_pprint.py 17.8 KB
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438
"""This module contains the _EstimatorPrettyPrinter class used in
BaseEstimator.__repr__ for pretty-printing estimators"""

# Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,
# 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018 Python Software Foundation;
# All Rights Reserved

# Authors: Fred L. Drake, Jr. <fdrake@acm.org> (built-in CPython pprint module)
#          Nicolas Hug (scikit-learn specific changes)

# License: PSF License version 2 (see below)

# PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2
# --------------------------------------------

# 1. This LICENSE AGREEMENT is between the Python Software Foundation ("PSF"),
# and the Individual or Organization ("Licensee") accessing and otherwise
# using this software ("Python") in source or binary form and its associated
# documentation.

# 2. Subject to the terms and conditions of this License Agreement, PSF hereby
# grants Licensee a nonexclusive, royalty-free, world-wide license to
# reproduce, analyze, test, perform and/or display publicly, prepare
# derivative works, distribute, and otherwise use Python alone or in any
# derivative version, provided, however, that PSF's License Agreement and
# PSF's notice of copyright, i.e., "Copyright (c) 2001, 2002, 2003, 2004,
# 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016,
# 2017, 2018 Python Software Foundation; All Rights Reserved" are retained in
# Python alone or in any derivative version prepared by Licensee.

# 3. In the event Licensee prepares a derivative work that is based on or
# incorporates Python or any part thereof, and wants to make the derivative
# work available to others as provided herein, then Licensee hereby agrees to
# include in any such work a brief summary of the changes made to Python.

# 4. PSF is making Python available to Licensee on an "AS IS" basis. PSF MAKES
# NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED. BY WAY OF EXAMPLE, BUT
# NOT LIMITATION, PSF MAKES NO AND DISCLAIMS ANY REPRESENTATION OR WARRANTY OF
# MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF
# PYTHON WILL NOT INFRINGE ANY THIRD PARTY RIGHTS.

# 5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON FOR ANY
# INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS A RESULT OF
# MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON, OR ANY DERIVATIVE
# THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.

# 6. This License Agreement will automatically terminate upon a material
# breach of its terms and conditions.

# 7. Nothing in this License Agreement shall be deemed to create any
# relationship of agency, partnership, or joint venture between PSF and
# Licensee. This License Agreement does not grant permission to use PSF
# trademarks or trade name in a trademark sense to endorse or promote products
# or services of Licensee, or any third party.

# 8. By copying, installing or otherwise using Python, Licensee agrees to be
# bound by the terms and conditions of this License Agreement.


# Brief summary of changes to original code:
# - "compact" parameter is supported for dicts, not just lists or tuples
# - estimators have a custom handler, they're not just treated as objects
# - long sequences (lists, tuples, dict items) with more than N elements are
#   shortened using ellipsis (', ...') at the end.

from inspect import signature
import pprint
from collections import OrderedDict

from ..base import BaseEstimator
from .._config import get_config
from . import is_scalar_nan


class KeyValTuple(tuple):
    """Dummy class for correctly rendering key-value tuples from dicts."""
    def __repr__(self):
        # needed for _dispatch[tuple.__repr__] not to be overridden
        return super().__repr__()


class KeyValTupleParam(KeyValTuple):
    """Dummy class for correctly rendering key-value tuples from parameters."""
    pass


def _changed_params(estimator):
    """Return dict (param_name: value) of parameters that were given to
    estimator with non-default values."""

    params = estimator.get_params(deep=False)
    filtered_params = {}
    init_func = getattr(estimator.__init__, 'deprecated_original',
                        estimator.__init__)
    init_params = signature(init_func).parameters
    init_params = {name: param.default for name, param in init_params.items()}

    for k, v in params.items():
        if (k not in init_params or (  # happens if k is part of a **kwargs
                repr(v) != repr(init_params[k]) and
                not (is_scalar_nan(init_params[k]) and is_scalar_nan(v)))):
            filtered_params[k] = v
    return filtered_params


class _EstimatorPrettyPrinter(pprint.PrettyPrinter):
    """Pretty Printer class for estimator objects.

    This extends the pprint.PrettyPrinter class, because:
    - we need estimators to be printed with their parameters, e.g.
      Estimator(param1=value1, ...) which is not supported by default.
    - the 'compact' parameter of PrettyPrinter is ignored for dicts, which
      may lead to very long representations that we want to avoid.

    Quick overview of pprint.PrettyPrinter (see also
    https://stackoverflow.com/questions/49565047/pprint-with-hex-numbers):

    - the entry point is the _format() method which calls format() (overridden
      here)
    - format() directly calls _safe_repr() for a first try at rendering the
      object
    - _safe_repr formats the whole object reccursively, only calling itself,
      not caring about line length or anything
    - back to _format(), if the output string is too long, _format() then calls
      the appropriate _pprint_TYPE() method (e.g. _pprint_list()) depending on
      the type of the object. This where the line length and the compact
      parameters are taken into account.
    - those _pprint_TYPE() methods will internally use the format() method for
      rendering the nested objects of an object (e.g. the elements of a list)

    In the end, everything has to be implemented twice: in _safe_repr and in
    the custom _pprint_TYPE methods. Unfortunately PrettyPrinter is really not
    straightforward to extend (especially when we want a compact output), so
    the code is a bit convoluted.

    This class overrides:
    - format() to support the changed_only parameter
    - _safe_repr to support printing of estimators (for when they fit on a
      single line)
    - _format_dict_items so that dict are correctly 'compacted'
    - _format_items so that ellipsis is used on long lists and tuples

    When estimators cannot be printed on a single line, the builtin _format()
    will call _pprint_estimator() because it was registered to do so (see
    _dispatch[BaseEstimator.__repr__] = _pprint_estimator).

    both _format_dict_items() and _pprint_estimator() use the
    _format_params_or_dict_items() method that will format parameters and
    key-value pairs respecting the compact parameter. This method needs another
    subroutine _pprint_key_val_tuple() used when a parameter or a key-value
    pair is too long to fit on a single line. This subroutine is called in
    _format() and is registered as well in the _dispatch dict (just like
    _pprint_estimator). We had to create the two classes KeyValTuple and
    KeyValTupleParam for this.
    """

    def __init__(self, indent=1, width=80, depth=None, stream=None, *,
                 compact=False, indent_at_name=True,
                 n_max_elements_to_show=None):
        super().__init__(indent, width, depth, stream, compact=compact)
        self._indent_at_name = indent_at_name
        if self._indent_at_name:
            self._indent_per_level = 1  # ignore indent param
        self._changed_only = get_config()['print_changed_only']
        # Max number of elements in a list, dict, tuple until we start using
        # ellipsis. This also affects the number of arguments of an estimators
        # (they are treated as dicts)
        self.n_max_elements_to_show = n_max_elements_to_show

    def format(self, object, context, maxlevels, level):
        return _safe_repr(object, context, maxlevels, level,
                          changed_only=self._changed_only)

    def _pprint_estimator(self, object, stream, indent, allowance, context,
                          level):
        stream.write(object.__class__.__name__ + '(')
        if self._indent_at_name:
            indent += len(object.__class__.__name__)

        if self._changed_only:
            params = _changed_params(object)
        else:
            params = object.get_params(deep=False)

        params = OrderedDict((name, val)
                             for (name, val) in sorted(params.items()))

        self._format_params(params.items(), stream, indent, allowance + 1,
                            context, level)
        stream.write(')')

    def _format_dict_items(self, items, stream, indent, allowance, context,
                           level):
        return self._format_params_or_dict_items(
            items, stream, indent, allowance, context, level, is_dict=True)

    def _format_params(self, items, stream, indent, allowance, context, level):
        return self._format_params_or_dict_items(
            items, stream, indent, allowance, context, level, is_dict=False)

    def _format_params_or_dict_items(self, object, stream, indent, allowance,
                                     context, level, is_dict):
        """Format dict items or parameters respecting the compact=True
        parameter. For some reason, the builtin rendering of dict items doesn't
        respect compact=True and will use one line per key-value if all cannot
        fit in a single line.
        Dict items will be rendered as <'key': value> while params will be
        rendered as <key=value>. The implementation is mostly copy/pasting from
        the builtin _format_items().
        This also adds ellipsis if the number of items is greater than
        self.n_max_elements_to_show.
        """
        write = stream.write
        indent += self._indent_per_level
        delimnl = ',\n' + ' ' * indent
        delim = ''
        width = max_width = self._width - indent + 1
        it = iter(object)
        try:
            next_ent = next(it)
        except StopIteration:
            return
        last = False
        n_items = 0
        while not last:
            if n_items == self.n_max_elements_to_show:
                write(', ...')
                break
            n_items += 1
            ent = next_ent
            try:
                next_ent = next(it)
            except StopIteration:
                last = True
                max_width -= allowance
                width -= allowance
            if self._compact:
                k, v = ent
                krepr = self._repr(k, context, level)
                vrepr = self._repr(v, context, level)
                if not is_dict:
                    krepr = krepr.strip("'")
                middle = ': ' if is_dict else '='
                rep = krepr + middle + vrepr
                w = len(rep) + 2
                if width < w:
                    width = max_width
                    if delim:
                        delim = delimnl
                if width >= w:
                    width -= w
                    write(delim)
                    delim = ', '
                    write(rep)
                    continue
            write(delim)
            delim = delimnl
            class_ = KeyValTuple if is_dict else KeyValTupleParam
            self._format(class_(ent), stream, indent,
                         allowance if last else 1, context, level)

    def _format_items(self, items, stream, indent, allowance, context, level):
        """Format the items of an iterable (list, tuple...). Same as the
        built-in _format_items, with support for ellipsis if the number of
        elements is greater than self.n_max_elements_to_show.
        """
        write = stream.write
        indent += self._indent_per_level
        if self._indent_per_level > 1:
            write((self._indent_per_level - 1) * ' ')
        delimnl = ',\n' + ' ' * indent
        delim = ''
        width = max_width = self._width - indent + 1
        it = iter(items)
        try:
            next_ent = next(it)
        except StopIteration:
            return
        last = False
        n_items = 0
        while not last:
            if n_items == self.n_max_elements_to_show:
                write(', ...')
                break
            n_items += 1
            ent = next_ent
            try:
                next_ent = next(it)
            except StopIteration:
                last = True
                max_width -= allowance
                width -= allowance
            if self._compact:
                rep = self._repr(ent, context, level)
                w = len(rep) + 2
                if width < w:
                    width = max_width
                    if delim:
                        delim = delimnl
                if width >= w:
                    width -= w
                    write(delim)
                    delim = ', '
                    write(rep)
                    continue
            write(delim)
            delim = delimnl
            self._format(ent, stream, indent,
                         allowance if last else 1, context, level)

    def _pprint_key_val_tuple(self, object, stream, indent, allowance, context,
                              level):
        """Pretty printing for key-value tuples from dict or parameters."""
        k, v = object
        rep = self._repr(k, context, level)
        if isinstance(object, KeyValTupleParam):
            rep = rep.strip("'")
            middle = '='
        else:
            middle = ': '
        stream.write(rep)
        stream.write(middle)
        self._format(v, stream, indent + len(rep) + len(middle), allowance,
                     context, level)

    # Note: need to copy _dispatch to prevent instances of the builtin
    # PrettyPrinter class to call methods of _EstimatorPrettyPrinter (see issue
    # 12906)
    # mypy error: "Type[PrettyPrinter]" has no attribute "_dispatch"
    _dispatch = pprint.PrettyPrinter._dispatch.copy()  # type: ignore
    _dispatch[BaseEstimator.__repr__] = _pprint_estimator
    _dispatch[KeyValTuple.__repr__] = _pprint_key_val_tuple


def _safe_repr(object, context, maxlevels, level, changed_only=False):
    """Same as the builtin _safe_repr, with added support for Estimator
    objects."""
    typ = type(object)

    if typ in pprint._builtin_scalars:
        return repr(object), True, False

    r = getattr(typ, "__repr__", None)
    if issubclass(typ, dict) and r is dict.__repr__:
        if not object:
            return "{}", True, False
        objid = id(object)
        if maxlevels and level >= maxlevels:
            return "{...}", False, objid in context
        if objid in context:
            return pprint._recursion(object), False, True
        context[objid] = 1
        readable = True
        recursive = False
        components = []
        append = components.append
        level += 1
        saferepr = _safe_repr
        items = sorted(object.items(), key=pprint._safe_tuple)
        for k, v in items:
            krepr, kreadable, krecur = saferepr(
                k, context, maxlevels, level, changed_only=changed_only)
            vrepr, vreadable, vrecur = saferepr(
                v, context, maxlevels, level, changed_only=changed_only)
            append("%s: %s" % (krepr, vrepr))
            readable = readable and kreadable and vreadable
            if krecur or vrecur:
                recursive = True
        del context[objid]
        return "{%s}" % ", ".join(components), readable, recursive

    if (issubclass(typ, list) and r is list.__repr__) or \
       (issubclass(typ, tuple) and r is tuple.__repr__):
        if issubclass(typ, list):
            if not object:
                return "[]", True, False
            format = "[%s]"
        elif len(object) == 1:
            format = "(%s,)"
        else:
            if not object:
                return "()", True, False
            format = "(%s)"
        objid = id(object)
        if maxlevels and level >= maxlevels:
            return format % "...", False, objid in context
        if objid in context:
            return pprint._recursion(object), False, True
        context[objid] = 1
        readable = True
        recursive = False
        components = []
        append = components.append
        level += 1
        for o in object:
            orepr, oreadable, orecur = _safe_repr(
                o, context, maxlevels, level, changed_only=changed_only)
            append(orepr)
            if not oreadable:
                readable = False
            if orecur:
                recursive = True
        del context[objid]
        return format % ", ".join(components), readable, recursive

    if issubclass(typ, BaseEstimator):
        objid = id(object)
        if maxlevels and level >= maxlevels:
            return "{...}", False, objid in context
        if objid in context:
            return pprint._recursion(object), False, True
        context[objid] = 1
        readable = True
        recursive = False
        if changed_only:
            params = _changed_params(object)
        else:
            params = object.get_params(deep=False)
        components = []
        append = components.append
        level += 1
        saferepr = _safe_repr
        items = sorted(params.items(), key=pprint._safe_tuple)
        for k, v in items:
            krepr, kreadable, krecur = saferepr(
                k, context, maxlevels, level, changed_only=changed_only)
            vrepr, vreadable, vrecur = saferepr(
                v, context, maxlevels, level, changed_only=changed_only)
            append("%s=%s" % (krepr.strip("'"), vrepr))
            readable = readable and kreadable and vreadable
            if krecur or vrecur:
                recursive = True
        del context[objid]
        return ("%s(%s)" % (typ.__name__, ", ".join(components)), readable,
                recursive)

    rep = repr(object)
    return rep, (rep and not rep.startswith('<')), False