kopia lustrzana https://github.com/mkdryden/telegram-stats-bot
stats: Display error message if counts query empty
rodzic
4fbdb8fdab
commit
39fb86c7e4
|
@ -18,6 +18,7 @@ Fixed
|
||||||
- Remove @ from random message to avoid pinging users
|
- Remove @ from random message to avoid pinging users
|
||||||
- Allow quotes in lquery parameters
|
- Allow quotes in lquery parameters
|
||||||
- Zero-fill days without data for history
|
- Zero-fill days without data for history
|
||||||
|
- Display error message if counts query empty
|
||||||
|
|
||||||
---------------------
|
---------------------
|
||||||
`0.4.0`_ - 2021-06-06
|
`0.4.0`_ - 2021-06-06
|
||||||
|
|
|
@ -133,7 +133,8 @@ class StatsRunner(object):
|
||||||
with self.engine.connect() as con:
|
with self.engine.connect() as con:
|
||||||
con.execute(query, sql_dict)
|
con.execute(query, sql_dict)
|
||||||
|
|
||||||
def get_chat_counts(self, n: int = 20, lquery: str = None, mtype: str = None, start: str = None, end: str = None) -> Tuple[str, None]:
|
def get_chat_counts(self, n: int = 20, lquery: str = None, mtype: str = None, start: str = None, end: str = None)\
|
||||||
|
-> Tuple[Union[str, None], Union[None, BytesIO]]:
|
||||||
"""
|
"""
|
||||||
Get top chat users
|
Get top chat users
|
||||||
:param lquery: Limit results to lexical query (&, |, !, <n>)
|
:param lquery: Limit results to lexical query (&, |, !, <n>)
|
||||||
|
@ -179,6 +180,9 @@ class StatsRunner(object):
|
||||||
with self.engine.connect() as con:
|
with self.engine.connect() as con:
|
||||||
df = pd.read_sql_query(query, con, params=sql_dict, index_col='from_user')
|
df = pd.read_sql_query(query, con, params=sql_dict, index_col='from_user')
|
||||||
|
|
||||||
|
if len(df) == 0:
|
||||||
|
return "No matching messages", None
|
||||||
|
|
||||||
user_df = pd.Series(self.users, name="user")
|
user_df = pd.Series(self.users, name="user")
|
||||||
user_df = user_df.apply(lambda x: x[0]) # Take only @usernames
|
user_df = user_df.apply(lambda x: x[0]) # Take only @usernames
|
||||||
df = df.join(user_df)
|
df = df.join(user_df)
|
||||||
|
|
Ładowanie…
Reference in New Issue