import os
os.environ["WEAVIATE_URL"] = "<REST_ENDPOINT>"
os.environ["WEAVIATE_API_KEY"] = "<API Key>"

import weaviate
from weaviate.classes.init import Auth
from weaviate.classes.query import Filter

weaviate_url = os.environ["WEAVIATE_URL"]
weaviate_api_key = os.environ["WEAVIATE_API_KEY"]

# Connect to Weaviate Cloud
client = weaviate.connect_to_weaviate_cloud(
    cluster_url=weaviate_url,
    auth_credentials=Auth.api_key(weaviate_api_key),
)

def delete_by_property(...): ...

# create collection and add data.
data_rows = [
    {"title": f"Object {i+1}"} for i in range(5)
]

collection = client.collections.get("collection_a")

with collection.batch.fixed_size(batch_size=200) as batch:
    for data_row in data_rows:
        batch.add_object(
            properties=data_row,
        )
        if batch.number_errors > 10:
            print("Batch import stopped due to excessive errors.")
            break

failed_objects = collection.batch.failed_objects
if failed_objects:
    print(f"Number of failed imports: {len(failed_objects)}")
    print(f"First failed object: {failed_objects[0]}")

# Execute the deletion
delete_by_property(
    collection_names="collection_a",
    filter_criteria=Filter.by_property("title").equal("Object 1"),
    if_error="continue"
)