microsoft / microsoft/GlobalMLBuildingFootprints

Google colab and API token access

Open
#24 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
2k
Forks
277
PR merge metrics
No merged PRs in 30d

Description

Hello!

I am trying to obtain the building polygons and locations using the google colab notebooks.
First, I requested access to Microsoft to be able to use Jupyter notebook and test the "Vatican city" example and it worked. Then I used the same code on google colab, and I got an error. To make sure, that this is not due to versions, I used printed all the packages versions on the Microsoft jupyter hub and installed them on my google colab.
However, I keep getting the same error.

The error I get is the following:

image

Code:

catalog = pystac_client.Client.open(
"https://planetarycomputer.microsoft.com/api/stac/v1"
)
items = catalog.search(
collections=["ms-buildings"], query={"msbuildings:region": {"eq": "Vatican City"}}
)
item = next(items.get_items())
item

collection = catalog.get_collection("ms-buildings")

asset = planetary_computer.sign(item.assets["data"])

df = geopandas.read_parquet(
asset.href, storage_options=asset.extra_fields["table:storage_options"]
)
df.head()

I am guessing the error, its the API token? but I think I am following the steps in the Microsoft API documentation for the datasets.
What am I doing wrong?

Thank you !

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

The reported entry point is the Google Colab notebook code using pystac_client.Client.open, planetary_computer.sign, and geopandas.read_parquet; first reproduce it in Colab and capture the full traceback and package versions rather than relying on the linked screenshot. Done means identifying the authentication or environment difference and documenting a verified way to retrieve the ms-buildings asset.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
api, cloud, data
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.