An alternative to python's dumbdbm
SemiDBM is an attempt at improving the dumbdbm in the python standard library. It’s a slight improvement in both performance and in durability. It can be used anywhere dumbdbm would be appropriate to use, which is basically when you have no other options available. It uses a similar design to dumbdbm which means that it does inherit some of the same problems as dumbdbm, but it also attempts to fix problems in dumbdbm, which makes it only a semi-dumb dbm :)
Below are a list of some of the improvements semidbm makes over dumbdbm.
Index and Data File In Sync
Both the index file and the data file are updated on every write operation. This ensures that the index and data file are always in sync with each other. This was a problem with dumbdbm. The index file was out of sync with the data file as soon as updates were performed. With semidbm, any create, update, or delete command will be written out to the index file.
Index and Data File Compaction
Semidbm uses a similar (but not identical) append only file format. This has the potential to grow to large sizes as space is never reclaimed. Semidbm addresses this in two ways:
- Compact the index when instantiated. Semidbm will compact the index if necessary when the index is initially loaded.
- Add a compact() method that compacts the index and the data file. This allows a client to compact the db whenever they need.
Semidbm is significantly faster than dumbdbm (keep in mind both are pure python libraries) in just about every way. There is a profile.py script distributed with the source that will give you an idea of the performance differences between the various dbms (it will benchmark any dbm from the stdlib you have installed you can compare against dbm, gdbm, Berkeley DB, etc.)
- Not thread safe; can’t be accessed by multiple processes.
- No support for opening in read only mode.
- The entire index must fit in memory.