Add pipeline snippets for Firestore #919
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| # [START basic_read] | ||
| pipeline = client.pipeline().collection("users") | ||
| for result in pipeline.execute(): | ||
| print(result.id + " => " + result.data) |
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f-strings are usually preferred to concatenation: print(f"{result.id} => {result.data}")
| # [START pipeline_concepts] | ||
| pipeline = client.pipeline() \ | ||
| .collection("cities") \ | ||
| .where(Field.of("population").greater_than(100000)) \ |
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suggestion: Python lets you break up large numbers, so you could do 100_000 for readability (and consider this for other large numbers in this file)
| # [START basic_read] | ||
| pipeline = client.pipeline().collection("users") | ||
| for result in pipeline.execute(): | ||
| print(result.id + " => " + result.data) |
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It looks like result.data is a method and not a property, so I think you need to call it: result.data()
| # [START field_or_constant] | ||
| pipeline = client.pipeline() \ | ||
| .collection("cities") \ | ||
| .where(Field.of("name").equal(Constant("Toronto"))) |
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you can also do Constant.of("Toronto"), to match Field.of. I'm not sure which is preferred
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| default_app = firebase_admin.initialize_app() | ||
| client = firestore.client(default_app, "your-new-enterprise-database") | ||
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We also have an async version of everything.
Often, we re-write the samples for both sync and async, and show both options in the language selection pickers. I'm not sure how you want to handle that here.
Maybe a couple samples for pipeline_initialization_async and basic_read_async is enough to show it exists, since the API is almost identical. Or maybe samples for async aren't needed for preview
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I will try to get to the async versions after Java and if I don't get to it by launch day it'll just be a follow-on.
| .execute() | ||
| # [END vector_length] | ||
| for res in result: | ||
| print(res) |
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It would be great if we could have a test file that exercises these functions. Even just running them without verifying outputs would be helpful to make sure no exceptions are thrown, but reading back results would be ideal
It looks like the other samples in this repo aren't tested though, so maybe that would be too much to set up
| Field.of("rating").average().as_("avg_rating"), | ||
| groups=[Field.of("genre")] | ||
| ) \ | ||
| .execute() |
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If you want to get rid of all the \, IIRC think you could do something like this:
results = (
client.pipeline()
.collection("books")
.aggregate(
Field.of("rating").average().as_("avg_rating"),
groups=[Field.of("genre")]
).execute()
)
(But test it first)
daniel-sanche
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daniel-sanche
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Consider adding more imports for Vector, and others that may be missing through the file
But overall LGTM
| # [START cosine_distance] | ||
| from google.cloud.firestore_v1.pipeline_expressions import Field | ||
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| sample_vector = Vector([0.0, 1.0, 2.0, 3.0, 4.0, 5.0]) |
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I'd recommend adding the import for Vector in the sample as well
(maybe you should remove most imports from the top of the file, so it will be clear where sample imports are needed?)
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