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transducer library for python, inspired by clojure

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# pyducers
Transducer library for python, inspired by clojure

## Table of contents
- [performance](#performance)
- [map](#map)
- [filter](#filter)
- [compose](#compose)
- [transduce](#transduce)
- [sequence](#sequence)

## performance

The performance test sums all even numbers below 1000000.

This library is very slow. Using tranducers, calculating that problem takes twice as much time compared to the version that uses a simple for loop, and filters inside the loop. And 50% slower to version that uses the builtin reduce and the filter iterator of the list.

```sh
$ python3 perftest.py
time: 0.315	result 249999500000	algorithm: transduce with filter
time: 0.170	result 249999500000	algorithm: with for loop
time: 0.218	result 249999500000	algorithm: builtin reduce with prefiltered list
```

## map
### syntax

This behaves the same way as in the standard library.
```python
map(f, coll)
```

`map` optionally receives multiple collections. In that case it applies `f` function for the zip of the collections.
```python
map(f, coll1, coll2, ...)
```

Supplying only an `f` function returns a transducer
```python
map(f)
```

### examples

```python
>>> def add(*args):
...     return sum(args)
...
>>> def square(n):
...     return n*n
...
>>> def inc(n):
...     return n+1
...
>>> from pyducers import map, transduce
>>> list(map(inc, [1, 2, 3]))
[2, 3, 4]
>>> list(map(add, [1, 2], [1, 2]))
[2, 4]
>>> transduce(map(square), add, [1, 2, 3])
14
>>> 1*1 + 2*2 + 3*3
14
```

## filter
### syntax
This behaves the same way as in the standard library:
```python
filter(f, coll)
```

Passing only `f` to filter returns the transducer
```python
filter(f)
```
### examples
```python
>>> def add(*args):
...     return sum(args)
...
>>> def evenp(num):
...     return num % 2 == 0
...
>>> from pyducers import filter, transduce
>>>
>>> list(filter(evenp, [1, 2, 3, 4]))
[2, 4]
>>> transduce(filter(evenp), add, [1, 2, 3, 4], 0)
6
```

## compose

`compose` function creates a function composition from the provided function. The functions are applied from right to left to the input
Note: when using `transducer` on the composition, the composed transducers are applied in the opposite order: from left to right.

### syntax
```python
compose(f, g, ...)
```

### examples
```python
>>> def add(*args):
...     return sum(args)
...
>>> def square(n):
...     return n*n
...
>>> def inc(n):
...     return n+1
...
>>> def two_times(n):
...     return 2*n
...
>>> def evenp(num):
...     return num % 2 == 0
...
>>> from pyducers import compose, transduce, map, filter
>>> compose(square, inc)(1)
4
>>> compose(inc, square)(1)
2
>>> compose(inc, square, two_times)(1)
5
>>> compose(two_times, square, inc)(1)
8
>>> transduce(compose(map(square), filter(evenp)), add, [1, 2, 3, 4], 0)
20
```

## transduce
`tranduce` reduces over a collection with the tranduced reduce function. Initial value can be optionally supplied.
### syntax
If `initial_value` is not provided, it will be generated by calling `reduce_function without arguments`: `reduce_function()`
```
transduce(transducer, reduce_function, coll, initial_value=None)
```
### examples
```python
>>> def add(*args):
...     return sum(args)
...
>>> def evenp(num):
...     return num % 2 == 0
...
>>> from pyducers import compose, transduce, map, filter
>>> transduce(filter(evenp), add, [1, 2, 3, 4], 0)
6
```

## sequence
`sequence` collects the result of the transducer into a collection.

### syntax

Without transducer, `sequence` simply transforms collection into a list.
```python
sequence(coll, xf=None)
```

### examples
```python
>>> def evenp(num):
...     return num % 2 == 0
...
>>> from pyducers import filter, sequence
>>> sequence([1, 2])
[1, 2]
>>> sequence([1, 2, 3, 4], filter(evenp))
[2, 4]
```

pyducers

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