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else:
self.current_id_meta = 1
if spectra:
c.execute('SELECT max(id) FROM library_spectra')
last_id_spectra = c.fetchone()[0]
if last_id_spectra:
self.current_id_spectra = last_id_spectra + 1
else:
self.current_id_spectra = 1
if spectra_annotation:
c.execute('SELECT max(id) FROM library_spectra_annotation')
last_id_spectra_annotation = c.fetchone()[0]
if last_id_spectra_annotation:
self.current_id_spectra_annotation = last_id_spectra_annotation + 1
else:
self.current_id_spectra_annotation = 1"
156,"def _parse_files(self, msp_pth, chunk, db_type, celery_obj=False):
""""""Parse the MSP files and insert into database
Args:
msp_pth (str): path to msp file or directory [required]
db_type (str): The type of database to submit to (either 'sqlite', 'mysql' or 'django_mysql') [required]
chunk (int): Chunks of spectra to parse data (useful to control memory usage) [required]
celery_obj (boolean): If using Django a Celery task object can be used to keep track on ongoing tasks
[default False]
""""""
if os.path.isdir(msp_pth):
c = 0
for folder, subs, files in sorted(os.walk(msp_pth)):
for msp_file in sorted(files):
msp_file_pth = os.path.join(folder, msp_file)
if os.path.isdir(msp_file_pth) or not msp_file_pth.lower().endswith(('txt', 'msp')):
continue
print('MSP FILE PATH', msp_file_pth)
self.num_lines = line_count(msp_file_pth)
# each file is processed separately but we want to still process in chunks so we save the number
# of spectra currently being processed with the c variable
with open(msp_file_pth, ""r"") as f:
c = self._parse_lines(f, chunk, db_type, celery_obj, c)
else:
self.num_lines = line_count(msp_pth)
with open(msp_pth, ""r"") as f:
self._parse_lines(f, chunk, db_type, celery_obj)
self.insert_data(remove_data=True, db_type=db_type)"
157,"def _parse_lines(self, f, chunk, db_type, celery_obj=False, c=0):
""""""Parse the MSP files and insert into database
Args:
f (file object): the opened file object
db_type (str): The type of database to submit to (either 'sqlite', 'mysql' or 'django_mysql') [required]
chunk (int): Chunks of spectra to parse data (useful to control memory usage) [required]
celery_obj (boolean): If using Django a Celery task object can be used to keep track on ongoing tasks
[default False]
c (int): Number of spectra currently processed (will reset to 0 after that chunk of spectra has been
inserted into the database
""""""
old = 0
for i, line in enumerate(f):
line = line.rstrip()
if i == 0:
old = self.current_id_meta
self._update_libdata(line)
if self.current_id_meta > old:
old = self.current_id_meta
c += 1
if c > chunk:
if celery_obj:
celery_obj.update_state(state='current spectra {}'.format(str(i)),
meta={'current': i, 'total': self.num_lines})
print(self.current_id_meta)
self.insert_data(remove_data=True, db_type=db_type)
self.update_source = False
c = 0
return c"
158,"def _update_libdata(self, line):
""""""Update the library meta data from the current line being parsed
Args:
line (str): The current line of the of the file being parsed
""""""
####################################################
# parse MONA Comments line
####################################################
# The mona msp files contain a ""comments"" line that contains lots of other information normally separated
# into by """"
if re.match('^Comment.*$', line, re.IGNORECASE):