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|
| """:mod:`itertools` is full of great examples of Python generator |
| usage. However, there are still some critical gaps. ``iterutils`` |
| fills many of those gaps with featureful, tested, and Pythonic |
| solutions. |
| |
| Many of the functions below have two versions, one which |
| returns an iterator (denoted by the ``*_iter`` naming pattern), and a |
| shorter-named convenience form that returns a list. Some of the |
| following are based on examples in itertools docs. |
| """ |
|
|
| import os |
| import math |
| import time |
| import codecs |
| import random |
| import itertools |
| from itertools import zip_longest |
| from collections.abc import Mapping, Sequence, Set, ItemsView, Iterable |
|
|
|
|
| try: |
| from .typeutils import make_sentinel |
| _UNSET = make_sentinel('_UNSET') |
| _REMAP_EXIT = make_sentinel('_REMAP_EXIT') |
| except ImportError: |
| _REMAP_EXIT = object() |
| _UNSET = object() |
|
|
|
|
| def is_iterable(obj): |
| """Similar in nature to :func:`callable`, ``is_iterable`` returns |
| ``True`` if an object is `iterable`_, ``False`` if not. |
| |
| >>> is_iterable([]) |
| True |
| >>> is_iterable(object()) |
| False |
| |
| .. _iterable: https://docs.python.org/2/glossary.html#term-iterable |
| """ |
| try: |
| iter(obj) |
| except TypeError: |
| return False |
| return True |
|
|
|
|
| def is_scalar(obj): |
| """A near-mirror of :func:`is_iterable`. Returns ``False`` if an |
| object is an iterable container type. Strings are considered |
| scalar as well, because strings are more often treated as whole |
| values as opposed to iterables of 1-character substrings. |
| |
| >>> is_scalar(object()) |
| True |
| >>> is_scalar(range(10)) |
| False |
| >>> is_scalar('hello') |
| True |
| """ |
| return not is_iterable(obj) or isinstance(obj, (str, bytes)) |
|
|
|
|
| def is_collection(obj): |
| """The opposite of :func:`is_scalar`. Returns ``True`` if an object |
| is an iterable other than a string. |
| |
| >>> is_collection(object()) |
| False |
| >>> is_collection(range(10)) |
| True |
| >>> is_collection('hello') |
| False |
| """ |
| return is_iterable(obj) and not isinstance(obj, (str, bytes)) |
|
|
|
|
| def split(src, sep=None, maxsplit=None): |
| """Splits an iterable based on a separator. Like :meth:`str.split`, |
| but for all iterables. Returns a list of lists. |
| |
| >>> split(['hi', 'hello', None, None, 'sup', None, 'soap', None]) |
| [['hi', 'hello'], ['sup'], ['soap']] |
| |
| See :func:`split_iter` docs for more info. |
| """ |
| return list(split_iter(src, sep, maxsplit)) |
|
|
|
|
| def split_iter(src, sep=None, maxsplit=None): |
| """Splits an iterable based on a separator, *sep*, a max of |
| *maxsplit* times (no max by default). *sep* can be: |
| |
| * a single value |
| * an iterable of separators |
| * a single-argument callable that returns True when a separator is |
| encountered |
| |
| ``split_iter()`` yields lists of non-separator values. A separator will |
| never appear in the output. |
| |
| >>> list(split_iter(['hi', 'hello', None, None, 'sup', None, 'soap', None])) |
| [['hi', 'hello'], ['sup'], ['soap']] |
| |
| Note that ``split_iter`` is based on :func:`str.split`, so if |
| *sep* is ``None``, ``split()`` **groups** separators. If empty lists |
| are desired between two contiguous ``None`` values, simply use |
| ``sep=[None]``: |
| |
| >>> list(split_iter(['hi', 'hello', None, None, 'sup', None])) |
| [['hi', 'hello'], ['sup']] |
| >>> list(split_iter(['hi', 'hello', None, None, 'sup', None], sep=[None])) |
| [['hi', 'hello'], [], ['sup'], []] |
| |
| Using a callable separator: |
| |
| >>> falsy_sep = lambda x: not x |
| >>> list(split_iter(['hi', 'hello', None, '', 'sup', False], falsy_sep)) |
| [['hi', 'hello'], [], ['sup'], []] |
| |
| See :func:`split` for a list-returning version. |
| |
| """ |
| if not is_iterable(src): |
| raise TypeError('expected an iterable') |
|
|
| if maxsplit is not None: |
| maxsplit = int(maxsplit) |
| if maxsplit == 0: |
| yield list(src) |
| return |
|
|
| if callable(sep): |
| sep_func = sep |
| elif not is_scalar(sep): |
| sep = frozenset(sep) |
| def sep_func(x): return x in sep |
| else: |
| def sep_func(x): return x == sep |
|
|
| cur_group = [] |
| split_count = 0 |
| for s in src: |
| if maxsplit is not None and split_count >= maxsplit: |
| def sep_func(x): return False |
| if sep_func(s): |
| if sep is None and not cur_group: |
| |
| |
| continue |
| split_count += 1 |
| yield cur_group |
| cur_group = [] |
| else: |
| cur_group.append(s) |
|
|
| if cur_group or sep is not None: |
| yield cur_group |
| return |
|
|
|
|
| def lstrip(iterable, strip_value=None): |
| """Strips values from the beginning of an iterable. Stripped items will |
| match the value of the argument strip_value. Functionality is analogous |
| to that of the method str.lstrip. Returns a list. |
| |
| >>> lstrip(['Foo', 'Bar', 'Bam'], 'Foo') |
| ['Bar', 'Bam'] |
| |
| """ |
| return list(lstrip_iter(iterable, strip_value)) |
|
|
|
|
| def lstrip_iter(iterable, strip_value=None): |
| """Strips values from the beginning of an iterable. Stripped items will |
| match the value of the argument strip_value. Functionality is analogous |
| to that of the method str.lstrip. Returns a generator. |
| |
| >>> list(lstrip_iter(['Foo', 'Bar', 'Bam'], 'Foo')) |
| ['Bar', 'Bam'] |
| |
| """ |
| iterator = iter(iterable) |
| for i in iterator: |
| if i != strip_value: |
| yield i |
| break |
| for i in iterator: |
| yield i |
|
|
|
|
| def rstrip(iterable, strip_value=None): |
| """Strips values from the end of an iterable. Stripped items will |
| match the value of the argument strip_value. Functionality is analogous |
| to that of the method str.rstrip. Returns a list. |
| |
| >>> rstrip(['Foo', 'Bar', 'Bam'], 'Bam') |
| ['Foo', 'Bar'] |
| |
| """ |
| return list(rstrip_iter(iterable, strip_value)) |
|
|
|
|
| def rstrip_iter(iterable, strip_value=None): |
| """Strips values from the end of an iterable. Stripped items will |
| match the value of the argument strip_value. Functionality is analogous |
| to that of the method str.rstrip. Returns a generator. |
| |
| >>> list(rstrip_iter(['Foo', 'Bar', 'Bam'], 'Bam')) |
| ['Foo', 'Bar'] |
| |
| """ |
| iterator = iter(iterable) |
| for i in iterator: |
| if i == strip_value: |
| cache = list() |
| cache.append(i) |
| broken = False |
| for i in iterator: |
| if i == strip_value: |
| cache.append(i) |
| else: |
| broken = True |
| break |
| if not broken: |
| return |
| yield from cache |
| yield i |
|
|
|
|
| def strip(iterable, strip_value=None): |
| """Strips values from the beginning and end of an iterable. Stripped items |
| will match the value of the argument strip_value. Functionality is |
| analogous to that of the method str.strip. Returns a list. |
| |
| >>> strip(['Fu', 'Foo', 'Bar', 'Bam', 'Fu'], 'Fu') |
| ['Foo', 'Bar', 'Bam'] |
| |
| """ |
| return list(strip_iter(iterable, strip_value)) |
|
|
|
|
| def strip_iter(iterable, strip_value=None): |
| """Strips values from the beginning and end of an iterable. Stripped items |
| will match the value of the argument strip_value. Functionality is |
| analogous to that of the method str.strip. Returns a generator. |
| |
| >>> list(strip_iter(['Fu', 'Foo', 'Bar', 'Bam', 'Fu'], 'Fu')) |
| ['Foo', 'Bar', 'Bam'] |
| |
| """ |
| return rstrip_iter(lstrip_iter(iterable, strip_value), strip_value) |
|
|
|
|
| def chunked(src, size, count=None, **kw): |
| """Returns a list of *count* chunks, each with *size* elements, |
| generated from iterable *src*. If *src* is not evenly divisible by |
| *size*, the final chunk will have fewer than *size* elements. |
| Provide the *fill* keyword argument to provide a pad value and |
| enable padding, otherwise no padding will take place. |
| |
| >>> chunked(range(10), 3) |
| [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] |
| >>> chunked(range(10), 3, fill=None) |
| [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, None, None]] |
| >>> chunked(range(10), 3, count=2) |
| [[0, 1, 2], [3, 4, 5]] |
| |
| See :func:`chunked_iter` for more info. |
| """ |
| chunk_iter = chunked_iter(src, size, **kw) |
| if count is None: |
| return list(chunk_iter) |
| else: |
| return list(itertools.islice(chunk_iter, count)) |
|
|
|
|
| def _validate_positive_int(value, name, strictly_positive=True): |
| value = int(value) |
| if value < 0 or (strictly_positive and value == 0): |
| raise ValueError('expected a positive integer ' + name) |
| return value |
|
|
|
|
| def chunked_iter(src, size, **kw): |
| """Generates *size*-sized chunks from *src* iterable. Unless the |
| optional *fill* keyword argument is provided, iterables not evenly |
| divisible by *size* will have a final chunk that is smaller than |
| *size*. |
| |
| >>> list(chunked_iter(range(10), 3)) |
| [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] |
| >>> list(chunked_iter(range(10), 3, fill=None)) |
| [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, None, None]] |
| |
| Note that ``fill=None`` in fact uses ``None`` as the fill value. |
| """ |
| |
| if not is_iterable(src): |
| raise TypeError('expected an iterable') |
| size = _validate_positive_int(size, 'chunk size') |
| do_fill = True |
| try: |
| fill_val = kw.pop('fill') |
| except KeyError: |
| do_fill = False |
| fill_val = None |
| if kw: |
| raise ValueError('got unexpected keyword arguments: %r' % kw.keys()) |
| if not src: |
| return |
|
|
| def postprocess(chk): return chk |
| if isinstance(src, (str, bytes)): |
| def postprocess(chk, _sep=type(src)()): return _sep.join(chk) |
| if isinstance(src, bytes): |
| def postprocess(chk): return bytes(chk) |
| src_iter = iter(src) |
| while True: |
| cur_chunk = list(itertools.islice(src_iter, size)) |
| if not cur_chunk: |
| break |
| lc = len(cur_chunk) |
| if lc < size and do_fill: |
| cur_chunk[lc:] = [fill_val] * (size - lc) |
| yield postprocess(cur_chunk) |
| return |
|
|
|
|
| def chunk_ranges(input_size, chunk_size, input_offset=0, overlap_size=0, align=False): |
| """Generates *chunk_size*-sized chunk ranges for an input with length *input_size*. |
| Optionally, a start of the input can be set via *input_offset*, and |
| and overlap between the chunks may be specified via *overlap_size*. |
| Also, if *align* is set to *True*, any items with *i % (chunk_size-overlap_size) == 0* |
| are always at the beginning of the chunk. |
| |
| Returns an iterator of (start, end) tuples, one tuple per chunk. |
| |
| >>> list(chunk_ranges(input_offset=10, input_size=10, chunk_size=5)) |
| [(10, 15), (15, 20)] |
| >>> list(chunk_ranges(input_offset=10, input_size=10, chunk_size=5, overlap_size=1)) |
| [(10, 15), (14, 19), (18, 20)] |
| >>> list(chunk_ranges(input_offset=10, input_size=10, chunk_size=5, overlap_size=2)) |
| [(10, 15), (13, 18), (16, 20)] |
| |
| >>> list(chunk_ranges(input_offset=4, input_size=15, chunk_size=5, align=False)) |
| [(4, 9), (9, 14), (14, 19)] |
| >>> list(chunk_ranges(input_offset=4, input_size=15, chunk_size=5, align=True)) |
| [(4, 5), (5, 10), (10, 15), (15, 19)] |
| |
| >>> list(chunk_ranges(input_offset=2, input_size=15, chunk_size=5, overlap_size=1, align=False)) |
| [(2, 7), (6, 11), (10, 15), (14, 17)] |
| >>> list(chunk_ranges(input_offset=2, input_size=15, chunk_size=5, overlap_size=1, align=True)) |
| [(2, 5), (4, 9), (8, 13), (12, 17)] |
| >>> list(chunk_ranges(input_offset=3, input_size=15, chunk_size=5, overlap_size=1, align=True)) |
| [(3, 5), (4, 9), (8, 13), (12, 17), (16, 18)] |
| """ |
| input_size = _validate_positive_int( |
| input_size, 'input_size', strictly_positive=False) |
| chunk_size = _validate_positive_int(chunk_size, 'chunk_size') |
| input_offset = _validate_positive_int( |
| input_offset, 'input_offset', strictly_positive=False) |
| overlap_size = _validate_positive_int( |
| overlap_size, 'overlap_size', strictly_positive=False) |
|
|
| input_stop = input_offset + input_size |
|
|
| if align: |
| initial_chunk_len = chunk_size - \ |
| input_offset % (chunk_size - overlap_size) |
| if initial_chunk_len != overlap_size: |
| yield (input_offset, min(input_offset + initial_chunk_len, input_stop)) |
| if input_offset + initial_chunk_len >= input_stop: |
| return |
| input_offset = input_offset + initial_chunk_len - overlap_size |
|
|
| for i in range(input_offset, input_stop, chunk_size - overlap_size): |
| yield (i, min(i + chunk_size, input_stop)) |
|
|
| if i + chunk_size >= input_stop: |
| return |
|
|
|
|
| def pairwise(src, end=_UNSET): |
| """Convenience function for calling :func:`windowed` on *src*, with |
| *size* set to 2. |
| |
| >>> pairwise(range(5)) |
| [(0, 1), (1, 2), (2, 3), (3, 4)] |
| >>> pairwise([]) |
| [] |
| |
| Unless *end* is set, the number of pairs is always one less than |
| the number of elements in the iterable passed in, except on an empty input, |
| which will return an empty list. |
| |
| With *end* set, a number of pairs equal to the length of *src* is returned, |
| with the last item of the last pair being equal to *end*. |
| |
| >>> list(pairwise(range(3), end=None)) |
| [(0, 1), (1, 2), (2, None)] |
| |
| This way, *end* values can be useful as sentinels to signal the end of the iterable. |
| """ |
| return windowed(src, 2, fill=end) |
|
|
|
|
| def pairwise_iter(src, end=_UNSET): |
| """Convenience function for calling :func:`windowed_iter` on *src*, |
| with *size* set to 2. |
| |
| >>> list(pairwise_iter(range(5))) |
| [(0, 1), (1, 2), (2, 3), (3, 4)] |
| >>> list(pairwise_iter([])) |
| [] |
| |
| Unless *end* is set, the number of pairs is always one less |
| than the number of elements in the iterable passed in, |
| or zero, when *src* is empty. |
| |
| With *end* set, a number of pairs equal to the length of *src* is returned, |
| with the last item of the last pair being equal to *end*. |
| |
| >>> list(pairwise_iter(range(3), end=None)) |
| [(0, 1), (1, 2), (2, None)] |
| |
| This way, *end* values can be useful as sentinels to signal the end |
| of the iterable. For infinite iterators, setting *end* has no effect. |
| """ |
| return windowed_iter(src, 2, fill=end) |
|
|
|
|
| def windowed(src, size, fill=_UNSET): |
| """Returns tuples with exactly length *size*. If *fill* is unset |
| and the iterable is too short to make a window of length *size*, |
| no tuples are returned. See :func:`windowed_iter` for more. |
| """ |
| return list(windowed_iter(src, size, fill=fill)) |
|
|
|
|
| def windowed_iter(src, size, fill=_UNSET): |
| """Returns tuples with length *size* which represent a sliding |
| window over iterable *src*. |
| |
| >>> list(windowed_iter(range(7), 3)) |
| [(0, 1, 2), (1, 2, 3), (2, 3, 4), (3, 4, 5), (4, 5, 6)] |
| |
| If *fill* is unset, and the iterable is too short to make a window |
| of length *size*, then no window tuples are returned. |
| |
| >>> list(windowed_iter(range(3), 5)) |
| [] |
| |
| With *fill* set, the iterator always yields a number of windows |
| equal to the length of the *src* iterable. |
| |
| >>> windowed(range(4), 3, fill=None) |
| [(0, 1, 2), (1, 2, 3), (2, 3, None), (3, None, None)] |
| |
| This way, *fill* values can be useful to signal the end of the iterable. |
| For infinite iterators, setting *fill* has no effect. |
| """ |
| tees = itertools.tee(src, size) |
| if fill is _UNSET: |
| try: |
| for i, t in enumerate(tees): |
| for _ in range(i): |
| next(t) |
| except StopIteration: |
| return zip([]) |
| return zip(*tees) |
|
|
| for i, t in enumerate(tees): |
| for _ in range(i): |
| try: |
| next(t) |
| except StopIteration: |
| continue |
| return zip_longest(*tees, fillvalue=fill) |
|
|
|
|
| def xfrange(stop, start=None, step=1.0): |
| """Same as :func:`frange`, but generator-based instead of returning a |
| list. |
| |
| >>> tuple(xfrange(1, 3, step=0.75)) |
| (1.0, 1.75, 2.5) |
| |
| See :func:`frange` for more details. |
| """ |
| if not step: |
| raise ValueError('step must be non-zero') |
| if start is None: |
| start, stop = 0.0, stop * 1.0 |
| else: |
| |
| stop, start = start * 1.0, stop * 1.0 |
| count = int(math.ceil((stop - start) / step)) |
| cur = start |
| for _ in range(count): |
| yield cur |
| cur += step |
|
|
|
|
| def frange(stop, start=None, step=1.0): |
| """A :func:`range` clone for float-based ranges. |
| |
| >>> frange(5) |
| [0.0, 1.0, 2.0, 3.0, 4.0] |
| >>> frange(6, step=1.25) |
| [0.0, 1.25, 2.5, 3.75, 5.0] |
| >>> frange(100.5, 101.5, 0.25) |
| [100.5, 100.75, 101.0, 101.25] |
| >>> frange(5, 0) |
| [] |
| >>> frange(5, 0, step=-1.25) |
| [5.0, 3.75, 2.5, 1.25] |
| """ |
| if not step: |
| raise ValueError('step must be non-zero') |
| if start is None: |
| start, stop = 0.0, stop * 1.0 |
| else: |
| |
| stop, start = start * 1.0, stop * 1.0 |
| count = int(math.ceil((stop - start) / step)) |
| ret = [None] * count |
| if not ret: |
| return ret |
| ret[0] = start |
| for i in range(1, count): |
| ret[i] = ret[i - 1] + step |
| return ret |
|
|
|
|
| def backoff(start, stop, count=None, factor=2.0, jitter=False): |
| """Returns a list of geometrically-increasing floating-point numbers, |
| suitable for usage with `exponential backoff`_. Exactly like |
| :func:`backoff_iter`, but without the ``'repeat'`` option for |
| *count*. See :func:`backoff_iter` for more details. |
| |
| .. _exponential backoff: https://en.wikipedia.org/wiki/Exponential_backoff |
| |
| >>> backoff(1, 10) |
| [1.0, 2.0, 4.0, 8.0, 10.0] |
| """ |
| if count == 'repeat': |
| raise ValueError("'repeat' supported in backoff_iter, not backoff") |
| return list(backoff_iter(start, stop, count=count, |
| factor=factor, jitter=jitter)) |
|
|
|
|
| def backoff_iter(start, stop, count=None, factor=2.0, jitter=False): |
| """Generates a sequence of geometrically-increasing floats, suitable |
| for usage with `exponential backoff`_. Starts with *start*, |
| increasing by *factor* until *stop* is reached, optionally |
| stopping iteration once *count* numbers are yielded. *factor* |
| defaults to 2. In general retrying with properly-configured |
| backoff creates a better-behaved component for a larger service |
| ecosystem. |
| |
| .. _exponential backoff: https://en.wikipedia.org/wiki/Exponential_backoff |
| |
| >>> list(backoff_iter(1.0, 10.0, count=5)) |
| [1.0, 2.0, 4.0, 8.0, 10.0] |
| >>> list(backoff_iter(1.0, 10.0, count=8)) |
| [1.0, 2.0, 4.0, 8.0, 10.0, 10.0, 10.0, 10.0] |
| >>> list(backoff_iter(0.25, 100.0, factor=10)) |
| [0.25, 2.5, 25.0, 100.0] |
| |
| A simplified usage example: |
| |
| .. code-block:: python |
| |
| for timeout in backoff_iter(0.25, 5.0): |
| try: |
| res = network_call() |
| break |
| except Exception as e: |
| log(e) |
| time.sleep(timeout) |
| |
| An enhancement for large-scale systems would be to add variation, |
| or *jitter*, to timeout values. This is done to avoid a thundering |
| herd on the receiving end of the network call. |
| |
| Finally, for *count*, the special value ``'repeat'`` can be passed to |
| continue yielding indefinitely. |
| |
| Args: |
| |
| start (float): Positive number for baseline. |
| stop (float): Positive number for maximum. |
| count (int): Number of steps before stopping |
| iteration. Defaults to the number of steps between *start* and |
| *stop*. Pass the string, `'repeat'`, to continue iteration |
| indefinitely. |
| factor (float): Rate of exponential increase. Defaults to `2.0`, |
| e.g., `[1, 2, 4, 8, 16]`. |
| jitter (float): A factor between `-1.0` and `1.0`, used to |
| uniformly randomize and thus spread out timeouts in a distributed |
| system, avoiding rhythm effects. Positive values use the base |
| backoff curve as a maximum, negative values use the curve as a |
| minimum. Set to 1.0 or `True` for a jitter approximating |
| Ethernet's time-tested backoff solution. Defaults to `False`. |
| |
| """ |
| start = float(start) |
| stop = float(stop) |
| factor = float(factor) |
| if start < 0.0: |
| raise ValueError('expected start >= 0, not %r' % start) |
| if factor < 1.0: |
| raise ValueError('expected factor >= 1.0, not %r' % factor) |
| if stop == 0.0: |
| raise ValueError('expected stop >= 0') |
| if stop < start: |
| raise ValueError('expected stop >= start, not %r' % stop) |
| if count is None: |
| denom = start if start else 1 |
| if factor == 1.0: |
| if start != stop: |
| raise ValueError('expected factor > 1.0 when count is None' |
| ' and start != stop, not %r' % factor) |
| count = 1 |
| else: |
| count = 1 + math.ceil(math.log(stop/denom, factor)) |
| count = count if start else count + 1 |
| if count != 'repeat' and count < 0: |
| raise ValueError('count must be positive or "repeat", not %r' % count) |
| if jitter: |
| jitter = float(jitter) |
| if not (-1.0 <= jitter <= 1.0): |
| raise ValueError('expected jitter -1 <= j <= 1, not: %r' % jitter) |
|
|
| cur, i = start, 0 |
| while count == 'repeat' or i < count: |
| if not jitter: |
| cur_ret = cur |
| elif jitter: |
| cur_ret = cur - (cur * jitter * random.random()) |
| yield cur_ret |
| i += 1 |
| if cur == 0: |
| cur = 1 |
| elif cur < stop: |
| cur *= factor |
| if cur > stop: |
| cur = stop |
| return |
|
|
|
|
| def bucketize(src, key=bool, value_transform=None, key_filter=None): |
| """Group values in the *src* iterable by the value returned by *key*. |
| |
| >>> bucketize(range(5)) |
| {False: [0], True: [1, 2, 3, 4]} |
| >>> is_odd = lambda x: x % 2 == 1 |
| >>> bucketize(range(5), is_odd) |
| {False: [0, 2, 4], True: [1, 3]} |
| |
| *key* is :class:`bool` by default, but can either be a callable or a string or a list |
| if it is a string, it is the name of the attribute on which to bucketize objects. |
| |
| >>> bucketize([1+1j, 2+2j, 1, 2], key='real') |
| {1.0: [(1+1j), 1], 2.0: [(2+2j), 2]} |
| |
| if *key* is a list, it contains the buckets where to put each object |
| |
| >>> bucketize([1,2,365,4,98],key=[0,1,2,0,2]) |
| {0: [1, 4], 1: [2], 2: [365, 98]} |
| |
| |
| Value lists are not deduplicated: |
| |
| >>> bucketize([None, None, None, 'hello']) |
| {False: [None, None, None], True: ['hello']} |
| |
| Bucketize into more than 3 groups |
| |
| >>> bucketize(range(10), lambda x: x % 3) |
| {0: [0, 3, 6, 9], 1: [1, 4, 7], 2: [2, 5, 8]} |
| |
| ``bucketize`` has a couple of advanced options useful in certain |
| cases. *value_transform* can be used to modify values as they are |
| added to buckets, and *key_filter* will allow excluding certain |
| buckets from being collected. |
| |
| >>> bucketize(range(5), value_transform=lambda x: x*x) |
| {False: [0], True: [1, 4, 9, 16]} |
| |
| >>> bucketize(range(10), key=lambda x: x % 3, key_filter=lambda k: k % 3 != 1) |
| {0: [0, 3, 6, 9], 2: [2, 5, 8]} |
| |
| Note in some of these examples there were at most two keys, ``True`` and |
| ``False``, and each key present has a list with at least one |
| item. See :func:`partition` for a version specialized for binary |
| use cases. |
| |
| """ |
| if not is_iterable(src): |
| raise TypeError('expected an iterable') |
| elif isinstance(key, list): |
| if len(key) != len(src): |
| raise ValueError("key and src have to be the same length") |
| src = zip(key, src) |
|
|
| if isinstance(key, str): |
| def key_func(x): return getattr(x, key, x) |
| elif callable(key): |
| key_func = key |
| elif isinstance(key, list): |
| def key_func(x): return x[0] |
| else: |
| raise TypeError('expected key to be callable or a string or a list') |
|
|
| if value_transform is None: |
| def value_transform(x): return x |
| if not callable(value_transform): |
| raise TypeError('expected callable value transform function') |
| if isinstance(key, list): |
| f = value_transform |
| def value_transform(x): return f(x[1]) |
|
|
| ret = {} |
| for val in src: |
| key_of_val = key_func(val) |
| if key_filter is None or key_filter(key_of_val): |
| ret.setdefault(key_of_val, []).append(value_transform(val)) |
| return ret |
|
|
|
|
| def partition(src, key=bool, *keys): |
| """No relation to :meth:`str.partition`, ``partition`` is like |
| :func:`bucketize`, but for added convenience returns a collection for |
| each predicate passed. |
| |
| ``partition`` now accepts multiple *key* functions and will return |
| ``N + 1`` lists for ``N`` predicates. Each value from *src* is placed |
| into the first list whose predicate evaluates to ``True`` with values |
| that match none of the predicates placed in the last list. |
| |
| >>> nonempty, empty = partition(['', '', 'hi', '', 'bye']) |
| >>> nonempty |
| ['hi', 'bye'] |
| |
| *key* defaults to :class:`bool`, but can be carefully overridden to |
| use either a function that returns either ``True`` or ``False`` or |
| a string name of the attribute on which to partition objects. |
| |
| >>> import string |
| >>> is_digit = lambda x: x in string.digits |
| >>> decimal_digits, hexletters = partition(string.hexdigits, is_digit) |
| >>> ''.join(decimal_digits), ''.join(hexletters) |
| ('0123456789', 'abcdefABCDEF') |
| |
| Multiple predicates may be supplied to divide into more buckets: |
| |
| >>> positive, negative, zero = partition(range(-1, 2), |
| ... lambda i: i > 0, |
| ... lambda i: i < 0) |
| >>> positive, negative, zero |
| ([1], [-1], [0]) |
| """ |
| if not is_iterable(src): |
| raise TypeError('expected an iterable') |
|
|
| def _make_key_func(k): |
| if isinstance(k, str): |
| return lambda x, k=k: getattr(x, k, False) |
| if callable(k): |
| return k |
| raise TypeError('expected key to be callable or a string') |
|
|
| key_funcs = [_make_key_func(key)] + [_make_key_func(k) for k in keys] |
| parts = [[] for _ in range(len(key_funcs) + 1)] |
|
|
| for val in src: |
| for idx, func in enumerate(key_funcs): |
| if func(val): |
| parts[idx].append(val) |
| break |
| else: |
| parts[-1].append(val) |
|
|
| return tuple(parts) |
|
|
|
|
| def unique(src, key=None): |
| """``unique()`` returns a list of unique values, as determined by |
| *key*, in the order they first appeared in the input iterable, |
| *src*. |
| |
| >>> ones_n_zeros = '11010110001010010101010' |
| >>> ''.join(unique(ones_n_zeros)) |
| '10' |
| |
| See :func:`unique_iter` docs for more details. |
| """ |
| return list(unique_iter(src, key)) |
|
|
|
|
| def unique_iter(src, key=None): |
| """Yield unique elements from the iterable, *src*, based on *key*, |
| in the order in which they first appeared in *src*. |
| |
| >>> repetitious = [1, 2, 3] * 10 |
| >>> list(unique_iter(repetitious)) |
| [1, 2, 3] |
| |
| By default, *key* is the object itself, but *key* can either be a |
| callable or, for convenience, a string name of the attribute on |
| which to uniqueify objects, falling back on identity when the |
| attribute is not present. |
| |
| >>> pleasantries = ['hi', 'hello', 'ok', 'bye', 'yes'] |
| >>> list(unique_iter(pleasantries, key=lambda x: len(x))) |
| ['hi', 'hello', 'bye'] |
| """ |
| if not is_iterable(src): |
| raise TypeError('expected an iterable, not %r' % type(src)) |
| if key is None: |
| def key_func(x): return x |
| elif callable(key): |
| key_func = key |
| elif isinstance(key, str): |
| def key_func(x): return getattr(x, key, x) |
| else: |
| raise TypeError('"key" expected a string or callable, not %r' % key) |
| seen = set() |
| for i in src: |
| k = key_func(i) |
| if k not in seen: |
| seen.add(k) |
| yield i |
| return |
|
|
|
|
| def redundant(src, key=None, groups=False): |
| """The complement of :func:`unique()`. |
| |
| By default returns non-unique/duplicate values as a list of the |
| *first* redundant value in *src*. Pass ``groups=True`` to get |
| groups of all values with redundancies, ordered by position of the |
| first redundant value. This is useful in conjunction with some |
| normalizing *key* function. |
| |
| >>> redundant([1, 2, 3, 4]) |
| [] |
| >>> redundant([1, 2, 3, 2, 3, 3, 4]) |
| [2, 3] |
| >>> redundant([1, 2, 3, 2, 3, 3, 4], groups=True) |
| [[2, 2], [3, 3, 3]] |
| |
| An example using a *key* function to do case-insensitive |
| redundancy detection. |
| |
| >>> redundant(['hi', 'Hi', 'HI', 'hello'], key=str.lower) |
| ['Hi'] |
| >>> redundant(['hi', 'Hi', 'HI', 'hello'], groups=True, key=str.lower) |
| [['hi', 'Hi', 'HI']] |
| |
| *key* should also be used when the values in *src* are not hashable. |
| |
| .. note:: |
| |
| This output of this function is designed for reporting |
| duplicates in contexts when a unique input is desired. Due to |
| the grouped return type, there is no streaming equivalent of |
| this function for the time being. |
| |
| """ |
| if key is None: |
| pass |
| elif callable(key): |
| key_func = key |
| elif isinstance(key, (str, bytes)): |
| def key_func(x): return getattr(x, key, x) |
| else: |
| raise TypeError('"key" expected a string or callable, not %r' % key) |
| seen = {} |
| redundant_order = [] |
| redundant_groups = {} |
| for i in src: |
| k = key_func(i) if key else i |
| if k not in seen: |
| seen[k] = i |
| else: |
| if k in redundant_groups: |
| if groups: |
| redundant_groups[k].append(i) |
| else: |
| redundant_order.append(k) |
| redundant_groups[k] = [seen[k], i] |
| if not groups: |
| ret = [redundant_groups[k][1] for k in redundant_order] |
| else: |
| ret = [redundant_groups[k] for k in redundant_order] |
| return ret |
|
|
|
|
| def one(src, default=None, key=None): |
| """Along the same lines as builtins, :func:`all` and :func:`any`, and |
| similar to :func:`first`, ``one()`` returns the single object in |
| the given iterable *src* that evaluates to ``True``, as determined |
| by callable *key*. If unset, *key* defaults to :class:`bool`. If |
| no such objects are found, *default* is returned. If *default* is |
| not passed, ``None`` is returned. |
| |
| If *src* has more than one object that evaluates to ``True``, or |
| if there is no object that fulfills such condition, return |
| *default*. It's like an `XOR`_ over an iterable. |
| |
| >>> one((True, False, False)) |
| True |
| >>> one((True, False, True)) |
| >>> one((0, 0, 'a')) |
| 'a' |
| >>> one((0, False, None)) |
| >>> one((True, True), default=False) |
| False |
| >>> bool(one(('', 1))) |
| True |
| >>> one((10, 20, 30, 42), key=lambda i: i > 40) |
| 42 |
| |
| See `Martín Gaitán's original repo`_ for further use cases. |
| |
| .. _Martín Gaitán's original repo: https://github.com/mgaitan/one |
| .. _XOR: https://en.wikipedia.org/wiki/Exclusive_or |
| |
| """ |
| ones = list(itertools.islice(filter(key, src), 2)) |
| return ones[0] if len(ones) == 1 else default |
|
|
|
|
| def first(iterable, default=None, key=None): |
| """Return first element of *iterable* that evaluates to ``True``, else |
| return ``None`` or optional *default*. Similar to :func:`one`. |
| |
| >>> first([0, False, None, [], (), 42]) |
| 42 |
| >>> first([0, False, None, [], ()]) is None |
| True |
| >>> first([0, False, None, [], ()], default='ohai') |
| 'ohai' |
| >>> import re |
| >>> m = first(re.match(regex, 'abc') for regex in ['b.*', 'a(.*)']) |
| >>> m.group(1) |
| 'bc' |
| |
| The optional *key* argument specifies a one-argument predicate function |
| like that used for *filter()*. The *key* argument, if supplied, should be |
| in keyword form. For example, finding the first even number in an iterable: |
| |
| >>> first([1, 1, 3, 4, 5], key=lambda x: x % 2 == 0) |
| 4 |
| |
| Contributed by Hynek Schlawack, author of `the original standalone module`_. |
| |
| .. _the original standalone module: https://github.com/hynek/first |
| """ |
| return next(filter(key, iterable), default) |
|
|
|
|
| def flatten_iter(iterable): |
| """``flatten_iter()`` yields all the elements from *iterable* while |
| collapsing any nested iterables. |
| |
| >>> nested = [[1, 2], [[3], [4, 5]]] |
| >>> list(flatten_iter(nested)) |
| [1, 2, 3, 4, 5] |
| """ |
| for item in iterable: |
| if isinstance(item, Iterable) and not isinstance(item, (str, bytes)): |
| yield from flatten_iter(item) |
| else: |
| yield item |
|
|
|
|
| def flatten(iterable): |
| """``flatten()`` returns a collapsed list of all the elements from |
| *iterable* while collapsing any nested iterables. |
| |
| >>> nested = [[1, 2], [[3], [4, 5]]] |
| >>> flatten(nested) |
| [1, 2, 3, 4, 5] |
| """ |
| return list(flatten_iter(iterable)) |
|
|
|
|
| def same(iterable, ref=_UNSET): |
| """``same()`` returns ``True`` when all values in *iterable* are |
| equal to one another, or optionally a reference value, |
| *ref*. Similar to :func:`all` and :func:`any` in that it evaluates |
| an iterable and returns a :class:`bool`. ``same()`` returns |
| ``True`` for empty iterables. |
| |
| >>> same([]) |
| True |
| >>> same([1]) |
| True |
| >>> same(['a', 'a', 'a']) |
| True |
| >>> same(range(20)) |
| False |
| >>> same([[], []]) |
| True |
| >>> same([[], []], ref='test') |
| False |
| |
| """ |
| iterator = iter(iterable) |
| if ref is _UNSET: |
| ref = next(iterator, ref) |
| return all(val == ref for val in iterator) |
|
|
|
|
| def default_visit(path, key, value): |
| |
| return key, value |
|
|
|
|
| |
| _orig_default_visit = default_visit |
|
|
|
|
| def default_enter(path, key, value): |
| |
| if isinstance(value, (str, bytes)): |
| return value, False |
| elif isinstance(value, Mapping): |
| return value.__class__(), ItemsView(value) |
| elif isinstance(value, Sequence): |
| return value.__class__(), enumerate(value) |
| elif isinstance(value, Set): |
| return value.__class__(), enumerate(value) |
| else: |
| |
| |
| return value, False |
|
|
|
|
| def default_exit(path, key, old_parent, new_parent, new_items): |
| |
| |
| ret = new_parent |
| if isinstance(new_parent, Mapping): |
| new_parent.update(new_items) |
| elif isinstance(new_parent, Sequence): |
| vals = [v for i, v in new_items] |
| try: |
| new_parent.extend(vals) |
| except AttributeError: |
| ret = new_parent.__class__(vals) |
| elif isinstance(new_parent, Set): |
| vals = [v for i, v in new_items] |
| try: |
| new_parent.update(vals) |
| except AttributeError: |
| ret = new_parent.__class__(vals) |
| else: |
| raise RuntimeError('unexpected iterable type: %r' % type(new_parent)) |
| return ret |
|
|
|
|
| def remap( |
| root, |
| visit=default_visit, |
| enter=default_enter, |
| exit=default_exit, |
| cache: bool = True, |
| **kwargs, |
| ): |
| """The remap ("recursive map") function is used to traverse and |
| transform nested structures. Lists, tuples, sets, and dictionaries |
| are just a few of the data structures nested into heterogeneous |
| tree-like structures that are so common in programming. |
| Unfortunately, Python's built-in ways to manipulate collections |
| are almost all flat. List comprehensions may be fast and succinct, |
| but they do not recurse, making it tedious to apply quick changes |
| or complex transforms to real-world data. |
| |
| remap goes where list comprehensions cannot. |
| |
| Here's an example of removing all Nones from some data: |
| |
| >>> from pprint import pprint |
| >>> reviews = {'Star Trek': {'TNG': 10, 'DS9': 8.5, 'ENT': None}, |
| ... 'Babylon 5': 6, 'Dr. Who': None} |
| >>> pprint(remap(reviews, lambda p, k, v: v is not None)) |
| {'Babylon 5': 6, 'Star Trek': {'DS9': 8.5, 'TNG': 10}} |
| |
| Notice how both Nones have been removed despite the nesting in the |
| dictionary. Not bad for a one-liner, and that's just the beginning. |
| See `this remap cookbook`_ for more delicious recipes. |
| |
| .. _this remap cookbook: http://sedimental.org/remap.html |
| |
| remap takes four main arguments: the object to traverse and three |
| optional callables which determine how the remapped object will be |
| created. |
| |
| Args: |
| |
| root: The target object to traverse. By default, remap |
| supports iterables like :class:`list`, :class:`tuple`, |
| :class:`dict`, and :class:`set`, but any object traversable by |
| *enter* will work. |
| visit (callable): This function is called on every item in |
| *root*. It must accept three positional arguments, *path*, |
| *key*, and *value*. *path* is simply a tuple of parents' |
| keys. *visit* should return the new key-value pair. It may |
| also return ``True`` as shorthand to keep the old item |
| unmodified, or ``False`` to drop the item from the new |
| structure. *visit* is called after *enter*, on the new parent. |
| |
| The *visit* function is called for every item in root, |
| including duplicate items. For traversable values, it is |
| called on the new parent object, after all its children |
| have been visited. The default visit behavior simply |
| returns the key-value pair unmodified. |
| enter (callable): This function controls which items in *root* |
| are traversed. It accepts the same arguments as *visit*: the |
| path, the key, and the value of the current item. It returns a |
| pair of the blank new parent, and an iterator over the items |
| which should be visited. If ``False`` is returned instead of |
| an iterator, the value will not be traversed. |
| |
| The *enter* function is only called once per unique value. The |
| default enter behavior support mappings, sequences, and |
| sets. Strings and all other iterables will not be traversed. |
| exit (callable): This function determines how to handle items |
| once they have been visited. It gets the same three |
| arguments as the other functions -- *path*, *key*, *value* |
| -- plus two more: the blank new parent object returned |
| from *enter*, and a list of the new items, as remapped by |
| *visit*. |
| |
| Like *enter*, the *exit* function is only called once per |
| unique value. The default exit behavior is to simply add |
| all new items to the new parent, e.g., using |
| :meth:`list.extend` and :meth:`dict.update` to add to the |
| new parent. Immutable objects, such as a :class:`tuple` or |
| :class:`namedtuple`, must be recreated from scratch, but |
| use the same type as the new parent passed back from the |
| *enter* function. |
| cache (bool): Controls whether to cache transformed |
| objects. Uses object identity for the cache. For example |
| this is turned off for applications like `research` which |
| need to traverse all trees. |
| reraise_visit (bool): A pragmatic convenience for the *visit* |
| callable. When set to ``False``, remap ignores any errors |
| raised by the *visit* callback. Items causing exceptions |
| are kept. See examples for more details. |
| trace (bool): Pass ``trace=True`` to print out the entire |
| traversal. Or pass a tuple of ``'visit'``, ``'enter'``, |
| or ``'exit'`` to print only the selected events. |
| |
| remap is designed to cover the majority of cases with just the |
| *visit* callable. While passing in multiple callables is very |
| empowering, remap is designed so very few cases should require |
| passing more than one function. |
| |
| When passing *enter* and *exit*, it's common and easiest to build |
| on the default behavior. Simply add ``from boltons.iterutils import |
| default_enter`` (or ``default_exit``), and have your enter/exit |
| function call the default behavior before or after your custom |
| logic. See `this example`_. |
| |
| Duplicate and self-referential objects (aka reference loops) are |
| automatically handled internally, `as shown here`_. |
| |
| .. _this example: http://sedimental.org/remap.html#sort_all_lists |
| .. _as shown here: http://sedimental.org/remap.html#corner_cases |
| |
| """ |
| |
| |
| if not callable(visit): |
| raise TypeError('visit expected callable, not: %r' % visit) |
| if not callable(enter): |
| raise TypeError('enter expected callable, not: %r' % enter) |
| if not callable(exit): |
| raise TypeError('exit expected callable, not: %r' % exit) |
| reraise_visit = kwargs.pop('reraise_visit', True) |
| trace = kwargs.pop('trace', ()) |
| if trace is True: |
| trace = ('visit', 'enter', 'exit') |
| elif isinstance(trace, str): |
| trace = (trace,) |
| if not isinstance(trace, (tuple, list, set)): |
| raise TypeError('trace expected tuple of event names, not: %r' % trace) |
| trace_enter, trace_exit, trace_visit = 'enter' in trace, 'exit' in trace, 'visit' in trace |
|
|
| if kwargs: |
| raise TypeError('unexpected keyword arguments: %r' % kwargs.keys()) |
|
|
| path, registry, stack = (), {}, [(None, root)] |
| new_items_stack = [] |
| while stack: |
| key, value = stack.pop() |
| id_value = id(value) |
| if key is _REMAP_EXIT: |
| key, new_parent, old_parent = value |
| id_value = id(old_parent) |
| path, new_items = new_items_stack.pop() |
| if trace_exit: |
| print(' .. remap exit:', path, '-', key, '-', |
| old_parent, '-', new_parent, '-', new_items) |
| value = exit(path, key, old_parent, new_parent, new_items) |
| if trace_exit: |
| print(' .. remap exit result:', value) |
| registry[id_value] = value |
| if not new_items_stack: |
| continue |
| elif cache and id_value in registry: |
| value = registry[id_value] |
| else: |
| if trace_enter: |
| print(' .. remap enter:', path, '-', key, '-', value) |
| res = enter(path, key, value) |
| if trace_enter: |
| print(' .. remap enter result:', res) |
| try: |
| new_parent, new_items = res |
| except TypeError: |
| |
| raise TypeError('enter should return a tuple of (new_parent,' |
| ' items_iterator), not: %r' % res) |
| if new_items is not False: |
| |
| registry[id_value] = new_parent |
| new_items_stack.append((path, [])) |
| if value is not root: |
| path += (key,) |
| stack.append((_REMAP_EXIT, (key, new_parent, value))) |
| if new_items: |
| stack.extend(reversed(list(new_items))) |
| if trace_enter: |
| print(' .. remap stack size now:', len(stack)) |
| continue |
| if visit is _orig_default_visit: |
| |
| visited_item = (key, value) |
| else: |
| try: |
| if trace_visit: |
| print(' .. remap visit:', path, '-', key, '-', value) |
| visited_item = visit(path, key, value) |
| except Exception: |
| if reraise_visit: |
| raise |
| visited_item = True |
| if visited_item is False: |
| if trace_visit: |
| print(' .. remap visit result: <drop>') |
| continue |
| elif visited_item is True: |
| visited_item = (key, value) |
| if trace_visit: |
| print(' .. remap visit result:', visited_item) |
| |
| |
| |
| try: |
| new_items_stack[-1][1].append(visited_item) |
| except IndexError: |
| raise TypeError('expected remappable root, not: %r' % root) |
| return value |
|
|
|
|
| class PathAccessError(KeyError, IndexError, TypeError): |
| """An amalgamation of KeyError, IndexError, and TypeError, |
| representing what can occur when looking up a path in a nested |
| object. |
| """ |
|
|
| def __init__(self, exc, seg, path): |
| self.exc = exc |
| self.seg = seg |
| self.path = path |
|
|
| def __repr__(self): |
| cn = self.__class__.__name__ |
| return f'{cn}({self.exc!r}, {self.seg!r}, {self.path!r})' |
|
|
| def __str__(self): |
| return ('could not access %r from path %r, got error: %r' |
| % (self.seg, self.path, self.exc)) |
|
|
|
|
| def get_path(root, path, default=_UNSET): |
| """Retrieve a value from a nested object via a tuple representing the |
| lookup path. |
| |
| >>> root = {'a': {'b': {'c': [[1], [2], [3]]}}} |
| >>> get_path(root, ('a', 'b', 'c', 2, 0)) |
| 3 |
| |
| The path tuple format is intentionally consistent with that of |
| :func:`remap`, but a single dotted string can also be passed. |
| |
| One of get_path's chief aims is improved error messaging. EAFP is |
| great, but the error messages are not. |
| |
| For instance, ``root['a']['b']['c'][2][1]`` gives back |
| ``IndexError: list index out of range`` |
| |
| What went out of range where? get_path currently raises |
| ``PathAccessError: could not access 2 from path ('a', 'b', 'c', 2, |
| 1), got error: IndexError('list index out of range',)``, a |
| subclass of IndexError and KeyError. |
| |
| You can also pass a default that covers the entire operation, |
| should the lookup fail at any level. |
| |
| Args: |
| root: The target nesting of dictionaries, lists, or other |
| objects supporting ``__getitem__``. |
| path (tuple): A sequence of strings and integers to be successively |
| looked up within *root*. A dot-separated (``a.b``) string may |
| also be passed. |
| default: The value to be returned should any |
| ``PathAccessError`` exceptions be raised. |
| """ |
| if isinstance(path, str): |
| path = path.split('.') |
| cur = root |
| try: |
| for seg in path: |
| try: |
| cur = cur[seg] |
| except (KeyError, IndexError) as exc: |
| raise PathAccessError(exc, seg, path) |
| except TypeError as exc: |
| |
| |
| try: |
| seg = int(seg) |
| cur = cur[seg] |
| except (ValueError, KeyError, IndexError, TypeError): |
| if not is_iterable(cur): |
| exc = TypeError('%r object is not indexable' |
| % type(cur).__name__) |
| raise PathAccessError(exc, seg, path) |
| except PathAccessError: |
| if default is _UNSET: |
| raise |
| return default |
| return cur |
|
|
|
|
| def research(root, query=lambda p, k, v: True, reraise=False, enter=default_enter): |
| """The :func:`research` function uses :func:`remap` to recurse over |
| any data nested in *root*, and find values which match a given |
| criterion, specified by the *query* callable. |
| |
| Results are returned as a list of ``(path, value)`` pairs. The |
| paths are tuples in the same format accepted by |
| :func:`get_path`. This can be useful for comparing values nested |
| in two or more different structures. |
| |
| Here's a simple example that finds all integers: |
| |
| >>> root = {'a': {'b': 1, 'c': (2, 'd', 3)}, 'e': None} |
| >>> res = research(root, query=lambda p, k, v: isinstance(v, int)) |
| >>> print(sorted(res)) |
| [(('a', 'b'), 1), (('a', 'c', 0), 2), (('a', 'c', 2), 3)] |
| |
| Note how *query* follows the same, familiar ``path, key, value`` |
| signature as the ``visit`` and ``enter`` functions on |
| :func:`remap`, and returns a :class:`bool`. |
| |
| Args: |
| root: The target object to search. Supports the same types of |
| objects as :func:`remap`, including :class:`list`, |
| :class:`tuple`, :class:`dict`, and :class:`set`. |
| query (callable): The function called on every object to |
| determine whether to include it in the search results. The |
| callable must accept three arguments, *path*, *key*, and |
| *value*, commonly abbreviated *p*, *k*, and *v*, same as |
| *enter* and *visit* from :func:`remap`. |
| reraise (bool): Whether to reraise exceptions raised by *query* |
| or to simply drop the result that caused the error. |
| |
| |
| With :func:`research` it's easy to inspect the details of a data |
| structure, like finding values that are at a certain depth (using |
| ``len(p)``) and much more. If more advanced functionality is |
| needed, check out the code and make your own :func:`remap` |
| wrapper, and consider `submitting a patch`_! |
| |
| .. _submitting a patch: https://github.com/mahmoud/boltons/pulls |
| """ |
| ret = [] |
|
|
| if not callable(query): |
| raise TypeError('query expected callable, not: %r' % query) |
|
|
| def _enter(path, key, value): |
| try: |
| if query(path, key, value): |
| ret.append((path + (key,), value)) |
| except Exception: |
| if reraise: |
| raise |
| return enter(path, key, value) |
|
|
| remap(root, enter=_enter, cache=False) |
| return ret |
|
|
|
|
| |
| |
| |
|
|
|
|
| |
|
|
| class GUIDerator: |
| """The GUIDerator is an iterator that yields a globally-unique |
| identifier (GUID) on every iteration. The GUIDs produced are |
| hexadecimal strings. |
| |
| Testing shows it to be around 12x faster than the uuid module. By |
| default it is also more compact, partly due to its default 96-bit |
| (24-hexdigit) length. 96 bits of randomness means that there is a |
| 1 in 2 ^ 32 chance of collision after 2 ^ 64 iterations. If more |
| or less uniqueness is desired, the *size* argument can be adjusted |
| accordingly. |
| |
| Args: |
| size (int): character length of the GUID, defaults to 24. Lengths |
| between 20 and 36 are considered valid. |
| |
| The GUIDerator has built-in fork protection that causes it to |
| detect a fork on next iteration and reseed accordingly. |
| |
| """ |
|
|
| def __init__(self, size=24): |
| self.size = size |
| if size < 20 or size > 36: |
| raise ValueError('expected 20 < size <= 36') |
| import hashlib |
| self._sha1 = hashlib.sha1 |
| self.count = itertools.count() |
| self.reseed() |
|
|
| def reseed(self): |
| import socket |
| self.pid = os.getpid() |
| self.salt = '-'.join([str(self.pid), |
| socket.gethostname() or '<nohostname>', |
| str(time.time()), |
| os.urandom(6).hex()]) |
| return |
|
|
| def __iter__(self): |
| return self |
|
|
| def __next__(self): |
| if os.getpid() != self.pid: |
| self.reseed() |
| target_bytes = (self.salt + str(next(self.count))).encode('utf8') |
| hash_text = self._sha1(target_bytes).hexdigest()[:self.size] |
| return hash_text |
|
|
| next = __next__ |
|
|
|
|
| class SequentialGUIDerator(GUIDerator): |
| """Much like the standard GUIDerator, the SequentialGUIDerator is an |
| iterator that yields a globally-unique identifier (GUID) on every |
| iteration. The GUIDs produced are hexadecimal strings. |
| |
| The SequentialGUIDerator differs in that it picks a starting GUID |
| value and increments every iteration. This yields GUIDs which are |
| of course unique, but also ordered and lexicographically sortable. |
| |
| The SequentialGUIDerator is around 50% faster than the normal |
| GUIDerator, making it almost 20x as fast as the built-in uuid |
| module. By default it is also more compact, partly due to its |
| 96-bit (24-hexdigit) default length. 96 bits of randomness means that |
| there is a 1 in 2 ^ 32 chance of collision after 2 ^ 64 |
| iterations. If more or less uniqueness is desired, the *size* |
| argument can be adjusted accordingly. |
| |
| Args: |
| size (int): character length of the GUID, defaults to 24. |
| |
| Note that with SequentialGUIDerator there is a chance of GUIDs |
| growing larger than the size configured. The SequentialGUIDerator |
| has built-in fork protection that causes it to detect a fork on |
| next iteration and reseed accordingly. |
| |
| """ |
|
|
| def reseed(self): |
| super().reseed() |
| start_str = self._sha1(self.salt.encode('utf8')).hexdigest() |
| self.start = int(start_str[:self.size], 16) |
| self.start |= (1 << ((self.size * 4) - 2)) |
|
|
| def __next__(self): |
| if os.getpid() != self.pid: |
| self.reseed() |
| return '%x' % (next(self.count) + self.start) |
|
|
| next = __next__ |
|
|
|
|
| guid_iter = GUIDerator() |
| seq_guid_iter = SequentialGUIDerator() |
|
|
|
|
| def soft_sorted(iterable, first=None, last=None, key=None, reverse=False): |
| """For when you care about the order of some elements, but not about |
| others. |
| |
| Use this to float to the top and/or sink to the bottom a specific |
| ordering, while sorting the rest of the elements according to |
| normal :func:`sorted` rules. |
| |
| >>> soft_sorted(['two', 'b', 'one', 'a'], first=['one', 'two']) |
| ['one', 'two', 'a', 'b'] |
| >>> soft_sorted(range(7), first=[6, 15], last=[2, 4], reverse=True) |
| [6, 5, 3, 1, 0, 2, 4] |
| >>> import string |
| >>> ''.join(soft_sorted(string.hexdigits, first='za1', last='b', key=str.lower)) |
| 'aA1023456789cCdDeEfFbB' |
| |
| Args: |
| iterable (list): A list or other iterable to sort. |
| first (list): A sequence to enforce for elements which should |
| appear at the beginning of the returned list. |
| last (list): A sequence to enforce for elements which should |
| appear at the end of the returned list. |
| key (callable): Callable used to generate a comparable key for |
| each item to be sorted, same as the key in |
| :func:`sorted`. Note that entries in *first* and *last* |
| should be the keys for the items. Defaults to |
| passthrough/the identity function. |
| reverse (bool): Whether or not elements not explicitly ordered |
| by *first* and *last* should be in reverse order or not. |
| |
| Returns a new list in sorted order. |
| """ |
| first = first or [] |
| last = last or [] |
| key = key or (lambda x: x) |
| seq = list(iterable) |
| other = [x for x in seq if not ( |
| (first and key(x) in first) or (last and key(x) in last))] |
| other.sort(key=key, reverse=reverse) |
|
|
| if first: |
| first = sorted([x for x in seq if key(x) in first], |
| key=lambda x: first.index(key(x))) |
| if last: |
| last = sorted([x for x in seq if key(x) in last], |
| key=lambda x: last.index(key(x))) |
| return first + other + last |
|
|
|
|
| def untyped_sorted(iterable, key=None, reverse=False): |
| """A version of :func:`sorted` which will happily sort an iterable of |
| heterogeneous types and return a new list, similar to legacy Python's |
| behavior. |
| |
| >>> untyped_sorted(['abc', 2.0, 1, 2, 'def']) |
| [1, 2.0, 2, 'abc', 'def'] |
| |
| Note how mutually orderable types are sorted as expected, as in |
| the case of the integers and floats above. |
| |
| .. note:: |
| |
| Results may vary across Python versions and builds, but the |
| function will produce a sorted list, except in the case of |
| explicitly unorderable objects. |
| |
| """ |
| class _Wrapper: |
| slots = ('obj',) |
|
|
| def __init__(self, obj): |
| self.obj = obj |
|
|
| def __lt__(self, other): |
| obj = key(self.obj) if key is not None else self.obj |
| other = key(other.obj) if key is not None else other.obj |
| try: |
| ret = obj < other |
| except TypeError: |
| ret = ((type(obj).__name__, id(type(obj)), obj) |
| < (type(other).__name__, id(type(other)), other)) |
| return ret |
|
|
| if key is not None and not callable(key): |
| raise TypeError('expected function or callable object for key, not: %r' |
| % key) |
|
|
| return sorted(iterable, key=_Wrapper, reverse=reverse) |
|
|
|
|
| """ |
| May actually be faster to do an isinstance check for a str path |
| |
| $ python -m timeit -s "x = [1]" "x[0]" |
| 10000000 loops, best of 3: 0.0207 usec per loop |
| $ python -m timeit -s "x = [1]" "try: x[0] \nexcept: pass" |
| 10000000 loops, best of 3: 0.029 usec per loop |
| $ python -m timeit -s "x = [1]" "try: x[1] \nexcept: pass" |
| 1000000 loops, best of 3: 0.315 usec per loop |
| # setting up try/except is fast, only around 0.01us |
| # actually triggering the exception takes almost 10x as long |
| |
| $ python -m timeit -s "x = [1]" "isinstance(x, basestring)" |
| 10000000 loops, best of 3: 0.141 usec per loop |
| $ python -m timeit -s "x = [1]" "isinstance(x, str)" |
| 10000000 loops, best of 3: 0.131 usec per loop |
| $ python -m timeit -s "x = [1]" "try: x.split('.')\n except: pass" |
| 1000000 loops, best of 3: 0.443 usec per loop |
| $ python -m timeit -s "x = [1]" "try: x.split('.') \nexcept AttributeError: pass" |
| 1000000 loops, best of 3: 0.544 usec per loop |
| """ |
|
|
