django1/django/db/migrations/optimizer.py

64 lines
2.8 KiB
Python

class MigrationOptimizer:
"""
Powers the optimization process, where you provide a list of Operations
and you are returned a list of equal or shorter length - operations
are merged into one if possible.
For example, a CreateModel and an AddField can be optimized into a
new CreateModel, and CreateModel and DeleteModel can be optimized into
nothing.
"""
def optimize(self, operations, app_label=None):
"""
Main optimization entry point. Pass in a list of Operation instances,
get out a new list of Operation instances.
Unfortunately, due to the scope of the optimization (two combinable
operations might be separated by several hundred others), this can't be
done as a peephole optimization with checks/output implemented on
the Operations themselves; instead, the optimizer looks at each
individual operation and scans forwards in the list to see if there
are any matches, stopping at boundaries - operations which can't
be optimized over (RunSQL, operations on the same field/model, etc.)
The inner loop is run until the starting list is the same as the result
list, and then the result is returned. This means that operation
optimization must be stable and always return an equal or shorter list.
The app_label argument is optional, but if you pass it you'll get more
efficient optimization.
"""
# Internal tracking variable for test assertions about # of loops
self._iterations = 0
while True:
result = self.optimize_inner(operations, app_label)
self._iterations += 1
if result == operations:
return result
operations = result
def optimize_inner(self, operations, app_label=None):
"""
Inner optimization loop.
"""
new_operations = []
for i, operation in enumerate(operations):
# Compare it to each operation after it
for j, other in enumerate(operations[i + 1:]):
in_between = operations[i + 1:i + j + 1]
result = operation.reduce(other, in_between, app_label)
if isinstance(result, list):
# Optimize! Add result, then remaining others, then return
new_operations.extend(result)
new_operations.extend(in_between)
new_operations.extend(operations[i + j + 2:])
return new_operations
if not result:
# We can't optimize across `other`.
new_operations.append(operation)
break
else:
new_operations.append(operation)
return new_operations