NVMe Log Page 0x81 (Sanitize Status) after every cycle and refusing to advance until SSTAT=0x1 confirms hardware completion. Implements a 50-cycle B→C→A phase matrix: 40 cycles NAND overwrite, 5 FTL block... -
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AWX
A web-based user interface built on top of Ansible
AWX provides a web-based user interface, REST API, and task engine built on top of Ansible. It is one of the upstream projects for Red Hat Ansible Automation Platform. Starting in version 18.0, the AWX Operator is the preferred way to install AWX. AWX can also alternatively be installed and run in Docker, but this install path is only recommended for development/test-oriented deployments, and has no official published release. Uses naming and structure consistent with the AWX HTTP API. Provides consistent output formats with optional machine-parsable formats. ... -
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Dominate
Dominate is a Python library for creating and manipulating HTML docs
...Dominate can also use keyword arguments to append attributes onto your tags. Most of the attributes are a direct copy from the HTML spec with a few variations. Through the use of the += operator and the .add() method you can easily create more advanced structures. By default, render() tries to make all output human readable, with one HTML element per line and two spaces of indentation. -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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Moriarty Project
Web-based OSINT tool for investigating phone number information
Moriarty Project is an open source web-based investigation tool designed to gather publicly available information about phone numbers. It allows users to input a phone number and analyze various details related to that number through multiple investigation features. It performs information gathering by scraping data from online sources to retrieve insights such as owner information, spam risk, and related web references. Users can select specific investigation features to run individually or... -
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Kopf
A Python framework to write Kubernetes operators
Kopf —Kubernetes Operator Pythonic Framework, is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). -
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Training Image Operators from Samples
Tools to train Image Operators automatically from a set of samples.
TRIOS - Training Image Operators from Samples is a set of tools to bring Image Processing closer to scientists in general. It is capable of estimating an operator between two images using only pairs of samples that contain an input image and the desired output. The operator is saved to a file and can be applied to any image. -
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littletable is a lightweight in-memory data manager of collections of Python objects, providing ORM-like access for querying and joining data using object attributes as pseudo-columns.
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Asterisk Monitor is a HTML interface that acts a operator pannel for asterisk to display user/peer status and calls. This uses a reverse AJAX, PHP and Python to originate, transfer and hangup calls, manage queues and meetme rooms.
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autodiff
Python class for automatic differentiation
Python automatic differentiation class for forward mode automatic differentiation using operator overloading and reimplemented math functions. Single and partial derivatives are supported. Supported operators: +, -, *, /, **, +=, -=, *=, /=, **= Available functions: sin, cos, tan, asin, acos, atan, sqrt, exp, log, log10, sinh, cosh, tanh, asinh, acosh, atanh See README file for usage examples.
