The documentation is difficult to find, and once you find it, it’s pretty abysmal. Here’s what I’ve found over the past 3 hours.
You need to install ibm_db
using pip
, as follows:
pip install ibm_db
You’ll want to create a connection object. The documentation is here.
Here’s what I wrote:
from ibm_db import connect
# Careful with the punctuation here - we have 3 arguments.
# The first is a big string with semicolons in it.
# (Strings separated by only whitespace, newlines included,
# are automatically joined together, in case you didn't know.)
# The last two are emptry strings.
connection = connect('DATABASE=<database name>;'
'HOSTNAME=<database ip>;' # 127.0.0.1 or localhost works if it's local
'PORT=<database port>;'
'PROTOCOL=TCPIP;'
'UID=<database username>;'
'PWD=<username password>;', '', '')
Next you should know that commands to ibm_db
never actually give you results. Instead, you need to call one of the fetch
methods on the command, repeatedly, to get the results. I wrote this helper function to deal with that.
def results(command):
from ibm_db import fetch_assoc
ret = []
result = fetch_assoc(command)
while result:
# This builds a list in memory. Theoretically, if there's a lot of rows,
# we could run out of memory. In practice, I've never had that happen.
# If it's ever a problem, you could use
# yield result
# Then this function would become a generator. You lose the ability to access
# results by index or slice them or whatever, but you retain
# the ability to iterate on them.
ret.append(result)
result = fetch_assoc(command)
return ret # Ditch this line if you choose to use a generator.
Now with that helper function defined, you can easily do something like get the information on all the tables in your database with the following:
from ibm_db import tables
t = results(tables(connection))
If you’d like to see everything in a given table, you could do something like this now:
from ibm_db import exec_immediate
sql="LIST * FROM " + t[170]['TABLE_NAME'] # Using our list of tables t from before...
rows = results(exec_immediate(connection, sql))
And now rows
contains a list
of rows from the 170th table in your database, where every row contains a dict
of column name: value.
Hope this all helps.