def extract_rewrites(data):
nls, cms = data
group_pairs_by_nl = {}
for nl, cm in zip(nls, cms):
nl = nl.strip()
cm = cm.strip()
if nl.lower() == "na":
continue
if not nl:
continue
if not cm:
continue
nl_temp = ' '.join(data_tools.basic_tokenizer(nl.decode('utf-8')))
if not nl_temp in group_pairs_by_nl:
group_pairs_by_nl[nl_temp] = {}
cm_temp = data_tools.cmd2template(cm)
if not cm_temp in group_pairs_by_nl[nl_temp]:
group_pairs_by_nl[nl_temp][cm_temp] = collections.defaultdict(int)
group_pairs_by_nl[nl_temp][cm_temp][cm] += 1
merged = set()
nls = group_pairs_by_nl.keys()
for i in xrange(len(nls)):
nl = nls[i]
cm_set = set(group_pairs_by_nl[nl].keys())
for j in xrange(i+1, len(nls)):
nl2 = nls[j]
cm_set2 = set(group_pairs_by_nl[nl2].keys())
if len(cm_set & cm_set2) >= 2:
for cm_temp in cm_set:
if not cm_temp in group_pairs_by_nl[nl2]:
group_pairs_by_nl[nl2][cm_temp] = \
group_pairs_by_nl[nl][cm_temp]
else:
for cm in group_pairs_by_nl[nl][cm_temp]:
group_pairs_by_nl[nl2][cm_temp][cm] += \
group_pairs_by_nl[nl][cm_temp][cm]
merged.add(i)
bash_paraphrases = {}
for i in xrange(len(nls)):
if i in merged:
continue
bash_paraphrases[nls[i]] = group_pairs_by_nl[nls[i]]
with DBConnection() as db:
db.create_schema()
for nl, cm_temps in sorted(bash_paraphrases.items(),
key=lambda x: len(x[1]), reverse=True):
if len(cm_temps) >= 2:
for cm_temp1 in cm_temps:
for cm_temp2 in cm_temps:
if cm_temp1 == cm_temp2:
continue
if not db.exist_rewrite((cm_temp1, cm_temp2)):
db.add_rewrite((cm_temp1, cm_temp2))
print("* {} --> {}".format(cm_temp1, cm_temp2))
print()
def group_data_by_cm(dataset, use_bucket=False, use_cm_temp=True):
if use_bucket:
dataset = reduce(lambda x,y: x + y, dataset)
grouped_dataset = {}
for i in xrange(len(dataset)):
nl_str, cm_str, nl, search_history = dataset[i]
if use_cm_temp:
cm_template = data_tools.cmd2template(cm_str)
else:
cm_template = cm_str
if cm_template in grouped_dataset:
grouped_dataset[cm_template][0].append(nl_str)
grouped_dataset[cm_template][1].append(cm_str)
grouped_dataset[cm_template][2].append(nl)
grouped_dataset[cm_template][3].append(search_history)
else:
grouped_dataset[cm_template] = [[nl_str], [cm_str], [nl], [search_history]]
return grouped_dataset
