Refactor in order to be able to get more data about the operations ru…

…n in the pipeline (#4)

* Add function to get the counts of all stages of the pipeline

* Update README, fix tuple -> Tuple, add checks that zero values don't end the stream

README.md

@@ -1,3 +1,72 @@
 # pipedata
 
-A framework for building pipelines for data processing
+Chained operations in Python, applied to data processing.
+
+## Installation
+
+```bash
+pip install pipedata
+```
+
+## An Example
+
+### Core Framework
+
+The core framework provides the building blocks for chaining operations.
+
+Running a stream:
+```py
+from pipedata.core import StreamStart
+
+
+result = (
+    StreamStart(range(10))
+    .filter(lambda x: x % 2 == 0)
+    .map(lambda x: x ^ 2)
+    .map_tuple(lambda x: x, 2)
+    .to_list()
+)
+print(result)
+#> [(2, 0), (6, 4), (10,)]
+```
+
+Creating a chain and then using it:
+```py
+import json
+from pipedata.core import ChainStart, Stream, StreamStart
+
+
+chain = (
+    ChainStart()
+    .filter(lambda x: x % 2 == 0)
+    .map(lambda x: x ^ 2)
+    .map_tuple(lambda x: sum(x), 2)
+)
+print(Stream(range(10), chain).to_list())
+#> [2, 10, 10]
+print(json.dumps(chain.get_counts(), indent=4))
+#> [
+#>     {
+#>         "name": "_identity",
+#>         "inputs": 10,
+#>         "outputs": 10
+#>     },
+#>     {
+#>         "name": "<lambda>",
+#>         "inputs": 10,
+#>         "outputs": 5
+#>     },
+#>     {
+#>         "name": "<lambda>",
+#>         "inputs": 5,
+#>         "outputs": 5
+#>     },
+#>     {
+#>         "name": "<lambda>",
+#>         "inputs": 5,
+#>         "outputs": 3
+#>     }
+#> ]
+print(StreamStart(range(10)).flat_map(chain).to_list())
+#> [2, 10, 10]
+```

src/pipedata/core/__init__.py

@@ -1,8 +1,9 @@
-from .chain import Chain
-from .stream import Stream, start_stream
+from .chain import Chain, ChainStart
+from .stream import Stream, StreamStart
 
 __all__ = [
     "Chain",
+    "ChainStart",
     "Stream",
-    "start_stream",
+    "StreamStart",
 ]

src/pipedata/core/chain.py

@@ -1,83 +1,192 @@
 from __future__ import annotations
 
-from typing import Callable, Generic, Iterator, Optional, Tuple, TypeVar
+from dataclasses import dataclass
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    Generic,
+    Iterator,
+    List,
+    Optional,
+    Tuple,
+    TypeVar,
+    Union,
+    cast,
+    overload,
+)
 
 from pipedata.core.itertools import take_next, take_up_to_n
 
 TStart = TypeVar("TStart")
 TEnd = TypeVar("TEnd")
-TNewEnd = TypeVar("TNewEnd")
+TOther = TypeVar("TOther")
 
 
 def _identity(input_iterator: Iterator[TEnd]) -> Iterator[TEnd]:
-    while element := take_next(input_iterator):
+    while (element := take_next(input_iterator)) is not None:
         yield element
 
 
-class Chain(Generic[TStart, TEnd]):
-    def __init__(self, action: Callable[[Iterator[TStart]], Iterator[TEnd]]) -> None:
-        self._action = action
+class CountingIterator(Iterator[TStart]):
+    def __init__(self, iterator: Iterator[TStart]) -> None:
+        self._iterator = iterator
+        self._count = 0
+
+    def __iter__(self) -> Iterator[TStart]:
+        return self
+
+    def __next__(self) -> TStart:
+        self._count += 1
+        try:
+            return next(self._iterator)
+        except StopIteration as err:
+            self._count -= 1
+            raise StopIteration from err
+
+    def get_count(self) -> int:
+        return self._count
+
+
+class CountedFunc(Generic[TStart, TEnd]):
+    def __init__(
+        self,
+        func: Callable[[Iterator[TStart]], Iterator[TEnd]],
+    ) -> None:
+        self._func = func
+        self._counting_input: Optional[CountingIterator[TStart]] = None
+        self._counting_output: Optional[CountingIterator[TEnd]] = None
+
+    @property
+    def __name__(self) -> str:  # noqa: A003
+        return self._func.__name__
+
+    def __call__(self, input_iterator: Iterator[TStart]) -> Iterator[TEnd]:
+        self._counting_input = CountingIterator(input_iterator)
+        self._counting_output = CountingIterator(self._func(self._counting_input))
+        return self._counting_output
 
-    @classmethod
-    def start(cls) -> Chain[TEnd, TEnd]:
-        return Chain(_identity)
+    def get_counts(self) -> Tuple[int, int]:
+        return (
+            0 if self._counting_input is None else self._counting_input.get_count(),
+            0 if self._counting_output is None else self._counting_output.get_count(),
+        )
 
-    def __call__(self, previous_step: Iterator[TStart]) -> Iterator[TEnd]:
-        return self._action(previous_step)
+
+@dataclass
+class StepCount:
+    name: str
+    inputs: int
+    outputs: int
+
+
+class Chain(Generic[TStart, TEnd]):
+    @overload
+    def __init__(
+        self,
+        previous_steps: Chain[TStart, TOther],
+        func: Callable[[Iterator[TOther]], Iterator[TEnd]],
+    ):
+        ...
+
+    @overload
+    def __init__(
+        self,
+        previous_steps: None,
+        func: Callable[[Iterator[TStart]], Iterator[TEnd]],
+    ):
+        ...
+
+    def __init__(
+        self,
+        previous_steps: Optional[Chain[TStart, TOther]],
+        func: Union[
+            Callable[[Iterator[TOther]], Iterator[TEnd]],
+            Callable[[Iterator[TStart]], Iterator[TEnd]],
+        ],
+    ) -> None:
+        self._previous_steps = previous_steps
+        self._func = CountedFunc(func)
+
+    def __call__(self, input_iterator: Iterator[TStart]) -> Iterator[TEnd]:
+        if self._previous_steps is None:
+            func = cast(CountedFunc[TStart, TEnd], self._func)
+            return func(input_iterator)
+
+        return self._func(self._previous_steps(input_iterator))  # type: ignore
 
     def flat_map(
-        self, func: Callable[[Iterator[TEnd]], Iterator[TNewEnd]]
-    ) -> Chain[TStart, TNewEnd]:
+        self, func: Callable[[Iterator[TEnd]], Iterator[TOther]]
+    ) -> Chain[TStart, TOther]:
         """
         Output zero or more elements from one or more input elements.
 
         This is a fully general operation, that can arbitrarily transform the
         stream of elements. It is the most powerful operation, and all the
         other operations are implemented in terms of it.
         """
-
-        def new_action(previous_step: Iterator[TStart]) -> Iterator[TNewEnd]:
-            return func(self._action(previous_step))
-
-        return Chain(new_action)
+        return Chain(self, func)
 
     def filter(self, func: Callable[[TEnd], bool]) -> Chain[TStart, TEnd]:  # noqa: A003
         """
         Remove elements from the stream that do not pass the filter function.
         """
 
         def new_action(previous_step: Iterator[TEnd]) -> Iterator[TEnd]:
-            while element := take_next(previous_step):
+            while (element := take_next(previous_step)) is not None:
                 if func(element) is True:
                     yield element
 
+        new_action.__name__ = func.__name__
         return self.flat_map(new_action)
 
     def map(  # noqa: A003
-        self, func: Callable[[TEnd], TNewEnd]
-    ) -> Chain[TStart, TNewEnd]:
+        self, func: Callable[[TEnd], TOther]
+    ) -> Chain[TStart, TOther]:
         """
         Return a single transformed element from each input element.
         """
 
-        def new_action(previous_step: Iterator[TEnd]) -> Iterator[TNewEnd]:
-            while element := take_next(previous_step):
+        def new_action(previous_step: Iterator[TEnd]) -> Iterator[TOther]:
+            while (element := take_next(previous_step)) is not None:
                 yield func(element)
 
+        new_action.__name__ = func.__name__
         return self.flat_map(new_action)
 
     def map_tuple(
-        self, func: Callable[[Tuple[TEnd, ...]], TNewEnd], n: Optional[int] = None
-    ) -> Chain[TStart, TNewEnd]:
+        self, func: Callable[[Tuple[TEnd, ...]], TOther], n: Optional[int] = None
+    ) -> Chain[TStart, TOther]:
         """
         Return a single transformed element from (up to) n input elements.
 
         If n is None, then apply the function to all the elements, and return
         an iterator of 1 element.
         """
 
-        def new_action(previous_step: Iterator[TEnd]) -> Iterator[TNewEnd]:
+        def new_action(previous_step: Iterator[TEnd]) -> Iterator[TOther]:
             while elements := take_up_to_n(previous_step, n):
                 yield func(elements)
 
+        new_action.__name__ = func.__name__
         return self.flat_map(new_action)
+
+    def get_counts(self) -> List[Dict[str, Any]]:
+        step_counts = []
+        if self._previous_steps is not None:
+            step_counts = self._previous_steps.get_counts()
+
+        inputs, outputs = self._func.get_counts()
+        step_counts.append(
+            {
+                "name": self._func.__name__,
+                "inputs": inputs,
+                "outputs": outputs,
+            }
+        )
+        return step_counts
+
+
+class ChainStart(Chain[TOther, TOther]):
+    def __init__(self) -> None:
+        super().__init__(None, _identity)

src/pipedata/core/stream.py

@@ -3,7 +3,9 @@
 import functools
 import itertools
 from typing import (
+    Any,
     Callable,
+    Dict,
     Iterable,
     Iterator,
     List,
@@ -13,7 +15,7 @@
     overload,
 )
 
-from .chain import Chain
+from .chain import Chain, ChainStart
 
 TStart = TypeVar("TStart")
 TEnd = TypeVar("TEnd")
@@ -69,7 +71,10 @@ def to_list(
     ) -> List[TEnd]:
         return list(itertools.islice(self, stop))
 
+    def get_counts(self) -> List[Dict[str, Any]]:
+        return self._chain.get_counts()
 
-def start_stream(items: Iterable[TStart]) -> Stream[TStart]:
-    chain = Chain[TStart, TStart].start()
-    return Stream(items, chain)
+
+class StreamStart(Stream[TEnd]):
+    def __init__(self, items: Iterable[TEnd]) -> None:
+        super().__init__(items, ChainStart[TEnd]())