{"id":18243830,"url":"https://github.com/hamedalemo/vector-data-tutorial","last_synced_at":"2026-05-15T20:02:18.056Z","repository":{"id":260991287,"uuid":"882900060","full_name":"HamedAlemo/vector-data-tutorial","owner":"HamedAlemo","description":"Notebooks to learn basics of geospatial vector data processing in Python","archived":false,"fork":false,"pushed_at":"2025-10-30T04:16:52.000Z","size":4368,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-30T06:20:23.064Z","etag":null,"topics":["geospatial","geospatial-analysis","geospatial-processing","geospatial-vector","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":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/HamedAlemo.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}},"created_at":"2024-11-04T02:22:31.000Z","updated_at":"2025-10-30T04:16:55.000Z","dependencies_parsed_at":null,"dependency_job_id":"cfb71261-3904-4cb4-8a18-a96c2ca2f71c","html_url":"https://github.com/HamedAlemo/vector-data-tutorial","commit_stats":{"total_commits":7,"total_committers":1,"mean_commits":7.0,"dds":0.0,"last_synced_commit":"bb1473ebc90604026578be3ccc4204332ba947a6"},"previous_names":["hamedalemo/vector-data-tutorial"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/HamedAlemo/vector-data-tutorial","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HamedAlemo%2Fvector-data-tutorial","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HamedAlemo%2Fvector-data-tutorial/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HamedAlemo%2Fvector-data-tutorial/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HamedAlemo%2Fvector-data-tutorial/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/HamedAlemo","download_url":"https://codeload.github.com/HamedAlemo/vector-data-tutorial/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HamedAlemo%2Fvector-data-tutorial/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33077926,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-15T11:35:32.926Z","status":"ssl_error","status_checked_at":"2026-05-15T11:35:31.362Z","response_time":103,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 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":["geospatial","geospatial-analysis","geospatial-processing","geospatial-vector","python"],"created_at":"2024-11-05T09:03:29.392Z","updated_at":"2026-05-15T20:02:18.051Z","avatar_url":"https://github.com/HamedAlemo.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Geospatial Vector Data Processing in Python\nThis repository contains an introduction to geospatial vector data processing in Python. This is part of the course on [Advanced Geospatial Analytics with Python](https://hamedalemo.github.io/advanced-geo-python/intro.html) taught since Fall 2023 at Clark University. \n\n## Requirements\n\nYou need to have Docker installed on your machine. \n\n\n## Instructions\n\nClone this repository to your local machine:\n\n```\ngit clone git@github.com:HamedAlemo/vector-data-tutorial.git\n```\n\nChange your directory to the cloned repository:\n\n```\ncd vector-data-tutorial\n```\n\nTo run the container, you have two options:\n\n\n### Option 1 - Pull Docker image from DockerHub (Recommended):\n\nIt's recommended to pull the Docker image from Dockerhub. Otherwise, if you prefer, you can build your own image using the instructions in the following section. \n\n```\ndocker pull hamedalemo/vector-tutorial:1.2\n```\n\n```\ndocker run -it -p 8888:8888 -p 8787:8787 -v $(pwd):/home/gisuser/ hamedalemo/vector-tutorial:1.2\n```\n- Copy the Jupyter Lab url and paste it in your browser. \n- Open `vector_analysis.ipynb`, `dask_geopandas_intro.ipynb`, and `scalable_vector_analysis.ipynb` and follow the instructions. \n\n\n### Option 2 - Build your Docker image:\n\n```\ndocker build -t vector-tutorial:1.2 .\n```\n\nRun the container as following after switching to the repository's directory locally:\n\n```\ndocker run -it -p 8888:8888 -p 8787:8787 -v $(pwd):/home/gisuser/ vector-tutorial:1.2\n```\n\n- Copy the Jupyter Lab url and paste it in your browser. \n- Open `vector_analysis.ipynb`, `dask_geopandas_intro.ipynb`, and `scalable_vector_analysis.ipynb` and follow the instructions. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhamedalemo%2Fvector-data-tutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhamedalemo%2Fvector-data-tutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhamedalemo%2Fvector-data-tutorial/lists"}