Merge branch 'develop' into iss66-cast-geom-ids-to-text

scripts/README.md

@@ -0,0 +1,15 @@
+## Automatic tests and utilities
+
+### Installation
+
+Python 2.7 should cover you.  Virtualenv recommended.
+
+    virtualenv venv
+    source venv/bin/activate
+    pip install -r requirements.txt
+
+### Execution
+
+Run automated tests against a hostname:
+
+    (venv) OBS_HOSTNAME=<hostname.cartodb.com> OBS_API_KEY=foobar nosetests autotest.py

scripts/autotest.py

@@ -0,0 +1,100 @@
+from nose.tools import assert_equal, assert_is_not_none
+from nose_parameterized import parameterized
+
+import os
+import re
+import requests
+
+HOSTNAME = os.environ['OBS_HOSTNAME']
+API_KEY = os.environ['OBS_API_KEY']
+META_HOSTNAME = os.environ.get('OBS_META_HOSTNAME', HOSTNAME)
+META_API_KEY = os.environ.get('OBS_META_API_KEY', API_KEY)
+USE_SCHEMA = 'OBS_USE_SCHEMA' in os.environ
+
+
+def query(q, is_meta=False, **options):
+    '''
+    Query the account.  Returned is the response, wrapped by the requests
+    library.
+    '''
+    url = 'https://{hostname}/api/v2/sql'.format(
+        hostname=META_HOSTNAME if is_meta else HOSTNAME)
+    params = options.copy()
+    params['q'] = re.sub(r'\s+', ' ', q)
+    params['api_key'] = META_API_KEY if is_meta else API_KEY
+    return requests.get(url, params=params)
+
+MEASURE_COLUMNS = [(r['id'], ) for r in query('''
+SELECT id FROM observatory.obs_column
+WHERE type ILIKE 'numeric'
+AND weight > 0
+''', is_meta=True).json()['rows']]
+
+CATEGORY_COLUMNS = [(r['id'], ) for r in query('''
+SELECT id FROM observatory.obs_column
+WHERE type ILIKE 'text'
+AND weight > 0
+''', is_meta=True).json()['rows']]
+
+BOUNDARY_COLUMNS = [(r['id'], ) for r in query('''
+SELECT id FROM observatory.obs_column
+WHERE type ILIKE 'geometry'
+AND weight > 0
+''', is_meta=True).json()['rows']]
+
+def default_point(column_id):
+    '''
+    Returns default test point for the column_id.
+    '''
+    if column_id == 'whosonfirst.wof_disputed_geom':
+        return 'CDB_LatLng(33.78, 76.57)'
+    elif column_id == 'whosonfirst.wof_marinearea_geom':
+        return 'CDB_LatLng(43.33, -68.47)'
+    elif column_id in ('us.census.tiger.school_district_elementary',
+                       'us.census.tiger.school_district_secondary',
+                       'us.census.tiger.school_district_elementary_clipped',
+                       'us.census.tiger.school_district_secondary_clipped'):
+        return 'CDB_LatLng(40.7025, -73.7067)'
+    elif column_id.startswith('es.ine'):
+        return 'CDB_LatLng(40.39, -3.7)'
+    elif column_id.startswith('us.zillow'):
+        return 'CDB_LatLng(28.3305906291771, -81.3544048197256)'
+    else:
+        return 'CDB_LatLng(40.7, -73.9)'
+
+
+@parameterized(MEASURE_COLUMNS)
+def test_measure_points(column_id):
+    resp = query('''
+SELECT * FROM {schema}OBS_GetMeasure({point}, '{column_id}')
+                 '''.format(column_id=column_id,
+                            schema='cdb_observatory.' if USE_SCHEMA else '',
+                            point=default_point(column_id)))
+    assert_equal(resp.status_code, 200)
+    rows = resp.json()['rows']
+    assert_equal(1, len(rows))
+    assert_is_not_none(rows[0].values()[0])
+
+@parameterized(CATEGORY_COLUMNS)
+def test_category_points(column_id):
+    resp = query('''
+SELECT * FROM {schema}OBS_GetCategory({point}, '{column_id}')
+                 '''.format(column_id=column_id,
+                            schema='cdb_observatory.' if USE_SCHEMA else '',
+                            point=default_point(column_id)))
+    assert_equal(resp.status_code, 200)
+    rows = resp.json()['rows']
+    assert_equal(1, len(rows))
+    assert_is_not_none(rows[0].values()[0])
+
+@parameterized(BOUNDARY_COLUMNS)
+def test_boundary_points(column_id):
+    resp = query('''
+SELECT * FROM {schema}OBS_GetBoundary({point}, '{column_id}')
+                 '''.format(column_id=column_id,
+                            schema='cdb_observatory.' if USE_SCHEMA else '',
+                            point=default_point(column_id)))
+    assert_equal(resp.status_code, 200)
+    rows = resp.json()['rows']
+    assert_equal(1, len(rows))
+    assert_is_not_none(rows[0].values()[0])

scripts/generate_fixtures.py

@@ -40,14 +40,15 @@ fixtures = [
     ('us.census.tiger.block_group', 'us.census.tiger.block_group', '2014'),
     ('us.census.tiger.zcta5', 'us.census.tiger.zcta5', '2014'),
     ('us.census.tiger.county', 'us.census.tiger.county', '2014'),
-    ('us.census.acs.B01001001', 'us.census.tiger.census_tract', '2009 - 2013'),
-    ('us.census.acs.B01001001_quantile', 'us.census.tiger.census_tract', '2009 - 2013'),
-    ('us.census.acs.B01001001', 'us.census.tiger.block_group', '2009 - 2013'),
-    ('us.census.acs.B01001001', 'us.census.tiger.block_group', '2010 - 2014'),
-    ('us.census.spielman_singleton_segments.X10', 'us.census.tiger.census_tract', '2009 - 2013'),
+    ('us.census.acs.B01003001', 'us.census.tiger.census_tract', '2010 - 2014'),
+    ('us.census.acs.B01003001_quantile', 'us.census.tiger.census_tract', '2010 - 2014'),
+    ('us.census.acs.B01003001', 'us.census.tiger.block_group', '2010 - 2014'),
+    ('us.census.spielman_singleton_segments.X10', 'us.census.tiger.census_tract', '2010 - 2014'),
     ('us.zillow.AllHomes_Zhvi', 'us.census.tiger.zcta5', '2014-01'),
     ('us.zillow.AllHomes_Zhvi', 'us.census.tiger.zcta5', '2016-03'),
     ('whosonfirst.wof_country_geom', 'whosonfirst.wof_country_geom', '2016'),
+    ('us.census.tiger.zcta5_clipped', 'us.census.tiger.zcta5_clipped', '2014'),
+    ('us.census.tiger.block_group_clipped', 'us.census.tiger.block_group_clipped', '2014'),
 ]
 
 unique_tables = set()

scripts/requirements.txt

@@ -0,0 +1,3 @@
+requests
+nose
+nose_parameterized