AFAIU and from docs, RealDictCursor is a specialized DictCursor that enables to access columns only from keys (aka columns name), whereas DictCursor enables to access data both from keys or index number.
I was wondering why RealDictCursor has been implemented if DictCursor offers more flexibility? Is it performance-wise (or memory-wise) so different (in favor of RealDictCursor I imagine...)?
In other words, what are RealDictCursor use cases vs DictCursor?
RealDictCursor is a cursor that uses a real dict as the base type for rows. This cursor doesn't allow normal indexing to fetch data. data can be fetched only with the help of keys of column names of the table.
extras – Miscellaneous goodies for Psycopg 2. This module is a generic place used to hold little helper functions and classes until a better place in the distribution is found.
The main advantage of real dictionary cursor is the easiness to get a query output as json.
Compare:
with psycopg2.connect('dbname=test') as connection:
with connection.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute("select * from my_table")
print(json.dumps(cursor.fetchall()))
versus
with psycopg2.connect('dbname=test') as connection:
with connection.cursor() as cursor:
cursor.execute("select * from my_table")
columns = [desc[0] for desc in cursor.description]
real_dict = [dict(zip(columns, row)) for row in cursor.fetchall()]
print(json.dumps(real_dict))
There is no important difference between these options when it comes to performance.
You cannot get an expected json using json.dumps(cursor.fetchall())
for regular or dictionary-like cursors and need the conversion showed above. On the other hand, real dictionary cursor produces a much larger result so you should not use it if you really do not need it.
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