spreadname = 'Import Test Sheet'
rowsize = 2
colsize = 52
# load object SHOULD HANDLE ERRORS GRACEFULLY
print('Opening ' + data_file)
object_list = ReadJSON(data_file)
# find out what types of objects you have. use as worksheet names.
# also, change all json object values to strings
typelist = []
for json_object in object_list:
json_object = FlatJSON(json_object, keys)
typetemp = str(json_object['@type'][0])
typelist.append(typetemp)
for name, value in json_object.items():
if type(value) is list:
if value == []:
json_object[name] = ''
elif type(value[0]) is dict:
json_object[name] = str(value)
else:
json_object[name] = ', '.join(value)
elif (type(value) is int) | (type(value) is float):
json_object[name] = str(value)
typelist = list(set(typelist))
typelist.sort()
# get column headers based on schema fields
# get all relevant schema
# if object is found, check for differences and patch it if needed.
else:
# compare new object to old one, remove identical fields. Also, remove fields not present in schema. SHOULD INFORM OF THIS OPERATION, BUT NOT NEEDED WHEN SINGLE PATCH CODE EXISTS.
for key in new_object.keys():
if new_object.get(key) == old_object.get(key):
new_object.pop(key)
elif not old_object.get(key):
new_object.pop(key)
# if there are any different fields, patch them. SHOULD ALLOW FOR USER TO VIEW/APPROVE DIFFERENCES
if new_object:
# inform user of the updates
print(object_id + ' has updates.')
#print(new_object)
# patch each field to object individually
for key,value in new_object.items():
patch_single = {}
patch_single[key] = value
print(patch_single)
response = patch_ENCODE(object_id,patch_single,keys)
# inform user there are no updates
else:
print(object_id + ' has no updates.')
# search criteria
search_value_string = 'GM12893'
search_key_string = 'biosample_term_name'
# file name for saved objects
find_file = 'find.json'
# retrieve the relevant objects
master_objects = ElasticSearchJSON(server,query,object_type,hitnum)
# flatten objects and select based on search criteria
object_list = []
for master_object in master_objects:
master_object = FlatJSON(master_object,keys)
for key,value in master_object.items():
if search_key_string in str(key):
#print(key)
if type(value) is unicode:
if search_value_string in str(value):
print('Object ' + master_object[u'accession'] + ' Selected. ' + str(key) + ' - ' + value)
object_list.append(master_object)
break
if type(value) is list:
for entry in value:
if search_value_string in str(entry):
print('Object ' + master_object[u'accession'] + ' Selected. ' + str(key) + ' - ' + entry)
object_list.append(master_object)
break
print(str(len(object_list)) + ' of ' + str(len(master_objects)) + ' Objects Found. Saved to ' + find_file + '.')
# post the new object(s). SHOULD HANDLE ERRORS GRACEFULLY
response = new_ENCODE(object_collection, new_object, keys)
# if object is found, check for differences and patch it if needed.
else:
# compare new object to old one, remove identical fields. Also, remove fields not present in schema. SHOULD INFORM OF THIS OPERATION, BUT NOT NEEDED WHEN SINGLE PATCH CODE EXISTS.
for key in new_object.keys():
if new_object.get(key) == old_object.get(key):
new_object.pop(key)
elif not old_object.get(key):
new_object.pop(key)
# if there are any different fields, patch them. SHOULD ALLOW FOR USER TO VIEW/APPROVE DIFFERENCES
if new_object:
# inform user of the updates
print(object_id + ' has updates.')
#print(new_object)
# patch each field to object individually
for key, value in new_object.items():
patch_single = {}
patch_single[key] = value
print(patch_single)
response = patch_ENCODE(object_id, patch_single, keys)
# inform user there are no updates
else:
print(object_id + ' has no updates.')
spreadname = 'Import Test Sheet'
rowsize = 2
colsize = 52
# load object SHOULD HANDLE ERRORS GRACEFULLY
print('Opening ' + data_file)
object_list = ReadJSON(data_file)
# find out what types of objects you have. use as worksheet names.
# also, change all json object values to strings
typelist = []
for json_object in object_list:
json_object = FlatJSON(json_object,keys)
typetemp = str(json_object['@type'][0])
typelist.append(typetemp)
for name,value in json_object.items():
if type(value) is list:
if value == []:
json_object[name] = ''
elif type(value[0]) is dict:
json_object[name] = str(value)
else:
json_object[name] = ', '.join(value)
elif (type(value) is int) | (type(value) is float):
json_object[name] = str(value)
typelist = list(set(typelist))
typelist.sort()
# get column headers based on schema fields
# get all relevant schema
