I have a dataset stored locally in an sqlite3 database. I extracted a column, performed some operations and now want to replace ALL of the values in the database column. How can I do this?
The length of the column and the list are guaranteed to be the same length. I simply want to update the table with the new values. Is there an easy way to do this all at once?
Using python 2.7
Edited to add:
myList is a pandas series backed by a numpy array of dtype 'object'. The table column, myCol is text formatted.
In [1]: curr.execute('UPDATE test SET myCol= ?', myList)
---------------------------------------------------------------------------
ProgrammingError Traceback (most recent call last)
f:\python\<ipython-input-52-ea41c426502a> in <module>()
----> 1 curr.execute('UPDATE test SET myCol = ?', myList)
ProgrammingError: Incorrect number of bindings supplied. The current statement uses 1, and there are 401125 supplied.
Use the .executemany()
method instead:
curr.executemany('UPDATE test SET myCol= ?', myList)
However, myList
must be a sequence of tuples here. If it is not, a generator expression will do to create these tuples:
curr.executemany('UPDATE test SET myCol= ?', ((val,) for val in myList))
Demonstration (with insertions):
>>> import sqlite3
>>> conn=sqlite3.connect(':memory:')
>>> conn.execute('CREATE TABLE test (myCol)')
<sqlite3.Cursor object at 0x10542f1f0>
>>> conn.commit()
>>> myList = ('foo', 'bar', 'spam')
>>> conn.executemany('INSERT into test values (?)', ((val,) for val in myList))
<sqlite3.Cursor object at 0x10542f180>
>>> list(conn.execute('select * from test'))
[(u'foo',), (u'bar',), (u'spam',)]
Note that for an UPDATE
statement, you have to have a WHERE
statement to identify what row to update. An UPDATE
without a WHERE
filter will update all rows.
Make sure your data has a row identifier to go with it; in this case it may be easier to use named parameters instead:
my_data = ({id=1, value='foo'}, {id=2, value='bar'})
cursor.executemany('UPDATE test SET myCol=:value WHERE rowId=:id', my_data)
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