import yaml

import time

import pprint

from oaklib import get_adapter

NULL_VALS = ['', 'Not mentioned', 'none mentioned', 'Not mentioned in the text',

'No genes mentioned', 'No genes mentioned in the text.']

lines = []

# adapter = get_adapter("sqlite:obo:CHEBI")

adapter = get_adapter("sqlite:obo:MONDO")

# output_file = "output_2000_0719.yaml"

# output_file = "output_100_0817.yaml"

# output_file = "output_100_0818.yaml"

output_file = "output_partial_50_0911.yaml"

def tripleprint(dict):

print(curr)

def forprint(lst):

for elem in lst:

print(elem)

def nprint(lst, n):

for i in range(n):

print(lst[i])

def sleepprint(lst):

for elem in lst:

print(elem)

time.sleep(0.5)

def enumprint(lst):

for index, elem in enumerate(lst):

print(str(index + 1) + ":\t" + str(elem))

with open(output_file, "r") as file:

to_print = False

perpetuators = tuple([" subject:", " predicate:", " object:", " "])

# perpetuators = tuple([" - subject:", " predicate:", " object:"])

for line in file:

line = line.strip("\n")

if line.startswith("extracted_object:"):

# if line.startswith(" disease_cellular_process_relationships:") and not line.startswith(" disease_cellular_process_relationships: "):

to_print = True

elif not line.startswith(perpetuators):

to_print = False

if to_print:

lines.append(line)

cleaned_lines = [x for x in list(filter(lambda elem: not(elem.isspace()), lines)) if x.strip()]

cleaned_lines = [x for x in cleaned_lines if x != "extracted_object: {}"]

i = 1

while i < len(cleaned_lines):

if cleaned_lines[i].startswith(" "):

cleaned_lines[i-1] += " "

cleaned_lines[i-1] += cleaned_lines[i][4:]

del cleaned_lines[i]

else:

i += 1

header = "extracted_object"

# header = " disease_cellular_process_relationships:"

i = 0

while i < len(cleaned_lines):

if cleaned_lines[i].startswith(header):

for index, elem in enumerate(cleaned_lines[i+1:i+4]):

if elem.startswith(header):

next_index = i + 1 + index

del cleaned_lines[i:next_index]

i -= 1

i += 1

grouped_lines = [cleaned_lines[n:n+4] for n in range(0, len(cleaned_lines), 4)]

# trimmed_dict = {"genes": [], "relationships": [], "exposures": []}

trimmed_dict = {"diseases": [], "relationships": [], "cellular processes": []}

for group in grouped_lines:

group.pop(0)

for group in grouped_lines:

subject = group[0].split(":", 1)[1].strip()

relation = group[1].split(":", 1)[1].strip()

object = group[2].split(":", 1)[1].strip()

# trimmed_dict["genes"].append(subject)

# trimmed_dict["relationships"].append(relation)

# trimmed_dict["exposures"].append(object)

trimmed_dict["diseases"].append(subject)

trimmed_dict["relationships"].append(relation)

trimmed_dict["cellular processes"].append(object)

for key, value in trimmed_dict.copy().items():

for i, elem in enumerate(value):

if elem.lower() in (val.lower() for val in NULL_VALS):

for key, value in trimmed_dict.items():

del value[i]

# subjects_with_chebi = []

# objects_with_ecto = []

subjects_with_mondo = []

key = next(iter(trimmed_dict))

for i in range(len(trimmed_dict[key])):

curr = []

for value in trimmed_dict.values():

curr.append(value[i])

# subjects_with_chebi.append(curr)

subjects_with_mondo.append(curr)

# objects_with_ecto.append(curr)

# subjects_with_chebi = [x for x in subjects_with_chebi if x[0].startswith("CHEBI:")]

subjects_with_mondo = [x for x in subjects_with_mondo if x[0].startswith("MONDO:")]

mondo_go = [x for x in subjects_with_mondo if x[2].startswith("GO:")]

# objects_with_ecto = [x for x in objects_with_ecto if x[2].startswith("ECTO:")]

forprint(mondo_go)

subjects_with_names = []

# for elem in subjects_with_chebi:

for elem in subjects_with_mondo:

curr = elem[:]

curr[0] = adapter.label(curr[0])

subjects_with_names.append(curr)

# forprint(subjects_with_names)