{"id":45175422,"url":"https://github.com/bihe/architecture-lab","last_synced_at":"2026-02-20T09:30:35.453Z","repository":{"id":286421434,"uuid":"961060247","full_name":"bihe/architecture-lab","owner":"bihe","description":"Data-Platform example for architecture lab (Salzburg University of Applied Sciences)","archived":false,"fork":false,"pushed_at":"2025-05-25T11:32:12.000Z","size":5223,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-25T12:32:16.212Z","etag":null,"topics":["docker","docker-compose","jupyter-notebook","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bihe.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-04-05T17:04:12.000Z","updated_at":"2025-05-25T11:32:12.000Z","dependencies_parsed_at":"2025-04-30T17:39:16.801Z","dependency_job_id":"3afce566-e203-4df0-9b1a-43159df26177","html_url":"https://github.com/bihe/architecture-lab","commit_stats":null,"previous_names":["bihe/architecture-lab"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/bihe/architecture-lab","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bihe%2Farchitecture-lab","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bihe%2Farchitecture-lab/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bihe%2Farchitecture-lab/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bihe%2Farchitecture-lab/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bihe","download_url":"https://codeload.github.com/bihe/architecture-lab/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bihe%2Farchitecture-lab/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29647600,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-20T09:27:29.698Z","status":"ssl_error","status_checked_at":"2026-02-20T09:26:12.373Z","response_time":59,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["docker","docker-compose","jupyter-notebook","python"],"created_at":"2026-02-20T09:30:34.742Z","updated_at":"2026-02-20T09:30:35.442Z","avatar_url":"https://github.com/bihe.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Architecture Lab\nThe repo provides examples to work with modern data-platform-architecture.\n\n\u003e A data platform serves as a unified system for efficiently managing and analyzing large\n\u003e datasets. It integrates components like databases, data lakes, and data warehouses to\n\u003e handle structured and / or unstructured data depending on the use cases.\n\n[Anatomy of a Data Platform — How to choose your data architecture](https://medium.com/@lou_adam/anatomy-of-a-data-platform-how-to-choose-your-data-architecture-bc36472e7783)\n\n[Jupyter](https://jupyter.org/) notebooks are used to create pipelines implementing a simplified **medallion architecture**\n\n\u003e A medallion architecture is a data design pattern used to logically organize data in a lakehouse,\n\u003e with the goal of incrementally and progressively improving the structure and quality of data as it\n\u003e flows through each layer of the architecture (from Bronze ⇒ Silver ⇒ Gold layer tables).\\\n\n[Medallion Architecture](https://www.databricks.com/glossary/medallion-architecture)\n\n\n## Prerequisites\n\n### Containers\nThe examples are provided as docker compose files. A working container setup with [docker](https://docs.docker.com/engine/install/) or [similar](https://podman.io/) is needed. From developer ergonomics perspective a decent shell is needed.\n\n\u003e [!NOTE]  \n\u003e **Docker**: The compose files where created on Linux with [docker-ce](https://docs.docker.com/engine/install/ubuntu/), tested on Windows with [Docker-Desktop](https://docs.docker.com/desktop/setup/install/windows-install/) on Mac with [OrbStack](https://orbstack.dev/). Other container-environments like [podman](https://podman.io/) may work/may need adaptions.\n\n### Shell\nIn a **Unix-like environments** like Mac/Linux typically a good shell is available out of the box (bash, zsh) in combination with a terminal (terminal, iTerm, Konsole, gnome-terminal, ...). \n\nFor **Windows** a good combination of shell/terminal is [PowerShell](https://github.com/PowerShell/PowerShell)/[Windows Terminal](https://learn.microsoft.com/en-us/windows/terminal/). \n\n\u003e [!NOTE]  \n\u003e **Powershell**: For windows users it might be necessary to set the execution-policy for powershell:\n\n```bash\nSet-ExecutionPolicy RemoteSigned -Scope CurrentUser\n```\n\n\u003e [!WARNING]  \n\u003e **cmd.exe**: If you use [cmd.exe](https://en.wikipedia.org/wiki/Cmd.exe), you are without help. Nobody should use this old command-interpreter anymore!\n\n### Python\nA modern package manager for python should be used to simplify dependency-management and environment setup.\n\n\u003e [!NOTE]  \n\u003e **uv**: I very much recommend [uv](https://github.com/astral-sh/uv) \"An extremely fast Python package and project manager, written in Rust.\"\n\n## Examples\n### 1_simple\nBasic setup to work with [Jupyter](https://jupyter.org/) / [PySpark](https://spark.apache.org/docs/latest/api/python/index.html)\n\n### 2_storage_stream\nIntroduce [Apache Kafka](https://kafka.apache.org/) for streaming data and [MinIO](https://github.com/minio/minio) as a S3-compatible storage backend.\n\n### 3_pipeline\nShows a simple data-pipeline with Bronze/Silver/Gold notebooks and storing data in [Parquet Format](https://parquet.apache.org/) and using [DuckDB](https://duckdb.org/) for data processing.\n\n### 4_user_interface\nA [streamlit](https://streamlit.io/) app to visualize the processed pipeline data in the **GOLD** layer. ","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbihe%2Farchitecture-lab","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbihe%2Farchitecture-lab","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbihe%2Farchitecture-lab/lists"}