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Project description
גamla is a performant functional programming library for python which supports async
.
Installation
pip install gamla
Debugging anonymous compositions
gamla.debug
It is sometimes hard to debug pipelines because you can't place ordinary breakpoints. For this gamla.debug
and gamla.debug_exception
were created.
gamla.debug
can be used within pipelines and provide a pdb breakpoint prompt where the value at this position can be referenced by x
.
def increment(x):
return x + 1
increment_twice = gamla.compose_left(increment, gamla.debug, increment)
increment_twice(1)
The above code will break with x
being 2.
When you have a long pipeline and want to debug at each step of the way, you can use gamla.debug_compose
and gamla.debug_compose_left
.
gamla.debug_exception
In some cases tracking down an exception involves inspecting code that runs many times. Consider the following example:
def increment(x):
return x + 1
def sometimes_has_a_bug(x):
if x == 666:
raise Exception
return x
increment_with_bug = gamla.map(gamla.compose_left(increment, sometimes_has_a_bug))
tuple(inrement_with_bug(range(1000)))
Adding a gamla.debug
here can be quite tedious, because the code will break many times.
Instead we can use gamla.debug_exception
to break only in the case the inner function raises, at which case we would get a breakpoint prompt, and be able to inspect the value causing the exception, use the name x
. This would like this:
increment_with_bug = gamla.map(gamla.compose_left(increment, gamla.debug_exception(sometimes_has_a_bug)))
One can also use gamla.debug_exception
using a decorator.
@gamla.debug_exception
def sometimes_has_a_bug(x):
if x == 666:
raise Exception
return x
Debug mode
gamla.compose(x, y, z)
produces a new function which doesn't have a proper name. If x
raises an exception, it is sometimes hard to figure out where this occurred. To overcome this, set the env variable GAMLA_DEBUG_MODE
(to anything) to get more useful exceptions. This is turned on only by flag because it incurs significant overhead so things might get slow.
Mixing asynchronous and synchronous code
Most functions in this lib will work seamlessly with async
and regular functions, and allow the developer to focus on the logic instead of deciding where to place an await
.
For example:
import asyncio
import gamla
def increment(i):
return i + 1
async def increment_async(i):
asyncio.sleep(1)
return i + 1
async def run():
mixed_composition = gamla.compose_left(increment, increment_async, increment)
return await mixed_composition(0) # returns 3!
Migrating from toolz
The main problems - toolz
is slow and does not support async
functions.
Why are curried functions and composition in toolz
slow?
These functions use an expensive inspect
call to look at a function’s arguments, and doing so at each run.
Why does gamla
not suffer from this problem?
Two reasons:
- It does not have binary signatures on things like
map
, so it doesn’t need to infer anything (these are higher order functions ingamla
). - The
gamla.curry
function eagerly pays for the signature inspection in advance, and remembers its results for future runs.
Function mapping and common gotchas:
Most functions are drop in replacements. Here are some examples:
curried.(filter|map|valmap|itemmap|keymap)
->gamla.$1
(make sure the call is with a single argument)toolz.identity
->gamla.identity
toolz.contains
->gamla.contains
toolz.lt
->gamla.greater_than
toolz.gt
->gamla.less_than
toolz.ge
->gamla.less_equals
toolz.le
->gamla.greater_equals
toolz.filter(None) -> gamla.filter(gamla.identity)
toolz.excepts(a, b, c)
->gamla.excepts(a, c, b)
toolz.excepts(a, b)
->gamla.excepts(a, gamla.just(None), b)
(following the “data-last” currying convention)
Releasing a new version
Increment the version in master, and pypi will automatically update.
Updating documentation after change in README.md
While in gamla directory:
- Install md-to-rst converter:
pip install m2r
- Convert README.md to README.rst:
m2r README.md
- Move README.rst to docs/source folder instead of existing one:
mv README.rst docs/source
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