Set API tests

datasetter/api.py

@@ -1,7 +1,9 @@
 import forge
+from fastapi import HTTPException
 from typing import Optional
 import pandas as pd
 import json
+from datasetter.dataset import FacetUnavailableError
 
 
 def as_json(doc):
@@ -11,7 +13,7 @@ def as_json(doc):
         )[0]
 
 
-def add_dataset(dataset, fast_api, uri):
+def add_dataset(fast_api, uri, dataset):
     """Create FastAPI endpoints to serve the dataset.
 
     Parameters
@@ -52,14 +54,18 @@ def count(**kwargs):
     @forge.sign(facet, rows, skip, *kwargs)
     def count_by(facet, rows=10, skip=0, **kwargs):
         filters = {key: val for key, val in kwargs.items() if val is not None}
-        result = dataset.count_by(facet, rows=rows, skip=skip, **filters)
+        try:
+            result = dataset.count_by(facet, rows=rows, skip=skip, **filters)
+        except FacetUnavailableError:
+            raise HTTPException(status_code=404,
+                                detail="FacetUnavailableError: no facet {}".format(facet))
         return as_json({
             "facet": facet,
             # "count": len(result),  # TODO : add "nunique" feature in count_by schema
             "rows": len(result),
             "skip": skip,
             "filters": filters,
-            "data": {str(key): int(val) for key, val in result.items()},
+            "data": [{"value": str(key), "count": int(val)} for key, val in result.items()],
             })
 
     @fast_api.get(uri + "/sample")

test/test_api.py

@@ -1,8 +1,43 @@
 # import pytest
 import numpy as np
 import pandas as pd
+from fastapi import FastAPI
+from fastapi.testclient import TestClient
 
-from datasetter.api import as_json
+from datasetter.utils import doc_equal
+from datasetter.api import as_json, add_dataset
+from datasetter.pandas_dataset import PandasDataset
+
+
+df = pd.DataFrame([
+    ['A', 'alpha', 1],
+    ['A', 'beta', 13],
+    ['A', 'gamma', 8],
+    ['B', 'alpha', 1],
+    ['B', 'beta', 31],
+    ['C', 'gamma', 9],
+    ['C', 'alpha', 2],
+    ['D', 'beta', 21],
+    ['D', 'gamma', 0],
+    ], columns=['letter', 'greek', 'number'])
+
+metadata = {
+    "description": "A simple dataset to make tests.",
+    "facets": ['letter', 'greek'],
+    "columns": [
+        {"name": "letter", "type": "string", "description": "A column with letters."},
+        {"name": "greek", "type": "string", "description": "A column with greek letters."},
+        {"name": "number", "type": "integer", "description": "A column with numbers."},
+        ]}
+
+dataset = PandasDataset(df, ['letter', 'greek'], metadata=metadata)
+
+app = FastAPI()
+add_dataset(app, 'pandas-dataset', dataset)
+# Launch app from parent directory with:
+# > uvicorn test.test_api:app --host 0.0.0.0 --port 8000 --reload
+
+client = TestClient(app)
 
 
 def test_as_json():
@@ -11,3 +46,114 @@ def test_as_json():
     assert as_json(np.NaN) is None
     assert as_json({}) == {}
     assert isinstance(as_json(pd.Timestamp.utcnow()), str)
+
+
+def test_metadata():
+    r = client.get('/pandas-dataset/')
+    assert r.status_code == 200
+    assert doc_equal(r.json(), metadata)
+
+
+def test_count():
+    r = client.get('/pandas-dataset/count')
+    assert r.status_code == 200
+    assert doc_equal(
+        r.json(),
+        {'count': 9, 'filters': {}})
+
+    r = client.get('/pandas-dataset/count?letter=A')
+    assert r.status_code == 200
+    assert doc_equal(
+        r.json(),
+        {'count': 3, 'filters': {'letter': 'A'}})
+
+    r = client.get('/pandas-dataset/count',
+                   params=dict(letter='A', greek='alpha'))
+    assert r.status_code == 200
+    assert doc_equal(
+        r.json(),
+        {'count': 1, 'filters': {'letter': 'A', 'greek': 'alpha'}})
+
+
+def test_count_by():
+    r = client.get('/pandas-dataset/count-by/letter')
+    assert r.status_code == 200
+    assert doc_equal(
+        r.json(),
+        {'facet': 'letter',
+         'rows': 4,
+         'skip': 0,
+         'filters': {},
+         'data': [
+             {'value': 'A', 'count': 3},
+             {'value': 'B', 'count': 2},
+             {'value': 'C', 'count': 2},
+             {'value': 'D', 'count': 2}]})
+
+    r = client.get('/pandas-dataset/count-by/greek')
+    assert r.status_code == 200
+    assert doc_equal(
+        r.json(),
+        {'facet': 'greek',
+         'rows': 3,
+         'skip': 0,
+         'filters': {},
+         'data': [
+             {'value': 'alpha', 'count': 3},
+             {'value': 'beta', 'count': 3},
+             {'value': 'gamma', 'count': 3}]})
+
+    r = client.get('/pandas-dataset/count-by/foo')
+    assert r.status_code == 404
+    assert doc_equal(
+        r.json(),
+        {'detail': 'FacetUnavailableError: no facet foo'})
+
+    r = client.get('/pandas-dataset/count-by/number')
+    assert r.status_code == 404
+    assert doc_equal(
+        r.json(),
+        {'detail': 'FacetUnavailableError: no facet number'})
+
+
+def test_sample():
+    r = client.get('/pandas-dataset/sample')
+    assert r.status_code == 200
+    assert doc_equal(
+        r.json(),
+        {'count': min(10, dataset.count()),
+         'rows': min(10, dataset.count()),
+         'skip': 0,
+         'filters': {},
+         'data': df.to_dict(orient='records')})
+
+    r = client.get('/pandas-dataset/sample?rows=3')
+    assert r.status_code == 200
+    assert doc_equal(
+        r.json(),
+        {'count': min(10, dataset.count()),
+         'rows': min(3, dataset.count()),
+         'skip': 0,
+         'filters': {},
+         'data': df.head(3).to_dict(orient='records')})
+
+    r = client.get('/pandas-dataset/sample?letter=A')
+    assert r.status_code == 200
+    assert doc_equal(
+        r.json(),
+        {'count': min(10, dataset.count(letter="A")),
+         'rows': min(3, dataset.count(letter="A")),
+         'skip': 0,
+         'filters': {'letter': 'A'},
+         'data': dataset.sample(letter='A').to_dict(orient='records')})
+
+    r = client.get('/pandas-dataset/sample?letter=A&rows=2')
+    assert r.status_code == 200
+    assert doc_equal(
+        r.json(),
+        {'count': dataset.count(letter="A"),
+         'rows': min(2, dataset.count(letter="A")),
+         'skip': 0,
+         'filters': {'letter': 'A'},
+         'data': (dataset.sample(letter='A').head(2)
+                  .to_dict(orient='records'))})

test/test_pandas_dataset.py

@@ -67,4 +67,3 @@ def test_sample():
 
     with pytest.raises(FacetUnavailableError):
         dataset.sample(number=12)
-    assert True