Open ExperimentsInHonesty opened 3 years ago
create a npm package for delivering the data. We need to get a backend person involved and we need to make one for each time they change, so la-shape-files-2021, la-shape-files-2022
next steps are talking to 311 team, tdm team, food oasis, luckparking
Feedback from Mike Morgan on 12/9: Since the shape files for the various districts are small enough (less than 50MB, see here), they can be stored in a repository. We should also consider making these available as npm and GeoJSON.
Notes from 3/11 meeting with Abe, Bonnie, John (Food Oasis) and Mike:
Food Oasis uses PostGRES DB's own geometry data type to run scripts, and then converts to geojson to send to client.
PostGRES can also consume geojson to convert to its proprietary geometric data type.
This issue will have to get re-written to check and see if the shape files are out of date. But the programming using the shape files, should be built first, given that up to date shape files, with no programming is useless.
Next steps: Create a script that can be run to automate downloading the various shape files from the various district types listed above. We will want to note the data the files was last updated and the date the file was downloaded.
Update on issue #118, district types reusable tool:
Familiarization: I conducted a review of each target site so that I can understand the layout, available data, and challenges in data extraction.
APIs: Looked for available apis to simplify the extraction process.
Created a spreadsheet to keep tabs on each site
Initiated a Jupyter Notebook to document coding and data collection/automation.
Using the GeoHub L.A. website I programmatically created shape files: Data Acquisition: Utilizing the GeoHub LA website, I identified and accessed URL endpoints for the API calls corresponding to our project's requirements. Data Extraction: Through programmatic queries, I fetched JSON data from the different district API endpoints, capturing geographical information such as boundaries, points of interest, and administrative divisions. Shapefile Creation: Using the gathered JSON data, I made shapefiles, the geospatial data format compatible with various GIS software and tools. Compression Exploration: To optimize storage and handling of the shapefiles, I'm trying out compressing the data using TruncatedSVD.
Update: Data Acquisition, Extraction, Shapefile, and compression exploration can be accessed in my repo, HERE
This week I will look into how we can run the data collection script on a quarterly basis and have it collect in Google Drive and/or GitHub, or whatever is best for the team.
Here's an update on data acquisition and extraction of district shape files:
I've also pushed all recent updates to the repository, and you can check the latest commits for detailed changes.
Project Update:
I can adjust the code to update a GitHub folder. We can do both Google Drive and GitHub, need be.
This week I refined the setup of environment variables to enhance both local development and CI/CD workflows in GitHub Actions. By leveraging os.getenv() for securely accessing environment variables I've streamlined the development process significantly. This ensures that applications run smoothly with the necessary configurations without hardcoding sensitive information.
Additionally, I've discussed with our project manager about updating the top-level Google folder structure. This change aims to improve the automation process for storing shape files.
I gathered all the information for transferring my current repo with the District Shape File pipeline, into a new repo established in Hack for LA account for housing the shape data. Below are the steps involved. The transfer will be completed within the week. In the meantime, shape file data is in Hack for LA Google Drive.
The following steps have been determined for transferring the repository associated with the district data collection:
Prepare New Repository
ETL Process Completion
Code Transfer Process
Transfer Automation Components
Update Documentation
@parcheesime Is there still work to be done on this issue or is it complete?
@akhaleghi I've successfully tested adding the Los Angeles district shape data in my own repository, complete with a README and automated scripts running on schedule. How we can integrate this into the Hack for L.A. repository. Should we create a dedicated directory like LA_District_ShapeFiles for the data?
@akhaleghi I've successfully tested adding the Los Angeles district shape data in my own repository, complete with a README and automated scripts running on schedule. How we can integrate this into the Hack for L.A. repository. Should we create a dedicated directory like LA_District_ShapeFiles for the data?
Follow-up: @akhaleghi I have the data updating on my personal repository. I will need assistance in adding my project to our data science repo. @salice may have made a one but it was awhile ago before the repository updates.
Overview
We need to create a tool so that each project at H4LA that renders points on a map can use District Files to help people analyze or view the data.
Action Items
Resources
Example Neighborhood Council Shape File
Initial Identification of Large Groups/Districts