def deleterows(self): # delete rows
if self.mode == "live":
archive = False
if self.mode == "archive":
archive = True
account = self.active
model = self.getmodel()
# get selected entry ids
entry_ids, source_rows = self.selectedids()
if len(entry_ids) > 0:
# retrieve cache data
cache = self.cache["index"][account]["inbox"][self.mode]
# use entry_ids to obtain cache row #'s
df = cache['data']
cache_rows = [int(df[df['entry_id'] == id].index[0]) for id in entry_ids]
# execute delete function in session
bridge.sess().delete_many(account, entry_ids, archive=archive)
# remove rows from cache
cache["data"].drop(cache_rows, axis=0, inplace=True)
cache["data"].reset_index(drop=True, inplace=True)
# remove rows from model
model.removeRows(cache["data"])
# refresh proxy model in view
self.filterModel.setFilterFixedString("")
def update(self):
extension = bridge.sess().update(gui=True)
for account in extension:
print(account)
test_model = self.cache["index"][account]["inbox"]["live"][
"object"]
print("...[PRE] model row count: {0}".format(
test_model.rowCount(None)))
if extension[account] is not None:
live_ext = extension[account]
#for row in extension[account]:
#live_ext.append(row)
#live_ext = pandas.DataFrame(live_ext)
#print(live_ext)
live_ext["archive_index"] = [
False for i in range(live_ext.shape[0])
]
live_cache = self.cache["index"][account]["inbox"]["live"]
live_cache["data"] = live_cache["data"].append(
live_ext, ignore_index=True)
live_model = self.cache["index"][account]["inbox"]["live"][
"object"]
live_model.addRows(live_cache["data"])
print("...[POST]: model row count: {0}".format(
live_model.rowCount(None)))
# refresh proxy model in view
self.filterModel.setFilterFixedString("")
def archiverows(self, entry_ids, source_rows, category):
if self.mode != "live": # if not in archive mode
return # do not continue
account = self.active
model = self.getmodel()
# retrieve cache data
live_cache = self.cache["index"][account]["inbox"]["live"]
arch_cache = self.cache["index"][account]["inbox"]["archive"]
# use entry_ids to obtain live cache row #'s
df = live_cache['data']
cache_rows = [
int(df[df['entry_id'] == id].index[0]) for id in entry_ids
]
# remove already-archived entry_ids from entry_ids & row_nums
for i in range(len(entry_ids) - 1, -1, -1):
id = entry_ids[i]
if id in list(arch_cache['data']['entry_id']):
entry_ids.pop(i)
cache_rows.pop(i)
source_rows.pop(i)
if len(entry_ids) > 0:
# execute archive function in session
bridge.sess().archive_many(account, entry_ids, category)
# update live cache's archive index
for n in cache_rows:
live_cache["data"].loc[n, "archive_index"] = category
# add archived rows to archive cache
# assume archive_index column = category column
arch_ext = pandas.DataFrame(
[live_cache["data"].loc[n].copy() for n in cache_rows])
# rename archive_index column to category
arch_ext.rename(columns={"archive_index": "category"},
inplace=True)
arch_cache["data"] = arch_cache["data"].append(arch_ext,
ignore_index=True)
# update live model archive index
model.addToArchive(live_cache["data"], source_rows)
# update archive model
archive_model = self.cache["index"][account]["inbox"]["archive"][
"object"]
archive_model.addRows(arch_cache["data"])
# refresh proxy model in view
self.filterModel.setFilterFixedString("")
# clear view selections
self.mainView.clearSelection()
def makemaster(self):
bridge.sess().makemaster()