Writing JSON/List into Lakehouse's Files

Hi dolphinantonym 👋

open() can’t write to an abfss://… URL. In Fabric notebooks, either use the Lakehouse File API path that’s mounted into the notebook, or use NotebookUtils (mssparkutils) to write to OneLake.

Option 1 > Use the mounted Lakehouse path (works with plain Python)

Make sure your target Lakehouse is attached as Default (pin icon). Then write to the File API path:

import json, os

out_path = "/lakehouse/default/Files/APIResponse.json" # File API path
os.makedirs("/lakehouse/default/Files", exist_ok=True)

with open(out_path, "w", encoding="utf-8") as f:
json.dump(AllResults, f, ensure_ascii=False, indent=2)

print("Wrote:", out_path)

Refresh the Files pane and you should see APIResponse.json. (The default Lakehouse mount point is /lakehouse/default. If you only provide a relative path like Files/..., Fabric will also resolve it to the default Lakehouse.)

Option 2> Use NotebookUtils (mssparkutils)

This is a one-liner that writes text content into OneLake:

from notebookutils import mssparkutils
import json

mssparkutils.fs.put("Files/APIResponse.json",
json.dumps(AllResults, ensure_ascii=False, indent=2),
True) # overwrite=True

You can verify with:

mssparkutils.fs.ls("Files")

Docs for fs.put/fs.ls here.

Why your original code didn’t show a file
open("abfss://…", "w") doesn’t target OneLake; Python’s open() doesn’t understand the ABFSS scheme. Use the mounted File API path (/lakehouse/default/...) or mssparkutils instead.

If your end goal is to query the API data later, consider landing it as a Delta table (instead of a raw JSON file):

df = spark.createDataFrame(AllResults) # list[dict]
df.write.format("delta").mode("append").save("Tables/APIResponse")

That creates/updates a managed Delta table under Tables, which you can query from the SQL endpoint.
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