adds fixture gen script

scripts/generate_fixtures.py

@@ -0,0 +1,83 @@
+
+## This script generates all of the fixtures needed for running tests based on
+##   Data Observatory functions. It creates SQL dumps of a small amount of data
+##   and all of the metadata. To add more data, add a new tuple to the fixtures
+##   list
+
+
+## get sqldumpr from https://github.com/talos/carto-sqldumpr
+from sqldumpr import Dumpr
+
+def get_tablename_query(column_id, boundary_id, timespan):
+    """
+        given a column_id, boundary-id (us.census.tiger.block_group), and
+        timespan, give back the current table hash from the data observatory
+    """
+    q = """
+        SELECT t.tablename, geoid_ct.colname colname
+        FROM obs_table t,
+             obs_column_table geoid_ct,
+             obs_column_table data_ct
+        WHERE
+             t.id = geoid_ct.table_id AND
+             t.id = data_ct.table_id AND
+             geoid_ct.column_id =
+        (SELECT source_id
+         FROM obs_column_to_column
+         WHERE target_id = '{boundary_id}'
+         AND reltype = 'geom_ref'
+        ) AND
+        data_ct.column_id = '{column_id}' AND
+        timespan = '{timespan}'
+    """.replace('\n','')
+
+    return q.format(column_id=column_id,
+                    boundary_id=boundary_id,
+                    timespan=timespan)
+
+def select_star(tablename):
+    return "SELECT * FROM {}".format(tablename)
+
+cdb = Dumpr('observatory.cartodb.com','')
+
+metadata = ['obs_table', 'obs_column_table', 'obs_column', 'obs_column_tag', 'obs_tag', 'obs_column_to_column']
+
+fixtures = [
+    ('us.census.tiger.census_tract', 'us.census.tiger.census_tract', '2014'),
+    ('us.census.tiger.block_group', 'us.census.tiger.block_group', '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.zillow.AllHomes_Zhvi', 'us.census.tiger.zcta5', '2014-01'),
+]
+
+unique_tables = set()
+
+for f in fixtures:
+    tablename_query = get_tablename_query(*f)
+    tablename = cdb.query(tablename_query).json()['rows'][0]['tablename']
+    colname = cdb.query(tablename_query).json()['rows'][0]['colname']
+    table_colname = (tablename, colname, )
+    if table_colname not in unique_tables:
+        print table_colname
+        unique_tables.add(table_colname)
+
+print unique_tables
+
+with open('src/pg/test/fixtures/load_fixtures.sql', 'w') as outfile:
+    with open('src/pg/test/fixtures/drop_fixtures.sql', 'w') as dropfiles:
+        outfile.write('SET client_min_messages TO WARNING;\n\set ECHO none\n')
+        dropfiles.write('SET client_min_messages TO WARNING;\n\set ECHO none\n')
+        for tablename in metadata:
+            cdb.dump(select_star(tablename), tablename, outfile)
+            dropfiles.write('DROP TABLE IF EXISTS observatory.{};\n'.format(tablename))
+            print tablename
+
+        for tablename, colname in unique_tables:
+            print ' '.join([select_star(tablename), "WHERE {} LIKE '36047%'".format(colname)])
+            cdb.dump(' '.join([select_star(tablename), "WHERE {} LIKE '36047%'".format(colname)]),
+               tablename, outfile)
+            dropfiles.write('DROP TABLE IF EXISTS observatory.{};\n'.format(tablename))