hongbomiao.com
A personal research and development (R&D) lab that facilitates the sharing of knowledge.
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hongbomiao.com is a personal research and development (R&D) lab that facilitates the sharing of knowledge. The repository covers a wide range of topics including web development, mobile development, desktop applications, API servers, cloud native technologies, data processing, machine learning, computer vision, embedded systems, simulation, database management, data cleaning, data orchestration, testing, ops, authentication, authorization, security, system tools, reverse engineering, Ethereum, hardware, network, guidelines, design, bots, and more. It provides detailed information on various tools, frameworks, libraries, and platforms used in these domains.
README:
A personal research and development (R&D) lab that facilitates the sharing of knowledge.
The diagram illustrates the repository's architecture, which is considered overly complex. It is essential to thoroughly understand the tradeoffs associated with before onboarding any technology into your project.
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- React - Web framework
- Vite - JavaScript build tool and development server
- TanStack Query - Hooks for fetching, caching and updating asynchronous data
- RxJS - Asynchronous programming with observable streams
- graphql-tag - GraphQL query parsing
- Bulma - CSS framework
- PurgeCSS - Unused CSS removing
- Jest - Unit testing, snapshot testing
- React Testing Library - React component testing
-
Storybook - Visual testing
- Chromatic - Storybook reviewing
- Cypress - End-to-end testing
- Lighthouse CI - Performance, accessibility, search engine optimization (SEO), progressive web app (PWA) analysis
- Sentry - Error tracking
- Report URI - Security reporting
- Google Tag Manager - Tag management
- Google Analytics - Web analytics
- FullStory - Experience analytics, session replay, heatmaps
- Namecheap - Domain
- Cloudflare - DNS, DDoS protection, CDN
- HTTP/3 Check - HTTP/3 checking
- hstspreload.org - HSTS checking
- Mozilla HTTP Observatory - Security monitoring
- UptimeRobot - Uptime monitoring
- SwiftUI - UI framework
- XCTest - Unit testing, performance testing
- Slather - Code coverage reports generating
- AndroidX - Android Jetpack
- JUnit - Unit testing, instrumented testing
- Expo - Universal native apps making platform
- React Native - Mobile application framework
- UI Kitten - UI library
- React Native Testing Library - React Native component testing
- Qt Quick - Cross-platform application development framework
- QML - Qt modeling language
- axum - Web framework
- Tokio - Asynchronous runtime
- tower-http - HTTP middleware and utilities (compression, CORS, timeout, trace)
- tower-governor - Rate limiting
- async-graphql - GraphQL (query, mutation, subscription, depth limit, complexity limit)
- tch-rs - Rust LibTorch (C++ API of PyTorch) bindings
- opencv-rust - Rust OpenCV bindings
- Tracing - Tracing
- dotenvy - Environment variables loading
- Gin - Web framework
- gRPC - Remote procedure call (RPC) framework
- graphql-go - GraphQL
- jwt-go - JSON Web Token (JWT)
- gin-contrib/cors - Cross-Origin Resource Sharing (CORS)
- opa - Open Policy Agent
- dgo - Dgraph client
- minio-go - MinIO client
- go-redis - Redis client
- pgx - PostgreSQL driver
- Resty - HTTP client
- Squirrel - SQL query builder
- apm-agent-go - Application performance monitoring (APM) agent
- OpenTelemetry Go - OpenTelemetry
- Prometheus Go - Prometheus
- Testify - Unit testing
- GoDotEnv - Environment variables loading
- jsonparser - JSON parser
- zerolog - Logging
- FastAPI - Web framework
- Uvicorn - Asynchronous server gateway interface (ASGI) server
- asyncpg - PostgreSQL client
- Tenacity - General-purpose retrying library
- pytest - Unit testing
- pydantic - Data validation
- HTTPX - HTTP client
- pypdf - PDF library
- Poe the Poet - Task runner
- uv - Python package management
- SWC - JavaScript compiler
- Express - Web framework
-
GraphQL.js, graphql-http - GraphQL
- graphql-ws, graphql-subscriptions - GraphQL subscription
- graphql-upload - GraphQL upload
- graphql-shield - GraphQL permissions
- graphql-depth-limit - GraphQL depth limit
- graphql-query-complexity - GraphQL complexity limit
- DataLoader - Batching and caching
- Knex.js - SQL query builder
- node-postgres - PostgreSQL client
- ioredis - Redis client
- rate-limiter-flexible - Rate limiting
- expressjs/cors - Cross-Origin Resource Sharing (CORS)
- jsonwebtoken, express-jwt - JSON Web Token (JWT)
- bcrypt - Password hashing
- axios - HTTP client
-
Helmet - HTTP header
Content-Security-Policy,Referrer-Policy,Strict-Transport-Security,X-Content-Type-Options,X-DNS-Prefetch-Control,X-Download-Options,X-Frame-Options,X-Permitted-Cross-Domain-Policies,X-XSS-Protection -
Report To - HTTP header
Report-To -
Network Error Logging - HTTP header
NEL -
express-request-id - HTTP header
X-Request-ID -
response-time - HTTP header
X-Response-Time - connect-timeout - Request timeout
- request-ip - IP address retrieving
- Terminus - Health check and graceful shutdown
- pino - Logging
- dotenv-flow - Environment variables loading
- Stryker - Mutation testing
- SuperTest - HTTP testing
- autocannon - HTTP benchmarking
- Clinic.js - Performance profiling
- Node.js - JavaScript runtime
- npm - JavaScript package management
- Sealed Secrets - Kubernetes secret encrypting
- ExternalDNS - Kubernetes services and Ingresses exposing
- cert-manager - Kubernetes X.509 certificate management
-
Hasura - GraphQL Engine
- hasura-metric-adapter - Hasura GraphQL Engine metric adapter
- Linkerd - Service mesh
- Caddy - Web server, reverse proxy, load balancer
- Traefik - Web server, reverse proxy, load balancer
- nginx - Web server, reverse proxy, load balancer
- Metrics Server - Kubernetes metrics
- Elastic APM - Application performance monitoring
- OpenTelemetry - Observability framework
- Jaeger - Distributed tracing system
- Netdata - Distributed monitoring platform
- Telegraf - Plugin-driven server agent
- Thanos - Highly available Prometheus setup with long-term storage capabilities
- Pixie - Observability tool for Kubernetes applications
- Docker - Container
- Skaffold - Continuous development for Kubernetes applications
- Multipass - VM management
- Locust - Load testing
- Cloudflare Tunnel - Tunneling
- Vertical Pod Autoscaler - Kubernetes vertical pod autoscaler
- K3s - Lightweight Kubernetes
- containerd - Container runtime
- Kubernetes - Container-orchestration system
- Trino - Distributed SQL query engine
-
PostgreSQL - Object-relational database
- Postgres Operator - PostgreSQL high-availability (HA) template
- Postgres Operator - PostgreSQL cluster provisioning
- pgAdmin - PostgreSQL management tool
-
MySQL - Relational database
- MariaDB - Fork of MySQL
- Hydra - Column-oriented SQL database
- ClickHouse - Column-oriented SQL database
- YugabyteDB - Distributed SQL database
- TimescaleDB - Time-series SQL database
-
InfluxDB - Time-series database
- InfluxDB Enterprise - Distributed time-series database
- Prometheus - Time-series database
- Loki - Log aggregation system
- DuckDB - Embedded analytical SQL database
- Apache Cassandra - Distributed wide-column NoSQL database
- Qdrant - Distributed vector database
- Chroma - Distributed vector database
- Dgraph - Distributed graph database
-
Elasticsearch - Distributed document-oriented search engine
- Kibana - Elasticsearch visualization
-
Redis - Distributed in-memory key–value database
- KeyDB - Multithreaded fork of Redis
- MinIO - Object storage
- Apache ZooKeeper - Distributed coordination system
-
Apache Hadoop - Software utility collection
- Apache Hadoop HDFS (Distributed File System) - Distributed file system
- Apache Hadoop YARN (Yet Another Resource Negotiator) - Resource management and job scheduling framework
- Apache Hadoop MapReduce - Data processing framework
- Apache Hive - Distributed data warehousing and SQL-like query language system built on top of Apache Hadoop
- Delta Lake - Data lakehouse
- Snowflake - Data warehouse
- golang-migrate/migrate - Database migrations
- Airbyte - Data integration
- Vector - Log collector
- Fluent Bit - Log collector
- Prefect - Orchestration platform
- Apache Airflow - Orchestration platform
- Temporal - Orchestration platform
-
Apache Spark - Data processing framework
- Spark ML - Spark machine learning
- pyspark - Spark API library
- Delight - Spark UI and history server
- Apache Sedona - Spatial data processing framework
-
Apache Flink - Data processing framework
- flink-streaming-java - Flink
- flink-connector-twitter - Flink Twitter connector
- flink-connector-jdbc - Flink JDBC Connector
- flink-connector-redis - Flink Redis connector
-
Apache Kafka - Distributed event streaming platform
- Client
-
librdkafka - Kafka C/C++ client
- libserdes - AVRO serialization and deserialization
- confluent-kafka - Kafka Python client
- rust-rdkafka - Kafka Rust client
-
librdkafka - Kafka C/C++ client
- Schema registry
- Confluent Schema Registry - Schema Registry
- Apicurio Registry - Schema Registry
- Replication
- MirrorMaker - Data replicating
- Connector
- Debezium - Distributed change-data-capture (CDC) platform
- debezium-connector-postgres - PostgreSQL CDC source connector
- confluentinc-kafka-connect-jdbc - JDBC source and sink connector
- confluentinc-kafka-connect-s3 - Amazon S3 Sink Connector
- snowflake-kafka-connector - Snowflake Sink Connector
- kafka-connect-elasticsearch - Elasticsearch sink connector
- http-connector-for-apache-kafka - HTTP sink connector
- kafka-connect-avro-converter - Confluent Avro converter
- apicurio-registry-distro-connect-converter - Apicurio Avro converter
- Management tool
- Redpanda Console - Kafka management
- AKHQ - Kafka management
- UI for Apache Kafka - Kafka management
- topicctl - Kafka topic management
- Client
- dbt - Data transformation
- Grafana - Data visualization
- Metabase - Data visualization
- Apache Superset - Data visualization
- Tableau - Data visualization
- IADS - Data visualization
- NumPy - Scientific computing library
-
pandas - Data analysis library
- GeoPandas - Spatial data library
- AWS SDK for pandas - pandas integration with AWS services
- Modin - pandas workflows scaling
- cuDF - GPU-powered DataFrame library
- Polars - Multithreaded, vectorized, query-engine-powered DataFrame library
-
JupyterLab - Web-based interactive computing platform
- nb-clean - Jupyter notebook cleaning
- Databricks - Unified data analytics platform
- Palantir - Data integration and analysis platform
- Data drift
- Covariate shift
- Concept drift
- Univariate drift
- Jensen-Shannen distance - categorical and continuous
- Hellinger - categorical and continuous
- Wasserstein - continuous
- Kolgomorov-Smirnov - continuous
- L-infinity - categorical
- Chi2 - categorical
- Multivariate drift
- Performance estimation
- Direct loss estimation (DLE) - Regression
- Mean absolute error (MAE)
- Mean absolute percentage error (MAPE)
- Mean squared error (MSE)
- Root mean squared error (RMSE)
- Mean squared logarithmic error (MSLE)
- Root mean squared logarithmic error (RMSLE)
- Confidence-based performance estimation (CBPE)- Classification
- Confusion matrix
- ROC AUC
- Accuracy
- Precision
- Recall
- F1 score
- Direct loss estimation (DLE) - Regression
- Regression analysis
- Linear regression
- Polynomial regression
- Lasso regression (L1 regularization)
- Ridge regression (L2 regularization)
- Elastic net (L1 + L2 regularization)
- Logistic regression
- Bayesian regression
- Stepwise regression
- Robust regression
- Ecological regression
- Quantile regression
- Ensemble learning
- Bagging
- Boosting
- Adaptive boosting
- AdaBoost
- Gradient boosting
- CatBoost
- XGBoost
- Adaptive boosting
- Stacking
-
PyTorch - Machine learning
- PyTorch Geometric - PyTorch geometric deep learning extension
- TorchServe - PyTorch models serving
-
Flax - Neural network for JAX
- Optax - Gradient processing and optimization for JAX
- Lightning - Deep Learning framework
- NeuralForecast - Neural forecasting
- Transformers - Machine learning models
- Gradio - Machine learning web application building
- Streamlit - Data web application building
- AutoGluon - Automated machine learning (AutoML) library
- OGB - Open graph benchmark
- Rasa - Machine learning framework for automated text and voice-based conversations
- CML - Continuous machine learning
- DVC - Data version control
- Feast - Feature store
- Kubeflow - Machine learning platform
- MLflow - Machine learning experiment tracking
- Weights & Biases - Machine learning experiment tracking
- NVIDIA Data Loading Library (DALI) - GPU-accelerated data loading and preprocessing pipeline
- NVIDIA Triton Inference Server - Inference server
- LlamaIndex - LLM application framework
- LangChain - LLM application framework
- MinerU - PDF parsing
- Docling - LLM application framework
- GPT4All - Local LLM models
- LiteLLM - LLM gateway
-
Open WebUI - AI chat interface
- Open WebUI Pipelines - OpenAI API plugin framework
- OpenCV - Computer vision library
- supervision - Computer vision library
- Ultralytics YOLOv8 - Object detection model
- Open3D - 3D data processing
- PyVista - 3D plotting and mesh analysis
- Visualization Toolkit (VTK) - Image processing, 3D graphics, volume rendering and visualization
- CUDA - Parallel computing
- Julia - High-performance dynamic programming language
- JAX - High-performance numerical computing
-
AWS ParallelCluster - High performance computing (HPC) cluster management
- NICE DCV - Remote display
- AWS Batch - Batch computing
- Open MPI - High-performance computing (HPC) library
- Slurm - Workload management
- Amazon EC2 - Cloud computing
- Ray - Distributed computing framework
- SkyPilot - Sky computing
- Qiskit - Quantum computing
-
Amazon Web Services
- Amazon Athena - Serverless query service
- Amazon Bedrock - Generative AI model service
- Amazon CloudTrail - Data governance, data compliance, data auditing
- Amazon DynamoDB - NoSQL database
- Amazon EBS - Block storage
- Amazon EC2 - Cloud computing
- Amazon ECR - Container registry
- Amazon EKS - Kubernetes
- Amazon EMR - Big data platform
- Amazon EventBridge - Serverless event bus
- Amazon MSK - Kafka
- Amazon RDS - Relational database service
- Amazon Route 53 - Domain Name System (DNS) web service
- Amazon S3 - Object storage
- Amazon Redshift - Data warehouse
- Amazon SageMaker - Machine learning platform
- Amazon SQS - Queue
- Amazon VPC - Virtual private cloud
- AWS Batch - Batch computing
- AWS Certificate Manager - SSL/TLS certificate management
- AWS CloudFormation - Infrastructure as code (IaC)
- AWS CodeCommit - Version control
-
AWS Glue - Serverless data integration
- AWS Glue Crawler - Data source discovery
- AWS Glue Data Catalog - Data catalog
- AWS Glue DataBrew - Data cleaning
- AWS IAM - Identity and access management
- AWS IoT Core - Internet of Things (IoT)
- AWS KMS - Key management service
- AWS Lake Formation - Data lake governance
-
AWS ParallelCluster - High performance computing (HPC) cluster management
- NICE DCV - Remote display
- AWS Secrets Manager - Password management
-
Google Cloud
-
BigQuery - Data warehouse
- BigQuery ML - BigQuery machine learning
- Dataprep - Data cleaning
- Looker Studio - Data visualization
- Vertex AI - Machine learning platform
-
BigQuery - Data warehouse
- Terraform - Infrastructure as code (IaC)
- Pulumi - Infrastructure as code (IaC)
- Karpenter - Kubernetes node autoscaler
- Prowler - Cloud security assessments
- Komiser - Cloud cost monitoring
- Argo CD - Declarative GitOps CD for Kubernetes
- Rancher - Kubernetes container management platform
- Goldilocks - Kubernetes resource requests recommendation
- Polaris - Kubernetes best practices validation
- Sloop - Kubernetes history visualization
- OpenCost - Kubernetes cost monitoring
- Kubecost - Kubernetes cost monitoring
- Diun - Container image update notifier
- Vagrant - Development environments building and distributing
- Ansible - IT automation system
- Discord - ChatOps
- Opsgenie - Incident management platform
- GitHub Actions - Continuous integration
- Apache Ranger - Authorization, auditing
- Ory Hydra - OAuth 2.0 and OpenID Connect server
- Open Policy Agent (OPA) - Policy-based control
- OPAL - Open-policy administration layer
- CodeQL - Variant analysis
- Gitleaks - Git secret scanning
- GitGuardian - Git secret scanning
- xxHash - Hash algorithm
- Ouch! - Compressing and decompressing program
- Rclone - Cloud storage sync program
- restic - Encrypted backup program
- Vim - Terminal-based text editor
- Zellij - Terminal multiplexer
- hexedit - File viewing and editing in hexadecimal and ASCII
- xxd - File viewing and editing in hexadecimal and ASCII
- strings - Strings of printable characters viewing
- objdump - Disassembler
- IDA - Disassembler
- Solidity - Contract-oriented programming language
- solc-js - JavaScript bindings for the Solidity compiler
- VHDL - Very High Speed Integrated Circuits Program (VHSIC) hardware description language
- pySerial - Serial communication library
- cantools - Controller Area Network (CAN) bus tools
- python-can - Controller Area Network (CAN) bus library
- Valgrind - Memory debugging and profiling
- Yocto Project - Linux distribution creating
- ROS - Robot operating system
- FreeRTOS - Real-time operating system
- ASTERIOS - Real-time, safety-critical applications development
-
RTI Connext - Real-time, distributed systems framework
- RTI Connext DDS - Data distribution service (DDS)
- OpenSCAD - 3D CAD Modeller
- Arduino Uno - Microcontroller board
- BeagleBone Black - Microcontroller board
- Raspberry Pi 4 Model B - Single-board computer (SBC)
- Jetson Nano - Single-board computer (SBC)
- Jetson TX2 - Single-board computer (SBC)
- AnyLogic - Simulation modeling tool
- LabVIEW - Graphical programming environment
-
VeriStand - Real-time testing and simulation
- niveristand - VeriStand API library
- npTDMS - TDMS files reading and writing
- PyVISA - Virtual instrument software architecture (VISA) API library
-
MATLAB - Programming and numeric computing platform
-
5G Toolbox - 5G communications systems simulation, analysis, and testing
- 6G Exploration Library - 6G communications systems simulation, analysis, and testing
- Aerospace Toolbox - Aerospace vehicle motion analysis and visualization
- Automated Driving Toolbox - ADAS and autonomous driving systems design, simulation, and testing
- Bioinformatics Toolbox - Genomic and proteomic data analysis and visualization
- Computer Vision Toolbox - Computer vision, 3D vision, and video processing systems design and testing
- Database Toolbox - Relational and NoSQL databases interacting
- Lidar Toolbox - Lidar processing systems design, analysis, and testing
- Navigation Toolbox - Autonomous navigation algorithms design, simulation, and deployment
- Satellite Communications Toolbox - Satellite communications systems simulation
- Signal Processing Toolbox - Signal processing and analysis
-
Simulink - Simulation and model-based designing
- Simscape - Multidomain physical systems simulation
-
5G Toolbox - 5G communications systems simulation, analysis, and testing
- CoppeliaSim - Robot simulation
- AeroSandbox - Aircraft design and optimization
- OpenAeroStruct - Aerostructural optimization
- OpenMDAO - Multidisciplinary analysis and optimization
- OpenFOAM - Computational fluid dynamics (CFD)
- SimScale - Computational fluid dynamics (CFD), finite element analysis (FEA), thermal simulation
- ParaView - Post-processing visualization
- PX4 - Flight control software
- CubeSat - Miniaturized satellite
- QGroundControl - Ground control station (GCS) for unmanned aerial vehicles (UAVs)
- ansible-lint - Ansible linter
- dotnet format - C# code formatter
- CSharpier - C# code formatter
- ClangFormat - C/C++ code formatter
- cpplint - C/C++ linter
- CMakeLint - CMake linter
- Prettier - Code formatter
- commitlint - Commit message linter
- Stylelint - CSS linter
- hadolint - Dockerfile linter
- gofmt - Go code formatter
- golangci-lint - Go linter
- @html-eslint - HTML linter
- ESLint - JavaScript linter
- @eslint/json - JSON linter
- Ktlint - Kotlin code formatter and linter
- detekt - Kotlin static type checker
- Kubeconform - Kubernetes manifest linter
- markdownlint-cli2 - Markdown linter
- MISS_HIT - MATLAB code formatter
- textlint - Natural language linter
- Buf - Protocol Buffers linter
- Black - Python code formatter
- autoflake, isort, Ruff - Python linter
- Mypy - Python static type checker
- qmllint - QML linter
- opa - Rego code formatter
- RuboCop - Ruby code formatter and linter
- rustfmt - Rust code formatter
- Clippy - Rust linter
- Scalafmt - Scala code formatter
- Scalafix - Scala linter
- ShellCheck - Shell linter
- solhint - Solidity linter
- SQLFluff - SQL code formatter and linter
- Taplo - TOML code formatter
- terraform - Terraform code formatter
- tsc - TypeScript static type checker
- VHDL Style Guide (VSG) - VHDL code formatter
- @prettier/plugin-xml - XML formatter
- yamllint - YAML linter
- GitHub - Version control
- SonarCloud, Codacy - Code reviews and analytics
- Codecov - Code coverage reports
- Depfu - Dependency monitoring
- FOSSA - License compliance
- Fusion 360 - Industrial design
- Blender - 3D graphic design
- Figma - UX design
- Renovate - Dependency updating
- CodeReview BOT - Code reviewing
- Mergify - Automatically merging
- Stale - Stale issues and pull requests closing
- ImgBot - Image compression
- semantic-release - Version management and package publishing
- Unit testing
- Marble testing
- Snapshot testing
- Visual testing
- Instrumented testing
- Smoke testing
- Sanity testing
- Compatibility testing
- Integration testing
- End-to-end testing
- Contract testing
- Mutation testing
- Performance testing
- Permutation testing
- Holdout testing
- Bias testing
- Duck testing
- Bus testing
- Load testing
- Durability testing
- Fault injection testing
- Parallel testing
- Acceptance testing
- Model-in-the-loop (MIL) testing
- Hardware-in-the-loop (HIL) testing
-
Environmental testing
- Vibration testing
-
Shock testing
- Drop testing
- Temperature testing
- Humidity testing
- Altitude testing
- Icing testing
- Rain testing
- Fungus testing
- Salt fog testing
- Lightning testing
- Structural testing
- Battery drop testing
- Battery vibration testing
- Dyno testing
- Flammability testing
- Wind tunnel testing
- Ground testing
- Flight testing
-
C
- Embedded C
- PsyC
-
C++
- CUDA C++
- C#
- CSS
- Docker
- Go
- GraphQL
- HCL
- HTML
-
Java
- Kotlin
- Scala
-
JavaScript
- TypeScript
- Makefile
- Markdown
- MATLAB
- Protocol Buffers
- Python
- QML
- Rego
- Ruby
- Rust
- Shell
- Solidity
-
SQL
- LogQL
- PromQL
- SedonaSQL
- Spark SQL
- Snowflake SQL
- Swift
- VHDL
- XML
- YAML
- P4 - Programming Protocol-independent Packet Processors
-
ZeroMQ - High-performance asynchronous messaging library
- NetMQ - C# implementation of ZeroMQ
- zmq.rs - Rust implementation of ZeroMQ
-
Open Systems Interconnection (OSI) model
- Layer 1: Physical layer
- Serial protocols
- Inter-Integrated Circuit (I²C)
- Serial Peripheral Interface (SPI)
- Controller Area Network (CAN)
- Serial protocols
- Layer 2: Data link layer
- Ethernet
- Wi-Fi
- Layer 3: Network layer
-
The Internet Protocol (IP)
- IPv4
- IPv6
- Time protocols
- Network Time Protocol (NTP)
- Precision Time Protocol (PTP)
- IRIG-B Time Protocol
-
The Internet Protocol (IP)
- Layer 4: Transport layer
- User Datagram Protocol (UDP)
- Transmission Control Protocol (TCP)
- QUIC
- Layer 5: Session layer
- WebSocket
- Web Real-Time Communication (WebRTC)
- Layer 6: Presentation layer
-
Remote Procedure Call (RPC)
- RPC frameworks
- Apache Avro
- Apache Thrift
- gRPC Remote Procedure Calls (gRPC)
- Binary data serialization formats
- Avro
- Thrift
- Protocol Buffers (Protobuf)
- RPC frameworks
-
Remote Procedure Call (RPC)
- Layer 7: Application layer
-
Hypertext Transfer Protocol (HTTP)
- Hypertext Transfer Protocol Secure (HTTPS)
- HTTP/0.9 - TCP/IP
- HTTP/1.0 - TCP/IP
- HTTP/1.1 - TCP/IP
- HTTP/2 - TCP/IP
- HTTP/3 - QUIC + UDP
- File transfer protocols
-
File Transfer Protocol (FTP)
- Secure File Transfer Protocol (SFTP)
- Server Message Block (SMB)
- Web Distributed Authoring and Versioning (WebDAV)
-
File Transfer Protocol (FTP)
- Email protocols
- Post Office Protocol (POP)
- Simple Mail Transfer Protocol (SMTP)
- Internet Message Access Protocol (IMAP)
- MQTT
-
Hypertext Transfer Protocol (HTTP)
- Layer 1: Physical layer
- 1G
- 2G
- 3G
- 3.9G - Long-Term Evolution (LTE)
- 4G - Long-Term Evolution (LTE) Advanced
- 4.5G - Long-Term Evolution (LTE) Advanced Pro
- 5G - 5G New Radio (NR)
- 5.5G - 5G Advanced
- 6G
-
Avionics Systems
- DO-178C - Software considerations in airborne systems and equipment certification
- DO-254 - Design assurance guidance for airborne electronic hardware
- ARP4754A - Guidelines for development of civil aircraft and systems
- DO-160G - Environmental conditions and test procedures for airborne equipment
- DO-331 - Model-based development and verification supplement to DO-178C and DO-278A
- DO-330 - Software tool qualification considerations
-
Drone Systems
- Pixhawk standards - Hardware specifications and guidelines for drone systems development
-
Automotive Systems
- ISO 26262 - Road vehicles — functional safety
- AUTOSAR - Automotive open system architecture
-
Industrial Robot Systems
- ISO 10218 - Robots and robotic devices — safety requirements for industrial robots
- ANSI/RIA R15.06-2012 - Industrial robots and robot systems — safety requirements
The following presents a model of a radar-based air defense system. Bombers are dispatched to destroy ground facilities, while the buildings are safeguarded by the air defense system, comprising two radars equipped with guided surface-to-air missiles.
OpenFOAM simulation results viewed by ParaView.
The toroidal propeller allows a small multirotor aircraft to operate more quietly than the ones that use traditional propellers.
The VHDL waveforms are displayed in GTKWave.
Chatbot on Telegram powered by Rasa.
Distributed hyperparameter optimization result by Weights & Biases.
The website supports HTTP/3.
Images on the website are using AVIF format.
The WebP is almost half the size of JPEG, and AVIF is under half the size of WebP.
Below is the Mozilla HTTP observatory report for the website.
Profiling result by Clinic.js and autocannon.
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This repository provides a comprehensive collection of resources, open-source tools, and knowledge related to quantitative analysis. It serves as a valuable knowledge base and navigation guide for individuals interested in various aspects of quantitative investing, including platforms, programming languages, mathematical foundations, machine learning, deep learning, and practical applications. The repository is well-structured and organized, with clear sections covering different topics. It includes resources on system platforms, programming codes, mathematical foundations, algorithm principles, machine learning, deep learning, reinforcement learning, graph networks, model deployment, and practical applications. Additionally, there are dedicated sections on quantitative trading and investment, as well as large models. The repository is actively maintained and updated, ensuring that users have access to the latest information and resources.
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AI-Catalog is a curated list of AI tools, platforms, and resources across various domains. It serves as a comprehensive repository for users to discover and explore a wide range of AI applications. The catalog includes tools for tasks such as text-to-image generation, summarization, prompt generation, writing assistance, code assistance, developer tools, low code/no code tools, audio editing, video generation, 3D modeling, search engines, chatbots, email assistants, fun tools, gaming, music generation, presentation tools, website builders, education assistants, autonomous AI agents, photo editing, AI extensions, deep face/deep fake detection, text-to-speech, startup tools, SQL-related AI tools, education tools, and text-to-video conversion.
llm_interview_note
This repository provides a comprehensive overview of large language models (LLMs), covering various aspects such as their history, types, underlying architecture, training techniques, and applications. It includes detailed explanations of key concepts like Transformer models, distributed training, fine-tuning, and reinforcement learning. The repository also discusses the evaluation and limitations of LLMs, including the phenomenon of hallucinations. Additionally, it provides a list of related courses and references for further exploration.
PythonPark
PythonPark is a paradise for learning Python, providing babysitter-level tutorials on AI labs, treasure videos, data structures, study guides, machine learning practicals, deep learning practicals, Python basics, web scraping, big company interview experiences, programming life, and resource sharing. Original articles are published at least twice a week, with the latest articles being first released on WeChat and videos on Bilibili. Join the WeChat group for technical discussions or to provide feedback. Continuously improving and outputting content!
LogChat
LogChat is an open-source and free AI chat client that supports various chat models and technologies such as ChatGPT, 讯飞星火, DeepSeek, LLM, TTS, STT, and Live2D. The tool provides a user-friendly interface designed using Qt Creator and can be used on Windows systems without any additional environment requirements. Users can interact with different AI models, perform voice synthesis and recognition, and customize Live2D character models. LogChat also offers features like language translation, AI platform integration, and menu items like screenshot editing, clock, and application launcher.
chatwiki
ChatWiki is an open-source knowledge base AI question-answering system. It is built on large language models (LLM) and retrieval-augmented generation (RAG) technologies, providing out-of-the-box data processing, model invocation capabilities, and helping enterprises quickly build their own knowledge base AI question-answering systems. It offers exclusive AI question-answering system, easy integration of models, data preprocessing, simple user interface design, and adaptability to different business scenarios.
awesome-llm-plaza
Awesome LLM plaza is a curated list of awesome LLM papers, projects, and resources. It is updated daily and includes resources from a variety of sources, including huggingface daily papers, twitter, github trending, paper with code, weixin, etc.
douyin-chatgpt-bot
Douyin ChatGPT Bot is an AI-driven system for automatic replies on Douyin, including comment and private message replies. It offers features such as comment filtering, customizable robot responses, and automated account management. The system aims to enhance user engagement and brand image on the Douyin platform, providing a seamless experience for managing interactions with followers and potential customers.
ChatGPT-airport-tizi-fanqiang
This repository provides a curated list of recommended airport proxies for accessing ChatGPT and other AI tools while bypassing internet restrictions. The proxies are tested and verified to ensure reliability and stability. The readme includes detailed instructions on how to set up and use the proxies with various devices and platforms. Additionally, the repository offers advanced tutorials on upgrading to GPT-4/Plus, deploying a 24/7 ChatGPT微信机器人 server, and using Claude-3 securely and for free.
DeepBattler
DeepBattler is a tool designed for Hearthstone Battlegrounds players, providing real-time strategic advice and insights to improve gameplay experience. It integrates with the Hearthstone Deck Tracker plugin and offers voice-assisted guidance. The tool is powered by a large language model (LLM) and can match the strength of top players on EU servers. Users can set up the tool by adding dependencies, configuring the plugin path, and launching the LLM agent. DeepBattler is licensed for personal, educational, and non-commercial use, with guidelines on non-commercial distribution and acknowledgment of external contributions.
higress
Higress is an open-source cloud-native API gateway built on the core of Istio and Envoy, based on Alibaba's internal practice of Envoy Gateway. It is designed for AI-native API gateway, serving AI businesses such as Tongyi Qianwen APP, Bailian Big Model API, and Machine Learning PAI platform. Higress provides capabilities to interface with LLM model vendors, AI observability, multi-model load balancing/fallback, AI token flow control, and AI caching. It offers features for AI gateway, Kubernetes Ingress gateway, microservices gateway, and security protection gateway, with advantages in production-level scalability, stream processing, extensibility, and ease of use.
llm-apps-java-spring-ai
The 'LLM Applications with Java and Spring AI' repository provides samples demonstrating how to build Java applications powered by Generative AI and Large Language Models (LLMs) using Spring AI. It includes projects for question answering, chat completion models, prompts, templates, multimodality, output converters, embedding models, document ETL pipeline, function calling, image models, and audio models. The repository also lists prerequisites such as Java 21, Docker/Podman, Mistral AI API Key, OpenAI API Key, and Ollama. Users can explore various use cases and projects to leverage LLMs for text generation, vector transformation, document processing, and more.
activepieces
Activepieces is an open source replacement for Zapier, designed to be extensible through a type-safe pieces framework written in Typescript. It features a user-friendly Workflow Builder with support for Branches, Loops, and Drag and Drop. Activepieces integrates with Google Sheets, OpenAI, Discord, and RSS, along with 80+ other integrations. The list of supported integrations continues to grow rapidly, thanks to valuable contributions from the community. Activepieces is an open ecosystem; all piece source code is available in the repository, and they are versioned and published directly to npmjs.com upon contributions. If you cannot find a specific piece on the pieces roadmap, please submit a request by visiting the following link: Request Piece Alternatively, if you are a developer, you can quickly build your own piece using our TypeScript framework. For guidance, please refer to the following guide: Contributor's Guide
how-to-optim-algorithm-in-cuda
This repository documents how to optimize common algorithms based on CUDA. It includes subdirectories with code implementations for specific optimizations. The optimizations cover topics such as compiling PyTorch from source, NVIDIA's reduce optimization, OneFlow's elementwise template, fast atomic add for half data types, upsample nearest2d optimization in OneFlow, optimized indexing in PyTorch, OneFlow's softmax kernel, linear attention optimization, and more. The repository also includes learning resources related to deep learning frameworks, compilers, and optimization techniques.
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taipy
Taipy is an open-source Python library for easy, end-to-end application development, featuring what-if analyses, smart pipeline execution, built-in scheduling, and deployment tools.
AirPower4T
AirPower4T is a development base library based on Vue3 TypeScript Element Plus Vite, using decorators, object-oriented, Hook and other front-end development methods. It provides many common components and some feedback components commonly used in background management systems, and provides a lot of enums and decorators.
hongbomiao.com
hongbomiao.com is a personal research and development (R&D) lab that facilitates the sharing of knowledge. The repository covers a wide range of topics including web development, mobile development, desktop applications, API servers, cloud native technologies, data processing, machine learning, computer vision, embedded systems, simulation, database management, data cleaning, data orchestration, testing, ops, authentication, authorization, security, system tools, reverse engineering, Ethereum, hardware, network, guidelines, design, bots, and more. It provides detailed information on various tools, frameworks, libraries, and platforms used in these domains.
gptme
GPTMe is a tool that allows users to interact with an LLM assistant directly in their terminal in a chat-style interface. The tool provides features for the assistant to run shell commands, execute code, read/write files, and more, making it suitable for various development and terminal-based tasks. It serves as a local alternative to ChatGPT's 'Code Interpreter,' offering flexibility and privacy when using a local model. GPTMe supports code execution, file manipulation, context passing, self-correction, and works with various AI models like GPT-4. It also includes a GitHub Bot for requesting changes and operates entirely in GitHub Actions. In progress features include handling long contexts intelligently, a web UI and API for conversations, web and desktop vision, and a tree-based conversation structure.
LAMBDA
LAMBDA is a code-free multi-agent data analysis system that utilizes large models to address data analysis challenges in complex data-driven applications. It allows users to perform complex data analysis tasks through human language instruction, seamlessly generate and debug code using two key agent roles, integrate external models and algorithms, and automatically generate reports. The system has demonstrated strong performance on various machine learning datasets, enhancing data science practice by integrating human and artificial intelligence.
Magick
Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.
metaflow
Metaflow is a user-friendly library designed to assist scientists and engineers in developing and managing real-world data science projects. Initially created at Netflix, Metaflow aimed to enhance the productivity of data scientists working on diverse projects ranging from traditional statistics to cutting-edge deep learning. For further information, refer to Metaflow's website and documentation.
SciMLBenchmarks.jl
SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem, including: * Benchmarks of equation solver implementations * Speed and robustness comparisons of methods for parameter estimation / inverse problems * Training universal differential equations (and subsets like neural ODEs) * Training of physics-informed neural networks (PINNs) * Surrogate comparisons, including radial basis functions, neural operators (DeepONets, Fourier Neural Operators), and more The SciML Bench suite is made to be a comprehensive open source benchmark from the ground up, covering the methods of computational science and scientific computing all the way to AI for science.
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AirGo
AirGo is a front and rear end separation, multi user, multi protocol proxy service management system, simple and easy to use. It supports vless, vmess, shadowsocks, and hysteria2.
mosec
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic
llm-code-interpreter
The 'llm-code-interpreter' repository is a deprecated plugin that provides a code interpreter on steroids for ChatGPT by E2B. It gives ChatGPT access to a sandboxed cloud environment with capabilities like running any code, accessing Linux OS, installing programs, using filesystem, running processes, and accessing the internet. The plugin exposes commands to run shell commands, read files, and write files, enabling various possibilities such as running different languages, installing programs, starting servers, deploying websites, and more. It is powered by the E2B API and is designed for agents to freely experiment within a sandboxed environment.
pezzo
Pezzo is a fully cloud-native and open-source LLMOps platform that allows users to observe and monitor AI operations, troubleshoot issues, save costs and latency, collaborate, manage prompts, and deliver AI changes instantly. It supports various clients for prompt management, observability, and caching. Users can run the full Pezzo stack locally using Docker Compose, with prerequisites including Node.js 18+, Docker, and a GraphQL Language Feature Support VSCode Extension. Contributions are welcome, and the source code is available under the Apache 2.0 License.
learn-generative-ai
Learn Cloud Applied Generative AI Engineering (GenEng) is a course focusing on the application of generative AI technologies in various industries. The course covers topics such as the economic impact of generative AI, the role of developers in adopting and integrating generative AI technologies, and the future trends in generative AI. Students will learn about tools like OpenAI API, LangChain, and Pinecone, and how to build and deploy Large Language Models (LLMs) for different applications. The course also explores the convergence of generative AI with Web 3.0 and its potential implications for decentralized intelligence.
gcloud-aio
This repository contains shared codebase for two projects: gcloud-aio and gcloud-rest. gcloud-aio is built for Python 3's asyncio, while gcloud-rest is a threadsafe requests-based implementation. It provides clients for Google Cloud services like Auth, BigQuery, Datastore, KMS, PubSub, Storage, and Task Queue. Users can install the library using pip and refer to the documentation for usage details. Developers can contribute to the project by following the contribution guide.
fluid
Fluid is an open source Kubernetes-native Distributed Dataset Orchestrator and Accelerator for data-intensive applications, such as big data and AI applications. It implements dataset abstraction, scalable cache runtime, automated data operations, elasticity and scheduling, and is runtime platform agnostic. Key concepts include Dataset and Runtime. Prerequisites include Kubernetes version > 1.16, Golang 1.18+, and Helm 3. The tool offers features like accelerating remote file accessing, machine learning, accelerating PVC, preloading dataset, and on-the-fly dataset cache scaling. Contributions are welcomed, and the project is under the Apache 2.0 license with a vendor-neutral approach.
aiges
AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.