def start(message): """ Show a keyboard for user's """ user_id = message.from_user.id kb, txt = utils.keyboard(user_id) bot.send_message(message.chat.id, text = txt, reply_markup = kb)
def anketa_skip_comment(bot, update, user_data):
user = get_or_create_user(db, update.effective_user, update.message)
text = """
<b>Имя Фамилия:</b> {anketa_name}
<b>Оценка:</b> {anketa_rating}""".format(**user_data)
update.message.reply_text(text, reply_markup=keyboard(),
parse_mode=ParseMode.HTML)
return ConversationHandler.END
def start(bot, update):
"""Send a message when the command /start is issued."""
# print(update.message)
user = get_or_create_user(db, update.effective_user, update.message)
# print(user)
text = 'Вызван /start, ВНИМАНИЕ БОТ НЕ ЗАСТРАХОВАН ОТ ВВОДА ВСЯКОЙ ХУЙНИ!'
game_dict[update.message.chat.id] = ORIG_CITIES.copy(
) # Формируем словарь с городами в момент начала пользования чатом,
# используя заранее заготовленный оригинал
update.message.reply_text(
text,
reply_markup=keyboard()) # можно добавить reply_markup в каждую строку
def draw_board(bot, update):
global board
for i in range(3):
update.message.reply_text(f"| {board[0 + i * 3]} | {board[1 + i * 3]} | {board[2 + i * 3]} |",
reply_markup=keyboard())
def consolidate_results(n_workers,
task_iterator,
fname,
result_locks,
debug=False):
# Create a helper for extracting files and making backups
backups, all_results = [], []
def _append_results(fname,
move_existing=True,
all_results=all_results,
backups=backups,
lock=None):
if os.path.exists(fname):
if (lock is None) or (lock.acquire()):
# Get results if they exist
store = pd.HDFStore(fname)
if '/results' in store.keys():
all_results.append(store['results'])
store.close()
# Move the file to a backup if required
if move_existing:
bak_fname = fname + '.bak'
# print('\nDoes %s already exist? %r\n' % (bak_fname,os.path.exists(bak_fname)))
# if os.path.exists(bak_fname):
# print('\'%s\' already exists.' % bak_fname)
# os.remove(bak_fname)
try:
os.rename(fname, bak_fname)
except Exception as e:
os.remove(bak_fname)
os.rename(fname, bak_fname)
backups.append(bak_fname)
# Release the lock if one was specified
if not (lock is None):
lock.release()
# Get existing completed results
_append_results(fname, move_existing=False)
# Get existing incomplete results
i_fname = fname.replace('.h5', '.incomplete.h5')
_append_results(i_fname, move_existing=False)
# Get results from each worker's record file
for wid, lock in enumerate(result_locks):
w_fname = fname.replace('.h5', '.worker_%d.h5' % wid)
_append_results(w_fname, lock=lock)
# Exit if there are no results
if len(all_results) == 0:
return
# Add the results to a single, new dataframe
df = pd.concat(all_results, ignore_index=True)
# Split the results into samples for completed and incompleted trials
gb = df.groupby(['seed']).size() == task_iterator.n_tasks_per_trial()
gb = gb.reset_index(level=['seed'])
gb = gb.rename(columns={0: '_is_complete'})
df = df.merge(gb, on=['seed'])
cresults = df.loc[df._is_complete, df.columns != '_is_complete']
iresults = df.loc[~df._is_complete, df.columns != '_is_complete']
if any(iresults.groupby(['seed', 'name', 'tid', 'pid']).size() > 1):
print([len(v) for v in all_results])
with pd.HDFStore(i_fname.replace('incomplete', 'reference')) as store:
print(i_fname.replace('incomplete', 'reference'))
store.put('results', iresults)
utils.keyboard()
else:
# Save completed trials
if len(cresults) > 0:
with pd.HDFStore(fname) as store:
store.put('results', cresults)
# Save incomplete trials
if len(iresults) > 0:
with pd.HDFStore(i_fname) as store:
store.put('results', iresults)
else:
if os.path.exists(i_fname):
os.remove(i_fname)
# Delete backups
for bak in backups:
os.remove(bak)
# Print a debug message if requred
if debug:
print('...............................................')
# with pd.HDFStore(fname) as store:
# if '/results' in store.keys():
# print('Completed results:')
# print( store['results'].groupby('seed').size())
# else:
# print('No complete results.')
# print()
with pd.HDFStore(i_fname) as store:
if '/results' in store.keys():
print('Incomplete results:')
print(store['results'].groupby('seed').size())
else:
print('No incomplete results.')
print('...............................................')