def test_remove_duplicate_rows(self):
# Expected values
test_tb = man.rmv_dups(self.tb41)
t_col1 = test_tb['col1']
t_col2 = test_tb['col2']
t_col3 = test_tb['col3']
self.assertEqual(len(t_col1), len(self.e_col41))
self.assertEqual(len(t_col2), len(self.e_col42))
self.assertEqual(len(t_col3), len(self.e_col43))
self.assertEqual(t_col1, self.e_col41)
self.assertEqual(t_col2, self.e_col42)
self.assertEqual(t_col3, self.e_col43)
def test_remove_duplicate_rows(self):
# Expected values
test_tb = man.rmv_dups(self.tb41)
t_col1 = test_tb['col1']
t_col2 = test_tb['col2']
t_col3 = test_tb['col3']
self.assertEqual(len(t_col1), len(self.e_col41))
self.assertEqual(len(t_col2), len(self.e_col42))
self.assertEqual(len(t_col3), len(self.e_col43))
self.assertEqual(t_col1, self.e_col41)
self.assertEqual(t_col2, self.e_col42)
self.assertEqual(t_col3, self.e_col43)
def atomic_query(query_str, tables):
'''
Does an atomic query using the provided tables
:param query_str: an atomic query is a valid query with one EMPRESTA and DE
:param tables: a dict of tb_name (keys): tables (values). Each table is a
dict of col_names (keys): col_entries (values)
:return: table (a dict), col_order (a list of col_names for printing)
'''
'''
if 'EMPRESTA pokemon_id DE pokemon' in query_str:
print(query_str)
'''
# Get list of intervals (start, end) to mark the start and end of sub-exprns
intervals = get_exprn_intervals(query_str)
# Get and label the sub-expressions: "keyword + [variables]"
sub_exprns = [query_str[itv[0]: itv[1]] for itv in intervals]
l_sub_exprns = label_exprns(sub_exprns)
'''
print('\nFor query: {0}'.format(query_str))
for label, exprn in l_sub_exprns.items():
print('{0}: {1}'.format(label, exprn))
'''
# Get the queried table names and columns
tnames = de(l_sub_exprns[' DE '])
cols, col_funcs = emp(l_sub_exprns['EMPRESTA '])
# Get the queried tables
tb_list = [tables.get(tname) for tname in tnames]
# Get the conditional subexpression if exists
onde = l_sub_exprns.get(' ONDE ', None)
if onde:
# eval_onde returns a dict {tname: table}
filtered_tbs = eval_onde(onde.replace('ONDE', '', 1).strip(), tables)
# Filter the tables by the conditions
tb_list = [filtered_tbs[tname] for tname in tnames]
# Finish off with executing EMPRESTA ... DE ...
# Do the string strip() here so that there won't be a case of ONDE being
# misinterpreted as DE
order = l_sub_exprns.get(' ORDENATELOS X ')
if order is not None:
# Order the tables if there is ORDENATELOS X
tb_list = order_cols(order.replace(' ORDENATELOS X ', ''),
tb_list)
# AGRUPATELOS
grp_line = l_sub_exprns.get(' AGRUPATELOS X ')
# TENIENDO
grp_fil_line = l_sub_exprns.get(' TENIENDO ')
# Add on the columns need for TENIENDO and AGRUPATELOS if they are not in
# the column list
new_cols = cols.copy()
if grp_line:
grp_col = grp_line.replace(' AGRUPATELOS X ', '').strip()
if grp_col not in new_cols:
new_cols.append(grp_col)
if grp_fil_line:
# split the line into var1, operator, var2
var1, oper, var2 = split_clauses(grp_fil_line.replace(' TENIENDO ', '')
.strip('() '))
if '(' in var1:
col_str = var1
else:
col_str = var2
# Assumes the var1 will be a function with column name
# Get the list of function names
func_keys = list(eva.FUNC.keys())
col_str, __ = [(strip_func(col_str), func) for func in func_keys
if func + '(' in col_str][0]
if col_str not in new_cols:
# Add the col if it is not in the list of columns
new_cols.append(col_str)
# Table list is reduced to a single table with all the columns stated in the
# cols (list)
result_tb = emp_de_two(tb_list, new_cols, col_funcs)
# Get groupings if grouping is not None
grouping = None
if grp_line:
grouping = get_grouping(grp_line.replace(' AGRUPATELOS X ', '').strip(),
result_tb)
if grp_fil_line:
# If there is a filter group condition, filter grouping
grouping = filter_grps(grp_fil_line.replace(' TENIENDO ', '')
.strip('() '), result_tb, grouping)
# Remove columns added for AGRUPATELOS and TENIENDO
result_tb = man.reduce_tb(result_tb, cols)
# Do the column functions on the result table
# result_tb = do_col_funcs(result_tb, col_funcs)
result_tb = do_col_funcs_two(result_tb, col_funcs, grouping)
# return result table and the cols order of the query
# If DIVERGENTE is true, remove duplicates
if col_funcs['DIVERGENTE']:
result_tb = man.rmv_dups(result_tb)
# Check for SOLO expression, if there is cut_off the rows
solo = l_sub_exprns.get(' SOLO ')
if solo is not None:
# Cut off rows
result_tb = cutoff_rows(solo.strip(' SOLO '), result_tb)
return result_tb, cols
