9 مستودعات
Mechanisms for applying updates based on specific criteria or business logic.
Distinguishing note: Focuses on conditional record modification rather than general data updates.
Explore 9 awesome GitHub repositories matching data & databases · Conditional Data Operations. Refine with filters or upvote what's useful.
Qdrant is a high-performance vector similarity database designed to store, index, and search high-dimensional vectors alongside structured metadata. It functions as a distributed search engine that manages large-scale data clusters, providing low-latency retrieval and complex filtering capabilities. The system is built to serve as a specialized middleware layer, connecting machine learning pipelines and AI agents to persistent storage for intelligent information retrieval and recommendation tasks. The platform distinguishes itself through advanced retrieval techniques, including support for h
Modifies records only when they match specific criteria to maintain accuracy and consistency.
This project is a reactive, offline-first NoSQL database engine designed for JavaScript applications. It provides a robust framework for managing application state by synchronizing data across browsers, mobile devices, and server-side runtimes. By treating local storage as the primary source of truth, it enables applications to remain functional without network connectivity, automatically reconciling changes with remote backends once a connection is restored. The database distinguishes itself through a modular architecture that supports cross-environment synchronization and high-performance d
Provides conditional logic for document modifications to ensure granular business rules during data synchronization.
This project is a feature-rich Go client library designed for interacting with Redis. It serves as a comprehensive interface for managing remote data stores, enabling developers to execute standard database commands, handle complex data structures, and perform asynchronous operations within Go applications. The library distinguishes itself through its support for advanced Redis capabilities, including connection pooling, pipelining, and transactional integrity. It provides specialized primitives for managing distributed clusters, including automated topology updates and request routing to sha
Enables conditional data writes to prevent race conditions during creation or registration.
General purpose redis client
Compare a stored value against a provided value and perform a subsequent operation only when they match.
pyinfra is an agentless infrastructure automation framework that turns declarative Python code into idempotent shell commands to manage servers, containers, and local machines over SSH without requiring any pre-installed software on target hosts. It operates by comparing the desired state of a system against its current state, using a dry-run simulation mode to preview changes and a fact-based conditional execution engine to gather host attributes at runtime and control which operations run. The tool compiles Python operations into optimized shell commands and executes them in parallel across
Provides conditional operation gating based on runtime callable conditions.
pyinfra is a Python-based infrastructure automation framework that turns Python code into shell commands for managing servers, Docker containers, and local machines. It operates as a declarative, idempotent deployment tool, applying desired system states by comparing target configurations against current states and making only the necessary changes. The framework provides a connector-based transport abstraction that unifies SSH, Docker, and local execution behind a common interface, with a parallel execution engine that manages concurrent operations across hosts. The tool distinguishes itself
Assigns a human-readable name to an operation and skips it unless user-supplied conditions return true.
r4ds هو منهج لعلوم البيانات ومورد تعليمي مصمم لإتقان لغة البرمجة R. يوفر مسار تعلم منظماً للعملية الشاملة لاستيراد البيانات، وتنظيمها، وتحويلها، وتصورها. يركز المشروع على دليل علوم البيانات القابل للتكرار ومنهج شامل لمعالجة البيانات. يتضمن دروساً تعليمية متخصصة حول قواعد الرسومات لتصور البيانات الطبقي والمنشورات التقنية التي تم إنشاؤها باستخدام Quarto والتي تمزج بين الكود القابل للتنفيذ والنثر السردي. تغطي المادة مجموعة واسعة من القدرات التحليلية، بما في ذلك استيعاب البيانات من مصادر متنوعة، وربط البيانات العلائقية، وإدارة المتغيرات الفئوية. كما تتناول تنظيف البيانات، والنمذجة الرياضية، وإنشاء تقارير وعروض تقديمية احترافية متعددة التنسيقات. يركز المنهج على التطبيق العملي للبرمجة الوظيفية ومبادئ البيانات المرتبة (Tidy data) لإنشاء تحليلات شفافة وقابلة للتكرار.
Modifies dataset values based on logical criteria to perform conditional data transformations.
Strawberry هي مكتبة GraphQL آمنة من حيث النوع لـ Python تتيح تصميم المخططات باستخدام تعليقات النوع (type annotations) و dataclasses في Python. تعمل كخادم GraphQL غير متزامن ومحرك تنفيذ، مما يوفر جسرًا لعرض المخططات عبر أطر عمل الويب المتوافقة مع ASGI مثل FastAPI و Django و Flask و Litestar. ينفذ المشروع GraphQL Federation، مما يسمح بإنشاء مخططات وكيانات موزعة تندمج في مخطط فائق موحد عبر خدمات متعددة. كما يتضمن مجموعة أدوات مخصصة لمواصفات Relay، تدعم تحديد الكائنات عالميًا والترقيم القائم على الاتصال. يغطي إطار العمل مجموعة واسعة من القدرات، بما في ذلك تدفق البيانات في الوقت الفعلي عبر WebSockets و Server-Sent Events، ورسم خرائط نماذج Pydantic، وتوليد الكود التلقائي. يوفر أدوات متكاملة للأمان والمراقبة، مثل تحديد تعقيد الاستعلام، والتحكم في الوصول القائم على الأدوار، وتتبع مقاييس التنفيذ. يمكن للمطورين إنشاء نماذج أولية باستخدام خادم تطوير مدمج مع واجهة فحص مخطط تفاعلية.
Uses GraphQL directives to conditionally include, skip, or modify the evaluation of fields during request execution.
This utility is a command-line tool designed to automate volume leveling across audio and video collections. By leveraging external media processing libraries, it adjusts files to a consistent target loudness level, ensuring uniform playback without the need for manual volume adjustments. The tool distinguishes itself through a two-pass analysis workflow that measures loudness statistics before applying precise gain adjustments. It maintains the relative loudness relationships between tracks when processing collections, ensuring that the dynamic balance of a group of files remains intact. Use
Evaluates file metadata and loudness metrics against target thresholds to skip redundant re-encoding and optimize computational resources.