Updating Objects on a Shelve

Now for one last script: let’s write a program that updates an instance (record) each time it runs, to prove the point that our objects really are persistent (i.e., that their current values are available every time a Python program runs). The following file, updatedb.py, prints the database and gives a raise to one of our stored objects each time. If you trace through what’s going on here, you’ll notice that we’re getting a lot of utility “for free”—printing our objects automatically employs the general __str__ overloading method, and we give raises by calling the giveRaise method we wrote earlier. This all “just works” for objects based on OOP’s inheritance model, even when they live in a file:

# File updatedb.py: update Person object on database

import shelve
db = shelve.open('persondb')               # Reopen shelve with same filename

for key in sorted(db):                     # Iterate to display database objects
    print(key, '\t=>', db[key])            # Prints with custom format

sue = db['Sue Jones']                      # Index by key to fetch
sue.giveRaise(.10)                         # Update in memory using class method
db['Sue Jones'] = sue                      # Assign to key to update in shelve
db.close()                                 # Close after making changes

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Because this script prints the database when it starts up, we have to run it a few times to see our objects change. Here it is in action, displaying all records and increasing sue’s pay each time it’s run (it’s a pretty good script for sue...):

c:\misc> updatedb.py
Bob Smith       => [Person: job=None, name=Bob Smith, pay=0]
Sue Jones       => [Person: job=dev, name=Sue Jones, pay=100000]
Tom Jones       => [Manager: job=mgr, name=Tom Jones, pay=50000]

c:\misc> updatedb.py
Bob Smith       => [Person: job=None, name=Bob Smith, pay=0]
Sue Jones       => [Person: job=dev, name=Sue Jones, pay=110000]
Tom Jones       => [Manager: job=mgr, name=Tom Jones, pay=50000]

c:\misc> updatedb.py
Bob Smith       => [Person: job=None, name=Bob Smith, pay=0]
Sue Jones       => [Person: job=dev, name=Sue Jones, pay=121000]
Tom Jones       => [Manager: job=mgr, name=Tom Jones, pay=50000]

c:\misc> updatedb.py
Bob Smith       => [Person: job=None, name=Bob Smith, pay=0]
Sue Jones       => [Person: job=dev, name=Sue Jones, pay=133100]
Tom Jones       => [Manager: job=mgr, name=Tom Jones, pay=50000]

Again, what we see here is a product of the shelve and pickle tools we get from Python, and of the behavior we coded in our classes ourselves. And once again, we can verify our script’s work at the interactive prompt (the shelve’s equivalent of a database client):

c:\misc> python
>>> import shelve
>>> db = shelve.open('persondb')             # Reopen database
>>> rec = db['Sue Jones']                    # Fetch object by key
>>> print(rec)
[Person: job=dev, name=Sue Jones, pay=146410]
>>> rec.lastName()
'Jones'
>>> rec.pay
146410

For another example of object persistence in this book, see the sidebar in Chapter 30 titled Why You Will Care: Classes and Persistence. It stores a somewhat larger composite object in a flat file with pickle instead of shelve, but the effect is similar. For more details on both pickles and shelves, see other books or Python’s manuals.

 

[62] Yes, we use “shelve” as a noun in Python, much to the chagrin of a variety of editors I’ve worked with over the years, both electronic and human.