Memoizing SQL queries

Say I have a function that runs a SQL query and returns a dataframe:

import pandas.io.sql as psql
import sqlalchemy

query_string = "select a from table;"

def run_my_query(my_query):
    # username, host, port and database are hard-coded here
    engine = sqlalchemy.create_engine('postgresql://{username}@{host}:{port}/{database}'.format(username=username, host=host, port=port, database=database))

    df = psql.read_sql(my_query, engine)
    return df

# Run the query (this is what I want to memoize)
df = run_my_query(my_query)

I would like to:

Be able to memoize my query above with one cache entry per value of query_string (ie per query)

Be able to force a cache reset on demand (eg based on some flag), eg so that I can update my cache if I think that the database has changed.

How can I do this with joblib, jug?

---

Yes, you can do this with joblib (this example basically pastes itself):

>>> from tempfile import mkdtemp
>>> cachedir = mkdtemp()

>>> from joblib import Memory
>>> memory = Memory(cachedir=cachedir, verbose=0)

>>> @memory.cache
... def run_my_query(my_query)
...     ...
...     return df

You can clear the cache using memory.clear() .

---

Note you could also use lru_cache or even "manually" with a simple dict:

def run_my_query(my_query, cache={})
    if my_query in cache:
        return cache[my_query]
    ...
    cache[my_query] = df
    return df

You could clear the cache with run_my_query.func_defaults[0].clear() (not sure I'd recommend this though, just thought it was a fun example).

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