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# optimize-later [](https://travis-ci.org/quantum5/optimize-later) [](https://codecov.io/gh/quantum5/optimize-later)
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> Premature optimization is the root of all evil (or at least most of it) in programming.
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>
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> -- <cite>Donald Knuth</cite>
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Wouldn't it be nice to have something to tell you when optimization is really necessary?
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Enter `optimize-later`.
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Instead of trying to guess what code ought to be optimized, `optimize-later` times potentially
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slow blocks of code for you, and calls a user-specified function when it exceeds the specified
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time limit. This way, you only have to optimize code when speed becomes a problem.
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## Usage
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```python
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from optimize_later import optimize_later
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### Basic usage. These examples will call your global callback.
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with optimize_later('test_block', 0.2):
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# potentially slow block of code...
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time.sleep(1)
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# Automatic block names from file and source line (slightly slow).
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with optimize_later(0.2):
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# potentially slow block of code...
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time.sleep(1)
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# Always warn. Good for exceptional cases that you suspect should not happen.
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with optimize_later():
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# potentially slow block of code...
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time.sleep(1)
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# Also available as a decorator.
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@optimize_later('bad-function', 0.2)
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def function_name():
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# potentially slow function...
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time.sleep(1)
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# Will use module:function as block name, if you do not specify a name.
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# There is no performance penalty this way, as the function name can be easily detected.
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@optimize_later(0.2)
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def function_name():
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# potentially slow function...
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time.sleep(1)
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### Blocks.
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with optimize_later() as o:
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with o.block('block 1'):
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# When the time limit of whole block is exceeded, your report will contain
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# a detailed breakdown by sub-blocks executed. This allows you to pinpoint
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# which exact block is the culprit.
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time.sleep(1)
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# optimize-later will automatically generate a block name for you from file and
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# line number, with a slightly performance penalty.
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with o.block() as b:
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# You can also nest blocks.
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with b.block():
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pass
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### Callbacks.
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from optimize_later import register_callback, deregister_callback, optimize_context
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@register_callback
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def my_report_function(report):
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# Short one line description.
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print(report.short())
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# Long description with breakdown based on blocks.
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print(report.long())
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# Details available in:
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# - report.name: block name
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# - report.limit: time limit
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# - report.delta: time consumed
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# - report.blocks: breakdown by blocks
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# - report.start, report.end: start and end time with an unspecified timer:
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# useful for building a relative timeline with blocks.
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deregister_callback(my_report_function)
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with optimize_context():
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# Register a callback here.
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register_callback(my_report_function)
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# Callback is not available here.
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@optimize_context
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def function():
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# This callback will be available for the duration of this function.
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register_callback(my_report_function)
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# Remove global callbacks for this block.
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with optimize_context([]):
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pass
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# or...
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@optimize_context([])
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def function():
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pass
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# Of course, you can specify a list of callbacks to enable exclusively as well.
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```
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A sample short report:
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```Block 'tests.py@152' took 0.011565s (+0.011565s over limit)```
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A sample long report:
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```
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Block 'tests.py@152' took 0.011565s (+0.011565s over limit), children:
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- Block 'tests.py@153' took 0.006662s, children:
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- Block 'tests.py@154' took 0.000002s
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- Block 'tests.py@156' took 0.000002s
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- Block 'tests.py@159' took 0.000001s
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```
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## Installation
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First, install the module with:
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```
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$ pip install optimize-later
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```
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Or if you want the latest bleeding edge version:
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```
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$ pip install -e git://github.com/quantum5/optimize-later.git
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```
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That's it!
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### Django
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If you are using Django, you might want to configure `optimize-later` in `settings.py` instead of
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adding callbacks directly.
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You have to add `'optimize-later'` to `INSTALLED_APPS`.
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Then, the list of callbacks as dot-separated import paths can be specified in `'OPTIMIZE_LATER_CALLBACKS'`
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in `settings.py`. For example:
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```python
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OPTIMIZE_LATER_CALLBACKS = [
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'myapp.optimize.report',
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'otherapp.optimize.report',
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]
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```
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