Search Results for "params-validate" - Page 2
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Showing 53 open source projects for "params-validate"
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Push Code. Get a Production URL. Done.Skip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Cut Your Data Warehouse Bill by 54%BigQuery delivers 54% lower TCO with serverless scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Universal Commerce Protocol
Specification and documentation for the Universal Commerce Protocol
...By standardizing how discovery, purchase, and post-purchase steps are represented, it helps reduce integration complexity and makes it easier for multiple parties to participate in the same end-to-end flow. UCP also supports reference implementations and samples so teams can validate behaviors, build clients, and test interoperability in realistic scenarios. -
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UCP Python SDK
The official Python SDK for UCP
...UCP itself is a modern, open-source standard that empowers seamless commerce interactions between platforms, AI agents, merchants, and payment providers without requiring bespoke integrations for every participant in the commerce ecosystem. This SDK provides Pydantic models for UCP schemas, making it easy for Python developers to construct, validate, and serialize protocol messages and data structures according to the UCP specification. By adhering to the official protocol standards, applications built on this SDK can participate in tasks like capability discovery, checkout flows, order management, and more, while remaining interoperable across different UCP implementations and surfaces. -
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EKS Best Practices
A best practices guide for day 2 operations
The Amazon EKS Best Practices Guide is a public repository containing comprehensive documentation and guidance for operating production-grade Kubernetes clusters on AWS’s managed service, Amazon EKS. Rather than a code library, it serves as a reference catalogue of patterns, anti-patterns, checklists and architectures across domains such as security, reliability, scalability, networking, cost optimization and hybrid cloud deployments. The repository is maintained by AWS but open to... -
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Double Conversion
Efficient binary-decimal & decimal-binary conversion routines for IEEE
...It is optimized for both speed and correctness, making it ideal for numerical computation libraries, serialization systems, and scripting engines. The codebase includes detailed documentation and comprehensive unit tests to validate correctness across various platforms. With flexible build options using SCons, CMake, or Bazel, Double Conversion integrates seamlessly into modern C++ development workflows. -
Go From Idea to Deployed AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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Mistral Finetune
Memory-efficient and performant finetuning of Mistral's models
mistral-finetune is an official lightweight codebase designed for memory-efficient and performant finetuning of Mistral’s open models (e.g. 7B, instruct variants). It builds on techniques like LoRA (Low-Rank Adaptation) to allow customizing models without full parameter updates, which reduces GPU memory footprint and training cost. The repo includes utilities for data preprocessing (e.g. reformat_data.py), validation scripts, and example YAML configs for training variants like 7B base or... -
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Prompt Declaration Language
Prompt Declaration Language is a declarative prompt programming lang
...Whether LLMs are used as coding assistants or software components, reliability remains an important concern. LLMs have a textual interface and the structure of useful prompts is not captured formally. Programming frameworks do not enforce or validate such structures since they are not specified in a machine-consumable way. The purpose of the Prompt Declaration Language (PDL) is to allow developers to specify the structure of prompts and to enforce it, while providing a unified programming framework for composing LLMs with rule-based systems. -
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MetricFlow
MetricFlow allows you to define, build, and maintain metrics in code
MetricFlow is an open-source semantic layer engine designed to help organizations define, manage, and query business metrics in a consistent, governed way. It works alongside a data stack—typically built with dbt—and allows you to express metrics as YAML‐based definitions tied to semantic models and dimension tables, rather than embedding logic ad-hoc across many dashboards or scripts. When a user or tool requests a metric (e.g., “monthly revenue by region”), MetricFlow generates optimized,... -
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Swiple
Swiple enables you to easily observe, understand, validate data
Swiple is an automated data monitoring platform that helps analytics and data engineering teams seamlessly monitor the quality of their data. With automated data analysis and profiling, scheduling and alerting, teams can resolve data quality issues before they impact mission critical resources. Experience hassle-free integration with Swiple's zero-infrastructure and zero-code setup. Seamlessly incorporate data quality checks into your existing workflows without any coding or infrastructure... -
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SQLBucket
Lightweight library to write, orchestrate and test your SQL ETL
SQLBucket is a lightweight framework to help write, orchestrate and validate SQL data pipelines. It gives the possibility to set variables and introduces some control flow using the fantastic Jinja2 library. It also implements a very simplistic unit and integration test framework where you can validate the results of your ETL in the form of SQL checks. With SQLBucket, you can apply TDD principles when writing data pipelines. -
Powerful App Monitoring Without Surprise BillsTired of monitoring tools that punish you for scaling? AppSignal offers transparent, predictable pricing with every feature unlocked on every plan. Track errors, monitor performance, detect anomalies, and manage logs across Ruby, Python, Node.js, and more. Trusted by developers since 2012 with free dev-to-dev support. No credit card required to start your 30-day trial.
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Auto-PyTorch
Automatic architecture search and hyperparameter optimization
While early AutoML frameworks focused on optimizing traditional ML pipelines and their hyperparameters, another trend in AutoML is to focus on neural architecture search. To bring the best of these two worlds together, we developed Auto-PyTorch, which jointly and robustly optimizes the network architecture and the training hyperparameters to enable fully automated deep learning (AutoDL). Auto-PyTorch is mainly developed to support tabular data (classification, regression) and time series... -
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miRPV
miRPV: An automated pipeline for miRNA Prediction and Validation in si
miRPV is an Automated tool that allows users to predict and validate microRNA from genome/gene sequence. System Requirement CPU: AMD64 (64bit) Memory: 2Gb RAM Storage: 5Gb Ubuntu 18.04 -
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Gluon CV Toolkit
Gluon CV Toolkit
GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection, semantic segmentation and pose estimation, to instance segmentation and video action recognition. ... -
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molten
A minimal, extensible, fast and productive framework
molten is a minimal, extensible, fast and productive framework for building HTTP APIs with Python. molten can automatically validate requests according to predefined schemas, ensuring that your handlers only ever run if given valid input. Schemas are PEP484-compatible, which means mypy and molten go hand-in-hand, making your code more easy to maintain. Schema instances are automatically serializable and you can pick and choose which fields to exclude from responses and requests. ... -
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NLP Architect
A model library for exploring state-of-the-art deep learning
...The library contains NLP/NLU-related models per task, different neural network topologies (which are used in models), procedures for simplifying workflows in the library, pre-defined data processors and dataset loaders and misc utilities. The library is designed to be a tool for model development: data pre-processing, build model, train, validate, infer, save or load a model. -
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Flasgger
Easy OpenAPI specs and Swagger UI for your Flask API
...Flasgger also comes with SwaggerUI embedded so you can access it and visualize and interact with your API resources. Flasgger also provides validation of the incoming data, using the same specification it can validate if the data received as a POST, PUT, PATCH is valid against the schema defined using YAML, Python dictionaries or Marshmallow Schemas. Flasgger can work with simple function views or MethodViews using docstring as specification, or using @swag_from decorator to get specification from YAML or dict and also provides SwaggerView which can use Marshmallow Schemas as specification. ... -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference... -
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SkyWater PDK
Open source process design kit for usage with SkyWater Technology
The SkyWater PDK is the first broadly available open-source process design kit for a commercial-grade CMOS node, enabling researchers, startups, and students to design real ASICs without proprietary NDAs. It provides the essential artifacts for digital and analog flows: SPICE models, DRC/LVS rules, extraction decks, and technology files for open tools like Magic and KLayout. Standard-cell libraries and IO pads are included so digital designers can use open synthesis and place-and-route to... -
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cocoNLP
A Chinese information extraction tool
cocoNLP is a lightweight natural-language processing toolkit geared toward practical information extraction from raw text, especially for Chinese and mixed Chinese–English content. Instead of requiring a heavy pipeline, it focuses on quick wins such as extracting names, places, organizations, emails, phone numbers, and dates directly from unstructured sentences. The project blends pattern-based methods with NLP heuristics, giving developers dependable results for real-world texts like chats,... -
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Optimized Storage for temporal Data
open Optimized Storage of time series data
...Uses any kind of relational database. Cross plateform with multiple languages (C++, C#, Java). Conditional storage based on value variation : DeltaValue and DeltaTime params. Get back data without losts. -
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Skater
Python library for model interpretation/explanations
...The concept of model interpretability in the field of machine learning is still new, largely subjective, and, at times, controversial. Model interpretation is the ability to explain and validate the decisions of a predictive model to enable fairness, accountability, and transparency in algorithmic decision-making. The library has embraced object-oriented and functional programming paradigms as deemed necessary to provide scalability and concurrency while keeping code brevity in mind. -
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BlockSparse
Efficient GPU kernels for block-sparse matrix multiplication
The blocksparse repository provides efficient GPU kernels (TensorFlow custom ops) for block-sparse matrix multiplication and convolution operations. The idea is to exploit block-level sparsity — i.e. treat matrices or weight tensors as composed of blocks, many of which may be zero or unused — to save compute and memory when sparsity patterns are structured. This is particularly useful in models like Sparse Transformers, where attention matrices or intermediate layers may adopt block-sparse... -
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Algorithms in Python
Data Structures and Algorithms in Python
Algorithms in Python is a collection of algorithm and data structure implementations (primarily in Python) meant to serve as both learning material and reference code for engineers. It includes code for graph algorithms, heap data structures, stacks, queues, and more — each implemented cleanly so learners can trace logic and adapt for their problems. The repository is particularly useful for people preparing for competitive programming, job interviews, or building a foundational... -
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...The researchers can verify the correctness of their new Smart Grid applications on a few devices and then use SCORE for large scale evaluation and performance prediction studies.Also, they can use SCORE to evaluate and validate the design and performance of their Smart Grid applications before large-scale deployment.
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Python XML Validator
Validates XML against xml schema. Based on Python lxml module.
Validates XML against xml schema. Based on Python lxml module. -
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EnigmaGPG Community
Sending encrypted data through internet web applications.
Enigma GPG Community allows you to encrypt / sign text and attachments using plugins in browsers, to send encrypted information via any Internet application that can only be understood by the intended recipient ensuring the authenticity, privacy and confidentiality of messages between the sender and receiver . Note the utility that can achieve this project because it aims to meet the global need for privacy on the web. Also applies to any web application that allows text input by the user...
