refactoring: metadata argument as iterable instead of dict

pyinfra/server/rest.py

@@ -14,13 +14,13 @@ logger = logging.getLogger("PIL.PngImagePlugin")
 logger.setLevel(logging.WARNING)
 
 
-def process_eagerly(url, data: Iterable[bytes], metadata: dict):
+def process_eagerly(url, data: Iterable[bytes], metadata: Iterable[dict]):
     """Posts `data` to `url` and aggregates responses for each element of `data`."""
     pipe = pipeline(url, identity)
-    yield from pipe(data, repeat(metadata))
+    yield from pipe(data, metadata)
 
 
-def process_lazily(url, data, metadata):
+def process_lazily(url, data: Iterable[bytes], metadata: Iterable[dict]):
     """Posts `data` to `url` and aggregates responses for each element of `data` by querying a pickup endpoint.
 
     Requires:
@@ -37,7 +37,7 @@ def process_lazily(url, data, metadata):
 
     pipe = pipeline(f"{url}/submit", receiver)
 
-    yield from pipe(data, repeat(metadata))
+    yield from pipe(data, metadata)
 
 
 def stream_response_payloads(endpoint):
@@ -58,16 +58,16 @@ def stream_response_payloads(endpoint):
 
 def pipeline(url, receiver):
     return rcompose(
-        sender(url),
+        head(url),
         receiver,
         flatten,  # each analysis call returns an iterable. Can be empty, singleton or multi item. Hence, flatten.
     )
 
 
-def sender(endpoint):
+def head(endpoint):
     """Builds a function that sends post or patch requests an endpoint."""
 
-    send_data_with_method_to_analyzer = starlift(http_method_dispatcher(endpoint))
+    send_data_with_method_to_analyzer = starlift(sender(endpoint))
 
     def send(data: Iterable[bytes], metadata: Iterable[dict]):
         """Sends packages of data and metadata to endpoint and returns response."""
@@ -85,7 +85,7 @@ def pack_data_and_metadata_for_rest_transfer(data: Iterable, metadata: Iterable)
     yield from starmap(pack, zip(data, metadata))
 
 
-def http_method_dispatcher(endpoint):
+def sender(endpoint):
     def send(method, data):
         response = method(endpoint, json=data)
         response.raise_for_status()

test/exploration_tests/partial_response_test.py

@@ -8,4 +8,4 @@ from pyinfra.server.rest import process_eagerly, unpack
 @pytest.mark.parametrize("item_type", ["pdf", "string", "image"])
 def test_sending_partial_request(url, input_data_items, metadata, operation, target_data_items, server_process):
     output = lmap(unpack, process_eagerly(f"{url}/process", input_data_items, metadata))
-    assert output == lmap(unpack, target_data_items)
+    assert output == target_data_items

test/exploration_tests/pickup_endpoint_test.py

@@ -8,4 +8,4 @@ from pyinfra.server.rest import unpack, process_lazily
 @pytest.mark.parametrize("item_type", ["string", "image", "pdf"])
 def test_pickup_endpoint(url, input_data_items, metadata, operation, target_data_items, server_process):
     output = lmap(unpack, process_lazily(url, input_data_items, metadata))
-    assert output == lmap(unpack, target_data_items)
+    assert output == target_data_items

test/fixtures/input.py

@@ -1,11 +1,11 @@
-from functools import partial
+from itertools import starmap, repeat
 
 import numpy as np
 import pytest
 from PIL import Image
 from funcy import lmap, compose, flatten
 
-from pyinfra.server.rest import pack, normalize_item
+from pyinfra.server.rest import pack, normalize_item, unpack
 from pyinfra.utils.func import star, lift
 from test.utils.image import image_to_bytes
 
@@ -32,8 +32,8 @@ def input_data_items(item_type, n_items, pdf):
 
 @pytest.fixture
 def target_data_items(input_data_items, item_type, operation, metadata):
-    op = compose(lift(star(pack)), normalize_item, partial(operation, metadata=metadata))
-    expected = list(flatten(map(op, input_data_items)))
+    op = compose(lift(star(pack)), normalize_item, operation)
+    expected = lmap(unpack, flatten(starmap(op, zip(input_data_items, metadata))))
     return expected
 
 
@@ -65,5 +65,5 @@ def images(n_items):
 
 
 @pytest.fixture
-def metadata():
-    return {"dummy": True}
+def metadata(n_items):
+    return list(repeat({"dummy": True}, n_items))