def test_similar_runs(root, rows_csv, **unused):
rows = load_rows_csv(rows_csv)
header = rows.pop(0)
try:
id_pos = header.index('_id')
except ValueError:
id_pos = None
rows = rows[0:10]
for row in rows:
row.pop(id_pos)
with tempdir(cleanup_on_error=CLEANUP_ON_ERROR):
with loom.preql.get_server(root, debug=True) as preql:
search_csv = 'search.csv'
preql.similar(rows, result_out=search_csv)
def test_similar_runs(root, rows_csv, **unused):
rows = load_rows_csv(rows_csv)
header = rows.pop(0)
try:
id_pos = header.index('_id')
except ValueError:
id_pos = None
rows = rows[0:10]
for row in rows:
row.pop(id_pos)
with tempdir(cleanup_on_error=CLEANUP_ON_ERROR):
with loom.preql.get_server(root, debug=True) as preql:
search_csv = 'search.csv'
preql.similar(rows, result_out=search_csv)
def test_search_runs(root, rows_csv, **unused):
rows = load_rows_csv(rows_csv)
header = rows.pop(0)
try:
id_pos = header.index('_id')
except ValueError:
id_pos = None
rows = rows[0:10]
with tempdir(cleanup_on_error=CLEANUP_ON_ERROR):
with loom.preql.get_server(root, debug=True) as preql:
for i, row in enumerate(rows):
row.pop(id_pos)
search_csv = 'search.{}.csv'.format(i)
preql.search(row, result_out=search_csv)
open(search_csv).read()
def test_search_runs(root, rows_csv, **unused):
rows = load_rows_csv(rows_csv)
header = rows.pop(0)
try:
id_pos = header.index('_id')
except ValueError:
id_pos = None
rows = rows[0:10]
with tempdir(cleanup_on_error=CLEANUP_ON_ERROR):
with loom.preql.get_server(root, debug=True) as preql:
for i, row in enumerate(rows):
row.pop(id_pos)
search_csv = 'search.{}.csv'.format(i)
preql.search(row, result_out=search_csv)
open(search_csv).read()
def make_fully_observed_row(rows_csv):
rows = iter(load_rows_csv(rows_csv))
header = rows.next()
try:
id_pos = header.index('_id')
except ValueError:
id_pos = None
dense_row = ['' for _ in header]
for row in rows:
if not any(condition == '' for condition in dense_row):
if id_pos is not None:
dense_row.pop(id_pos)
return dense_row
for i, (condition, x) in enumerate(izip(dense_row, row)):
if condition == '':
dense_row[i] = x
raise SkipTest('no dense row could be constructed')
def make_fully_observed_row(rows_csv):
rows = iter(load_rows_csv(rows_csv))
header = rows.next()
try:
id_pos = header.index('_id')
except ValueError:
id_pos = None
dense_row = ['' for _ in header]
for row in rows:
if not any(condition == '' for condition in dense_row):
if id_pos is not None:
dense_row.pop(id_pos)
return dense_row
for i, (condition, x) in enumerate(izip(dense_row, row)):
if condition == '':
dense_row[i] = x
raise SkipTest('no dense row could be constructed')
