A database like sqlite3 (built into the stdlib for almost all builds of Python) is a possible solution, but it's a pretty major change. Instead of just writing this:
dial(phone_numbers[person])
… you have to write this:
cur = db.execute('SELECT number FROM phone_numbers WHERE person=?', (person_id,)) dial(cur.fetchone()[0])
Fortunately, there's a much simpler answer: the dbm family of modules. It gives you a simple dict-like interface, built on top of a simple key-value database. The data are kept on disk, using a hash table implementation optimized for on-disk storage (with in-memory caching), instead of an in-memory hash table. There are limits to it (see below), but in many cases it just works.
Unfortunately, it scares a lot of people away. If you search for "python dbm", the first thing you'll find is probably the docs for the Python 2.7 dbm module, which it says only supports Unix.
This is because all the modules shuffled around between 2.x and 3.x. Rest assured, you can use the dbm family on Windows, you just can't (usually) use the specific module that's called dbm on Python 2.7.
Limitations
A dbm database can only store strings, both as keys and values. (In fact, it only stores bytes, and by default uses your default encoding if you give it Unicode strings.)
If you want to store arbitrary (pickleable) Python object as value, but can live with strings for keys, see the shelve module.
If you need your keys to be something other than strings, then dbm may not be the answer. If you have a way to decorate and undecorate your values as strings that's unambiguous and efficient, you can write a wrapper… but often if you're getting that fancy, you need something better than dbm.
Generally, only one program can use a dbm database file at the same time. If you want to share data between processes, dbm is not the answer.
Despite all having the same API, the different implementations have different storage formats. Some of them may also use incompatible storage on different platforms. So, a dbm database is generally not portable between machines.
What does "dbm" mean, and is it Unix-only?
The actual library named dbm is Unix-only—as in real, licensed, 1970s-style AT&T Unix; not linux or even OS X. Nobody uses it today, but it's the ancestor of a whole family of simple key-value databases used today, like ndbm, gdbm, and Berkeley DB, and that family is often collectively called dbm.
In Python 3.x, dbm is a package in the standard library that includes and wraps up all of the database modules.
In Python 2.x, those modules were all scattered around the stdlib. The top-level wrapper module is named anydbm, and the name dbm is used for the specific ndbm implementation.
Berkeley DB
Berkeley DB is a more powerful replacement for dbm. It has a lot of features dbm doesn't, but also a completely different API. Versions up to 1.x were BSD-licensed; later versions were Sleepycat-licensed, and then dual-licensed as AGPL or commercial. Also, each major version has changed the API considerably. So, many people have stuck with older versions. 1.85 is still in use today—it's available for Windows, and built-in on Macs.
What does Python support?
If you use the wrappers, your code will work on every platform. But it may be using the "dumb" implementation on some. If this matters to you, you'll have to know what's available so you can decide what you want to use.
Python 2.7 and 3.4 mostly support the same libraries, but under different names. I'll give the 3.x names first, separated by a slash where relevant.
In general, the wrappers around C libraries are present if the library was present when you built Python. But of course you probably don't build Python, you just install it from a binary, or it comes with your OS. The official Windows installers don't contain any of the implementations except dumb. The official Mac installers contain dumb and ndbm. Apple's pre-installed Python versions contain dumb, ndbm, and bsddb185. Linux distros may include any of dumb, ndbm, gdbm, bsddb185, and bsddb, and will usually have packages for any they don't include; you'll have to check your distro. Similarly for FreeBSD, Solaris, etc. And if you use a third-party installation like ActiveState or Enthought, you'll have to check the documentation.
- dbm / anydbm (and whichdb). Wrapper that uses the appropriate module for existing files, and the best available module for new ones.
- dbm.dumb / dumbdbm. Simple, pure-Python implementation that's always available.
- dbm.ndbm / dbm. Wrapper around ndbm, or around gdbm's ndbm-compat mode.
- dbm.gnu / gdbm. Wrapper around gdbm.
- bsddb: Obsolete wrapper around Berkeley DB 1.x-4.x, deprecated since 2.6. Does not provide a dbm-style API, but the dbhash module wraps it with one. You probably don't want this.
- bsddb185: Third-party (but you may have it pre-installed) wrapper around Berkeley DB 1.85. Includes the dbhash-style wrapper to provide a dbm-style API.
- pybsddb: Third-party wrapper around Berkeley DB 5.0+. Includes the dbhash-style wrapper to provide a dbm-style API.
So, what should you use? That depends on a whole lot of factors, but here are some rough rules of thumb:
- If you don't need to support Windows, or dumb is fast enough, just use dbm/anydbm's generic wrappers and don't worry about it.
- If you aren't distributing your project, or are willing to dual-license your open source project as AGPL, or to buy a license for your commercial project, consider Berkeley DB 5.0+ and pybsddb.
- If you don't mind compiling Python yourself on Windows, consider ndbm.
- Otherwise, consider Berkeley DB 1.85 and bsddb185.
You might also want to look at third-party Python bundles like ActiveState to see if they can guarantee a better-than-dumb dbm on every platform you care about.
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