two version of R2R are here HEAD master

3 files changed, 758 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/setuptools/_vendor/jaraco/functools/__init__.py b/.venv/lib/python3.12/site-packages/setuptools/_vendor/jaraco/functools/__init__.py
new file mode 100644
index 00000000..ca6c22fa
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/setuptools/_vendor/jaraco/functools/__init__.py
@@ -0,0 +1,633 @@
+import collections.abc
+import functools
+import inspect
+import itertools
+import operator
+import time
+import types
+import warnings
+
+import more_itertools
+
+
+def compose(*funcs):
+    """
+    Compose any number of unary functions into a single unary function.
+
+    >>> import textwrap
+    >>> expected = str.strip(textwrap.dedent(compose.__doc__))
+    >>> strip_and_dedent = compose(str.strip, textwrap.dedent)
+    >>> strip_and_dedent(compose.__doc__) == expected
+    True
+
+    Compose also allows the innermost function to take arbitrary arguments.
+
+    >>> round_three = lambda x: round(x, ndigits=3)
+    >>> f = compose(round_three, int.__truediv__)
+    >>> [f(3*x, x+1) for x in range(1,10)]
+    [1.5, 2.0, 2.25, 2.4, 2.5, 2.571, 2.625, 2.667, 2.7]
+    """
+
+    def compose_two(f1, f2):
+        return lambda *args, **kwargs: f1(f2(*args, **kwargs))
+
+    return functools.reduce(compose_two, funcs)
+
+
+def once(func):
+    """
+    Decorate func so it's only ever called the first time.
+
+    This decorator can ensure that an expensive or non-idempotent function
+    will not be expensive on subsequent calls and is idempotent.
+
+    >>> add_three = once(lambda a: a+3)
+    >>> add_three(3)
+    6
+    >>> add_three(9)
+    6
+    >>> add_three('12')
+    6
+
+    To reset the stored value, simply clear the property ``saved_result``.
+
+    >>> del add_three.saved_result
+    >>> add_three(9)
+    12
+    >>> add_three(8)
+    12
+
+    Or invoke 'reset()' on it.
+
+    >>> add_three.reset()
+    >>> add_three(-3)
+    0
+    >>> add_three(0)
+    0
+    """
+
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        if not hasattr(wrapper, 'saved_result'):
+            wrapper.saved_result = func(*args, **kwargs)
+        return wrapper.saved_result
+
+    wrapper.reset = lambda: vars(wrapper).__delitem__('saved_result')
+    return wrapper
+
+
+def method_cache(method, cache_wrapper=functools.lru_cache()):
+    """
+    Wrap lru_cache to support storing the cache data in the object instances.
+
+    Abstracts the common paradigm where the method explicitly saves an
+    underscore-prefixed protected property on first call and returns that
+    subsequently.
+
+    >>> class MyClass:
+    ...     calls = 0
+    ...
+    ...     @method_cache
+    ...     def method(self, value):
+    ...         self.calls += 1
+    ...         return value
+
+    >>> a = MyClass()
+    >>> a.method(3)
+    3
+    >>> for x in range(75):
+    ...     res = a.method(x)
+    >>> a.calls
+    75
+
+    Note that the apparent behavior will be exactly like that of lru_cache
+    except that the cache is stored on each instance, so values in one
+    instance will not flush values from another, and when an instance is
+    deleted, so are the cached values for that instance.
+
+    >>> b = MyClass()
+    >>> for x in range(35):
+    ...     res = b.method(x)
+    >>> b.calls
+    35
+    >>> a.method(0)
+    0
+    >>> a.calls
+    75
+
+    Note that if method had been decorated with ``functools.lru_cache()``,
+    a.calls would have been 76 (due to the cached value of 0 having been
+    flushed by the 'b' instance).
+
+    Clear the cache with ``.cache_clear()``
+
+    >>> a.method.cache_clear()
+
+    Same for a method that hasn't yet been called.
+
+    >>> c = MyClass()
+    >>> c.method.cache_clear()
+
+    Another cache wrapper may be supplied:
+
+    >>> cache = functools.lru_cache(maxsize=2)
+    >>> MyClass.method2 = method_cache(lambda self: 3, cache_wrapper=cache)
+    >>> a = MyClass()
+    >>> a.method2()
+    3
+
+    Caution - do not subsequently wrap the method with another decorator, such
+    as ``@property``, which changes the semantics of the function.
+
+    See also
+    http://code.activestate.com/recipes/577452-a-memoize-decorator-for-instance-methods/
+    for another implementation and additional justification.
+    """
+
+    def wrapper(self, *args, **kwargs):
+        # it's the first call, replace the method with a cached, bound method
+        bound_method = types.MethodType(method, self)
+        cached_method = cache_wrapper(bound_method)
+        setattr(self, method.__name__, cached_method)
+        return cached_method(*args, **kwargs)
+
+    # Support cache clear even before cache has been created.
+    wrapper.cache_clear = lambda: None
+
+    return _special_method_cache(method, cache_wrapper) or wrapper
+
+
+def _special_method_cache(method, cache_wrapper):
+    """
+    Because Python treats special methods differently, it's not
+    possible to use instance attributes to implement the cached
+    methods.
+
+    Instead, install the wrapper method under a different name
+    and return a simple proxy to that wrapper.
+
+    https://github.com/jaraco/jaraco.functools/issues/5
+    """
+    name = method.__name__
+    special_names = '__getattr__', '__getitem__'
+
+    if name not in special_names:
+        return None
+
+    wrapper_name = '__cached' + name
+
+    def proxy(self, /, *args, **kwargs):
+        if wrapper_name not in vars(self):
+            bound = types.MethodType(method, self)
+            cache = cache_wrapper(bound)
+            setattr(self, wrapper_name, cache)
+        else:
+            cache = getattr(self, wrapper_name)
+        return cache(*args, **kwargs)
+
+    return proxy
+
+
+def apply(transform):
+    """
+    Decorate a function with a transform function that is
+    invoked on results returned from the decorated function.
+
+    >>> @apply(reversed)
+    ... def get_numbers(start):
+    ...     "doc for get_numbers"
+    ...     return range(start, start+3)
+    >>> list(get_numbers(4))
+    [6, 5, 4]
+    >>> get_numbers.__doc__
+    'doc for get_numbers'
+    """
+
+    def wrap(func):
+        return functools.wraps(func)(compose(transform, func))
+
+    return wrap
+
+
+def result_invoke(action):
+    r"""
+    Decorate a function with an action function that is
+    invoked on the results returned from the decorated
+    function (for its side effect), then return the original
+    result.
+
+    >>> @result_invoke(print)
+    ... def add_two(a, b):
+    ...     return a + b
+    >>> x = add_two(2, 3)
+    5
+    >>> x
+    5
+    """
+
+    def wrap(func):
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            result = func(*args, **kwargs)
+            action(result)
+            return result
+
+        return wrapper
+
+    return wrap
+
+
+def invoke(f, /, *args, **kwargs):
+    """
+    Call a function for its side effect after initialization.
+
+    The benefit of using the decorator instead of simply invoking a function
+    after defining it is that it makes explicit the author's intent for the
+    function to be called immediately. Whereas if one simply calls the
+    function immediately, it's less obvious if that was intentional or
+    incidental. It also avoids repeating the name - the two actions, defining
+    the function and calling it immediately are modeled separately, but linked
+    by the decorator construct.
+
+    The benefit of having a function construct (opposed to just invoking some
+    behavior inline) is to serve as a scope in which the behavior occurs. It
+    avoids polluting the global namespace with local variables, provides an
+    anchor on which to attach documentation (docstring), keeps the behavior
+    logically separated (instead of conceptually separated or not separated at
+    all), and provides potential to re-use the behavior for testing or other
+    purposes.
+
+    This function is named as a pithy way to communicate, "call this function
+    primarily for its side effect", or "while defining this function, also
+    take it aside and call it". It exists because there's no Python construct
+    for "define and call" (nor should there be, as decorators serve this need
+    just fine). The behavior happens immediately and synchronously.
+
+    >>> @invoke
+    ... def func(): print("called")
+    called
+    >>> func()
+    called
+
+    Use functools.partial to pass parameters to the initial call
+
+    >>> @functools.partial(invoke, name='bingo')
+    ... def func(name): print('called with', name)
+    called with bingo
+    """
+    f(*args, **kwargs)
+    return f
+
+
+class Throttler:
+    """Rate-limit a function (or other callable)."""
+
+    def __init__(self, func, max_rate=float('Inf')):
+        if isinstance(func, Throttler):
+            func = func.func
+        self.func = func
+        self.max_rate = max_rate
+        self.reset()
+
+    def reset(self):
+        self.last_called = 0
+
+    def __call__(self, *args, **kwargs):
+        self._wait()
+        return self.func(*args, **kwargs)
+
+    def _wait(self):
+        """Ensure at least 1/max_rate seconds from last call."""
+        elapsed = time.time() - self.last_called
+        must_wait = 1 / self.max_rate - elapsed
+        time.sleep(max(0, must_wait))
+        self.last_called = time.time()
+
+    def __get__(self, obj, owner=None):
+        return first_invoke(self._wait, functools.partial(self.func, obj))
+
+
+def first_invoke(func1, func2):
+    """
+    Return a function that when invoked will invoke func1 without
+    any parameters (for its side effect) and then invoke func2
+    with whatever parameters were passed, returning its result.
+    """
+
+    def wrapper(*args, **kwargs):
+        func1()
+        return func2(*args, **kwargs)
+
+    return wrapper
+
+
+method_caller = first_invoke(
+    lambda: warnings.warn(
+        '`jaraco.functools.method_caller` is deprecated, '
+        'use `operator.methodcaller` instead',
+        DeprecationWarning,
+        stacklevel=3,
+    ),
+    operator.methodcaller,
+)
+
+
+def retry_call(func, cleanup=lambda: None, retries=0, trap=()):
+    """
+    Given a callable func, trap the indicated exceptions
+    for up to 'retries' times, invoking cleanup on the
+    exception. On the final attempt, allow any exceptions
+    to propagate.
+    """
+    attempts = itertools.count() if retries == float('inf') else range(retries)
+    for _ in attempts:
+        try:
+            return func()
+        except trap:
+            cleanup()
+
+    return func()
+
+
+def retry(*r_args, **r_kwargs):
+    """
+    Decorator wrapper for retry_call. Accepts arguments to retry_call
+    except func and then returns a decorator for the decorated function.
+
+    Ex:
+
+    >>> @retry(retries=3)
+    ... def my_func(a, b):
+    ...     "this is my funk"
+    ...     print(a, b)
+    >>> my_func.__doc__
+    'this is my funk'
+    """
+
+    def decorate(func):
+        @functools.wraps(func)
+        def wrapper(*f_args, **f_kwargs):
+            bound = functools.partial(func, *f_args, **f_kwargs)
+            return retry_call(bound, *r_args, **r_kwargs)
+
+        return wrapper
+
+    return decorate
+
+
+def print_yielded(func):
+    """
+    Convert a generator into a function that prints all yielded elements.
+
+    >>> @print_yielded
+    ... def x():
+    ...     yield 3; yield None
+    >>> x()
+    3
+    None
+    """
+    print_all = functools.partial(map, print)
+    print_results = compose(more_itertools.consume, print_all, func)
+    return functools.wraps(func)(print_results)
+
+
+def pass_none(func):
+    """
+    Wrap func so it's not called if its first param is None.
+
+    >>> print_text = pass_none(print)
+    >>> print_text('text')
+    text
+    >>> print_text(None)
+    """
+
+    @functools.wraps(func)
+    def wrapper(param, /, *args, **kwargs):
+        if param is not None:
+            return func(param, *args, **kwargs)
+        return None
+
+    return wrapper
+
+
+def assign_params(func, namespace):
+    """
+    Assign parameters from namespace where func solicits.
+
+    >>> def func(x, y=3):
+    ...     print(x, y)
+    >>> assigned = assign_params(func, dict(x=2, z=4))
+    >>> assigned()
+    2 3
+
+    The usual errors are raised if a function doesn't receive
+    its required parameters:
+
+    >>> assigned = assign_params(func, dict(y=3, z=4))
+    >>> assigned()
+    Traceback (most recent call last):
+    TypeError: func() ...argument...
+
+    It even works on methods:
+
+    >>> class Handler:
+    ...     def meth(self, arg):
+    ...         print(arg)
+    >>> assign_params(Handler().meth, dict(arg='crystal', foo='clear'))()
+    crystal
+    """
+    sig = inspect.signature(func)
+    params = sig.parameters.keys()
+    call_ns = {k: namespace[k] for k in params if k in namespace}
+    return functools.partial(func, **call_ns)
+
+
+def save_method_args(method):
+    """
+    Wrap a method such that when it is called, the args and kwargs are
+    saved on the method.
+
+    >>> class MyClass:
+    ...     @save_method_args
+    ...     def method(self, a, b):
+    ...         print(a, b)
+    >>> my_ob = MyClass()
+    >>> my_ob.method(1, 2)
+    1 2
+    >>> my_ob._saved_method.args
+    (1, 2)
+    >>> my_ob._saved_method.kwargs
+    {}
+    >>> my_ob.method(a=3, b='foo')
+    3 foo
+    >>> my_ob._saved_method.args
+    ()
+    >>> my_ob._saved_method.kwargs == dict(a=3, b='foo')
+    True
+
+    The arguments are stored on the instance, allowing for
+    different instance to save different args.
+
+    >>> your_ob = MyClass()
+    >>> your_ob.method({str('x'): 3}, b=[4])
+    {'x': 3} [4]
+    >>> your_ob._saved_method.args
+    ({'x': 3},)
+    >>> my_ob._saved_method.args
+    ()
+    """
+    args_and_kwargs = collections.namedtuple('args_and_kwargs', 'args kwargs')
+
+    @functools.wraps(method)
+    def wrapper(self, /, *args, **kwargs):
+        attr_name = '_saved_' + method.__name__
+        attr = args_and_kwargs(args, kwargs)
+        setattr(self, attr_name, attr)
+        return method(self, *args, **kwargs)
+
+    return wrapper
+
+
+def except_(*exceptions, replace=None, use=None):
+    """
+    Replace the indicated exceptions, if raised, with the indicated
+    literal replacement or evaluated expression (if present).
+
+    >>> safe_int = except_(ValueError)(int)
+    >>> safe_int('five')
+    >>> safe_int('5')
+    5
+
+    Specify a literal replacement with ``replace``.
+
+    >>> safe_int_r = except_(ValueError, replace=0)(int)
+    >>> safe_int_r('five')
+    0
+
+    Provide an expression to ``use`` to pass through particular parameters.
+
+    >>> safe_int_pt = except_(ValueError, use='args[0]')(int)
+    >>> safe_int_pt('five')
+    'five'
+
+    """
+
+    def decorate(func):
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            try:
+                return func(*args, **kwargs)
+            except exceptions:
+                try:
+                    return eval(use)
+                except TypeError:
+                    return replace
+
+        return wrapper
+
+    return decorate
+
+
+def identity(x):
+    """
+    Return the argument.
+
+    >>> o = object()
+    >>> identity(o) is o
+    True
+    """
+    return x
+
+
+def bypass_when(check, *, _op=identity):
+    """
+    Decorate a function to return its parameter when ``check``.
+
+    >>> bypassed = []  # False
+
+    >>> @bypass_when(bypassed)
+    ... def double(x):
+    ...     return x * 2
+    >>> double(2)
+    4
+    >>> bypassed[:] = [object()]  # True
+    >>> double(2)
+    2
+    """
+
+    def decorate(func):
+        @functools.wraps(func)
+        def wrapper(param, /):
+            return param if _op(check) else func(param)
+
+        return wrapper
+
+    return decorate
+
+
+def bypass_unless(check):
+    """
+    Decorate a function to return its parameter unless ``check``.
+
+    >>> enabled = [object()]  # True
+
+    >>> @bypass_unless(enabled)
+    ... def double(x):
+    ...     return x * 2
+    >>> double(2)
+    4
+    >>> del enabled[:]  # False
+    >>> double(2)
+    2
+    """
+    return bypass_when(check, _op=operator.not_)
+
+
+@functools.singledispatch
+def _splat_inner(args, func):
+    """Splat args to func."""
+    return func(*args)
+
+
+@_splat_inner.register
+def _(args: collections.abc.Mapping, func):
+    """Splat kargs to func as kwargs."""
+    return func(**args)
+
+
+def splat(func):
+    """
+    Wrap func to expect its parameters to be passed positionally in a tuple.
+
+    Has a similar effect to that of ``itertools.starmap`` over
+    simple ``map``.
+
+    >>> pairs = [(-1, 1), (0, 2)]
+    >>> more_itertools.consume(itertools.starmap(print, pairs))
+    -1 1
+    0 2
+    >>> more_itertools.consume(map(splat(print), pairs))
+    -1 1
+    0 2
+
+    The approach generalizes to other iterators that don't have a "star"
+    equivalent, such as a "starfilter".
+
+    >>> list(filter(splat(operator.add), pairs))
+    [(0, 2)]
+
+    Splat also accepts a mapping argument.
+
+    >>> def is_nice(msg, code):
+    ...     return "smile" in msg or code == 0
+    >>> msgs = [
+    ...     dict(msg='smile!', code=20),
+    ...     dict(msg='error :(', code=1),
+    ...     dict(msg='unknown', code=0),
+    ... ]
+    >>> for msg in filter(splat(is_nice), msgs):
+    ...     print(msg)
+    {'msg': 'smile!', 'code': 20}
+    {'msg': 'unknown', 'code': 0}
+    """
+    return functools.wraps(func)(functools.partial(_splat_inner, func=func))
diff --git a/.venv/lib/python3.12/site-packages/setuptools/_vendor/jaraco/functools/__init__.pyi b/.venv/lib/python3.12/site-packages/setuptools/_vendor/jaraco/functools/__init__.pyi
new file mode 100644
index 00000000..19191bf9
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/setuptools/_vendor/jaraco/functools/__init__.pyi
@@ -0,0 +1,125 @@
+from collections.abc import Callable, Hashable, Iterator
+from functools import partial
+from operator import methodcaller
+import sys
+from typing import (
+    Any,
+    Generic,
+    Protocol,
+    TypeVar,
+    overload,
+)
+
+if sys.version_info >= (3, 10):
+    from typing import Concatenate, ParamSpec
+else:
+    from typing_extensions import Concatenate, ParamSpec
+
+_P = ParamSpec('_P')
+_R = TypeVar('_R')
+_T = TypeVar('_T')
+_R1 = TypeVar('_R1')
+_R2 = TypeVar('_R2')
+_V = TypeVar('_V')
+_S = TypeVar('_S')
+_R_co = TypeVar('_R_co', covariant=True)
+
+class _OnceCallable(Protocol[_P, _R]):
+    saved_result: _R
+    reset: Callable[[], None]
+    def __call__(self, *args: _P.args, **kwargs: _P.kwargs) -> _R: ...
+
+class _ProxyMethodCacheWrapper(Protocol[_R_co]):
+    cache_clear: Callable[[], None]
+    def __call__(self, *args: Hashable, **kwargs: Hashable) -> _R_co: ...
+
+class _MethodCacheWrapper(Protocol[_R_co]):
+    def cache_clear(self) -> None: ...
+    def __call__(self, *args: Hashable, **kwargs: Hashable) -> _R_co: ...
+
+# `compose()` overloads below will cover most use cases.
+
+@overload
+def compose(
+    __func1: Callable[[_R], _T],
+    __func2: Callable[_P, _R],
+    /,
+) -> Callable[_P, _T]: ...
+@overload
+def compose(
+    __func1: Callable[[_R], _T],
+    __func2: Callable[[_R1], _R],
+    __func3: Callable[_P, _R1],
+    /,
+) -> Callable[_P, _T]: ...
+@overload
+def compose(
+    __func1: Callable[[_R], _T],
+    __func2: Callable[[_R2], _R],
+    __func3: Callable[[_R1], _R2],
+    __func4: Callable[_P, _R1],
+    /,
+) -> Callable[_P, _T]: ...
+def once(func: Callable[_P, _R]) -> _OnceCallable[_P, _R]: ...
+def method_cache(
+    method: Callable[..., _R],
+    cache_wrapper: Callable[[Callable[..., _R]], _MethodCacheWrapper[_R]] = ...,
+) -> _MethodCacheWrapper[_R] | _ProxyMethodCacheWrapper[_R]: ...
+def apply(
+    transform: Callable[[_R], _T]
+) -> Callable[[Callable[_P, _R]], Callable[_P, _T]]: ...
+def result_invoke(
+    action: Callable[[_R], Any]
+) -> Callable[[Callable[_P, _R]], Callable[_P, _R]]: ...
+def invoke(
+    f: Callable[_P, _R], /, *args: _P.args, **kwargs: _P.kwargs
+) -> Callable[_P, _R]: ...
+
+class Throttler(Generic[_R]):
+    last_called: float
+    func: Callable[..., _R]
+    max_rate: float
+    def __init__(
+        self, func: Callable[..., _R] | Throttler[_R], max_rate: float = ...
+    ) -> None: ...
+    def reset(self) -> None: ...
+    def __call__(self, *args: Any, **kwargs: Any) -> _R: ...
+    def __get__(self, obj: Any, owner: type[Any] | None = ...) -> Callable[..., _R]: ...
+
+def first_invoke(
+    func1: Callable[..., Any], func2: Callable[_P, _R]
+) -> Callable[_P, _R]: ...
+
+method_caller: Callable[..., methodcaller]
+
+def retry_call(
+    func: Callable[..., _R],
+    cleanup: Callable[..., None] = ...,
+    retries: int | float = ...,
+    trap: type[BaseException] | tuple[type[BaseException], ...] = ...,
+) -> _R: ...
+def retry(
+    cleanup: Callable[..., None] = ...,
+    retries: int | float = ...,
+    trap: type[BaseException] | tuple[type[BaseException], ...] = ...,
+) -> Callable[[Callable[..., _R]], Callable[..., _R]]: ...
+def print_yielded(func: Callable[_P, Iterator[Any]]) -> Callable[_P, None]: ...
+def pass_none(
+    func: Callable[Concatenate[_T, _P], _R]
+) -> Callable[Concatenate[_T, _P], _R]: ...
+def assign_params(
+    func: Callable[..., _R], namespace: dict[str, Any]
+) -> partial[_R]: ...
+def save_method_args(
+    method: Callable[Concatenate[_S, _P], _R]
+) -> Callable[Concatenate[_S, _P], _R]: ...
+def except_(
+    *exceptions: type[BaseException], replace: Any = ..., use: Any = ...
+) -> Callable[[Callable[_P, Any]], Callable[_P, Any]]: ...
+def identity(x: _T) -> _T: ...
+def bypass_when(
+    check: _V, *, _op: Callable[[_V], Any] = ...
+) -> Callable[[Callable[[_T], _R]], Callable[[_T], _T | _R]]: ...
+def bypass_unless(
+    check: Any,
+) -> Callable[[Callable[[_T], _R]], Callable[[_T], _T | _R]]: ...
diff --git a/.venv/lib/python3.12/site-packages/setuptools/_vendor/jaraco/functools/py.typed b/.venv/lib/python3.12/site-packages/setuptools/_vendor/jaraco/functools/py.typed
new file mode 100644
index 00000000..e69de29b
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/setuptools/_vendor/jaraco/functools/py.typed