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167,765 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
The provided code snippet includes necessary dependencies for implementing the `composite` function. Write a Python function `def composite(image1, image2, mask)` to solve the following problem:
Create composite image by blending images using a transparency mask. :param image1: The first image. :param image2: The second image. Must have the same mode and size as the first image. :param mask: A mask image. This image can have mode "1", "L", or "RGBA", and must have the same size as the other two images.
Here is the function:
def composite(image1, image2, mask):
"""
Create composite image by blending images using a transparency mask.
:param image1: The first image.
:param image2: The second image. Must have the same mode and
size as the first image.
:param mask: A mask image. This image can have mode
"1", "L", or "RGBA", and must have the same size as the
other two images.
"""
image = image2.copy()
image.paste(image1, None, mask)
return image | Create composite image by blending images using a transparency mask. :param image1: The first image. :param image2: The second image. Must have the same mode and size as the first image. :param mask: A mask image. This image can have mode "1", "L", or "RGBA", and must have the same size as the other two images. |
167,766 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
The provided code snippet includes necessary dependencies for implementing the `eval` function. Write a Python function `def eval(image, *args)` to solve the following problem:
Applies the function (which should take one argument) to each pixel in the given image. If the image has more than one band, the same function is applied to each band. Note that the function is evaluated once for each possible pixel value, so you cannot use random components or other generators. :param image: The input image. :param function: A function object, taking one integer argument. :returns: An :py:class:`~PIL.Image.Image` object.
Here is the function:
def eval(image, *args):
"""
Applies the function (which should take one argument) to each pixel
in the given image. If the image has more than one band, the same
function is applied to each band. Note that the function is
evaluated once for each possible pixel value, so you cannot use
random components or other generators.
:param image: The input image.
:param function: A function object, taking one integer argument.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
return image.point(args[0]) | Applies the function (which should take one argument) to each pixel in the given image. If the image has more than one band, the same function is applied to each band. Note that the function is evaluated once for each possible pixel value, so you cannot use random components or other generators. :param image: The input image. :param function: A function object, taking one integer argument. :returns: An :py:class:`~PIL.Image.Image` object. |
167,767 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
ID = []
OPEN = {}
The provided code snippet includes necessary dependencies for implementing the `register_open` function. Write a Python function `def register_open(id, factory, accept=None)` to solve the following problem:
Register an image file plugin. This function should not be used in application code. :param id: An image format identifier. :param factory: An image file factory method. :param accept: An optional function that can be used to quickly reject images having another format.
Here is the function:
def register_open(id, factory, accept=None):
"""
Register an image file plugin. This function should not be used
in application code.
:param id: An image format identifier.
:param factory: An image file factory method.
:param accept: An optional function that can be used to quickly
reject images having another format.
"""
id = id.upper()
ID.append(id)
OPEN[id] = factory, accept | Register an image file plugin. This function should not be used in application code. :param id: An image format identifier. :param factory: An image file factory method. :param accept: An optional function that can be used to quickly reject images having another format. |
167,768 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
MIME = {}
The provided code snippet includes necessary dependencies for implementing the `register_mime` function. Write a Python function `def register_mime(id, mimetype)` to solve the following problem:
Registers an image MIME type. This function should not be used in application code. :param id: An image format identifier. :param mimetype: The image MIME type for this format.
Here is the function:
def register_mime(id, mimetype):
"""
Registers an image MIME type. This function should not be used
in application code.
:param id: An image format identifier.
:param mimetype: The image MIME type for this format.
"""
MIME[id.upper()] = mimetype | Registers an image MIME type. This function should not be used in application code. :param id: An image format identifier. :param mimetype: The image MIME type for this format. |
167,769 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
SAVE = {}
The provided code snippet includes necessary dependencies for implementing the `register_save` function. Write a Python function `def register_save(id, driver)` to solve the following problem:
Registers an image save function. This function should not be used in application code. :param id: An image format identifier. :param driver: A function to save images in this format.
Here is the function:
def register_save(id, driver):
"""
Registers an image save function. This function should not be
used in application code.
:param id: An image format identifier.
:param driver: A function to save images in this format.
"""
SAVE[id.upper()] = driver | Registers an image save function. This function should not be used in application code. :param id: An image format identifier. :param driver: A function to save images in this format. |
167,770 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
SAVE_ALL = {}
The provided code snippet includes necessary dependencies for implementing the `register_save_all` function. Write a Python function `def register_save_all(id, driver)` to solve the following problem:
Registers an image function to save all the frames of a multiframe format. This function should not be used in application code. :param id: An image format identifier. :param driver: A function to save images in this format.
Here is the function:
def register_save_all(id, driver):
"""
Registers an image function to save all the frames
of a multiframe format. This function should not be
used in application code.
:param id: An image format identifier.
:param driver: A function to save images in this format.
"""
SAVE_ALL[id.upper()] = driver | Registers an image function to save all the frames of a multiframe format. This function should not be used in application code. :param id: An image format identifier. :param driver: A function to save images in this format. |
167,771 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
def register_extension(id, extension):
"""
Registers an image extension. This function should not be
used in application code.
:param id: An image format identifier.
:param extension: An extension used for this format.
"""
EXTENSION[extension.lower()] = id.upper()
The provided code snippet includes necessary dependencies for implementing the `register_extensions` function. Write a Python function `def register_extensions(id, extensions)` to solve the following problem:
Registers image extensions. This function should not be used in application code. :param id: An image format identifier. :param extensions: A list of extensions used for this format.
Here is the function:
def register_extensions(id, extensions):
"""
Registers image extensions. This function should not be
used in application code.
:param id: An image format identifier.
:param extensions: A list of extensions used for this format.
"""
for extension in extensions:
register_extension(id, extension) | Registers image extensions. This function should not be used in application code. :param id: An image format identifier. :param extensions: A list of extensions used for this format. |
167,772 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
EXTENSION = {}
def init():
"""
Explicitly initializes the Python Imaging Library. This function
loads all available file format drivers.
"""
global _initialized
if _initialized >= 2:
return 0
for plugin in _plugins:
try:
logger.debug("Importing %s", plugin)
__import__(f"PIL.{plugin}", globals(), locals(), [])
except ImportError as e:
logger.debug("Image: failed to import %s: %s", plugin, e)
if OPEN or SAVE:
_initialized = 2
return 1
The provided code snippet includes necessary dependencies for implementing the `registered_extensions` function. Write a Python function `def registered_extensions()` to solve the following problem:
Returns a dictionary containing all file extensions belonging to registered plugins
Here is the function:
def registered_extensions():
"""
Returns a dictionary containing all file extensions belonging
to registered plugins
"""
if not EXTENSION:
init()
return EXTENSION | Returns a dictionary containing all file extensions belonging to registered plugins |
167,773 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
DECODERS = {}
The provided code snippet includes necessary dependencies for implementing the `register_decoder` function. Write a Python function `def register_decoder(name, decoder)` to solve the following problem:
Registers an image decoder. This function should not be used in application code. :param name: The name of the decoder :param decoder: A callable(mode, args) that returns an ImageFile.PyDecoder object .. versionadded:: 4.1.0
Here is the function:
def register_decoder(name, decoder):
"""
Registers an image decoder. This function should not be
used in application code.
:param name: The name of the decoder
:param decoder: A callable(mode, args) that returns an
ImageFile.PyDecoder object
.. versionadded:: 4.1.0
"""
DECODERS[name] = decoder | Registers an image decoder. This function should not be used in application code. :param name: The name of the decoder :param decoder: A callable(mode, args) that returns an ImageFile.PyDecoder object .. versionadded:: 4.1.0 |
167,774 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
ENCODERS = {}
The provided code snippet includes necessary dependencies for implementing the `register_encoder` function. Write a Python function `def register_encoder(name, encoder)` to solve the following problem:
Registers an image encoder. This function should not be used in application code. :param name: The name of the encoder :param encoder: A callable(mode, args) that returns an ImageFile.PyEncoder object .. versionadded:: 4.1.0
Here is the function:
def register_encoder(name, encoder):
"""
Registers an image encoder. This function should not be
used in application code.
:param name: The name of the encoder
:param encoder: A callable(mode, args) that returns an
ImageFile.PyEncoder object
.. versionadded:: 4.1.0
"""
ENCODERS[name] = encoder | Registers an image encoder. This function should not be used in application code. :param name: The name of the encoder :param encoder: A callable(mode, args) that returns an ImageFile.PyEncoder object .. versionadded:: 4.1.0 |
167,775 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
def _show(image, **options):
from . import ImageShow
ImageShow.show(image, **options) | null |
167,776 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
class Image:
"""
This class represents an image object. To create
:py:class:`~PIL.Image.Image` objects, use the appropriate factory
functions. There's hardly ever any reason to call the Image constructor
directly.
* :py:func:`~PIL.Image.open`
* :py:func:`~PIL.Image.new`
* :py:func:`~PIL.Image.frombytes`
"""
format = None
format_description = None
_close_exclusive_fp_after_loading = True
def __init__(self):
# FIXME: take "new" parameters / other image?
# FIXME: turn mode and size into delegating properties?
self.im = None
self.mode = ""
self._size = (0, 0)
self.palette = None
self.info = {}
self._category = 0
self.readonly = 0
self.pyaccess = None
self._exif = None
def __getattr__(self, name):
if name == "category":
warnings.warn(
"Image categories are deprecated and will be removed in Pillow 10 "
"(2023-07-01). Use is_animated instead.",
DeprecationWarning,
stacklevel=2,
)
return self._category
raise AttributeError(name)
def width(self):
return self.size[0]
def height(self):
return self.size[1]
def size(self):
return self._size
def _new(self, im):
new = Image()
new.im = im
new.mode = im.mode
new._size = im.size
if im.mode in ("P", "PA"):
if self.palette:
new.palette = self.palette.copy()
else:
from . import ImagePalette
new.palette = ImagePalette.ImagePalette()
new.info = self.info.copy()
return new
# Context manager support
def __enter__(self):
return self
def __exit__(self, *args):
if hasattr(self, "fp") and getattr(self, "_exclusive_fp", False):
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
def close(self):
"""
Closes the file pointer, if possible.
This operation will destroy the image core and release its memory.
The image data will be unusable afterward.
This function is required to close images that have multiple frames or
have not had their file read and closed by the
:py:meth:`~PIL.Image.Image.load` method. See :ref:`file-handling` for
more information.
"""
try:
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
except Exception as msg:
logger.debug("Error closing: %s", msg)
if getattr(self, "map", None):
self.map = None
# Instead of simply setting to None, we're setting up a
# deferred error that will better explain that the core image
# object is gone.
self.im = deferred_error(ValueError("Operation on closed image"))
def _copy(self):
self.load()
self.im = self.im.copy()
self.pyaccess = None
self.readonly = 0
def _ensure_mutable(self):
if self.readonly:
self._copy()
else:
self.load()
def _dump(self, file=None, format=None, **options):
suffix = ""
if format:
suffix = "." + format
if not file:
f, filename = tempfile.mkstemp(suffix)
os.close(f)
else:
filename = file
if not filename.endswith(suffix):
filename = filename + suffix
self.load()
if not format or format == "PPM":
self.im.save_ppm(filename)
else:
self.save(filename, format, **options)
return filename
def __eq__(self, other):
return (
self.__class__ is other.__class__
and self.mode == other.mode
and self.size == other.size
and self.info == other.info
and self._category == other._category
and self.readonly == other.readonly
and self.getpalette() == other.getpalette()
and self.tobytes() == other.tobytes()
)
def __repr__(self):
return "<%s.%s image mode=%s size=%dx%d at 0x%X>" % (
self.__class__.__module__,
self.__class__.__name__,
self.mode,
self.size[0],
self.size[1],
id(self),
)
def _repr_png_(self):
"""iPython display hook support
:returns: png version of the image as bytes
"""
b = io.BytesIO()
try:
self.save(b, "PNG")
except Exception as e:
raise ValueError("Could not save to PNG for display") from e
return b.getvalue()
class _ArrayData:
def __init__(self, new):
self.__array_interface__ = new
def __array__(self, dtype=None):
# numpy array interface support
import numpy as np
new = {}
shape, typestr = _conv_type_shape(self)
new["shape"] = shape
new["typestr"] = typestr
new["version"] = 3
if self.mode == "1":
# Binary images need to be extended from bits to bytes
# See: https://github.com/python-pillow/Pillow/issues/350
new["data"] = self.tobytes("raw", "L")
else:
new["data"] = self.tobytes()
return np.array(self._ArrayData(new), dtype)
def __getstate__(self):
return [self.info, self.mode, self.size, self.getpalette(), self.tobytes()]
def __setstate__(self, state):
Image.__init__(self)
self.tile = []
info, mode, size, palette, data = state
self.info = info
self.mode = mode
self._size = size
self.im = core.new(mode, size)
if mode in ("L", "LA", "P", "PA") and palette:
self.putpalette(palette)
self.frombytes(data)
def tobytes(self, encoder_name="raw", *args):
"""
Return image as a bytes object.
.. warning::
This method returns the raw image data from the internal
storage. For compressed image data (e.g. PNG, JPEG) use
:meth:`~.save`, with a BytesIO parameter for in-memory
data.
:param encoder_name: What encoder to use. The default is to
use the standard "raw" encoder.
:param args: Extra arguments to the encoder.
:returns: A :py:class:`bytes` object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
if encoder_name == "raw" and args == ():
args = self.mode
self.load()
# unpack data
e = _getencoder(self.mode, encoder_name, args)
e.setimage(self.im)
bufsize = max(65536, self.size[0] * 4) # see RawEncode.c
data = []
while True:
l, s, d = e.encode(bufsize)
data.append(d)
if s:
break
if s < 0:
raise RuntimeError(f"encoder error {s} in tobytes")
return b"".join(data)
def tobitmap(self, name="image"):
"""
Returns the image converted to an X11 bitmap.
.. note:: This method only works for mode "1" images.
:param name: The name prefix to use for the bitmap variables.
:returns: A string containing an X11 bitmap.
:raises ValueError: If the mode is not "1"
"""
self.load()
if self.mode != "1":
raise ValueError("not a bitmap")
data = self.tobytes("xbm")
return b"".join(
[
f"#define {name}_width {self.size[0]}\n".encode("ascii"),
f"#define {name}_height {self.size[1]}\n".encode("ascii"),
f"static char {name}_bits[] = {{\n".encode("ascii"),
data,
b"};",
]
)
def frombytes(self, data, decoder_name="raw", *args):
"""
Loads this image with pixel data from a bytes object.
This method is similar to the :py:func:`~PIL.Image.frombytes` function,
but loads data into this image instead of creating a new image object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
# default format
if decoder_name == "raw" and args == ():
args = self.mode
# unpack data
d = _getdecoder(self.mode, decoder_name, args)
d.setimage(self.im)
s = d.decode(data)
if s[0] >= 0:
raise ValueError("not enough image data")
if s[1] != 0:
raise ValueError("cannot decode image data")
def load(self):
"""
Allocates storage for the image and loads the pixel data. In
normal cases, you don't need to call this method, since the
Image class automatically loads an opened image when it is
accessed for the first time.
If the file associated with the image was opened by Pillow, then this
method will close it. The exception to this is if the image has
multiple frames, in which case the file will be left open for seek
operations. See :ref:`file-handling` for more information.
:returns: An image access object.
:rtype: :ref:`PixelAccess` or :py:class:`PIL.PyAccess`
"""
if self.im and self.palette and self.palette.dirty:
# realize palette
mode, arr = self.palette.getdata()
if mode == "RGBA":
mode = "RGB"
self.info["transparency"] = arr[3::4]
arr = bytes(
value for (index, value) in enumerate(arr) if index % 4 != 3
)
palette_length = self.im.putpalette(mode, arr)
self.palette.dirty = 0
self.palette.rawmode = None
if "transparency" in self.info and mode in ("LA", "PA"):
if isinstance(self.info["transparency"], int):
self.im.putpalettealpha(self.info["transparency"], 0)
else:
self.im.putpalettealphas(self.info["transparency"])
self.palette.mode = "RGBA"
else:
self.palette.mode = "RGB"
self.palette.palette = self.im.getpalette()[: palette_length * 3]
if self.im:
if cffi and USE_CFFI_ACCESS:
if self.pyaccess:
return self.pyaccess
from . import PyAccess
self.pyaccess = PyAccess.new(self, self.readonly)
if self.pyaccess:
return self.pyaccess
return self.im.pixel_access(self.readonly)
def verify(self):
"""
Verifies the contents of a file. For data read from a file, this
method attempts to determine if the file is broken, without
actually decoding the image data. If this method finds any
problems, it raises suitable exceptions. If you need to load
the image after using this method, you must reopen the image
file.
"""
pass
def convert(self, mode=None, matrix=None, dither=None, palette=WEB, colors=256):
"""
Returns a converted copy of this image. For the "P" mode, this
method translates pixels through the palette. If mode is
omitted, a mode is chosen so that all information in the image
and the palette can be represented without a palette.
The current version supports all possible conversions between
"L", "RGB" and "CMYK." The ``matrix`` argument only supports "L"
and "RGB".
When translating a color image to greyscale (mode "L"),
the library uses the ITU-R 601-2 luma transform::
L = R * 299/1000 + G * 587/1000 + B * 114/1000
The default method of converting a greyscale ("L") or "RGB"
image into a bilevel (mode "1") image uses Floyd-Steinberg
dither to approximate the original image luminosity levels. If
dither is :data:`NONE`, all values larger than 127 are set to 255 (white),
all other values to 0 (black). To use other thresholds, use the
:py:meth:`~PIL.Image.Image.point` method.
When converting from "RGBA" to "P" without a ``matrix`` argument,
this passes the operation to :py:meth:`~PIL.Image.Image.quantize`,
and ``dither`` and ``palette`` are ignored.
:param mode: The requested mode. See: :ref:`concept-modes`.
:param matrix: An optional conversion matrix. If given, this
should be 4- or 12-tuple containing floating point values.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Note that this is not used when ``matrix`` is supplied.
:param palette: Palette to use when converting from mode "RGB"
to "P". Available palettes are :data:`WEB` or :data:`ADAPTIVE`.
:param colors: Number of colors to use for the :data:`ADAPTIVE` palette.
Defaults to 256.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
has_transparency = self.info.get("transparency") is not None
if not mode and self.mode == "P":
# determine default mode
if self.palette:
mode = self.palette.mode
else:
mode = "RGB"
if mode == "RGB" and has_transparency:
mode = "RGBA"
if not mode or (mode == self.mode and not matrix):
return self.copy()
if matrix:
# matrix conversion
if mode not in ("L", "RGB"):
raise ValueError("illegal conversion")
im = self.im.convert_matrix(mode, matrix)
new = self._new(im)
if has_transparency and self.im.bands == 3:
transparency = new.info["transparency"]
def convert_transparency(m, v):
v = m[0] * v[0] + m[1] * v[1] + m[2] * v[2] + m[3] * 0.5
return max(0, min(255, int(v)))
if mode == "L":
transparency = convert_transparency(matrix, transparency)
elif len(mode) == 3:
transparency = tuple(
convert_transparency(matrix[i * 4 : i * 4 + 4], transparency)
for i in range(0, len(transparency))
)
new.info["transparency"] = transparency
return new
if mode == "P" and self.mode == "RGBA":
return self.quantize(colors)
trns = None
delete_trns = False
# transparency handling
if has_transparency:
if self.mode in ("1", "L", "I", "RGB") and mode == "RGBA":
# Use transparent conversion to promote from transparent
# color to an alpha channel.
new_im = self._new(
self.im.convert_transparent(mode, self.info["transparency"])
)
del new_im.info["transparency"]
return new_im
elif self.mode in ("L", "RGB", "P") and mode in ("L", "RGB", "P"):
t = self.info["transparency"]
if isinstance(t, bytes):
# Dragons. This can't be represented by a single color
warnings.warn(
"Palette images with Transparency expressed in bytes should be "
"converted to RGBA images"
)
delete_trns = True
else:
# get the new transparency color.
# use existing conversions
trns_im = Image()._new(core.new(self.mode, (1, 1)))
if self.mode == "P":
trns_im.putpalette(self.palette)
if isinstance(t, tuple):
err = "Couldn't allocate a palette color for transparency"
try:
t = trns_im.palette.getcolor(t, self)
except ValueError as e:
if str(e) == "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
t = None
else:
raise ValueError(err) from e
if t is None:
trns = None
else:
trns_im.putpixel((0, 0), t)
if mode in ("L", "RGB"):
trns_im = trns_im.convert(mode)
else:
# can't just retrieve the palette number, got to do it
# after quantization.
trns_im = trns_im.convert("RGB")
trns = trns_im.getpixel((0, 0))
elif self.mode == "P" and mode in ("LA", "PA", "RGBA"):
t = self.info["transparency"]
delete_trns = True
if isinstance(t, bytes):
self.im.putpalettealphas(t)
elif isinstance(t, int):
self.im.putpalettealpha(t, 0)
else:
raise ValueError("Transparency for P mode should be bytes or int")
if mode == "P" and palette == ADAPTIVE:
im = self.im.quantize(colors)
new = self._new(im)
from . import ImagePalette
new.palette = ImagePalette.ImagePalette("RGB", new.im.getpalette("RGB"))
if delete_trns:
# This could possibly happen if we requantize to fewer colors.
# The transparency would be totally off in that case.
del new.info["transparency"]
if trns is not None:
try:
new.info["transparency"] = new.palette.getcolor(trns, new)
except Exception:
# if we can't make a transparent color, don't leave the old
# transparency hanging around to mess us up.
del new.info["transparency"]
warnings.warn("Couldn't allocate palette entry for transparency")
return new
# colorspace conversion
if dither is None:
dither = FLOYDSTEINBERG
try:
im = self.im.convert(mode, dither)
except ValueError:
try:
# normalize source image and try again
im = self.im.convert(getmodebase(self.mode))
im = im.convert(mode, dither)
except KeyError as e:
raise ValueError("illegal conversion") from e
new_im = self._new(im)
if mode == "P" and palette != ADAPTIVE:
from . import ImagePalette
new_im.palette = ImagePalette.ImagePalette("RGB", list(range(256)) * 3)
if delete_trns:
# crash fail if we leave a bytes transparency in an rgb/l mode.
del new_im.info["transparency"]
if trns is not None:
if new_im.mode == "P":
try:
new_im.info["transparency"] = new_im.palette.getcolor(trns, new_im)
except ValueError as e:
del new_im.info["transparency"]
if str(e) != "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
warnings.warn(
"Couldn't allocate palette entry for transparency"
)
else:
new_im.info["transparency"] = trns
return new_im
def quantize(self, colors=256, method=None, kmeans=0, palette=None, dither=1):
"""
Convert the image to 'P' mode with the specified number
of colors.
:param colors: The desired number of colors, <= 256
:param method: :data:`MEDIANCUT` (median cut),
:data:`MAXCOVERAGE` (maximum coverage),
:data:`FASTOCTREE` (fast octree),
:data:`LIBIMAGEQUANT` (libimagequant; check support using
:py:func:`PIL.features.check_feature`
with ``feature="libimagequant"``).
By default, :data:`MEDIANCUT` will be used.
The exception to this is RGBA images. :data:`MEDIANCUT` and
:data:`MAXCOVERAGE` do not support RGBA images, so
:data:`FASTOCTREE` is used by default instead.
:param kmeans: Integer
:param palette: Quantize to the palette of given
:py:class:`PIL.Image.Image`.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Default: 1 (legacy setting)
:returns: A new image
"""
self.load()
if method is None:
# defaults:
method = MEDIANCUT
if self.mode == "RGBA":
method = FASTOCTREE
if self.mode == "RGBA" and method not in (FASTOCTREE, LIBIMAGEQUANT):
# Caller specified an invalid mode.
raise ValueError(
"Fast Octree (method == 2) and libimagequant (method == 3) "
"are the only valid methods for quantizing RGBA images"
)
if palette:
# use palette from reference image
palette.load()
if palette.mode != "P":
raise ValueError("bad mode for palette image")
if self.mode != "RGB" and self.mode != "L":
raise ValueError(
"only RGB or L mode images can be quantized to a palette"
)
im = self.im.convert("P", dither, palette.im)
new_im = self._new(im)
new_im.palette = palette.palette.copy()
return new_im
im = self._new(self.im.quantize(colors, method, kmeans))
from . import ImagePalette
mode = im.im.getpalettemode()
palette = im.im.getpalette(mode, mode)[: colors * len(mode)]
im.palette = ImagePalette.ImagePalette(mode, palette)
return im
def copy(self):
"""
Copies this image. Use this method if you wish to paste things
into an image, but still retain the original.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
return self._new(self.im.copy())
__copy__ = copy
def crop(self, box=None):
"""
Returns a rectangular region from this image. The box is a
4-tuple defining the left, upper, right, and lower pixel
coordinate. See :ref:`coordinate-system`.
Note: Prior to Pillow 3.4.0, this was a lazy operation.
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if box is None:
return self.copy()
self.load()
return self._new(self._crop(self.im, box))
def _crop(self, im, box):
"""
Returns a rectangular region from the core image object im.
This is equivalent to calling im.crop((x0, y0, x1, y1)), but
includes additional sanity checks.
:param im: a core image object
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:returns: A core image object.
"""
x0, y0, x1, y1 = map(int, map(round, box))
absolute_values = (abs(x1 - x0), abs(y1 - y0))
_decompression_bomb_check(absolute_values)
return im.crop((x0, y0, x1, y1))
def draft(self, mode, size):
"""
Configures the image file loader so it returns a version of the
image that as closely as possible matches the given mode and
size. For example, you can use this method to convert a color
JPEG to greyscale while loading it.
If any changes are made, returns a tuple with the chosen ``mode`` and
``box`` with coordinates of the original image within the altered one.
Note that this method modifies the :py:class:`~PIL.Image.Image` object
in place. If the image has already been loaded, this method has no
effect.
Note: This method is not implemented for most images. It is
currently implemented only for JPEG and MPO images.
:param mode: The requested mode.
:param size: The requested size.
"""
pass
def _expand(self, xmargin, ymargin=None):
if ymargin is None:
ymargin = xmargin
self.load()
return self._new(self.im.expand(xmargin, ymargin, 0))
def filter(self, filter):
"""
Filters this image using the given filter. For a list of
available filters, see the :py:mod:`~PIL.ImageFilter` module.
:param filter: Filter kernel.
:returns: An :py:class:`~PIL.Image.Image` object."""
from . import ImageFilter
self.load()
if isinstance(filter, Callable):
filter = filter()
if not hasattr(filter, "filter"):
raise TypeError(
"filter argument should be ImageFilter.Filter instance or class"
)
multiband = isinstance(filter, ImageFilter.MultibandFilter)
if self.im.bands == 1 or multiband:
return self._new(filter.filter(self.im))
ims = []
for c in range(self.im.bands):
ims.append(self._new(filter.filter(self.im.getband(c))))
return merge(self.mode, ims)
def getbands(self):
"""
Returns a tuple containing the name of each band in this image.
For example, ``getbands`` on an RGB image returns ("R", "G", "B").
:returns: A tuple containing band names.
:rtype: tuple
"""
return ImageMode.getmode(self.mode).bands
def getbbox(self):
"""
Calculates the bounding box of the non-zero regions in the
image.
:returns: The bounding box is returned as a 4-tuple defining the
left, upper, right, and lower pixel coordinate. See
:ref:`coordinate-system`. If the image is completely empty, this
method returns None.
"""
self.load()
return self.im.getbbox()
def getcolors(self, maxcolors=256):
"""
Returns a list of colors used in this image.
The colors will be in the image's mode. For example, an RGB image will
return a tuple of (red, green, blue) color values, and a P image will
return the index of the color in the palette.
:param maxcolors: Maximum number of colors. If this number is
exceeded, this method returns None. The default limit is
256 colors.
:returns: An unsorted list of (count, pixel) values.
"""
self.load()
if self.mode in ("1", "L", "P"):
h = self.im.histogram()
out = []
for i in range(256):
if h[i]:
out.append((h[i], i))
if len(out) > maxcolors:
return None
return out
return self.im.getcolors(maxcolors)
def getdata(self, band=None):
"""
Returns the contents of this image as a sequence object
containing pixel values. The sequence object is flattened, so
that values for line one follow directly after the values of
line zero, and so on.
Note that the sequence object returned by this method is an
internal PIL data type, which only supports certain sequence
operations. To convert it to an ordinary sequence (e.g. for
printing), use ``list(im.getdata())``.
:param band: What band to return. The default is to return
all bands. To return a single band, pass in the index
value (e.g. 0 to get the "R" band from an "RGB" image).
:returns: A sequence-like object.
"""
self.load()
if band is not None:
return self.im.getband(band)
return self.im # could be abused
def getextrema(self):
"""
Gets the the minimum and maximum pixel values for each band in
the image.
:returns: For a single-band image, a 2-tuple containing the
minimum and maximum pixel value. For a multi-band image,
a tuple containing one 2-tuple for each band.
"""
self.load()
if self.im.bands > 1:
extrema = []
for i in range(self.im.bands):
extrema.append(self.im.getband(i).getextrema())
return tuple(extrema)
return self.im.getextrema()
def _getxmp(self, xmp_tags):
def get_name(tag):
return tag.split("}")[1]
def get_value(element):
value = {get_name(k): v for k, v in element.attrib.items()}
children = list(element)
if children:
for child in children:
name = get_name(child.tag)
child_value = get_value(child)
if name in value:
if not isinstance(value[name], list):
value[name] = [value[name]]
value[name].append(child_value)
else:
value[name] = child_value
elif value:
if element.text:
value["text"] = element.text
else:
return element.text
return value
if ElementTree is None:
warnings.warn("XMP data cannot be read without defusedxml dependency")
return {}
else:
root = ElementTree.fromstring(xmp_tags)
return {get_name(root.tag): get_value(root)}
def getexif(self):
if self._exif is None:
self._exif = Exif()
exif_info = self.info.get("exif")
if exif_info is None:
if "Raw profile type exif" in self.info:
exif_info = bytes.fromhex(
"".join(self.info["Raw profile type exif"].split("\n")[3:])
)
elif hasattr(self, "tag_v2"):
self._exif.endian = self.tag_v2._endian
self._exif.load_from_fp(self.fp, self.tag_v2._offset)
if exif_info is not None:
self._exif.load(exif_info)
# XMP tags
if 0x0112 not in self._exif:
xmp_tags = self.info.get("XML:com.adobe.xmp")
if xmp_tags:
match = re.search(r'tiff:Orientation="([0-9])"', xmp_tags)
if match:
self._exif[0x0112] = int(match[1])
return self._exif
def getim(self):
"""
Returns a capsule that points to the internal image memory.
:returns: A capsule object.
"""
self.load()
return self.im.ptr
def getpalette(self):
"""
Returns the image palette as a list.
:returns: A list of color values [r, g, b, ...], or None if the
image has no palette.
"""
self.load()
try:
return list(self.im.getpalette())
except ValueError:
return None # no palette
def getpixel(self, xy):
"""
Returns the pixel value at a given position.
:param xy: The coordinate, given as (x, y). See
:ref:`coordinate-system`.
:returns: The pixel value. If the image is a multi-layer image,
this method returns a tuple.
"""
self.load()
if self.pyaccess:
return self.pyaccess.getpixel(xy)
return self.im.getpixel(xy)
def getprojection(self):
"""
Get projection to x and y axes
:returns: Two sequences, indicating where there are non-zero
pixels along the X-axis and the Y-axis, respectively.
"""
self.load()
x, y = self.im.getprojection()
return list(x), list(y)
def histogram(self, mask=None, extrema=None):
"""
Returns a histogram for the image. The histogram is returned as
a list of pixel counts, one for each pixel value in the source
image. If the image has more than one band, the histograms for
all bands are concatenated (for example, the histogram for an
"RGB" image contains 768 values).
A bilevel image (mode "1") is treated as a greyscale ("L") image
by this method.
If a mask is provided, the method returns a histogram for those
parts of the image where the mask image is non-zero. The mask
image must have the same size as the image, and be either a
bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A list containing pixel counts.
"""
self.load()
if mask:
mask.load()
return self.im.histogram((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.histogram(extrema)
return self.im.histogram()
def entropy(self, mask=None, extrema=None):
"""
Calculates and returns the entropy for the image.
A bilevel image (mode "1") is treated as a greyscale ("L")
image by this method.
If a mask is provided, the method employs the histogram for
those parts of the image where the mask image is non-zero.
The mask image must have the same size as the image, and be
either a bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A float value representing the image entropy
"""
self.load()
if mask:
mask.load()
return self.im.entropy((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.entropy(extrema)
return self.im.entropy()
def paste(self, im, box=None, mask=None):
"""
Pastes another image into this image. The box argument is either
a 2-tuple giving the upper left corner, a 4-tuple defining the
left, upper, right, and lower pixel coordinate, or None (same as
(0, 0)). See :ref:`coordinate-system`. If a 4-tuple is given, the size
of the pasted image must match the size of the region.
If the modes don't match, the pasted image is converted to the mode of
this image (see the :py:meth:`~PIL.Image.Image.convert` method for
details).
Instead of an image, the source can be a integer or tuple
containing pixel values. The method then fills the region
with the given color. When creating RGB images, you can
also use color strings as supported by the ImageColor module.
If a mask is given, this method updates only the regions
indicated by the mask. You can use either "1", "L" or "RGBA"
images (in the latter case, the alpha band is used as mask).
Where the mask is 255, the given image is copied as is. Where
the mask is 0, the current value is preserved. Intermediate
values will mix the two images together, including their alpha
channels if they have them.
See :py:meth:`~PIL.Image.Image.alpha_composite` if you want to
combine images with respect to their alpha channels.
:param im: Source image or pixel value (integer or tuple).
:param box: An optional 4-tuple giving the region to paste into.
If a 2-tuple is used instead, it's treated as the upper left
corner. If omitted or None, the source is pasted into the
upper left corner.
If an image is given as the second argument and there is no
third, the box defaults to (0, 0), and the second argument
is interpreted as a mask image.
:param mask: An optional mask image.
"""
if isImageType(box) and mask is None:
# abbreviated paste(im, mask) syntax
mask = box
box = None
if box is None:
box = (0, 0)
if len(box) == 2:
# upper left corner given; get size from image or mask
if isImageType(im):
size = im.size
elif isImageType(mask):
size = mask.size
else:
# FIXME: use self.size here?
raise ValueError("cannot determine region size; use 4-item box")
box += (box[0] + size[0], box[1] + size[1])
if isinstance(im, str):
from . import ImageColor
im = ImageColor.getcolor(im, self.mode)
elif isImageType(im):
im.load()
if self.mode != im.mode:
if self.mode != "RGB" or im.mode not in ("RGBA", "RGBa"):
# should use an adapter for this!
im = im.convert(self.mode)
im = im.im
self._ensure_mutable()
if mask:
mask.load()
self.im.paste(im, box, mask.im)
else:
self.im.paste(im, box)
def alpha_composite(self, im, dest=(0, 0), source=(0, 0)):
"""'In-place' analog of Image.alpha_composite. Composites an image
onto this image.
:param im: image to composite over this one
:param dest: Optional 2 tuple (left, top) specifying the upper
left corner in this (destination) image.
:param source: Optional 2 (left, top) tuple for the upper left
corner in the overlay source image, or 4 tuple (left, top, right,
bottom) for the bounds of the source rectangle
Performance Note: Not currently implemented in-place in the core layer.
"""
if not isinstance(source, (list, tuple)):
raise ValueError("Source must be a tuple")
if not isinstance(dest, (list, tuple)):
raise ValueError("Destination must be a tuple")
if not len(source) in (2, 4):
raise ValueError("Source must be a 2 or 4-tuple")
if not len(dest) == 2:
raise ValueError("Destination must be a 2-tuple")
if min(source) < 0:
raise ValueError("Source must be non-negative")
if len(source) == 2:
source = source + im.size
# over image, crop if it's not the whole thing.
if source == (0, 0) + im.size:
overlay = im
else:
overlay = im.crop(source)
# target for the paste
box = dest + (dest[0] + overlay.width, dest[1] + overlay.height)
# destination image. don't copy if we're using the whole image.
if box == (0, 0) + self.size:
background = self
else:
background = self.crop(box)
result = alpha_composite(background, overlay)
self.paste(result, box)
def point(self, lut, mode=None):
"""
Maps this image through a lookup table or function.
:param lut: A lookup table, containing 256 (or 65536 if
self.mode=="I" and mode == "L") values per band in the
image. A function can be used instead, it should take a
single argument. The function is called once for each
possible pixel value, and the resulting table is applied to
all bands of the image.
It may also be an :py:class:`~PIL.Image.ImagePointHandler`
object::
class Example(Image.ImagePointHandler):
def point(self, data):
# Return result
:param mode: Output mode (default is same as input). In the
current version, this can only be used if the source image
has mode "L" or "P", and the output has mode "1" or the
source image mode is "I" and the output mode is "L".
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
if isinstance(lut, ImagePointHandler):
return lut.point(self)
if callable(lut):
# if it isn't a list, it should be a function
if self.mode in ("I", "I;16", "F"):
# check if the function can be used with point_transform
# UNDONE wiredfool -- I think this prevents us from ever doing
# a gamma function point transform on > 8bit images.
scale, offset = _getscaleoffset(lut)
return self._new(self.im.point_transform(scale, offset))
# for other modes, convert the function to a table
lut = [lut(i) for i in range(256)] * self.im.bands
if self.mode == "F":
# FIXME: _imaging returns a confusing error message for this case
raise ValueError("point operation not supported for this mode")
return self._new(self.im.point(lut, mode))
def putalpha(self, alpha):
"""
Adds or replaces the alpha layer in this image. If the image
does not have an alpha layer, it's converted to "LA" or "RGBA".
The new layer must be either "L" or "1".
:param alpha: The new alpha layer. This can either be an "L" or "1"
image having the same size as this image, or an integer or
other color value.
"""
self._ensure_mutable()
if self.mode not in ("LA", "PA", "RGBA"):
# attempt to promote self to a matching alpha mode
try:
mode = getmodebase(self.mode) + "A"
try:
self.im.setmode(mode)
except (AttributeError, ValueError) as e:
# do things the hard way
im = self.im.convert(mode)
if im.mode not in ("LA", "PA", "RGBA"):
raise ValueError from e # sanity check
self.im = im
self.pyaccess = None
self.mode = self.im.mode
except KeyError as e:
raise ValueError("illegal image mode") from e
if self.mode in ("LA", "PA"):
band = 1
else:
band = 3
if isImageType(alpha):
# alpha layer
if alpha.mode not in ("1", "L"):
raise ValueError("illegal image mode")
alpha.load()
if alpha.mode == "1":
alpha = alpha.convert("L")
else:
# constant alpha
try:
self.im.fillband(band, alpha)
except (AttributeError, ValueError):
# do things the hard way
alpha = new("L", self.size, alpha)
else:
return
self.im.putband(alpha.im, band)
def putdata(self, data, scale=1.0, offset=0.0):
"""
Copies pixel data from a flattened sequence object into the image. The
values should start at the upper left corner (0, 0), continue to the
end of the line, followed directly by the first value of the second
line, and so on. Data will be read until either the image or the
sequence ends. The scale and offset values are used to adjust the
sequence values: **pixel = value*scale + offset**.
:param data: A flattened sequence object.
:param scale: An optional scale value. The default is 1.0.
:param offset: An optional offset value. The default is 0.0.
"""
self._ensure_mutable()
self.im.putdata(data, scale, offset)
def putpalette(self, data, rawmode="RGB"):
"""
Attaches a palette to this image. The image must be a "P", "PA", "L"
or "LA" image.
The palette sequence must contain at most 256 colors, made up of one
integer value for each channel in the raw mode.
For example, if the raw mode is "RGB", then it can contain at most 768
values, made up of red, green and blue values for the corresponding pixel
index in the 256 colors.
If the raw mode is "RGBA", then it can contain at most 1024 values,
containing red, green, blue and alpha values.
Alternatively, an 8-bit string may be used instead of an integer sequence.
:param data: A palette sequence (either a list or a string).
:param rawmode: The raw mode of the palette. Either "RGB", "RGBA", or a
mode that can be transformed to "RGB" (e.g. "R", "BGR;15", "RGBA;L").
"""
from . import ImagePalette
if self.mode not in ("L", "LA", "P", "PA"):
raise ValueError("illegal image mode")
if isinstance(data, ImagePalette.ImagePalette):
palette = ImagePalette.raw(data.rawmode, data.palette)
else:
if not isinstance(data, bytes):
data = bytes(data)
palette = ImagePalette.raw(rawmode, data)
self.mode = "PA" if "A" in self.mode else "P"
self.palette = palette
self.palette.mode = "RGB"
self.load() # install new palette
def putpixel(self, xy, value):
"""
Modifies the pixel at the given position. The color is given as
a single numerical value for single-band images, and a tuple for
multi-band images. In addition to this, RGB and RGBA tuples are
accepted for P images.
Note that this method is relatively slow. For more extensive changes,
use :py:meth:`~PIL.Image.Image.paste` or the :py:mod:`~PIL.ImageDraw`
module instead.
See:
* :py:meth:`~PIL.Image.Image.paste`
* :py:meth:`~PIL.Image.Image.putdata`
* :py:mod:`~PIL.ImageDraw`
:param xy: The pixel coordinate, given as (x, y). See
:ref:`coordinate-system`.
:param value: The pixel value.
"""
if self.readonly:
self._copy()
self.load()
if self.pyaccess:
return self.pyaccess.putpixel(xy, value)
if (
self.mode == "P"
and isinstance(value, (list, tuple))
and len(value) in [3, 4]
):
# RGB or RGBA value for a P image
value = self.palette.getcolor(value, self)
return self.im.putpixel(xy, value)
def remap_palette(self, dest_map, source_palette=None):
"""
Rewrites the image to reorder the palette.
:param dest_map: A list of indexes into the original palette.
e.g. ``[1,0]`` would swap a two item palette, and ``list(range(256))``
is the identity transform.
:param source_palette: Bytes or None.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
from . import ImagePalette
if self.mode not in ("L", "P"):
raise ValueError("illegal image mode")
if source_palette is None:
if self.mode == "P":
self.load()
source_palette = self.im.getpalette("RGB")[:768]
else: # L-mode
source_palette = bytearray(i // 3 for i in range(768))
palette_bytes = b""
new_positions = [0] * 256
# pick only the used colors from the palette
for i, oldPosition in enumerate(dest_map):
palette_bytes += source_palette[oldPosition * 3 : oldPosition * 3 + 3]
new_positions[oldPosition] = i
# replace the palette color id of all pixel with the new id
# Palette images are [0..255], mapped through a 1 or 3
# byte/color map. We need to remap the whole image
# from palette 1 to palette 2. New_positions is
# an array of indexes into palette 1. Palette 2 is
# palette 1 with any holes removed.
# We're going to leverage the convert mechanism to use the
# C code to remap the image from palette 1 to palette 2,
# by forcing the source image into 'L' mode and adding a
# mapping 'L' mode palette, then converting back to 'L'
# sans palette thus converting the image bytes, then
# assigning the optimized RGB palette.
# perf reference, 9500x4000 gif, w/~135 colors
# 14 sec prepatch, 1 sec postpatch with optimization forced.
mapping_palette = bytearray(new_positions)
m_im = self.copy()
m_im.mode = "P"
m_im.palette = ImagePalette.ImagePalette("RGB", palette=mapping_palette * 3)
# possibly set palette dirty, then
# m_im.putpalette(mapping_palette, 'L') # converts to 'P'
# or just force it.
# UNDONE -- this is part of the general issue with palettes
m_im.im.putpalette("RGB;L", m_im.palette.tobytes())
m_im = m_im.convert("L")
# Internally, we require 768 bytes for a palette.
new_palette_bytes = palette_bytes + (768 - len(palette_bytes)) * b"\x00"
m_im.putpalette(new_palette_bytes)
m_im.palette = ImagePalette.ImagePalette("RGB", palette=palette_bytes)
return m_im
def _get_safe_box(self, size, resample, box):
"""Expands the box so it includes adjacent pixels
that may be used by resampling with the given resampling filter.
"""
filter_support = _filters_support[resample] - 0.5
scale_x = (box[2] - box[0]) / size[0]
scale_y = (box[3] - box[1]) / size[1]
support_x = filter_support * scale_x
support_y = filter_support * scale_y
return (
max(0, int(box[0] - support_x)),
max(0, int(box[1] - support_y)),
min(self.size[0], math.ceil(box[2] + support_x)),
min(self.size[1], math.ceil(box[3] + support_y)),
)
def resize(self, size, resample=None, box=None, reducing_gap=None):
"""
Returns a resized copy of this image.
:param size: The requested size in pixels, as a 2-tuple:
(width, height).
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If the image has mode "1" or "P", it is always set to
:py:data:`PIL.Image.NEAREST`.
If the image mode specifies a number of bits, such as "I;16", then the
default filter is :py:data:`PIL.Image.NEAREST`.
Otherwise, the default filter is :py:data:`PIL.Image.BICUBIC`.
See: :ref:`concept-filters`.
:param box: An optional 4-tuple of floats providing
the source image region to be scaled.
The values must be within (0, 0, width, height) rectangle.
If omitted or None, the entire source is used.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce`.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is None (no optimization).
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if resample is None:
type_special = ";" in self.mode
resample = NEAREST if type_special else BICUBIC
elif resample not in (NEAREST, BILINEAR, BICUBIC, LANCZOS, BOX, HAMMING):
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(LANCZOS, "Image.LANCZOS"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
(BOX, "Image.BOX"),
(HAMMING, "Image.HAMMING"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
if reducing_gap is not None and reducing_gap < 1.0:
raise ValueError("reducing_gap must be 1.0 or greater")
size = tuple(size)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if self.size == size and box == (0, 0) + self.size:
return self.copy()
if self.mode in ("1", "P"):
resample = NEAREST
if self.mode in ["LA", "RGBA"] and resample != NEAREST:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.resize(size, resample, box)
return im.convert(self.mode)
self.load()
if reducing_gap is not None and resample != NEAREST:
factor_x = int((box[2] - box[0]) / size[0] / reducing_gap) or 1
factor_y = int((box[3] - box[1]) / size[1] / reducing_gap) or 1
if factor_x > 1 or factor_y > 1:
reduce_box = self._get_safe_box(size, resample, box)
factor = (factor_x, factor_y)
if callable(self.reduce):
self = self.reduce(factor, box=reduce_box)
else:
self = Image.reduce(self, factor, box=reduce_box)
box = (
(box[0] - reduce_box[0]) / factor_x,
(box[1] - reduce_box[1]) / factor_y,
(box[2] - reduce_box[0]) / factor_x,
(box[3] - reduce_box[1]) / factor_y,
)
return self._new(self.im.resize(size, resample, box))
def reduce(self, factor, box=None):
"""
Returns a copy of the image reduced ``factor`` times.
If the size of the image is not dividable by ``factor``,
the resulting size will be rounded up.
:param factor: A greater than 0 integer or tuple of two integers
for width and height separately.
:param box: An optional 4-tuple of ints providing
the source image region to be reduced.
The values must be within ``(0, 0, width, height)`` rectangle.
If omitted or ``None``, the entire source is used.
"""
if not isinstance(factor, (list, tuple)):
factor = (factor, factor)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if factor == (1, 1) and box == (0, 0) + self.size:
return self.copy()
if self.mode in ["LA", "RGBA"]:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.reduce(factor, box)
return im.convert(self.mode)
self.load()
return self._new(self.im.reduce(factor, box))
def rotate(
self,
angle,
resample=NEAREST,
expand=0,
center=None,
translate=None,
fillcolor=None,
):
"""
Returns a rotated copy of this image. This method returns a
copy of this image, rotated the given number of degrees counter
clockwise around its centre.
:param angle: In degrees counter clockwise.
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC`
(cubic spline interpolation in a 4x4 environment).
If omitted, or if the image has mode "1" or "P", it is
set to :py:data:`PIL.Image.NEAREST`. See :ref:`concept-filters`.
:param expand: Optional expansion flag. If true, expands the output
image to make it large enough to hold the entire rotated image.
If false or omitted, make the output image the same size as the
input image. Note that the expand flag assumes rotation around
the center and no translation.
:param center: Optional center of rotation (a 2-tuple). Origin is
the upper left corner. Default is the center of the image.
:param translate: An optional post-rotate translation (a 2-tuple).
:param fillcolor: An optional color for area outside the rotated image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
angle = angle % 360.0
# Fast paths regardless of filter, as long as we're not
# translating or changing the center.
if not (center or translate):
if angle == 0:
return self.copy()
if angle == 180:
return self.transpose(ROTATE_180)
if angle in (90, 270) and (expand or self.width == self.height):
return self.transpose(ROTATE_90 if angle == 90 else ROTATE_270)
# Calculate the affine matrix. Note that this is the reverse
# transformation (from destination image to source) because we
# want to interpolate the (discrete) destination pixel from
# the local area around the (floating) source pixel.
# The matrix we actually want (note that it operates from the right):
# (1, 0, tx) (1, 0, cx) ( cos a, sin a, 0) (1, 0, -cx)
# (0, 1, ty) * (0, 1, cy) * (-sin a, cos a, 0) * (0, 1, -cy)
# (0, 0, 1) (0, 0, 1) ( 0, 0, 1) (0, 0, 1)
# The reverse matrix is thus:
# (1, 0, cx) ( cos -a, sin -a, 0) (1, 0, -cx) (1, 0, -tx)
# (0, 1, cy) * (-sin -a, cos -a, 0) * (0, 1, -cy) * (0, 1, -ty)
# (0, 0, 1) ( 0, 0, 1) (0, 0, 1) (0, 0, 1)
# In any case, the final translation may be updated at the end to
# compensate for the expand flag.
w, h = self.size
if translate is None:
post_trans = (0, 0)
else:
post_trans = translate
if center is None:
# FIXME These should be rounded to ints?
rotn_center = (w / 2.0, h / 2.0)
else:
rotn_center = center
angle = -math.radians(angle)
matrix = [
round(math.cos(angle), 15),
round(math.sin(angle), 15),
0.0,
round(-math.sin(angle), 15),
round(math.cos(angle), 15),
0.0,
]
def transform(x, y, matrix):
(a, b, c, d, e, f) = matrix
return a * x + b * y + c, d * x + e * y + f
matrix[2], matrix[5] = transform(
-rotn_center[0] - post_trans[0], -rotn_center[1] - post_trans[1], matrix
)
matrix[2] += rotn_center[0]
matrix[5] += rotn_center[1]
if expand:
# calculate output size
xx = []
yy = []
for x, y in ((0, 0), (w, 0), (w, h), (0, h)):
x, y = transform(x, y, matrix)
xx.append(x)
yy.append(y)
nw = math.ceil(max(xx)) - math.floor(min(xx))
nh = math.ceil(max(yy)) - math.floor(min(yy))
# We multiply a translation matrix from the right. Because of its
# special form, this is the same as taking the image of the
# translation vector as new translation vector.
matrix[2], matrix[5] = transform(-(nw - w) / 2.0, -(nh - h) / 2.0, matrix)
w, h = nw, nh
return self.transform((w, h), AFFINE, matrix, resample, fillcolor=fillcolor)
def save(self, fp, format=None, **params):
"""
Saves this image under the given filename. If no format is
specified, the format to use is determined from the filename
extension, if possible.
Keyword options can be used to provide additional instructions
to the writer. If a writer doesn't recognise an option, it is
silently ignored. The available options are described in the
:doc:`image format documentation
<../handbook/image-file-formats>` for each writer.
You can use a file object instead of a filename. In this case,
you must always specify the format. The file object must
implement the ``seek``, ``tell``, and ``write``
methods, and be opened in binary mode.
:param fp: A filename (string), pathlib.Path object or file object.
:param format: Optional format override. If omitted, the
format to use is determined from the filename extension.
If a file object was used instead of a filename, this
parameter should always be used.
:param params: Extra parameters to the image writer.
:returns: None
:exception ValueError: If the output format could not be determined
from the file name. Use the format option to solve this.
:exception OSError: If the file could not be written. The file
may have been created, and may contain partial data.
"""
filename = ""
open_fp = False
if isinstance(fp, Path):
filename = str(fp)
open_fp = True
elif isPath(fp):
filename = fp
open_fp = True
elif fp == sys.stdout:
try:
fp = sys.stdout.buffer
except AttributeError:
pass
if not filename and hasattr(fp, "name") and isPath(fp.name):
# only set the name for metadata purposes
filename = fp.name
# may mutate self!
self._ensure_mutable()
save_all = params.pop("save_all", False)
self.encoderinfo = params
self.encoderconfig = ()
preinit()
ext = os.path.splitext(filename)[1].lower()
if not format:
if ext not in EXTENSION:
init()
try:
format = EXTENSION[ext]
except KeyError as e:
raise ValueError(f"unknown file extension: {ext}") from e
if format.upper() not in SAVE:
init()
if save_all:
save_handler = SAVE_ALL[format.upper()]
else:
save_handler = SAVE[format.upper()]
if open_fp:
if params.get("append", False):
# Open also for reading ("+"), because TIFF save_all
# writer needs to go back and edit the written data.
fp = builtins.open(filename, "r+b")
else:
fp = builtins.open(filename, "w+b")
try:
save_handler(self, fp, filename)
finally:
# do what we can to clean up
if open_fp:
fp.close()
def seek(self, frame):
"""
Seeks to the given frame in this sequence file. If you seek
beyond the end of the sequence, the method raises an
``EOFError`` exception. When a sequence file is opened, the
library automatically seeks to frame 0.
See :py:meth:`~PIL.Image.Image.tell`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:param frame: Frame number, starting at 0.
:exception EOFError: If the call attempts to seek beyond the end
of the sequence.
"""
# overridden by file handlers
if frame != 0:
raise EOFError
def show(self, title=None):
"""
Displays this image. This method is mainly intended for debugging purposes.
This method calls :py:func:`PIL.ImageShow.show` internally. You can use
:py:func:`PIL.ImageShow.register` to override its default behaviour.
The image is first saved to a temporary file. By default, it will be in
PNG format.
On Unix, the image is then opened using the **display**, **eog** or
**xv** utility, depending on which one can be found.
On macOS, the image is opened with the native Preview application.
On Windows, the image is opened with the standard PNG display utility.
:param title: Optional title to use for the image window, where possible.
"""
_show(self, title=title)
def split(self):
"""
Split this image into individual bands. This method returns a
tuple of individual image bands from an image. For example,
splitting an "RGB" image creates three new images each
containing a copy of one of the original bands (red, green,
blue).
If you need only one band, :py:meth:`~PIL.Image.Image.getchannel`
method can be more convenient and faster.
:returns: A tuple containing bands.
"""
self.load()
if self.im.bands == 1:
ims = [self.copy()]
else:
ims = map(self._new, self.im.split())
return tuple(ims)
def getchannel(self, channel):
"""
Returns an image containing a single channel of the source image.
:param channel: What channel to return. Could be index
(0 for "R" channel of "RGB") or channel name
("A" for alpha channel of "RGBA").
:returns: An image in "L" mode.
.. versionadded:: 4.3.0
"""
self.load()
if isinstance(channel, str):
try:
channel = self.getbands().index(channel)
except ValueError as e:
raise ValueError(f'The image has no channel "{channel}"') from e
return self._new(self.im.getband(channel))
def tell(self):
"""
Returns the current frame number. See :py:meth:`~PIL.Image.Image.seek`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:returns: Frame number, starting with 0.
"""
return 0
def thumbnail(self, size, resample=BICUBIC, reducing_gap=2.0):
"""
Make this image into a thumbnail. This method modifies the
image to contain a thumbnail version of itself, no larger than
the given size. This method calculates an appropriate thumbnail
size to preserve the aspect of the image, calls the
:py:meth:`~PIL.Image.Image.draft` method to configure the file reader
(where applicable), and finally resizes the image.
Note that this function modifies the :py:class:`~PIL.Image.Image`
object in place. If you need to use the full resolution image as well,
apply this method to a :py:meth:`~PIL.Image.Image.copy` of the original
image.
:param size: Requested size.
:param resample: Optional resampling filter. This can be one
of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If omitted, it defaults to :py:data:`PIL.Image.BICUBIC`.
(was :py:data:`PIL.Image.NEAREST` prior to version 2.5.0).
See: :ref:`concept-filters`.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce` or
:py:meth:`~PIL.Image.Image.draft` for JPEG images.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is 2.0 (very close to fair resampling
while still being faster in many cases).
:returns: None
"""
x, y = map(math.floor, size)
if x >= self.width and y >= self.height:
return
def round_aspect(number, key):
return max(min(math.floor(number), math.ceil(number), key=key), 1)
# preserve aspect ratio
aspect = self.width / self.height
if x / y >= aspect:
x = round_aspect(y * aspect, key=lambda n: abs(aspect - n / y))
else:
y = round_aspect(
x / aspect, key=lambda n: 0 if n == 0 else abs(aspect - x / n)
)
size = (x, y)
box = None
if reducing_gap is not None:
res = self.draft(None, (size[0] * reducing_gap, size[1] * reducing_gap))
if res is not None:
box = res[1]
if self.size != size:
im = self.resize(size, resample, box=box, reducing_gap=reducing_gap)
self.im = im.im
self._size = size
self.mode = self.im.mode
self.readonly = 0
self.pyaccess = None
# FIXME: the different transform methods need further explanation
# instead of bloating the method docs, add a separate chapter.
def transform(
self, size, method, data=None, resample=NEAREST, fill=1, fillcolor=None
):
"""
Transforms this image. This method creates a new image with the
given size, and the same mode as the original, and copies data
to the new image using the given transform.
:param size: The output size.
:param method: The transformation method. This is one of
:py:data:`PIL.Image.EXTENT` (cut out a rectangular subregion),
:py:data:`PIL.Image.AFFINE` (affine transform),
:py:data:`PIL.Image.PERSPECTIVE` (perspective transform),
:py:data:`PIL.Image.QUAD` (map a quadrilateral to a rectangle), or
:py:data:`PIL.Image.MESH` (map a number of source quadrilaterals
in one operation).
It may also be an :py:class:`~PIL.Image.ImageTransformHandler`
object::
class Example(Image.ImageTransformHandler):
def transform(self, size, data, resample, fill=1):
# Return result
It may also be an object with a ``method.getdata`` method
that returns a tuple supplying new ``method`` and ``data`` values::
class Example:
def getdata(self):
method = Image.EXTENT
data = (0, 0, 100, 100)
return method, data
:param data: Extra data to the transformation method.
:param resample: Optional resampling filter. It can be one of
:py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC` (cubic spline
interpolation in a 4x4 environment). If omitted, or if the image
has mode "1" or "P", it is set to :py:data:`PIL.Image.NEAREST`.
See: :ref:`concept-filters`.
:param fill: If ``method`` is an
:py:class:`~PIL.Image.ImageTransformHandler` object, this is one of
the arguments passed to it. Otherwise, it is unused.
:param fillcolor: Optional fill color for the area outside the
transform in the output image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if self.mode in ("LA", "RGBA") and resample != NEAREST:
return (
self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
.transform(size, method, data, resample, fill, fillcolor)
.convert(self.mode)
)
if isinstance(method, ImageTransformHandler):
return method.transform(size, self, resample=resample, fill=fill)
if hasattr(method, "getdata"):
# compatibility w. old-style transform objects
method, data = method.getdata()
if data is None:
raise ValueError("missing method data")
im = new(self.mode, size, fillcolor)
if self.mode == "P" and self.palette:
im.palette = self.palette.copy()
im.info = self.info.copy()
if method == MESH:
# list of quads
for box, quad in data:
im.__transformer(box, self, QUAD, quad, resample, fillcolor is None)
else:
im.__transformer(
(0, 0) + size, self, method, data, resample, fillcolor is None
)
return im
def __transformer(self, box, image, method, data, resample=NEAREST, fill=1):
w = box[2] - box[0]
h = box[3] - box[1]
if method == AFFINE:
data = data[0:6]
elif method == EXTENT:
# convert extent to an affine transform
x0, y0, x1, y1 = data
xs = (x1 - x0) / w
ys = (y1 - y0) / h
method = AFFINE
data = (xs, 0, x0, 0, ys, y0)
elif method == PERSPECTIVE:
data = data[0:8]
elif method == QUAD:
# quadrilateral warp. data specifies the four corners
# given as NW, SW, SE, and NE.
nw = data[0:2]
sw = data[2:4]
se = data[4:6]
ne = data[6:8]
x0, y0 = nw
As = 1.0 / w
At = 1.0 / h
data = (
x0,
(ne[0] - x0) * As,
(sw[0] - x0) * At,
(se[0] - sw[0] - ne[0] + x0) * As * At,
y0,
(ne[1] - y0) * As,
(sw[1] - y0) * At,
(se[1] - sw[1] - ne[1] + y0) * As * At,
)
else:
raise ValueError("unknown transformation method")
if resample not in (NEAREST, BILINEAR, BICUBIC):
if resample in (BOX, HAMMING, LANCZOS):
message = {
BOX: "Image.BOX",
HAMMING: "Image.HAMMING",
LANCZOS: "Image.LANCZOS/Image.ANTIALIAS",
}[resample] + f" ({resample}) cannot be used."
else:
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
image.load()
self.load()
if image.mode in ("1", "P"):
resample = NEAREST
self.im.transform2(box, image.im, method, data, resample, fill)
def transpose(self, method):
"""
Transpose image (flip or rotate in 90 degree steps)
:param method: One of :py:data:`PIL.Image.FLIP_LEFT_RIGHT`,
:py:data:`PIL.Image.FLIP_TOP_BOTTOM`, :py:data:`PIL.Image.ROTATE_90`,
:py:data:`PIL.Image.ROTATE_180`, :py:data:`PIL.Image.ROTATE_270`,
:py:data:`PIL.Image.TRANSPOSE` or :py:data:`PIL.Image.TRANSVERSE`.
:returns: Returns a flipped or rotated copy of this image.
"""
self.load()
return self._new(self.im.transpose(method))
def effect_spread(self, distance):
"""
Randomly spread pixels in an image.
:param distance: Distance to spread pixels.
"""
self.load()
return self._new(self.im.effect_spread(distance))
def toqimage(self):
"""Returns a QImage copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqimage(self)
def toqpixmap(self):
"""Returns a QPixmap copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqpixmap(self)
The provided code snippet includes necessary dependencies for implementing the `effect_mandelbrot` function. Write a Python function `def effect_mandelbrot(size, extent, quality)` to solve the following problem:
Generate a Mandelbrot set covering the given extent. :param size: The requested size in pixels, as a 2-tuple: (width, height). :param extent: The extent to cover, as a 4-tuple: (x0, y0, x1, y2). :param quality: Quality.
Here is the function:
def effect_mandelbrot(size, extent, quality):
"""
Generate a Mandelbrot set covering the given extent.
:param size: The requested size in pixels, as a 2-tuple:
(width, height).
:param extent: The extent to cover, as a 4-tuple:
(x0, y0, x1, y2).
:param quality: Quality.
"""
return Image()._new(core.effect_mandelbrot(size, extent, quality)) | Generate a Mandelbrot set covering the given extent. :param size: The requested size in pixels, as a 2-tuple: (width, height). :param extent: The extent to cover, as a 4-tuple: (x0, y0, x1, y2). :param quality: Quality. |
167,777 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
class Image:
"""
This class represents an image object. To create
:py:class:`~PIL.Image.Image` objects, use the appropriate factory
functions. There's hardly ever any reason to call the Image constructor
directly.
* :py:func:`~PIL.Image.open`
* :py:func:`~PIL.Image.new`
* :py:func:`~PIL.Image.frombytes`
"""
format = None
format_description = None
_close_exclusive_fp_after_loading = True
def __init__(self):
# FIXME: take "new" parameters / other image?
# FIXME: turn mode and size into delegating properties?
self.im = None
self.mode = ""
self._size = (0, 0)
self.palette = None
self.info = {}
self._category = 0
self.readonly = 0
self.pyaccess = None
self._exif = None
def __getattr__(self, name):
if name == "category":
warnings.warn(
"Image categories are deprecated and will be removed in Pillow 10 "
"(2023-07-01). Use is_animated instead.",
DeprecationWarning,
stacklevel=2,
)
return self._category
raise AttributeError(name)
def width(self):
return self.size[0]
def height(self):
return self.size[1]
def size(self):
return self._size
def _new(self, im):
new = Image()
new.im = im
new.mode = im.mode
new._size = im.size
if im.mode in ("P", "PA"):
if self.palette:
new.palette = self.palette.copy()
else:
from . import ImagePalette
new.palette = ImagePalette.ImagePalette()
new.info = self.info.copy()
return new
# Context manager support
def __enter__(self):
return self
def __exit__(self, *args):
if hasattr(self, "fp") and getattr(self, "_exclusive_fp", False):
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
def close(self):
"""
Closes the file pointer, if possible.
This operation will destroy the image core and release its memory.
The image data will be unusable afterward.
This function is required to close images that have multiple frames or
have not had their file read and closed by the
:py:meth:`~PIL.Image.Image.load` method. See :ref:`file-handling` for
more information.
"""
try:
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
except Exception as msg:
logger.debug("Error closing: %s", msg)
if getattr(self, "map", None):
self.map = None
# Instead of simply setting to None, we're setting up a
# deferred error that will better explain that the core image
# object is gone.
self.im = deferred_error(ValueError("Operation on closed image"))
def _copy(self):
self.load()
self.im = self.im.copy()
self.pyaccess = None
self.readonly = 0
def _ensure_mutable(self):
if self.readonly:
self._copy()
else:
self.load()
def _dump(self, file=None, format=None, **options):
suffix = ""
if format:
suffix = "." + format
if not file:
f, filename = tempfile.mkstemp(suffix)
os.close(f)
else:
filename = file
if not filename.endswith(suffix):
filename = filename + suffix
self.load()
if not format or format == "PPM":
self.im.save_ppm(filename)
else:
self.save(filename, format, **options)
return filename
def __eq__(self, other):
return (
self.__class__ is other.__class__
and self.mode == other.mode
and self.size == other.size
and self.info == other.info
and self._category == other._category
and self.readonly == other.readonly
and self.getpalette() == other.getpalette()
and self.tobytes() == other.tobytes()
)
def __repr__(self):
return "<%s.%s image mode=%s size=%dx%d at 0x%X>" % (
self.__class__.__module__,
self.__class__.__name__,
self.mode,
self.size[0],
self.size[1],
id(self),
)
def _repr_png_(self):
"""iPython display hook support
:returns: png version of the image as bytes
"""
b = io.BytesIO()
try:
self.save(b, "PNG")
except Exception as e:
raise ValueError("Could not save to PNG for display") from e
return b.getvalue()
class _ArrayData:
def __init__(self, new):
self.__array_interface__ = new
def __array__(self, dtype=None):
# numpy array interface support
import numpy as np
new = {}
shape, typestr = _conv_type_shape(self)
new["shape"] = shape
new["typestr"] = typestr
new["version"] = 3
if self.mode == "1":
# Binary images need to be extended from bits to bytes
# See: https://github.com/python-pillow/Pillow/issues/350
new["data"] = self.tobytes("raw", "L")
else:
new["data"] = self.tobytes()
return np.array(self._ArrayData(new), dtype)
def __getstate__(self):
return [self.info, self.mode, self.size, self.getpalette(), self.tobytes()]
def __setstate__(self, state):
Image.__init__(self)
self.tile = []
info, mode, size, palette, data = state
self.info = info
self.mode = mode
self._size = size
self.im = core.new(mode, size)
if mode in ("L", "LA", "P", "PA") and palette:
self.putpalette(palette)
self.frombytes(data)
def tobytes(self, encoder_name="raw", *args):
"""
Return image as a bytes object.
.. warning::
This method returns the raw image data from the internal
storage. For compressed image data (e.g. PNG, JPEG) use
:meth:`~.save`, with a BytesIO parameter for in-memory
data.
:param encoder_name: What encoder to use. The default is to
use the standard "raw" encoder.
:param args: Extra arguments to the encoder.
:returns: A :py:class:`bytes` object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
if encoder_name == "raw" and args == ():
args = self.mode
self.load()
# unpack data
e = _getencoder(self.mode, encoder_name, args)
e.setimage(self.im)
bufsize = max(65536, self.size[0] * 4) # see RawEncode.c
data = []
while True:
l, s, d = e.encode(bufsize)
data.append(d)
if s:
break
if s < 0:
raise RuntimeError(f"encoder error {s} in tobytes")
return b"".join(data)
def tobitmap(self, name="image"):
"""
Returns the image converted to an X11 bitmap.
.. note:: This method only works for mode "1" images.
:param name: The name prefix to use for the bitmap variables.
:returns: A string containing an X11 bitmap.
:raises ValueError: If the mode is not "1"
"""
self.load()
if self.mode != "1":
raise ValueError("not a bitmap")
data = self.tobytes("xbm")
return b"".join(
[
f"#define {name}_width {self.size[0]}\n".encode("ascii"),
f"#define {name}_height {self.size[1]}\n".encode("ascii"),
f"static char {name}_bits[] = {{\n".encode("ascii"),
data,
b"};",
]
)
def frombytes(self, data, decoder_name="raw", *args):
"""
Loads this image with pixel data from a bytes object.
This method is similar to the :py:func:`~PIL.Image.frombytes` function,
but loads data into this image instead of creating a new image object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
# default format
if decoder_name == "raw" and args == ():
args = self.mode
# unpack data
d = _getdecoder(self.mode, decoder_name, args)
d.setimage(self.im)
s = d.decode(data)
if s[0] >= 0:
raise ValueError("not enough image data")
if s[1] != 0:
raise ValueError("cannot decode image data")
def load(self):
"""
Allocates storage for the image and loads the pixel data. In
normal cases, you don't need to call this method, since the
Image class automatically loads an opened image when it is
accessed for the first time.
If the file associated with the image was opened by Pillow, then this
method will close it. The exception to this is if the image has
multiple frames, in which case the file will be left open for seek
operations. See :ref:`file-handling` for more information.
:returns: An image access object.
:rtype: :ref:`PixelAccess` or :py:class:`PIL.PyAccess`
"""
if self.im and self.palette and self.palette.dirty:
# realize palette
mode, arr = self.palette.getdata()
if mode == "RGBA":
mode = "RGB"
self.info["transparency"] = arr[3::4]
arr = bytes(
value for (index, value) in enumerate(arr) if index % 4 != 3
)
palette_length = self.im.putpalette(mode, arr)
self.palette.dirty = 0
self.palette.rawmode = None
if "transparency" in self.info and mode in ("LA", "PA"):
if isinstance(self.info["transparency"], int):
self.im.putpalettealpha(self.info["transparency"], 0)
else:
self.im.putpalettealphas(self.info["transparency"])
self.palette.mode = "RGBA"
else:
self.palette.mode = "RGB"
self.palette.palette = self.im.getpalette()[: palette_length * 3]
if self.im:
if cffi and USE_CFFI_ACCESS:
if self.pyaccess:
return self.pyaccess
from . import PyAccess
self.pyaccess = PyAccess.new(self, self.readonly)
if self.pyaccess:
return self.pyaccess
return self.im.pixel_access(self.readonly)
def verify(self):
"""
Verifies the contents of a file. For data read from a file, this
method attempts to determine if the file is broken, without
actually decoding the image data. If this method finds any
problems, it raises suitable exceptions. If you need to load
the image after using this method, you must reopen the image
file.
"""
pass
def convert(self, mode=None, matrix=None, dither=None, palette=WEB, colors=256):
"""
Returns a converted copy of this image. For the "P" mode, this
method translates pixels through the palette. If mode is
omitted, a mode is chosen so that all information in the image
and the palette can be represented without a palette.
The current version supports all possible conversions between
"L", "RGB" and "CMYK." The ``matrix`` argument only supports "L"
and "RGB".
When translating a color image to greyscale (mode "L"),
the library uses the ITU-R 601-2 luma transform::
L = R * 299/1000 + G * 587/1000 + B * 114/1000
The default method of converting a greyscale ("L") or "RGB"
image into a bilevel (mode "1") image uses Floyd-Steinberg
dither to approximate the original image luminosity levels. If
dither is :data:`NONE`, all values larger than 127 are set to 255 (white),
all other values to 0 (black). To use other thresholds, use the
:py:meth:`~PIL.Image.Image.point` method.
When converting from "RGBA" to "P" without a ``matrix`` argument,
this passes the operation to :py:meth:`~PIL.Image.Image.quantize`,
and ``dither`` and ``palette`` are ignored.
:param mode: The requested mode. See: :ref:`concept-modes`.
:param matrix: An optional conversion matrix. If given, this
should be 4- or 12-tuple containing floating point values.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Note that this is not used when ``matrix`` is supplied.
:param palette: Palette to use when converting from mode "RGB"
to "P". Available palettes are :data:`WEB` or :data:`ADAPTIVE`.
:param colors: Number of colors to use for the :data:`ADAPTIVE` palette.
Defaults to 256.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
has_transparency = self.info.get("transparency") is not None
if not mode and self.mode == "P":
# determine default mode
if self.palette:
mode = self.palette.mode
else:
mode = "RGB"
if mode == "RGB" and has_transparency:
mode = "RGBA"
if not mode or (mode == self.mode and not matrix):
return self.copy()
if matrix:
# matrix conversion
if mode not in ("L", "RGB"):
raise ValueError("illegal conversion")
im = self.im.convert_matrix(mode, matrix)
new = self._new(im)
if has_transparency and self.im.bands == 3:
transparency = new.info["transparency"]
def convert_transparency(m, v):
v = m[0] * v[0] + m[1] * v[1] + m[2] * v[2] + m[3] * 0.5
return max(0, min(255, int(v)))
if mode == "L":
transparency = convert_transparency(matrix, transparency)
elif len(mode) == 3:
transparency = tuple(
convert_transparency(matrix[i * 4 : i * 4 + 4], transparency)
for i in range(0, len(transparency))
)
new.info["transparency"] = transparency
return new
if mode == "P" and self.mode == "RGBA":
return self.quantize(colors)
trns = None
delete_trns = False
# transparency handling
if has_transparency:
if self.mode in ("1", "L", "I", "RGB") and mode == "RGBA":
# Use transparent conversion to promote from transparent
# color to an alpha channel.
new_im = self._new(
self.im.convert_transparent(mode, self.info["transparency"])
)
del new_im.info["transparency"]
return new_im
elif self.mode in ("L", "RGB", "P") and mode in ("L", "RGB", "P"):
t = self.info["transparency"]
if isinstance(t, bytes):
# Dragons. This can't be represented by a single color
warnings.warn(
"Palette images with Transparency expressed in bytes should be "
"converted to RGBA images"
)
delete_trns = True
else:
# get the new transparency color.
# use existing conversions
trns_im = Image()._new(core.new(self.mode, (1, 1)))
if self.mode == "P":
trns_im.putpalette(self.palette)
if isinstance(t, tuple):
err = "Couldn't allocate a palette color for transparency"
try:
t = trns_im.palette.getcolor(t, self)
except ValueError as e:
if str(e) == "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
t = None
else:
raise ValueError(err) from e
if t is None:
trns = None
else:
trns_im.putpixel((0, 0), t)
if mode in ("L", "RGB"):
trns_im = trns_im.convert(mode)
else:
# can't just retrieve the palette number, got to do it
# after quantization.
trns_im = trns_im.convert("RGB")
trns = trns_im.getpixel((0, 0))
elif self.mode == "P" and mode in ("LA", "PA", "RGBA"):
t = self.info["transparency"]
delete_trns = True
if isinstance(t, bytes):
self.im.putpalettealphas(t)
elif isinstance(t, int):
self.im.putpalettealpha(t, 0)
else:
raise ValueError("Transparency for P mode should be bytes or int")
if mode == "P" and palette == ADAPTIVE:
im = self.im.quantize(colors)
new = self._new(im)
from . import ImagePalette
new.palette = ImagePalette.ImagePalette("RGB", new.im.getpalette("RGB"))
if delete_trns:
# This could possibly happen if we requantize to fewer colors.
# The transparency would be totally off in that case.
del new.info["transparency"]
if trns is not None:
try:
new.info["transparency"] = new.palette.getcolor(trns, new)
except Exception:
# if we can't make a transparent color, don't leave the old
# transparency hanging around to mess us up.
del new.info["transparency"]
warnings.warn("Couldn't allocate palette entry for transparency")
return new
# colorspace conversion
if dither is None:
dither = FLOYDSTEINBERG
try:
im = self.im.convert(mode, dither)
except ValueError:
try:
# normalize source image and try again
im = self.im.convert(getmodebase(self.mode))
im = im.convert(mode, dither)
except KeyError as e:
raise ValueError("illegal conversion") from e
new_im = self._new(im)
if mode == "P" and palette != ADAPTIVE:
from . import ImagePalette
new_im.palette = ImagePalette.ImagePalette("RGB", list(range(256)) * 3)
if delete_trns:
# crash fail if we leave a bytes transparency in an rgb/l mode.
del new_im.info["transparency"]
if trns is not None:
if new_im.mode == "P":
try:
new_im.info["transparency"] = new_im.palette.getcolor(trns, new_im)
except ValueError as e:
del new_im.info["transparency"]
if str(e) != "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
warnings.warn(
"Couldn't allocate palette entry for transparency"
)
else:
new_im.info["transparency"] = trns
return new_im
def quantize(self, colors=256, method=None, kmeans=0, palette=None, dither=1):
"""
Convert the image to 'P' mode with the specified number
of colors.
:param colors: The desired number of colors, <= 256
:param method: :data:`MEDIANCUT` (median cut),
:data:`MAXCOVERAGE` (maximum coverage),
:data:`FASTOCTREE` (fast octree),
:data:`LIBIMAGEQUANT` (libimagequant; check support using
:py:func:`PIL.features.check_feature`
with ``feature="libimagequant"``).
By default, :data:`MEDIANCUT` will be used.
The exception to this is RGBA images. :data:`MEDIANCUT` and
:data:`MAXCOVERAGE` do not support RGBA images, so
:data:`FASTOCTREE` is used by default instead.
:param kmeans: Integer
:param palette: Quantize to the palette of given
:py:class:`PIL.Image.Image`.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Default: 1 (legacy setting)
:returns: A new image
"""
self.load()
if method is None:
# defaults:
method = MEDIANCUT
if self.mode == "RGBA":
method = FASTOCTREE
if self.mode == "RGBA" and method not in (FASTOCTREE, LIBIMAGEQUANT):
# Caller specified an invalid mode.
raise ValueError(
"Fast Octree (method == 2) and libimagequant (method == 3) "
"are the only valid methods for quantizing RGBA images"
)
if palette:
# use palette from reference image
palette.load()
if palette.mode != "P":
raise ValueError("bad mode for palette image")
if self.mode != "RGB" and self.mode != "L":
raise ValueError(
"only RGB or L mode images can be quantized to a palette"
)
im = self.im.convert("P", dither, palette.im)
new_im = self._new(im)
new_im.palette = palette.palette.copy()
return new_im
im = self._new(self.im.quantize(colors, method, kmeans))
from . import ImagePalette
mode = im.im.getpalettemode()
palette = im.im.getpalette(mode, mode)[: colors * len(mode)]
im.palette = ImagePalette.ImagePalette(mode, palette)
return im
def copy(self):
"""
Copies this image. Use this method if you wish to paste things
into an image, but still retain the original.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
return self._new(self.im.copy())
__copy__ = copy
def crop(self, box=None):
"""
Returns a rectangular region from this image. The box is a
4-tuple defining the left, upper, right, and lower pixel
coordinate. See :ref:`coordinate-system`.
Note: Prior to Pillow 3.4.0, this was a lazy operation.
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if box is None:
return self.copy()
self.load()
return self._new(self._crop(self.im, box))
def _crop(self, im, box):
"""
Returns a rectangular region from the core image object im.
This is equivalent to calling im.crop((x0, y0, x1, y1)), but
includes additional sanity checks.
:param im: a core image object
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:returns: A core image object.
"""
x0, y0, x1, y1 = map(int, map(round, box))
absolute_values = (abs(x1 - x0), abs(y1 - y0))
_decompression_bomb_check(absolute_values)
return im.crop((x0, y0, x1, y1))
def draft(self, mode, size):
"""
Configures the image file loader so it returns a version of the
image that as closely as possible matches the given mode and
size. For example, you can use this method to convert a color
JPEG to greyscale while loading it.
If any changes are made, returns a tuple with the chosen ``mode`` and
``box`` with coordinates of the original image within the altered one.
Note that this method modifies the :py:class:`~PIL.Image.Image` object
in place. If the image has already been loaded, this method has no
effect.
Note: This method is not implemented for most images. It is
currently implemented only for JPEG and MPO images.
:param mode: The requested mode.
:param size: The requested size.
"""
pass
def _expand(self, xmargin, ymargin=None):
if ymargin is None:
ymargin = xmargin
self.load()
return self._new(self.im.expand(xmargin, ymargin, 0))
def filter(self, filter):
"""
Filters this image using the given filter. For a list of
available filters, see the :py:mod:`~PIL.ImageFilter` module.
:param filter: Filter kernel.
:returns: An :py:class:`~PIL.Image.Image` object."""
from . import ImageFilter
self.load()
if isinstance(filter, Callable):
filter = filter()
if not hasattr(filter, "filter"):
raise TypeError(
"filter argument should be ImageFilter.Filter instance or class"
)
multiband = isinstance(filter, ImageFilter.MultibandFilter)
if self.im.bands == 1 or multiband:
return self._new(filter.filter(self.im))
ims = []
for c in range(self.im.bands):
ims.append(self._new(filter.filter(self.im.getband(c))))
return merge(self.mode, ims)
def getbands(self):
"""
Returns a tuple containing the name of each band in this image.
For example, ``getbands`` on an RGB image returns ("R", "G", "B").
:returns: A tuple containing band names.
:rtype: tuple
"""
return ImageMode.getmode(self.mode).bands
def getbbox(self):
"""
Calculates the bounding box of the non-zero regions in the
image.
:returns: The bounding box is returned as a 4-tuple defining the
left, upper, right, and lower pixel coordinate. See
:ref:`coordinate-system`. If the image is completely empty, this
method returns None.
"""
self.load()
return self.im.getbbox()
def getcolors(self, maxcolors=256):
"""
Returns a list of colors used in this image.
The colors will be in the image's mode. For example, an RGB image will
return a tuple of (red, green, blue) color values, and a P image will
return the index of the color in the palette.
:param maxcolors: Maximum number of colors. If this number is
exceeded, this method returns None. The default limit is
256 colors.
:returns: An unsorted list of (count, pixel) values.
"""
self.load()
if self.mode in ("1", "L", "P"):
h = self.im.histogram()
out = []
for i in range(256):
if h[i]:
out.append((h[i], i))
if len(out) > maxcolors:
return None
return out
return self.im.getcolors(maxcolors)
def getdata(self, band=None):
"""
Returns the contents of this image as a sequence object
containing pixel values. The sequence object is flattened, so
that values for line one follow directly after the values of
line zero, and so on.
Note that the sequence object returned by this method is an
internal PIL data type, which only supports certain sequence
operations. To convert it to an ordinary sequence (e.g. for
printing), use ``list(im.getdata())``.
:param band: What band to return. The default is to return
all bands. To return a single band, pass in the index
value (e.g. 0 to get the "R" band from an "RGB" image).
:returns: A sequence-like object.
"""
self.load()
if band is not None:
return self.im.getband(band)
return self.im # could be abused
def getextrema(self):
"""
Gets the the minimum and maximum pixel values for each band in
the image.
:returns: For a single-band image, a 2-tuple containing the
minimum and maximum pixel value. For a multi-band image,
a tuple containing one 2-tuple for each band.
"""
self.load()
if self.im.bands > 1:
extrema = []
for i in range(self.im.bands):
extrema.append(self.im.getband(i).getextrema())
return tuple(extrema)
return self.im.getextrema()
def _getxmp(self, xmp_tags):
def get_name(tag):
return tag.split("}")[1]
def get_value(element):
value = {get_name(k): v for k, v in element.attrib.items()}
children = list(element)
if children:
for child in children:
name = get_name(child.tag)
child_value = get_value(child)
if name in value:
if not isinstance(value[name], list):
value[name] = [value[name]]
value[name].append(child_value)
else:
value[name] = child_value
elif value:
if element.text:
value["text"] = element.text
else:
return element.text
return value
if ElementTree is None:
warnings.warn("XMP data cannot be read without defusedxml dependency")
return {}
else:
root = ElementTree.fromstring(xmp_tags)
return {get_name(root.tag): get_value(root)}
def getexif(self):
if self._exif is None:
self._exif = Exif()
exif_info = self.info.get("exif")
if exif_info is None:
if "Raw profile type exif" in self.info:
exif_info = bytes.fromhex(
"".join(self.info["Raw profile type exif"].split("\n")[3:])
)
elif hasattr(self, "tag_v2"):
self._exif.endian = self.tag_v2._endian
self._exif.load_from_fp(self.fp, self.tag_v2._offset)
if exif_info is not None:
self._exif.load(exif_info)
# XMP tags
if 0x0112 not in self._exif:
xmp_tags = self.info.get("XML:com.adobe.xmp")
if xmp_tags:
match = re.search(r'tiff:Orientation="([0-9])"', xmp_tags)
if match:
self._exif[0x0112] = int(match[1])
return self._exif
def getim(self):
"""
Returns a capsule that points to the internal image memory.
:returns: A capsule object.
"""
self.load()
return self.im.ptr
def getpalette(self):
"""
Returns the image palette as a list.
:returns: A list of color values [r, g, b, ...], or None if the
image has no palette.
"""
self.load()
try:
return list(self.im.getpalette())
except ValueError:
return None # no palette
def getpixel(self, xy):
"""
Returns the pixel value at a given position.
:param xy: The coordinate, given as (x, y). See
:ref:`coordinate-system`.
:returns: The pixel value. If the image is a multi-layer image,
this method returns a tuple.
"""
self.load()
if self.pyaccess:
return self.pyaccess.getpixel(xy)
return self.im.getpixel(xy)
def getprojection(self):
"""
Get projection to x and y axes
:returns: Two sequences, indicating where there are non-zero
pixels along the X-axis and the Y-axis, respectively.
"""
self.load()
x, y = self.im.getprojection()
return list(x), list(y)
def histogram(self, mask=None, extrema=None):
"""
Returns a histogram for the image. The histogram is returned as
a list of pixel counts, one for each pixel value in the source
image. If the image has more than one band, the histograms for
all bands are concatenated (for example, the histogram for an
"RGB" image contains 768 values).
A bilevel image (mode "1") is treated as a greyscale ("L") image
by this method.
If a mask is provided, the method returns a histogram for those
parts of the image where the mask image is non-zero. The mask
image must have the same size as the image, and be either a
bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A list containing pixel counts.
"""
self.load()
if mask:
mask.load()
return self.im.histogram((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.histogram(extrema)
return self.im.histogram()
def entropy(self, mask=None, extrema=None):
"""
Calculates and returns the entropy for the image.
A bilevel image (mode "1") is treated as a greyscale ("L")
image by this method.
If a mask is provided, the method employs the histogram for
those parts of the image where the mask image is non-zero.
The mask image must have the same size as the image, and be
either a bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A float value representing the image entropy
"""
self.load()
if mask:
mask.load()
return self.im.entropy((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.entropy(extrema)
return self.im.entropy()
def paste(self, im, box=None, mask=None):
"""
Pastes another image into this image. The box argument is either
a 2-tuple giving the upper left corner, a 4-tuple defining the
left, upper, right, and lower pixel coordinate, or None (same as
(0, 0)). See :ref:`coordinate-system`. If a 4-tuple is given, the size
of the pasted image must match the size of the region.
If the modes don't match, the pasted image is converted to the mode of
this image (see the :py:meth:`~PIL.Image.Image.convert` method for
details).
Instead of an image, the source can be a integer or tuple
containing pixel values. The method then fills the region
with the given color. When creating RGB images, you can
also use color strings as supported by the ImageColor module.
If a mask is given, this method updates only the regions
indicated by the mask. You can use either "1", "L" or "RGBA"
images (in the latter case, the alpha band is used as mask).
Where the mask is 255, the given image is copied as is. Where
the mask is 0, the current value is preserved. Intermediate
values will mix the two images together, including their alpha
channels if they have them.
See :py:meth:`~PIL.Image.Image.alpha_composite` if you want to
combine images with respect to their alpha channels.
:param im: Source image or pixel value (integer or tuple).
:param box: An optional 4-tuple giving the region to paste into.
If a 2-tuple is used instead, it's treated as the upper left
corner. If omitted or None, the source is pasted into the
upper left corner.
If an image is given as the second argument and there is no
third, the box defaults to (0, 0), and the second argument
is interpreted as a mask image.
:param mask: An optional mask image.
"""
if isImageType(box) and mask is None:
# abbreviated paste(im, mask) syntax
mask = box
box = None
if box is None:
box = (0, 0)
if len(box) == 2:
# upper left corner given; get size from image or mask
if isImageType(im):
size = im.size
elif isImageType(mask):
size = mask.size
else:
# FIXME: use self.size here?
raise ValueError("cannot determine region size; use 4-item box")
box += (box[0] + size[0], box[1] + size[1])
if isinstance(im, str):
from . import ImageColor
im = ImageColor.getcolor(im, self.mode)
elif isImageType(im):
im.load()
if self.mode != im.mode:
if self.mode != "RGB" or im.mode not in ("RGBA", "RGBa"):
# should use an adapter for this!
im = im.convert(self.mode)
im = im.im
self._ensure_mutable()
if mask:
mask.load()
self.im.paste(im, box, mask.im)
else:
self.im.paste(im, box)
def alpha_composite(self, im, dest=(0, 0), source=(0, 0)):
"""'In-place' analog of Image.alpha_composite. Composites an image
onto this image.
:param im: image to composite over this one
:param dest: Optional 2 tuple (left, top) specifying the upper
left corner in this (destination) image.
:param source: Optional 2 (left, top) tuple for the upper left
corner in the overlay source image, or 4 tuple (left, top, right,
bottom) for the bounds of the source rectangle
Performance Note: Not currently implemented in-place in the core layer.
"""
if not isinstance(source, (list, tuple)):
raise ValueError("Source must be a tuple")
if not isinstance(dest, (list, tuple)):
raise ValueError("Destination must be a tuple")
if not len(source) in (2, 4):
raise ValueError("Source must be a 2 or 4-tuple")
if not len(dest) == 2:
raise ValueError("Destination must be a 2-tuple")
if min(source) < 0:
raise ValueError("Source must be non-negative")
if len(source) == 2:
source = source + im.size
# over image, crop if it's not the whole thing.
if source == (0, 0) + im.size:
overlay = im
else:
overlay = im.crop(source)
# target for the paste
box = dest + (dest[0] + overlay.width, dest[1] + overlay.height)
# destination image. don't copy if we're using the whole image.
if box == (0, 0) + self.size:
background = self
else:
background = self.crop(box)
result = alpha_composite(background, overlay)
self.paste(result, box)
def point(self, lut, mode=None):
"""
Maps this image through a lookup table or function.
:param lut: A lookup table, containing 256 (or 65536 if
self.mode=="I" and mode == "L") values per band in the
image. A function can be used instead, it should take a
single argument. The function is called once for each
possible pixel value, and the resulting table is applied to
all bands of the image.
It may also be an :py:class:`~PIL.Image.ImagePointHandler`
object::
class Example(Image.ImagePointHandler):
def point(self, data):
# Return result
:param mode: Output mode (default is same as input). In the
current version, this can only be used if the source image
has mode "L" or "P", and the output has mode "1" or the
source image mode is "I" and the output mode is "L".
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
if isinstance(lut, ImagePointHandler):
return lut.point(self)
if callable(lut):
# if it isn't a list, it should be a function
if self.mode in ("I", "I;16", "F"):
# check if the function can be used with point_transform
# UNDONE wiredfool -- I think this prevents us from ever doing
# a gamma function point transform on > 8bit images.
scale, offset = _getscaleoffset(lut)
return self._new(self.im.point_transform(scale, offset))
# for other modes, convert the function to a table
lut = [lut(i) for i in range(256)] * self.im.bands
if self.mode == "F":
# FIXME: _imaging returns a confusing error message for this case
raise ValueError("point operation not supported for this mode")
return self._new(self.im.point(lut, mode))
def putalpha(self, alpha):
"""
Adds or replaces the alpha layer in this image. If the image
does not have an alpha layer, it's converted to "LA" or "RGBA".
The new layer must be either "L" or "1".
:param alpha: The new alpha layer. This can either be an "L" or "1"
image having the same size as this image, or an integer or
other color value.
"""
self._ensure_mutable()
if self.mode not in ("LA", "PA", "RGBA"):
# attempt to promote self to a matching alpha mode
try:
mode = getmodebase(self.mode) + "A"
try:
self.im.setmode(mode)
except (AttributeError, ValueError) as e:
# do things the hard way
im = self.im.convert(mode)
if im.mode not in ("LA", "PA", "RGBA"):
raise ValueError from e # sanity check
self.im = im
self.pyaccess = None
self.mode = self.im.mode
except KeyError as e:
raise ValueError("illegal image mode") from e
if self.mode in ("LA", "PA"):
band = 1
else:
band = 3
if isImageType(alpha):
# alpha layer
if alpha.mode not in ("1", "L"):
raise ValueError("illegal image mode")
alpha.load()
if alpha.mode == "1":
alpha = alpha.convert("L")
else:
# constant alpha
try:
self.im.fillband(band, alpha)
except (AttributeError, ValueError):
# do things the hard way
alpha = new("L", self.size, alpha)
else:
return
self.im.putband(alpha.im, band)
def putdata(self, data, scale=1.0, offset=0.0):
"""
Copies pixel data from a flattened sequence object into the image. The
values should start at the upper left corner (0, 0), continue to the
end of the line, followed directly by the first value of the second
line, and so on. Data will be read until either the image or the
sequence ends. The scale and offset values are used to adjust the
sequence values: **pixel = value*scale + offset**.
:param data: A flattened sequence object.
:param scale: An optional scale value. The default is 1.0.
:param offset: An optional offset value. The default is 0.0.
"""
self._ensure_mutable()
self.im.putdata(data, scale, offset)
def putpalette(self, data, rawmode="RGB"):
"""
Attaches a palette to this image. The image must be a "P", "PA", "L"
or "LA" image.
The palette sequence must contain at most 256 colors, made up of one
integer value for each channel in the raw mode.
For example, if the raw mode is "RGB", then it can contain at most 768
values, made up of red, green and blue values for the corresponding pixel
index in the 256 colors.
If the raw mode is "RGBA", then it can contain at most 1024 values,
containing red, green, blue and alpha values.
Alternatively, an 8-bit string may be used instead of an integer sequence.
:param data: A palette sequence (either a list or a string).
:param rawmode: The raw mode of the palette. Either "RGB", "RGBA", or a
mode that can be transformed to "RGB" (e.g. "R", "BGR;15", "RGBA;L").
"""
from . import ImagePalette
if self.mode not in ("L", "LA", "P", "PA"):
raise ValueError("illegal image mode")
if isinstance(data, ImagePalette.ImagePalette):
palette = ImagePalette.raw(data.rawmode, data.palette)
else:
if not isinstance(data, bytes):
data = bytes(data)
palette = ImagePalette.raw(rawmode, data)
self.mode = "PA" if "A" in self.mode else "P"
self.palette = palette
self.palette.mode = "RGB"
self.load() # install new palette
def putpixel(self, xy, value):
"""
Modifies the pixel at the given position. The color is given as
a single numerical value for single-band images, and a tuple for
multi-band images. In addition to this, RGB and RGBA tuples are
accepted for P images.
Note that this method is relatively slow. For more extensive changes,
use :py:meth:`~PIL.Image.Image.paste` or the :py:mod:`~PIL.ImageDraw`
module instead.
See:
* :py:meth:`~PIL.Image.Image.paste`
* :py:meth:`~PIL.Image.Image.putdata`
* :py:mod:`~PIL.ImageDraw`
:param xy: The pixel coordinate, given as (x, y). See
:ref:`coordinate-system`.
:param value: The pixel value.
"""
if self.readonly:
self._copy()
self.load()
if self.pyaccess:
return self.pyaccess.putpixel(xy, value)
if (
self.mode == "P"
and isinstance(value, (list, tuple))
and len(value) in [3, 4]
):
# RGB or RGBA value for a P image
value = self.palette.getcolor(value, self)
return self.im.putpixel(xy, value)
def remap_palette(self, dest_map, source_palette=None):
"""
Rewrites the image to reorder the palette.
:param dest_map: A list of indexes into the original palette.
e.g. ``[1,0]`` would swap a two item palette, and ``list(range(256))``
is the identity transform.
:param source_palette: Bytes or None.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
from . import ImagePalette
if self.mode not in ("L", "P"):
raise ValueError("illegal image mode")
if source_palette is None:
if self.mode == "P":
self.load()
source_palette = self.im.getpalette("RGB")[:768]
else: # L-mode
source_palette = bytearray(i // 3 for i in range(768))
palette_bytes = b""
new_positions = [0] * 256
# pick only the used colors from the palette
for i, oldPosition in enumerate(dest_map):
palette_bytes += source_palette[oldPosition * 3 : oldPosition * 3 + 3]
new_positions[oldPosition] = i
# replace the palette color id of all pixel with the new id
# Palette images are [0..255], mapped through a 1 or 3
# byte/color map. We need to remap the whole image
# from palette 1 to palette 2. New_positions is
# an array of indexes into palette 1. Palette 2 is
# palette 1 with any holes removed.
# We're going to leverage the convert mechanism to use the
# C code to remap the image from palette 1 to palette 2,
# by forcing the source image into 'L' mode and adding a
# mapping 'L' mode palette, then converting back to 'L'
# sans palette thus converting the image bytes, then
# assigning the optimized RGB palette.
# perf reference, 9500x4000 gif, w/~135 colors
# 14 sec prepatch, 1 sec postpatch with optimization forced.
mapping_palette = bytearray(new_positions)
m_im = self.copy()
m_im.mode = "P"
m_im.palette = ImagePalette.ImagePalette("RGB", palette=mapping_palette * 3)
# possibly set palette dirty, then
# m_im.putpalette(mapping_palette, 'L') # converts to 'P'
# or just force it.
# UNDONE -- this is part of the general issue with palettes
m_im.im.putpalette("RGB;L", m_im.palette.tobytes())
m_im = m_im.convert("L")
# Internally, we require 768 bytes for a palette.
new_palette_bytes = palette_bytes + (768 - len(palette_bytes)) * b"\x00"
m_im.putpalette(new_palette_bytes)
m_im.palette = ImagePalette.ImagePalette("RGB", palette=palette_bytes)
return m_im
def _get_safe_box(self, size, resample, box):
"""Expands the box so it includes adjacent pixels
that may be used by resampling with the given resampling filter.
"""
filter_support = _filters_support[resample] - 0.5
scale_x = (box[2] - box[0]) / size[0]
scale_y = (box[3] - box[1]) / size[1]
support_x = filter_support * scale_x
support_y = filter_support * scale_y
return (
max(0, int(box[0] - support_x)),
max(0, int(box[1] - support_y)),
min(self.size[0], math.ceil(box[2] + support_x)),
min(self.size[1], math.ceil(box[3] + support_y)),
)
def resize(self, size, resample=None, box=None, reducing_gap=None):
"""
Returns a resized copy of this image.
:param size: The requested size in pixels, as a 2-tuple:
(width, height).
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If the image has mode "1" or "P", it is always set to
:py:data:`PIL.Image.NEAREST`.
If the image mode specifies a number of bits, such as "I;16", then the
default filter is :py:data:`PIL.Image.NEAREST`.
Otherwise, the default filter is :py:data:`PIL.Image.BICUBIC`.
See: :ref:`concept-filters`.
:param box: An optional 4-tuple of floats providing
the source image region to be scaled.
The values must be within (0, 0, width, height) rectangle.
If omitted or None, the entire source is used.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce`.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is None (no optimization).
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if resample is None:
type_special = ";" in self.mode
resample = NEAREST if type_special else BICUBIC
elif resample not in (NEAREST, BILINEAR, BICUBIC, LANCZOS, BOX, HAMMING):
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(LANCZOS, "Image.LANCZOS"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
(BOX, "Image.BOX"),
(HAMMING, "Image.HAMMING"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
if reducing_gap is not None and reducing_gap < 1.0:
raise ValueError("reducing_gap must be 1.0 or greater")
size = tuple(size)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if self.size == size and box == (0, 0) + self.size:
return self.copy()
if self.mode in ("1", "P"):
resample = NEAREST
if self.mode in ["LA", "RGBA"] and resample != NEAREST:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.resize(size, resample, box)
return im.convert(self.mode)
self.load()
if reducing_gap is not None and resample != NEAREST:
factor_x = int((box[2] - box[0]) / size[0] / reducing_gap) or 1
factor_y = int((box[3] - box[1]) / size[1] / reducing_gap) or 1
if factor_x > 1 or factor_y > 1:
reduce_box = self._get_safe_box(size, resample, box)
factor = (factor_x, factor_y)
if callable(self.reduce):
self = self.reduce(factor, box=reduce_box)
else:
self = Image.reduce(self, factor, box=reduce_box)
box = (
(box[0] - reduce_box[0]) / factor_x,
(box[1] - reduce_box[1]) / factor_y,
(box[2] - reduce_box[0]) / factor_x,
(box[3] - reduce_box[1]) / factor_y,
)
return self._new(self.im.resize(size, resample, box))
def reduce(self, factor, box=None):
"""
Returns a copy of the image reduced ``factor`` times.
If the size of the image is not dividable by ``factor``,
the resulting size will be rounded up.
:param factor: A greater than 0 integer or tuple of two integers
for width and height separately.
:param box: An optional 4-tuple of ints providing
the source image region to be reduced.
The values must be within ``(0, 0, width, height)`` rectangle.
If omitted or ``None``, the entire source is used.
"""
if not isinstance(factor, (list, tuple)):
factor = (factor, factor)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if factor == (1, 1) and box == (0, 0) + self.size:
return self.copy()
if self.mode in ["LA", "RGBA"]:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.reduce(factor, box)
return im.convert(self.mode)
self.load()
return self._new(self.im.reduce(factor, box))
def rotate(
self,
angle,
resample=NEAREST,
expand=0,
center=None,
translate=None,
fillcolor=None,
):
"""
Returns a rotated copy of this image. This method returns a
copy of this image, rotated the given number of degrees counter
clockwise around its centre.
:param angle: In degrees counter clockwise.
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC`
(cubic spline interpolation in a 4x4 environment).
If omitted, or if the image has mode "1" or "P", it is
set to :py:data:`PIL.Image.NEAREST`. See :ref:`concept-filters`.
:param expand: Optional expansion flag. If true, expands the output
image to make it large enough to hold the entire rotated image.
If false or omitted, make the output image the same size as the
input image. Note that the expand flag assumes rotation around
the center and no translation.
:param center: Optional center of rotation (a 2-tuple). Origin is
the upper left corner. Default is the center of the image.
:param translate: An optional post-rotate translation (a 2-tuple).
:param fillcolor: An optional color for area outside the rotated image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
angle = angle % 360.0
# Fast paths regardless of filter, as long as we're not
# translating or changing the center.
if not (center or translate):
if angle == 0:
return self.copy()
if angle == 180:
return self.transpose(ROTATE_180)
if angle in (90, 270) and (expand or self.width == self.height):
return self.transpose(ROTATE_90 if angle == 90 else ROTATE_270)
# Calculate the affine matrix. Note that this is the reverse
# transformation (from destination image to source) because we
# want to interpolate the (discrete) destination pixel from
# the local area around the (floating) source pixel.
# The matrix we actually want (note that it operates from the right):
# (1, 0, tx) (1, 0, cx) ( cos a, sin a, 0) (1, 0, -cx)
# (0, 1, ty) * (0, 1, cy) * (-sin a, cos a, 0) * (0, 1, -cy)
# (0, 0, 1) (0, 0, 1) ( 0, 0, 1) (0, 0, 1)
# The reverse matrix is thus:
# (1, 0, cx) ( cos -a, sin -a, 0) (1, 0, -cx) (1, 0, -tx)
# (0, 1, cy) * (-sin -a, cos -a, 0) * (0, 1, -cy) * (0, 1, -ty)
# (0, 0, 1) ( 0, 0, 1) (0, 0, 1) (0, 0, 1)
# In any case, the final translation may be updated at the end to
# compensate for the expand flag.
w, h = self.size
if translate is None:
post_trans = (0, 0)
else:
post_trans = translate
if center is None:
# FIXME These should be rounded to ints?
rotn_center = (w / 2.0, h / 2.0)
else:
rotn_center = center
angle = -math.radians(angle)
matrix = [
round(math.cos(angle), 15),
round(math.sin(angle), 15),
0.0,
round(-math.sin(angle), 15),
round(math.cos(angle), 15),
0.0,
]
def transform(x, y, matrix):
(a, b, c, d, e, f) = matrix
return a * x + b * y + c, d * x + e * y + f
matrix[2], matrix[5] = transform(
-rotn_center[0] - post_trans[0], -rotn_center[1] - post_trans[1], matrix
)
matrix[2] += rotn_center[0]
matrix[5] += rotn_center[1]
if expand:
# calculate output size
xx = []
yy = []
for x, y in ((0, 0), (w, 0), (w, h), (0, h)):
x, y = transform(x, y, matrix)
xx.append(x)
yy.append(y)
nw = math.ceil(max(xx)) - math.floor(min(xx))
nh = math.ceil(max(yy)) - math.floor(min(yy))
# We multiply a translation matrix from the right. Because of its
# special form, this is the same as taking the image of the
# translation vector as new translation vector.
matrix[2], matrix[5] = transform(-(nw - w) / 2.0, -(nh - h) / 2.0, matrix)
w, h = nw, nh
return self.transform((w, h), AFFINE, matrix, resample, fillcolor=fillcolor)
def save(self, fp, format=None, **params):
"""
Saves this image under the given filename. If no format is
specified, the format to use is determined from the filename
extension, if possible.
Keyword options can be used to provide additional instructions
to the writer. If a writer doesn't recognise an option, it is
silently ignored. The available options are described in the
:doc:`image format documentation
<../handbook/image-file-formats>` for each writer.
You can use a file object instead of a filename. In this case,
you must always specify the format. The file object must
implement the ``seek``, ``tell``, and ``write``
methods, and be opened in binary mode.
:param fp: A filename (string), pathlib.Path object or file object.
:param format: Optional format override. If omitted, the
format to use is determined from the filename extension.
If a file object was used instead of a filename, this
parameter should always be used.
:param params: Extra parameters to the image writer.
:returns: None
:exception ValueError: If the output format could not be determined
from the file name. Use the format option to solve this.
:exception OSError: If the file could not be written. The file
may have been created, and may contain partial data.
"""
filename = ""
open_fp = False
if isinstance(fp, Path):
filename = str(fp)
open_fp = True
elif isPath(fp):
filename = fp
open_fp = True
elif fp == sys.stdout:
try:
fp = sys.stdout.buffer
except AttributeError:
pass
if not filename and hasattr(fp, "name") and isPath(fp.name):
# only set the name for metadata purposes
filename = fp.name
# may mutate self!
self._ensure_mutable()
save_all = params.pop("save_all", False)
self.encoderinfo = params
self.encoderconfig = ()
preinit()
ext = os.path.splitext(filename)[1].lower()
if not format:
if ext not in EXTENSION:
init()
try:
format = EXTENSION[ext]
except KeyError as e:
raise ValueError(f"unknown file extension: {ext}") from e
if format.upper() not in SAVE:
init()
if save_all:
save_handler = SAVE_ALL[format.upper()]
else:
save_handler = SAVE[format.upper()]
if open_fp:
if params.get("append", False):
# Open also for reading ("+"), because TIFF save_all
# writer needs to go back and edit the written data.
fp = builtins.open(filename, "r+b")
else:
fp = builtins.open(filename, "w+b")
try:
save_handler(self, fp, filename)
finally:
# do what we can to clean up
if open_fp:
fp.close()
def seek(self, frame):
"""
Seeks to the given frame in this sequence file. If you seek
beyond the end of the sequence, the method raises an
``EOFError`` exception. When a sequence file is opened, the
library automatically seeks to frame 0.
See :py:meth:`~PIL.Image.Image.tell`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:param frame: Frame number, starting at 0.
:exception EOFError: If the call attempts to seek beyond the end
of the sequence.
"""
# overridden by file handlers
if frame != 0:
raise EOFError
def show(self, title=None):
"""
Displays this image. This method is mainly intended for debugging purposes.
This method calls :py:func:`PIL.ImageShow.show` internally. You can use
:py:func:`PIL.ImageShow.register` to override its default behaviour.
The image is first saved to a temporary file. By default, it will be in
PNG format.
On Unix, the image is then opened using the **display**, **eog** or
**xv** utility, depending on which one can be found.
On macOS, the image is opened with the native Preview application.
On Windows, the image is opened with the standard PNG display utility.
:param title: Optional title to use for the image window, where possible.
"""
_show(self, title=title)
def split(self):
"""
Split this image into individual bands. This method returns a
tuple of individual image bands from an image. For example,
splitting an "RGB" image creates three new images each
containing a copy of one of the original bands (red, green,
blue).
If you need only one band, :py:meth:`~PIL.Image.Image.getchannel`
method can be more convenient and faster.
:returns: A tuple containing bands.
"""
self.load()
if self.im.bands == 1:
ims = [self.copy()]
else:
ims = map(self._new, self.im.split())
return tuple(ims)
def getchannel(self, channel):
"""
Returns an image containing a single channel of the source image.
:param channel: What channel to return. Could be index
(0 for "R" channel of "RGB") or channel name
("A" for alpha channel of "RGBA").
:returns: An image in "L" mode.
.. versionadded:: 4.3.0
"""
self.load()
if isinstance(channel, str):
try:
channel = self.getbands().index(channel)
except ValueError as e:
raise ValueError(f'The image has no channel "{channel}"') from e
return self._new(self.im.getband(channel))
def tell(self):
"""
Returns the current frame number. See :py:meth:`~PIL.Image.Image.seek`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:returns: Frame number, starting with 0.
"""
return 0
def thumbnail(self, size, resample=BICUBIC, reducing_gap=2.0):
"""
Make this image into a thumbnail. This method modifies the
image to contain a thumbnail version of itself, no larger than
the given size. This method calculates an appropriate thumbnail
size to preserve the aspect of the image, calls the
:py:meth:`~PIL.Image.Image.draft` method to configure the file reader
(where applicable), and finally resizes the image.
Note that this function modifies the :py:class:`~PIL.Image.Image`
object in place. If you need to use the full resolution image as well,
apply this method to a :py:meth:`~PIL.Image.Image.copy` of the original
image.
:param size: Requested size.
:param resample: Optional resampling filter. This can be one
of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If omitted, it defaults to :py:data:`PIL.Image.BICUBIC`.
(was :py:data:`PIL.Image.NEAREST` prior to version 2.5.0).
See: :ref:`concept-filters`.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce` or
:py:meth:`~PIL.Image.Image.draft` for JPEG images.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is 2.0 (very close to fair resampling
while still being faster in many cases).
:returns: None
"""
x, y = map(math.floor, size)
if x >= self.width and y >= self.height:
return
def round_aspect(number, key):
return max(min(math.floor(number), math.ceil(number), key=key), 1)
# preserve aspect ratio
aspect = self.width / self.height
if x / y >= aspect:
x = round_aspect(y * aspect, key=lambda n: abs(aspect - n / y))
else:
y = round_aspect(
x / aspect, key=lambda n: 0 if n == 0 else abs(aspect - x / n)
)
size = (x, y)
box = None
if reducing_gap is not None:
res = self.draft(None, (size[0] * reducing_gap, size[1] * reducing_gap))
if res is not None:
box = res[1]
if self.size != size:
im = self.resize(size, resample, box=box, reducing_gap=reducing_gap)
self.im = im.im
self._size = size
self.mode = self.im.mode
self.readonly = 0
self.pyaccess = None
# FIXME: the different transform methods need further explanation
# instead of bloating the method docs, add a separate chapter.
def transform(
self, size, method, data=None, resample=NEAREST, fill=1, fillcolor=None
):
"""
Transforms this image. This method creates a new image with the
given size, and the same mode as the original, and copies data
to the new image using the given transform.
:param size: The output size.
:param method: The transformation method. This is one of
:py:data:`PIL.Image.EXTENT` (cut out a rectangular subregion),
:py:data:`PIL.Image.AFFINE` (affine transform),
:py:data:`PIL.Image.PERSPECTIVE` (perspective transform),
:py:data:`PIL.Image.QUAD` (map a quadrilateral to a rectangle), or
:py:data:`PIL.Image.MESH` (map a number of source quadrilaterals
in one operation).
It may also be an :py:class:`~PIL.Image.ImageTransformHandler`
object::
class Example(Image.ImageTransformHandler):
def transform(self, size, data, resample, fill=1):
# Return result
It may also be an object with a ``method.getdata`` method
that returns a tuple supplying new ``method`` and ``data`` values::
class Example:
def getdata(self):
method = Image.EXTENT
data = (0, 0, 100, 100)
return method, data
:param data: Extra data to the transformation method.
:param resample: Optional resampling filter. It can be one of
:py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC` (cubic spline
interpolation in a 4x4 environment). If omitted, or if the image
has mode "1" or "P", it is set to :py:data:`PIL.Image.NEAREST`.
See: :ref:`concept-filters`.
:param fill: If ``method`` is an
:py:class:`~PIL.Image.ImageTransformHandler` object, this is one of
the arguments passed to it. Otherwise, it is unused.
:param fillcolor: Optional fill color for the area outside the
transform in the output image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if self.mode in ("LA", "RGBA") and resample != NEAREST:
return (
self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
.transform(size, method, data, resample, fill, fillcolor)
.convert(self.mode)
)
if isinstance(method, ImageTransformHandler):
return method.transform(size, self, resample=resample, fill=fill)
if hasattr(method, "getdata"):
# compatibility w. old-style transform objects
method, data = method.getdata()
if data is None:
raise ValueError("missing method data")
im = new(self.mode, size, fillcolor)
if self.mode == "P" and self.palette:
im.palette = self.palette.copy()
im.info = self.info.copy()
if method == MESH:
# list of quads
for box, quad in data:
im.__transformer(box, self, QUAD, quad, resample, fillcolor is None)
else:
im.__transformer(
(0, 0) + size, self, method, data, resample, fillcolor is None
)
return im
def __transformer(self, box, image, method, data, resample=NEAREST, fill=1):
w = box[2] - box[0]
h = box[3] - box[1]
if method == AFFINE:
data = data[0:6]
elif method == EXTENT:
# convert extent to an affine transform
x0, y0, x1, y1 = data
xs = (x1 - x0) / w
ys = (y1 - y0) / h
method = AFFINE
data = (xs, 0, x0, 0, ys, y0)
elif method == PERSPECTIVE:
data = data[0:8]
elif method == QUAD:
# quadrilateral warp. data specifies the four corners
# given as NW, SW, SE, and NE.
nw = data[0:2]
sw = data[2:4]
se = data[4:6]
ne = data[6:8]
x0, y0 = nw
As = 1.0 / w
At = 1.0 / h
data = (
x0,
(ne[0] - x0) * As,
(sw[0] - x0) * At,
(se[0] - sw[0] - ne[0] + x0) * As * At,
y0,
(ne[1] - y0) * As,
(sw[1] - y0) * At,
(se[1] - sw[1] - ne[1] + y0) * As * At,
)
else:
raise ValueError("unknown transformation method")
if resample not in (NEAREST, BILINEAR, BICUBIC):
if resample in (BOX, HAMMING, LANCZOS):
message = {
BOX: "Image.BOX",
HAMMING: "Image.HAMMING",
LANCZOS: "Image.LANCZOS/Image.ANTIALIAS",
}[resample] + f" ({resample}) cannot be used."
else:
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
image.load()
self.load()
if image.mode in ("1", "P"):
resample = NEAREST
self.im.transform2(box, image.im, method, data, resample, fill)
def transpose(self, method):
"""
Transpose image (flip or rotate in 90 degree steps)
:param method: One of :py:data:`PIL.Image.FLIP_LEFT_RIGHT`,
:py:data:`PIL.Image.FLIP_TOP_BOTTOM`, :py:data:`PIL.Image.ROTATE_90`,
:py:data:`PIL.Image.ROTATE_180`, :py:data:`PIL.Image.ROTATE_270`,
:py:data:`PIL.Image.TRANSPOSE` or :py:data:`PIL.Image.TRANSVERSE`.
:returns: Returns a flipped or rotated copy of this image.
"""
self.load()
return self._new(self.im.transpose(method))
def effect_spread(self, distance):
"""
Randomly spread pixels in an image.
:param distance: Distance to spread pixels.
"""
self.load()
return self._new(self.im.effect_spread(distance))
def toqimage(self):
"""Returns a QImage copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqimage(self)
def toqpixmap(self):
"""Returns a QPixmap copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqpixmap(self)
The provided code snippet includes necessary dependencies for implementing the `effect_noise` function. Write a Python function `def effect_noise(size, sigma)` to solve the following problem:
Generate Gaussian noise centered around 128. :param size: The requested size in pixels, as a 2-tuple: (width, height). :param sigma: Standard deviation of noise.
Here is the function:
def effect_noise(size, sigma):
"""
Generate Gaussian noise centered around 128.
:param size: The requested size in pixels, as a 2-tuple:
(width, height).
:param sigma: Standard deviation of noise.
"""
return Image()._new(core.effect_noise(size, sigma)) | Generate Gaussian noise centered around 128. :param size: The requested size in pixels, as a 2-tuple: (width, height). :param sigma: Standard deviation of noise. |
167,778 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
class Image:
"""
This class represents an image object. To create
:py:class:`~PIL.Image.Image` objects, use the appropriate factory
functions. There's hardly ever any reason to call the Image constructor
directly.
* :py:func:`~PIL.Image.open`
* :py:func:`~PIL.Image.new`
* :py:func:`~PIL.Image.frombytes`
"""
format = None
format_description = None
_close_exclusive_fp_after_loading = True
def __init__(self):
# FIXME: take "new" parameters / other image?
# FIXME: turn mode and size into delegating properties?
self.im = None
self.mode = ""
self._size = (0, 0)
self.palette = None
self.info = {}
self._category = 0
self.readonly = 0
self.pyaccess = None
self._exif = None
def __getattr__(self, name):
if name == "category":
warnings.warn(
"Image categories are deprecated and will be removed in Pillow 10 "
"(2023-07-01). Use is_animated instead.",
DeprecationWarning,
stacklevel=2,
)
return self._category
raise AttributeError(name)
def width(self):
return self.size[0]
def height(self):
return self.size[1]
def size(self):
return self._size
def _new(self, im):
new = Image()
new.im = im
new.mode = im.mode
new._size = im.size
if im.mode in ("P", "PA"):
if self.palette:
new.palette = self.palette.copy()
else:
from . import ImagePalette
new.palette = ImagePalette.ImagePalette()
new.info = self.info.copy()
return new
# Context manager support
def __enter__(self):
return self
def __exit__(self, *args):
if hasattr(self, "fp") and getattr(self, "_exclusive_fp", False):
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
def close(self):
"""
Closes the file pointer, if possible.
This operation will destroy the image core and release its memory.
The image data will be unusable afterward.
This function is required to close images that have multiple frames or
have not had their file read and closed by the
:py:meth:`~PIL.Image.Image.load` method. See :ref:`file-handling` for
more information.
"""
try:
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
except Exception as msg:
logger.debug("Error closing: %s", msg)
if getattr(self, "map", None):
self.map = None
# Instead of simply setting to None, we're setting up a
# deferred error that will better explain that the core image
# object is gone.
self.im = deferred_error(ValueError("Operation on closed image"))
def _copy(self):
self.load()
self.im = self.im.copy()
self.pyaccess = None
self.readonly = 0
def _ensure_mutable(self):
if self.readonly:
self._copy()
else:
self.load()
def _dump(self, file=None, format=None, **options):
suffix = ""
if format:
suffix = "." + format
if not file:
f, filename = tempfile.mkstemp(suffix)
os.close(f)
else:
filename = file
if not filename.endswith(suffix):
filename = filename + suffix
self.load()
if not format or format == "PPM":
self.im.save_ppm(filename)
else:
self.save(filename, format, **options)
return filename
def __eq__(self, other):
return (
self.__class__ is other.__class__
and self.mode == other.mode
and self.size == other.size
and self.info == other.info
and self._category == other._category
and self.readonly == other.readonly
and self.getpalette() == other.getpalette()
and self.tobytes() == other.tobytes()
)
def __repr__(self):
return "<%s.%s image mode=%s size=%dx%d at 0x%X>" % (
self.__class__.__module__,
self.__class__.__name__,
self.mode,
self.size[0],
self.size[1],
id(self),
)
def _repr_png_(self):
"""iPython display hook support
:returns: png version of the image as bytes
"""
b = io.BytesIO()
try:
self.save(b, "PNG")
except Exception as e:
raise ValueError("Could not save to PNG for display") from e
return b.getvalue()
class _ArrayData:
def __init__(self, new):
self.__array_interface__ = new
def __array__(self, dtype=None):
# numpy array interface support
import numpy as np
new = {}
shape, typestr = _conv_type_shape(self)
new["shape"] = shape
new["typestr"] = typestr
new["version"] = 3
if self.mode == "1":
# Binary images need to be extended from bits to bytes
# See: https://github.com/python-pillow/Pillow/issues/350
new["data"] = self.tobytes("raw", "L")
else:
new["data"] = self.tobytes()
return np.array(self._ArrayData(new), dtype)
def __getstate__(self):
return [self.info, self.mode, self.size, self.getpalette(), self.tobytes()]
def __setstate__(self, state):
Image.__init__(self)
self.tile = []
info, mode, size, palette, data = state
self.info = info
self.mode = mode
self._size = size
self.im = core.new(mode, size)
if mode in ("L", "LA", "P", "PA") and palette:
self.putpalette(palette)
self.frombytes(data)
def tobytes(self, encoder_name="raw", *args):
"""
Return image as a bytes object.
.. warning::
This method returns the raw image data from the internal
storage. For compressed image data (e.g. PNG, JPEG) use
:meth:`~.save`, with a BytesIO parameter for in-memory
data.
:param encoder_name: What encoder to use. The default is to
use the standard "raw" encoder.
:param args: Extra arguments to the encoder.
:returns: A :py:class:`bytes` object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
if encoder_name == "raw" and args == ():
args = self.mode
self.load()
# unpack data
e = _getencoder(self.mode, encoder_name, args)
e.setimage(self.im)
bufsize = max(65536, self.size[0] * 4) # see RawEncode.c
data = []
while True:
l, s, d = e.encode(bufsize)
data.append(d)
if s:
break
if s < 0:
raise RuntimeError(f"encoder error {s} in tobytes")
return b"".join(data)
def tobitmap(self, name="image"):
"""
Returns the image converted to an X11 bitmap.
.. note:: This method only works for mode "1" images.
:param name: The name prefix to use for the bitmap variables.
:returns: A string containing an X11 bitmap.
:raises ValueError: If the mode is not "1"
"""
self.load()
if self.mode != "1":
raise ValueError("not a bitmap")
data = self.tobytes("xbm")
return b"".join(
[
f"#define {name}_width {self.size[0]}\n".encode("ascii"),
f"#define {name}_height {self.size[1]}\n".encode("ascii"),
f"static char {name}_bits[] = {{\n".encode("ascii"),
data,
b"};",
]
)
def frombytes(self, data, decoder_name="raw", *args):
"""
Loads this image with pixel data from a bytes object.
This method is similar to the :py:func:`~PIL.Image.frombytes` function,
but loads data into this image instead of creating a new image object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
# default format
if decoder_name == "raw" and args == ():
args = self.mode
# unpack data
d = _getdecoder(self.mode, decoder_name, args)
d.setimage(self.im)
s = d.decode(data)
if s[0] >= 0:
raise ValueError("not enough image data")
if s[1] != 0:
raise ValueError("cannot decode image data")
def load(self):
"""
Allocates storage for the image and loads the pixel data. In
normal cases, you don't need to call this method, since the
Image class automatically loads an opened image when it is
accessed for the first time.
If the file associated with the image was opened by Pillow, then this
method will close it. The exception to this is if the image has
multiple frames, in which case the file will be left open for seek
operations. See :ref:`file-handling` for more information.
:returns: An image access object.
:rtype: :ref:`PixelAccess` or :py:class:`PIL.PyAccess`
"""
if self.im and self.palette and self.palette.dirty:
# realize palette
mode, arr = self.palette.getdata()
if mode == "RGBA":
mode = "RGB"
self.info["transparency"] = arr[3::4]
arr = bytes(
value for (index, value) in enumerate(arr) if index % 4 != 3
)
palette_length = self.im.putpalette(mode, arr)
self.palette.dirty = 0
self.palette.rawmode = None
if "transparency" in self.info and mode in ("LA", "PA"):
if isinstance(self.info["transparency"], int):
self.im.putpalettealpha(self.info["transparency"], 0)
else:
self.im.putpalettealphas(self.info["transparency"])
self.palette.mode = "RGBA"
else:
self.palette.mode = "RGB"
self.palette.palette = self.im.getpalette()[: palette_length * 3]
if self.im:
if cffi and USE_CFFI_ACCESS:
if self.pyaccess:
return self.pyaccess
from . import PyAccess
self.pyaccess = PyAccess.new(self, self.readonly)
if self.pyaccess:
return self.pyaccess
return self.im.pixel_access(self.readonly)
def verify(self):
"""
Verifies the contents of a file. For data read from a file, this
method attempts to determine if the file is broken, without
actually decoding the image data. If this method finds any
problems, it raises suitable exceptions. If you need to load
the image after using this method, you must reopen the image
file.
"""
pass
def convert(self, mode=None, matrix=None, dither=None, palette=WEB, colors=256):
"""
Returns a converted copy of this image. For the "P" mode, this
method translates pixels through the palette. If mode is
omitted, a mode is chosen so that all information in the image
and the palette can be represented without a palette.
The current version supports all possible conversions between
"L", "RGB" and "CMYK." The ``matrix`` argument only supports "L"
and "RGB".
When translating a color image to greyscale (mode "L"),
the library uses the ITU-R 601-2 luma transform::
L = R * 299/1000 + G * 587/1000 + B * 114/1000
The default method of converting a greyscale ("L") or "RGB"
image into a bilevel (mode "1") image uses Floyd-Steinberg
dither to approximate the original image luminosity levels. If
dither is :data:`NONE`, all values larger than 127 are set to 255 (white),
all other values to 0 (black). To use other thresholds, use the
:py:meth:`~PIL.Image.Image.point` method.
When converting from "RGBA" to "P" without a ``matrix`` argument,
this passes the operation to :py:meth:`~PIL.Image.Image.quantize`,
and ``dither`` and ``palette`` are ignored.
:param mode: The requested mode. See: :ref:`concept-modes`.
:param matrix: An optional conversion matrix. If given, this
should be 4- or 12-tuple containing floating point values.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Note that this is not used when ``matrix`` is supplied.
:param palette: Palette to use when converting from mode "RGB"
to "P". Available palettes are :data:`WEB` or :data:`ADAPTIVE`.
:param colors: Number of colors to use for the :data:`ADAPTIVE` palette.
Defaults to 256.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
has_transparency = self.info.get("transparency") is not None
if not mode and self.mode == "P":
# determine default mode
if self.palette:
mode = self.palette.mode
else:
mode = "RGB"
if mode == "RGB" and has_transparency:
mode = "RGBA"
if not mode or (mode == self.mode and not matrix):
return self.copy()
if matrix:
# matrix conversion
if mode not in ("L", "RGB"):
raise ValueError("illegal conversion")
im = self.im.convert_matrix(mode, matrix)
new = self._new(im)
if has_transparency and self.im.bands == 3:
transparency = new.info["transparency"]
def convert_transparency(m, v):
v = m[0] * v[0] + m[1] * v[1] + m[2] * v[2] + m[3] * 0.5
return max(0, min(255, int(v)))
if mode == "L":
transparency = convert_transparency(matrix, transparency)
elif len(mode) == 3:
transparency = tuple(
convert_transparency(matrix[i * 4 : i * 4 + 4], transparency)
for i in range(0, len(transparency))
)
new.info["transparency"] = transparency
return new
if mode == "P" and self.mode == "RGBA":
return self.quantize(colors)
trns = None
delete_trns = False
# transparency handling
if has_transparency:
if self.mode in ("1", "L", "I", "RGB") and mode == "RGBA":
# Use transparent conversion to promote from transparent
# color to an alpha channel.
new_im = self._new(
self.im.convert_transparent(mode, self.info["transparency"])
)
del new_im.info["transparency"]
return new_im
elif self.mode in ("L", "RGB", "P") and mode in ("L", "RGB", "P"):
t = self.info["transparency"]
if isinstance(t, bytes):
# Dragons. This can't be represented by a single color
warnings.warn(
"Palette images with Transparency expressed in bytes should be "
"converted to RGBA images"
)
delete_trns = True
else:
# get the new transparency color.
# use existing conversions
trns_im = Image()._new(core.new(self.mode, (1, 1)))
if self.mode == "P":
trns_im.putpalette(self.palette)
if isinstance(t, tuple):
err = "Couldn't allocate a palette color for transparency"
try:
t = trns_im.palette.getcolor(t, self)
except ValueError as e:
if str(e) == "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
t = None
else:
raise ValueError(err) from e
if t is None:
trns = None
else:
trns_im.putpixel((0, 0), t)
if mode in ("L", "RGB"):
trns_im = trns_im.convert(mode)
else:
# can't just retrieve the palette number, got to do it
# after quantization.
trns_im = trns_im.convert("RGB")
trns = trns_im.getpixel((0, 0))
elif self.mode == "P" and mode in ("LA", "PA", "RGBA"):
t = self.info["transparency"]
delete_trns = True
if isinstance(t, bytes):
self.im.putpalettealphas(t)
elif isinstance(t, int):
self.im.putpalettealpha(t, 0)
else:
raise ValueError("Transparency for P mode should be bytes or int")
if mode == "P" and palette == ADAPTIVE:
im = self.im.quantize(colors)
new = self._new(im)
from . import ImagePalette
new.palette = ImagePalette.ImagePalette("RGB", new.im.getpalette("RGB"))
if delete_trns:
# This could possibly happen if we requantize to fewer colors.
# The transparency would be totally off in that case.
del new.info["transparency"]
if trns is not None:
try:
new.info["transparency"] = new.palette.getcolor(trns, new)
except Exception:
# if we can't make a transparent color, don't leave the old
# transparency hanging around to mess us up.
del new.info["transparency"]
warnings.warn("Couldn't allocate palette entry for transparency")
return new
# colorspace conversion
if dither is None:
dither = FLOYDSTEINBERG
try:
im = self.im.convert(mode, dither)
except ValueError:
try:
# normalize source image and try again
im = self.im.convert(getmodebase(self.mode))
im = im.convert(mode, dither)
except KeyError as e:
raise ValueError("illegal conversion") from e
new_im = self._new(im)
if mode == "P" and palette != ADAPTIVE:
from . import ImagePalette
new_im.palette = ImagePalette.ImagePalette("RGB", list(range(256)) * 3)
if delete_trns:
# crash fail if we leave a bytes transparency in an rgb/l mode.
del new_im.info["transparency"]
if trns is not None:
if new_im.mode == "P":
try:
new_im.info["transparency"] = new_im.palette.getcolor(trns, new_im)
except ValueError as e:
del new_im.info["transparency"]
if str(e) != "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
warnings.warn(
"Couldn't allocate palette entry for transparency"
)
else:
new_im.info["transparency"] = trns
return new_im
def quantize(self, colors=256, method=None, kmeans=0, palette=None, dither=1):
"""
Convert the image to 'P' mode with the specified number
of colors.
:param colors: The desired number of colors, <= 256
:param method: :data:`MEDIANCUT` (median cut),
:data:`MAXCOVERAGE` (maximum coverage),
:data:`FASTOCTREE` (fast octree),
:data:`LIBIMAGEQUANT` (libimagequant; check support using
:py:func:`PIL.features.check_feature`
with ``feature="libimagequant"``).
By default, :data:`MEDIANCUT` will be used.
The exception to this is RGBA images. :data:`MEDIANCUT` and
:data:`MAXCOVERAGE` do not support RGBA images, so
:data:`FASTOCTREE` is used by default instead.
:param kmeans: Integer
:param palette: Quantize to the palette of given
:py:class:`PIL.Image.Image`.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Default: 1 (legacy setting)
:returns: A new image
"""
self.load()
if method is None:
# defaults:
method = MEDIANCUT
if self.mode == "RGBA":
method = FASTOCTREE
if self.mode == "RGBA" and method not in (FASTOCTREE, LIBIMAGEQUANT):
# Caller specified an invalid mode.
raise ValueError(
"Fast Octree (method == 2) and libimagequant (method == 3) "
"are the only valid methods for quantizing RGBA images"
)
if palette:
# use palette from reference image
palette.load()
if palette.mode != "P":
raise ValueError("bad mode for palette image")
if self.mode != "RGB" and self.mode != "L":
raise ValueError(
"only RGB or L mode images can be quantized to a palette"
)
im = self.im.convert("P", dither, palette.im)
new_im = self._new(im)
new_im.palette = palette.palette.copy()
return new_im
im = self._new(self.im.quantize(colors, method, kmeans))
from . import ImagePalette
mode = im.im.getpalettemode()
palette = im.im.getpalette(mode, mode)[: colors * len(mode)]
im.palette = ImagePalette.ImagePalette(mode, palette)
return im
def copy(self):
"""
Copies this image. Use this method if you wish to paste things
into an image, but still retain the original.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
return self._new(self.im.copy())
__copy__ = copy
def crop(self, box=None):
"""
Returns a rectangular region from this image. The box is a
4-tuple defining the left, upper, right, and lower pixel
coordinate. See :ref:`coordinate-system`.
Note: Prior to Pillow 3.4.0, this was a lazy operation.
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if box is None:
return self.copy()
self.load()
return self._new(self._crop(self.im, box))
def _crop(self, im, box):
"""
Returns a rectangular region from the core image object im.
This is equivalent to calling im.crop((x0, y0, x1, y1)), but
includes additional sanity checks.
:param im: a core image object
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:returns: A core image object.
"""
x0, y0, x1, y1 = map(int, map(round, box))
absolute_values = (abs(x1 - x0), abs(y1 - y0))
_decompression_bomb_check(absolute_values)
return im.crop((x0, y0, x1, y1))
def draft(self, mode, size):
"""
Configures the image file loader so it returns a version of the
image that as closely as possible matches the given mode and
size. For example, you can use this method to convert a color
JPEG to greyscale while loading it.
If any changes are made, returns a tuple with the chosen ``mode`` and
``box`` with coordinates of the original image within the altered one.
Note that this method modifies the :py:class:`~PIL.Image.Image` object
in place. If the image has already been loaded, this method has no
effect.
Note: This method is not implemented for most images. It is
currently implemented only for JPEG and MPO images.
:param mode: The requested mode.
:param size: The requested size.
"""
pass
def _expand(self, xmargin, ymargin=None):
if ymargin is None:
ymargin = xmargin
self.load()
return self._new(self.im.expand(xmargin, ymargin, 0))
def filter(self, filter):
"""
Filters this image using the given filter. For a list of
available filters, see the :py:mod:`~PIL.ImageFilter` module.
:param filter: Filter kernel.
:returns: An :py:class:`~PIL.Image.Image` object."""
from . import ImageFilter
self.load()
if isinstance(filter, Callable):
filter = filter()
if not hasattr(filter, "filter"):
raise TypeError(
"filter argument should be ImageFilter.Filter instance or class"
)
multiband = isinstance(filter, ImageFilter.MultibandFilter)
if self.im.bands == 1 or multiband:
return self._new(filter.filter(self.im))
ims = []
for c in range(self.im.bands):
ims.append(self._new(filter.filter(self.im.getband(c))))
return merge(self.mode, ims)
def getbands(self):
"""
Returns a tuple containing the name of each band in this image.
For example, ``getbands`` on an RGB image returns ("R", "G", "B").
:returns: A tuple containing band names.
:rtype: tuple
"""
return ImageMode.getmode(self.mode).bands
def getbbox(self):
"""
Calculates the bounding box of the non-zero regions in the
image.
:returns: The bounding box is returned as a 4-tuple defining the
left, upper, right, and lower pixel coordinate. See
:ref:`coordinate-system`. If the image is completely empty, this
method returns None.
"""
self.load()
return self.im.getbbox()
def getcolors(self, maxcolors=256):
"""
Returns a list of colors used in this image.
The colors will be in the image's mode. For example, an RGB image will
return a tuple of (red, green, blue) color values, and a P image will
return the index of the color in the palette.
:param maxcolors: Maximum number of colors. If this number is
exceeded, this method returns None. The default limit is
256 colors.
:returns: An unsorted list of (count, pixel) values.
"""
self.load()
if self.mode in ("1", "L", "P"):
h = self.im.histogram()
out = []
for i in range(256):
if h[i]:
out.append((h[i], i))
if len(out) > maxcolors:
return None
return out
return self.im.getcolors(maxcolors)
def getdata(self, band=None):
"""
Returns the contents of this image as a sequence object
containing pixel values. The sequence object is flattened, so
that values for line one follow directly after the values of
line zero, and so on.
Note that the sequence object returned by this method is an
internal PIL data type, which only supports certain sequence
operations. To convert it to an ordinary sequence (e.g. for
printing), use ``list(im.getdata())``.
:param band: What band to return. The default is to return
all bands. To return a single band, pass in the index
value (e.g. 0 to get the "R" band from an "RGB" image).
:returns: A sequence-like object.
"""
self.load()
if band is not None:
return self.im.getband(band)
return self.im # could be abused
def getextrema(self):
"""
Gets the the minimum and maximum pixel values for each band in
the image.
:returns: For a single-band image, a 2-tuple containing the
minimum and maximum pixel value. For a multi-band image,
a tuple containing one 2-tuple for each band.
"""
self.load()
if self.im.bands > 1:
extrema = []
for i in range(self.im.bands):
extrema.append(self.im.getband(i).getextrema())
return tuple(extrema)
return self.im.getextrema()
def _getxmp(self, xmp_tags):
def get_name(tag):
return tag.split("}")[1]
def get_value(element):
value = {get_name(k): v for k, v in element.attrib.items()}
children = list(element)
if children:
for child in children:
name = get_name(child.tag)
child_value = get_value(child)
if name in value:
if not isinstance(value[name], list):
value[name] = [value[name]]
value[name].append(child_value)
else:
value[name] = child_value
elif value:
if element.text:
value["text"] = element.text
else:
return element.text
return value
if ElementTree is None:
warnings.warn("XMP data cannot be read without defusedxml dependency")
return {}
else:
root = ElementTree.fromstring(xmp_tags)
return {get_name(root.tag): get_value(root)}
def getexif(self):
if self._exif is None:
self._exif = Exif()
exif_info = self.info.get("exif")
if exif_info is None:
if "Raw profile type exif" in self.info:
exif_info = bytes.fromhex(
"".join(self.info["Raw profile type exif"].split("\n")[3:])
)
elif hasattr(self, "tag_v2"):
self._exif.endian = self.tag_v2._endian
self._exif.load_from_fp(self.fp, self.tag_v2._offset)
if exif_info is not None:
self._exif.load(exif_info)
# XMP tags
if 0x0112 not in self._exif:
xmp_tags = self.info.get("XML:com.adobe.xmp")
if xmp_tags:
match = re.search(r'tiff:Orientation="([0-9])"', xmp_tags)
if match:
self._exif[0x0112] = int(match[1])
return self._exif
def getim(self):
"""
Returns a capsule that points to the internal image memory.
:returns: A capsule object.
"""
self.load()
return self.im.ptr
def getpalette(self):
"""
Returns the image palette as a list.
:returns: A list of color values [r, g, b, ...], or None if the
image has no palette.
"""
self.load()
try:
return list(self.im.getpalette())
except ValueError:
return None # no palette
def getpixel(self, xy):
"""
Returns the pixel value at a given position.
:param xy: The coordinate, given as (x, y). See
:ref:`coordinate-system`.
:returns: The pixel value. If the image is a multi-layer image,
this method returns a tuple.
"""
self.load()
if self.pyaccess:
return self.pyaccess.getpixel(xy)
return self.im.getpixel(xy)
def getprojection(self):
"""
Get projection to x and y axes
:returns: Two sequences, indicating where there are non-zero
pixels along the X-axis and the Y-axis, respectively.
"""
self.load()
x, y = self.im.getprojection()
return list(x), list(y)
def histogram(self, mask=None, extrema=None):
"""
Returns a histogram for the image. The histogram is returned as
a list of pixel counts, one for each pixel value in the source
image. If the image has more than one band, the histograms for
all bands are concatenated (for example, the histogram for an
"RGB" image contains 768 values).
A bilevel image (mode "1") is treated as a greyscale ("L") image
by this method.
If a mask is provided, the method returns a histogram for those
parts of the image where the mask image is non-zero. The mask
image must have the same size as the image, and be either a
bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A list containing pixel counts.
"""
self.load()
if mask:
mask.load()
return self.im.histogram((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.histogram(extrema)
return self.im.histogram()
def entropy(self, mask=None, extrema=None):
"""
Calculates and returns the entropy for the image.
A bilevel image (mode "1") is treated as a greyscale ("L")
image by this method.
If a mask is provided, the method employs the histogram for
those parts of the image where the mask image is non-zero.
The mask image must have the same size as the image, and be
either a bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A float value representing the image entropy
"""
self.load()
if mask:
mask.load()
return self.im.entropy((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.entropy(extrema)
return self.im.entropy()
def paste(self, im, box=None, mask=None):
"""
Pastes another image into this image. The box argument is either
a 2-tuple giving the upper left corner, a 4-tuple defining the
left, upper, right, and lower pixel coordinate, or None (same as
(0, 0)). See :ref:`coordinate-system`. If a 4-tuple is given, the size
of the pasted image must match the size of the region.
If the modes don't match, the pasted image is converted to the mode of
this image (see the :py:meth:`~PIL.Image.Image.convert` method for
details).
Instead of an image, the source can be a integer or tuple
containing pixel values. The method then fills the region
with the given color. When creating RGB images, you can
also use color strings as supported by the ImageColor module.
If a mask is given, this method updates only the regions
indicated by the mask. You can use either "1", "L" or "RGBA"
images (in the latter case, the alpha band is used as mask).
Where the mask is 255, the given image is copied as is. Where
the mask is 0, the current value is preserved. Intermediate
values will mix the two images together, including their alpha
channels if they have them.
See :py:meth:`~PIL.Image.Image.alpha_composite` if you want to
combine images with respect to their alpha channels.
:param im: Source image or pixel value (integer or tuple).
:param box: An optional 4-tuple giving the region to paste into.
If a 2-tuple is used instead, it's treated as the upper left
corner. If omitted or None, the source is pasted into the
upper left corner.
If an image is given as the second argument and there is no
third, the box defaults to (0, 0), and the second argument
is interpreted as a mask image.
:param mask: An optional mask image.
"""
if isImageType(box) and mask is None:
# abbreviated paste(im, mask) syntax
mask = box
box = None
if box is None:
box = (0, 0)
if len(box) == 2:
# upper left corner given; get size from image or mask
if isImageType(im):
size = im.size
elif isImageType(mask):
size = mask.size
else:
# FIXME: use self.size here?
raise ValueError("cannot determine region size; use 4-item box")
box += (box[0] + size[0], box[1] + size[1])
if isinstance(im, str):
from . import ImageColor
im = ImageColor.getcolor(im, self.mode)
elif isImageType(im):
im.load()
if self.mode != im.mode:
if self.mode != "RGB" or im.mode not in ("RGBA", "RGBa"):
# should use an adapter for this!
im = im.convert(self.mode)
im = im.im
self._ensure_mutable()
if mask:
mask.load()
self.im.paste(im, box, mask.im)
else:
self.im.paste(im, box)
def alpha_composite(self, im, dest=(0, 0), source=(0, 0)):
"""'In-place' analog of Image.alpha_composite. Composites an image
onto this image.
:param im: image to composite over this one
:param dest: Optional 2 tuple (left, top) specifying the upper
left corner in this (destination) image.
:param source: Optional 2 (left, top) tuple for the upper left
corner in the overlay source image, or 4 tuple (left, top, right,
bottom) for the bounds of the source rectangle
Performance Note: Not currently implemented in-place in the core layer.
"""
if not isinstance(source, (list, tuple)):
raise ValueError("Source must be a tuple")
if not isinstance(dest, (list, tuple)):
raise ValueError("Destination must be a tuple")
if not len(source) in (2, 4):
raise ValueError("Source must be a 2 or 4-tuple")
if not len(dest) == 2:
raise ValueError("Destination must be a 2-tuple")
if min(source) < 0:
raise ValueError("Source must be non-negative")
if len(source) == 2:
source = source + im.size
# over image, crop if it's not the whole thing.
if source == (0, 0) + im.size:
overlay = im
else:
overlay = im.crop(source)
# target for the paste
box = dest + (dest[0] + overlay.width, dest[1] + overlay.height)
# destination image. don't copy if we're using the whole image.
if box == (0, 0) + self.size:
background = self
else:
background = self.crop(box)
result = alpha_composite(background, overlay)
self.paste(result, box)
def point(self, lut, mode=None):
"""
Maps this image through a lookup table or function.
:param lut: A lookup table, containing 256 (or 65536 if
self.mode=="I" and mode == "L") values per band in the
image. A function can be used instead, it should take a
single argument. The function is called once for each
possible pixel value, and the resulting table is applied to
all bands of the image.
It may also be an :py:class:`~PIL.Image.ImagePointHandler`
object::
class Example(Image.ImagePointHandler):
def point(self, data):
# Return result
:param mode: Output mode (default is same as input). In the
current version, this can only be used if the source image
has mode "L" or "P", and the output has mode "1" or the
source image mode is "I" and the output mode is "L".
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
if isinstance(lut, ImagePointHandler):
return lut.point(self)
if callable(lut):
# if it isn't a list, it should be a function
if self.mode in ("I", "I;16", "F"):
# check if the function can be used with point_transform
# UNDONE wiredfool -- I think this prevents us from ever doing
# a gamma function point transform on > 8bit images.
scale, offset = _getscaleoffset(lut)
return self._new(self.im.point_transform(scale, offset))
# for other modes, convert the function to a table
lut = [lut(i) for i in range(256)] * self.im.bands
if self.mode == "F":
# FIXME: _imaging returns a confusing error message for this case
raise ValueError("point operation not supported for this mode")
return self._new(self.im.point(lut, mode))
def putalpha(self, alpha):
"""
Adds or replaces the alpha layer in this image. If the image
does not have an alpha layer, it's converted to "LA" or "RGBA".
The new layer must be either "L" or "1".
:param alpha: The new alpha layer. This can either be an "L" or "1"
image having the same size as this image, or an integer or
other color value.
"""
self._ensure_mutable()
if self.mode not in ("LA", "PA", "RGBA"):
# attempt to promote self to a matching alpha mode
try:
mode = getmodebase(self.mode) + "A"
try:
self.im.setmode(mode)
except (AttributeError, ValueError) as e:
# do things the hard way
im = self.im.convert(mode)
if im.mode not in ("LA", "PA", "RGBA"):
raise ValueError from e # sanity check
self.im = im
self.pyaccess = None
self.mode = self.im.mode
except KeyError as e:
raise ValueError("illegal image mode") from e
if self.mode in ("LA", "PA"):
band = 1
else:
band = 3
if isImageType(alpha):
# alpha layer
if alpha.mode not in ("1", "L"):
raise ValueError("illegal image mode")
alpha.load()
if alpha.mode == "1":
alpha = alpha.convert("L")
else:
# constant alpha
try:
self.im.fillband(band, alpha)
except (AttributeError, ValueError):
# do things the hard way
alpha = new("L", self.size, alpha)
else:
return
self.im.putband(alpha.im, band)
def putdata(self, data, scale=1.0, offset=0.0):
"""
Copies pixel data from a flattened sequence object into the image. The
values should start at the upper left corner (0, 0), continue to the
end of the line, followed directly by the first value of the second
line, and so on. Data will be read until either the image or the
sequence ends. The scale and offset values are used to adjust the
sequence values: **pixel = value*scale + offset**.
:param data: A flattened sequence object.
:param scale: An optional scale value. The default is 1.0.
:param offset: An optional offset value. The default is 0.0.
"""
self._ensure_mutable()
self.im.putdata(data, scale, offset)
def putpalette(self, data, rawmode="RGB"):
"""
Attaches a palette to this image. The image must be a "P", "PA", "L"
or "LA" image.
The palette sequence must contain at most 256 colors, made up of one
integer value for each channel in the raw mode.
For example, if the raw mode is "RGB", then it can contain at most 768
values, made up of red, green and blue values for the corresponding pixel
index in the 256 colors.
If the raw mode is "RGBA", then it can contain at most 1024 values,
containing red, green, blue and alpha values.
Alternatively, an 8-bit string may be used instead of an integer sequence.
:param data: A palette sequence (either a list or a string).
:param rawmode: The raw mode of the palette. Either "RGB", "RGBA", or a
mode that can be transformed to "RGB" (e.g. "R", "BGR;15", "RGBA;L").
"""
from . import ImagePalette
if self.mode not in ("L", "LA", "P", "PA"):
raise ValueError("illegal image mode")
if isinstance(data, ImagePalette.ImagePalette):
palette = ImagePalette.raw(data.rawmode, data.palette)
else:
if not isinstance(data, bytes):
data = bytes(data)
palette = ImagePalette.raw(rawmode, data)
self.mode = "PA" if "A" in self.mode else "P"
self.palette = palette
self.palette.mode = "RGB"
self.load() # install new palette
def putpixel(self, xy, value):
"""
Modifies the pixel at the given position. The color is given as
a single numerical value for single-band images, and a tuple for
multi-band images. In addition to this, RGB and RGBA tuples are
accepted for P images.
Note that this method is relatively slow. For more extensive changes,
use :py:meth:`~PIL.Image.Image.paste` or the :py:mod:`~PIL.ImageDraw`
module instead.
See:
* :py:meth:`~PIL.Image.Image.paste`
* :py:meth:`~PIL.Image.Image.putdata`
* :py:mod:`~PIL.ImageDraw`
:param xy: The pixel coordinate, given as (x, y). See
:ref:`coordinate-system`.
:param value: The pixel value.
"""
if self.readonly:
self._copy()
self.load()
if self.pyaccess:
return self.pyaccess.putpixel(xy, value)
if (
self.mode == "P"
and isinstance(value, (list, tuple))
and len(value) in [3, 4]
):
# RGB or RGBA value for a P image
value = self.palette.getcolor(value, self)
return self.im.putpixel(xy, value)
def remap_palette(self, dest_map, source_palette=None):
"""
Rewrites the image to reorder the palette.
:param dest_map: A list of indexes into the original palette.
e.g. ``[1,0]`` would swap a two item palette, and ``list(range(256))``
is the identity transform.
:param source_palette: Bytes or None.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
from . import ImagePalette
if self.mode not in ("L", "P"):
raise ValueError("illegal image mode")
if source_palette is None:
if self.mode == "P":
self.load()
source_palette = self.im.getpalette("RGB")[:768]
else: # L-mode
source_palette = bytearray(i // 3 for i in range(768))
palette_bytes = b""
new_positions = [0] * 256
# pick only the used colors from the palette
for i, oldPosition in enumerate(dest_map):
palette_bytes += source_palette[oldPosition * 3 : oldPosition * 3 + 3]
new_positions[oldPosition] = i
# replace the palette color id of all pixel with the new id
# Palette images are [0..255], mapped through a 1 or 3
# byte/color map. We need to remap the whole image
# from palette 1 to palette 2. New_positions is
# an array of indexes into palette 1. Palette 2 is
# palette 1 with any holes removed.
# We're going to leverage the convert mechanism to use the
# C code to remap the image from palette 1 to palette 2,
# by forcing the source image into 'L' mode and adding a
# mapping 'L' mode palette, then converting back to 'L'
# sans palette thus converting the image bytes, then
# assigning the optimized RGB palette.
# perf reference, 9500x4000 gif, w/~135 colors
# 14 sec prepatch, 1 sec postpatch with optimization forced.
mapping_palette = bytearray(new_positions)
m_im = self.copy()
m_im.mode = "P"
m_im.palette = ImagePalette.ImagePalette("RGB", palette=mapping_palette * 3)
# possibly set palette dirty, then
# m_im.putpalette(mapping_palette, 'L') # converts to 'P'
# or just force it.
# UNDONE -- this is part of the general issue with palettes
m_im.im.putpalette("RGB;L", m_im.palette.tobytes())
m_im = m_im.convert("L")
# Internally, we require 768 bytes for a palette.
new_palette_bytes = palette_bytes + (768 - len(palette_bytes)) * b"\x00"
m_im.putpalette(new_palette_bytes)
m_im.palette = ImagePalette.ImagePalette("RGB", palette=palette_bytes)
return m_im
def _get_safe_box(self, size, resample, box):
"""Expands the box so it includes adjacent pixels
that may be used by resampling with the given resampling filter.
"""
filter_support = _filters_support[resample] - 0.5
scale_x = (box[2] - box[0]) / size[0]
scale_y = (box[3] - box[1]) / size[1]
support_x = filter_support * scale_x
support_y = filter_support * scale_y
return (
max(0, int(box[0] - support_x)),
max(0, int(box[1] - support_y)),
min(self.size[0], math.ceil(box[2] + support_x)),
min(self.size[1], math.ceil(box[3] + support_y)),
)
def resize(self, size, resample=None, box=None, reducing_gap=None):
"""
Returns a resized copy of this image.
:param size: The requested size in pixels, as a 2-tuple:
(width, height).
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If the image has mode "1" or "P", it is always set to
:py:data:`PIL.Image.NEAREST`.
If the image mode specifies a number of bits, such as "I;16", then the
default filter is :py:data:`PIL.Image.NEAREST`.
Otherwise, the default filter is :py:data:`PIL.Image.BICUBIC`.
See: :ref:`concept-filters`.
:param box: An optional 4-tuple of floats providing
the source image region to be scaled.
The values must be within (0, 0, width, height) rectangle.
If omitted or None, the entire source is used.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce`.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is None (no optimization).
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if resample is None:
type_special = ";" in self.mode
resample = NEAREST if type_special else BICUBIC
elif resample not in (NEAREST, BILINEAR, BICUBIC, LANCZOS, BOX, HAMMING):
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(LANCZOS, "Image.LANCZOS"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
(BOX, "Image.BOX"),
(HAMMING, "Image.HAMMING"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
if reducing_gap is not None and reducing_gap < 1.0:
raise ValueError("reducing_gap must be 1.0 or greater")
size = tuple(size)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if self.size == size and box == (0, 0) + self.size:
return self.copy()
if self.mode in ("1", "P"):
resample = NEAREST
if self.mode in ["LA", "RGBA"] and resample != NEAREST:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.resize(size, resample, box)
return im.convert(self.mode)
self.load()
if reducing_gap is not None and resample != NEAREST:
factor_x = int((box[2] - box[0]) / size[0] / reducing_gap) or 1
factor_y = int((box[3] - box[1]) / size[1] / reducing_gap) or 1
if factor_x > 1 or factor_y > 1:
reduce_box = self._get_safe_box(size, resample, box)
factor = (factor_x, factor_y)
if callable(self.reduce):
self = self.reduce(factor, box=reduce_box)
else:
self = Image.reduce(self, factor, box=reduce_box)
box = (
(box[0] - reduce_box[0]) / factor_x,
(box[1] - reduce_box[1]) / factor_y,
(box[2] - reduce_box[0]) / factor_x,
(box[3] - reduce_box[1]) / factor_y,
)
return self._new(self.im.resize(size, resample, box))
def reduce(self, factor, box=None):
"""
Returns a copy of the image reduced ``factor`` times.
If the size of the image is not dividable by ``factor``,
the resulting size will be rounded up.
:param factor: A greater than 0 integer or tuple of two integers
for width and height separately.
:param box: An optional 4-tuple of ints providing
the source image region to be reduced.
The values must be within ``(0, 0, width, height)`` rectangle.
If omitted or ``None``, the entire source is used.
"""
if not isinstance(factor, (list, tuple)):
factor = (factor, factor)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if factor == (1, 1) and box == (0, 0) + self.size:
return self.copy()
if self.mode in ["LA", "RGBA"]:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.reduce(factor, box)
return im.convert(self.mode)
self.load()
return self._new(self.im.reduce(factor, box))
def rotate(
self,
angle,
resample=NEAREST,
expand=0,
center=None,
translate=None,
fillcolor=None,
):
"""
Returns a rotated copy of this image. This method returns a
copy of this image, rotated the given number of degrees counter
clockwise around its centre.
:param angle: In degrees counter clockwise.
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC`
(cubic spline interpolation in a 4x4 environment).
If omitted, or if the image has mode "1" or "P", it is
set to :py:data:`PIL.Image.NEAREST`. See :ref:`concept-filters`.
:param expand: Optional expansion flag. If true, expands the output
image to make it large enough to hold the entire rotated image.
If false or omitted, make the output image the same size as the
input image. Note that the expand flag assumes rotation around
the center and no translation.
:param center: Optional center of rotation (a 2-tuple). Origin is
the upper left corner. Default is the center of the image.
:param translate: An optional post-rotate translation (a 2-tuple).
:param fillcolor: An optional color for area outside the rotated image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
angle = angle % 360.0
# Fast paths regardless of filter, as long as we're not
# translating or changing the center.
if not (center or translate):
if angle == 0:
return self.copy()
if angle == 180:
return self.transpose(ROTATE_180)
if angle in (90, 270) and (expand or self.width == self.height):
return self.transpose(ROTATE_90 if angle == 90 else ROTATE_270)
# Calculate the affine matrix. Note that this is the reverse
# transformation (from destination image to source) because we
# want to interpolate the (discrete) destination pixel from
# the local area around the (floating) source pixel.
# The matrix we actually want (note that it operates from the right):
# (1, 0, tx) (1, 0, cx) ( cos a, sin a, 0) (1, 0, -cx)
# (0, 1, ty) * (0, 1, cy) * (-sin a, cos a, 0) * (0, 1, -cy)
# (0, 0, 1) (0, 0, 1) ( 0, 0, 1) (0, 0, 1)
# The reverse matrix is thus:
# (1, 0, cx) ( cos -a, sin -a, 0) (1, 0, -cx) (1, 0, -tx)
# (0, 1, cy) * (-sin -a, cos -a, 0) * (0, 1, -cy) * (0, 1, -ty)
# (0, 0, 1) ( 0, 0, 1) (0, 0, 1) (0, 0, 1)
# In any case, the final translation may be updated at the end to
# compensate for the expand flag.
w, h = self.size
if translate is None:
post_trans = (0, 0)
else:
post_trans = translate
if center is None:
# FIXME These should be rounded to ints?
rotn_center = (w / 2.0, h / 2.0)
else:
rotn_center = center
angle = -math.radians(angle)
matrix = [
round(math.cos(angle), 15),
round(math.sin(angle), 15),
0.0,
round(-math.sin(angle), 15),
round(math.cos(angle), 15),
0.0,
]
def transform(x, y, matrix):
(a, b, c, d, e, f) = matrix
return a * x + b * y + c, d * x + e * y + f
matrix[2], matrix[5] = transform(
-rotn_center[0] - post_trans[0], -rotn_center[1] - post_trans[1], matrix
)
matrix[2] += rotn_center[0]
matrix[5] += rotn_center[1]
if expand:
# calculate output size
xx = []
yy = []
for x, y in ((0, 0), (w, 0), (w, h), (0, h)):
x, y = transform(x, y, matrix)
xx.append(x)
yy.append(y)
nw = math.ceil(max(xx)) - math.floor(min(xx))
nh = math.ceil(max(yy)) - math.floor(min(yy))
# We multiply a translation matrix from the right. Because of its
# special form, this is the same as taking the image of the
# translation vector as new translation vector.
matrix[2], matrix[5] = transform(-(nw - w) / 2.0, -(nh - h) / 2.0, matrix)
w, h = nw, nh
return self.transform((w, h), AFFINE, matrix, resample, fillcolor=fillcolor)
def save(self, fp, format=None, **params):
"""
Saves this image under the given filename. If no format is
specified, the format to use is determined from the filename
extension, if possible.
Keyword options can be used to provide additional instructions
to the writer. If a writer doesn't recognise an option, it is
silently ignored. The available options are described in the
:doc:`image format documentation
<../handbook/image-file-formats>` for each writer.
You can use a file object instead of a filename. In this case,
you must always specify the format. The file object must
implement the ``seek``, ``tell``, and ``write``
methods, and be opened in binary mode.
:param fp: A filename (string), pathlib.Path object or file object.
:param format: Optional format override. If omitted, the
format to use is determined from the filename extension.
If a file object was used instead of a filename, this
parameter should always be used.
:param params: Extra parameters to the image writer.
:returns: None
:exception ValueError: If the output format could not be determined
from the file name. Use the format option to solve this.
:exception OSError: If the file could not be written. The file
may have been created, and may contain partial data.
"""
filename = ""
open_fp = False
if isinstance(fp, Path):
filename = str(fp)
open_fp = True
elif isPath(fp):
filename = fp
open_fp = True
elif fp == sys.stdout:
try:
fp = sys.stdout.buffer
except AttributeError:
pass
if not filename and hasattr(fp, "name") and isPath(fp.name):
# only set the name for metadata purposes
filename = fp.name
# may mutate self!
self._ensure_mutable()
save_all = params.pop("save_all", False)
self.encoderinfo = params
self.encoderconfig = ()
preinit()
ext = os.path.splitext(filename)[1].lower()
if not format:
if ext not in EXTENSION:
init()
try:
format = EXTENSION[ext]
except KeyError as e:
raise ValueError(f"unknown file extension: {ext}") from e
if format.upper() not in SAVE:
init()
if save_all:
save_handler = SAVE_ALL[format.upper()]
else:
save_handler = SAVE[format.upper()]
if open_fp:
if params.get("append", False):
# Open also for reading ("+"), because TIFF save_all
# writer needs to go back and edit the written data.
fp = builtins.open(filename, "r+b")
else:
fp = builtins.open(filename, "w+b")
try:
save_handler(self, fp, filename)
finally:
# do what we can to clean up
if open_fp:
fp.close()
def seek(self, frame):
"""
Seeks to the given frame in this sequence file. If you seek
beyond the end of the sequence, the method raises an
``EOFError`` exception. When a sequence file is opened, the
library automatically seeks to frame 0.
See :py:meth:`~PIL.Image.Image.tell`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:param frame: Frame number, starting at 0.
:exception EOFError: If the call attempts to seek beyond the end
of the sequence.
"""
# overridden by file handlers
if frame != 0:
raise EOFError
def show(self, title=None):
"""
Displays this image. This method is mainly intended for debugging purposes.
This method calls :py:func:`PIL.ImageShow.show` internally. You can use
:py:func:`PIL.ImageShow.register` to override its default behaviour.
The image is first saved to a temporary file. By default, it will be in
PNG format.
On Unix, the image is then opened using the **display**, **eog** or
**xv** utility, depending on which one can be found.
On macOS, the image is opened with the native Preview application.
On Windows, the image is opened with the standard PNG display utility.
:param title: Optional title to use for the image window, where possible.
"""
_show(self, title=title)
def split(self):
"""
Split this image into individual bands. This method returns a
tuple of individual image bands from an image. For example,
splitting an "RGB" image creates three new images each
containing a copy of one of the original bands (red, green,
blue).
If you need only one band, :py:meth:`~PIL.Image.Image.getchannel`
method can be more convenient and faster.
:returns: A tuple containing bands.
"""
self.load()
if self.im.bands == 1:
ims = [self.copy()]
else:
ims = map(self._new, self.im.split())
return tuple(ims)
def getchannel(self, channel):
"""
Returns an image containing a single channel of the source image.
:param channel: What channel to return. Could be index
(0 for "R" channel of "RGB") or channel name
("A" for alpha channel of "RGBA").
:returns: An image in "L" mode.
.. versionadded:: 4.3.0
"""
self.load()
if isinstance(channel, str):
try:
channel = self.getbands().index(channel)
except ValueError as e:
raise ValueError(f'The image has no channel "{channel}"') from e
return self._new(self.im.getband(channel))
def tell(self):
"""
Returns the current frame number. See :py:meth:`~PIL.Image.Image.seek`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:returns: Frame number, starting with 0.
"""
return 0
def thumbnail(self, size, resample=BICUBIC, reducing_gap=2.0):
"""
Make this image into a thumbnail. This method modifies the
image to contain a thumbnail version of itself, no larger than
the given size. This method calculates an appropriate thumbnail
size to preserve the aspect of the image, calls the
:py:meth:`~PIL.Image.Image.draft` method to configure the file reader
(where applicable), and finally resizes the image.
Note that this function modifies the :py:class:`~PIL.Image.Image`
object in place. If you need to use the full resolution image as well,
apply this method to a :py:meth:`~PIL.Image.Image.copy` of the original
image.
:param size: Requested size.
:param resample: Optional resampling filter. This can be one
of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If omitted, it defaults to :py:data:`PIL.Image.BICUBIC`.
(was :py:data:`PIL.Image.NEAREST` prior to version 2.5.0).
See: :ref:`concept-filters`.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce` or
:py:meth:`~PIL.Image.Image.draft` for JPEG images.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is 2.0 (very close to fair resampling
while still being faster in many cases).
:returns: None
"""
x, y = map(math.floor, size)
if x >= self.width and y >= self.height:
return
def round_aspect(number, key):
return max(min(math.floor(number), math.ceil(number), key=key), 1)
# preserve aspect ratio
aspect = self.width / self.height
if x / y >= aspect:
x = round_aspect(y * aspect, key=lambda n: abs(aspect - n / y))
else:
y = round_aspect(
x / aspect, key=lambda n: 0 if n == 0 else abs(aspect - x / n)
)
size = (x, y)
box = None
if reducing_gap is not None:
res = self.draft(None, (size[0] * reducing_gap, size[1] * reducing_gap))
if res is not None:
box = res[1]
if self.size != size:
im = self.resize(size, resample, box=box, reducing_gap=reducing_gap)
self.im = im.im
self._size = size
self.mode = self.im.mode
self.readonly = 0
self.pyaccess = None
# FIXME: the different transform methods need further explanation
# instead of bloating the method docs, add a separate chapter.
def transform(
self, size, method, data=None, resample=NEAREST, fill=1, fillcolor=None
):
"""
Transforms this image. This method creates a new image with the
given size, and the same mode as the original, and copies data
to the new image using the given transform.
:param size: The output size.
:param method: The transformation method. This is one of
:py:data:`PIL.Image.EXTENT` (cut out a rectangular subregion),
:py:data:`PIL.Image.AFFINE` (affine transform),
:py:data:`PIL.Image.PERSPECTIVE` (perspective transform),
:py:data:`PIL.Image.QUAD` (map a quadrilateral to a rectangle), or
:py:data:`PIL.Image.MESH` (map a number of source quadrilaterals
in one operation).
It may also be an :py:class:`~PIL.Image.ImageTransformHandler`
object::
class Example(Image.ImageTransformHandler):
def transform(self, size, data, resample, fill=1):
# Return result
It may also be an object with a ``method.getdata`` method
that returns a tuple supplying new ``method`` and ``data`` values::
class Example:
def getdata(self):
method = Image.EXTENT
data = (0, 0, 100, 100)
return method, data
:param data: Extra data to the transformation method.
:param resample: Optional resampling filter. It can be one of
:py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC` (cubic spline
interpolation in a 4x4 environment). If omitted, or if the image
has mode "1" or "P", it is set to :py:data:`PIL.Image.NEAREST`.
See: :ref:`concept-filters`.
:param fill: If ``method`` is an
:py:class:`~PIL.Image.ImageTransformHandler` object, this is one of
the arguments passed to it. Otherwise, it is unused.
:param fillcolor: Optional fill color for the area outside the
transform in the output image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if self.mode in ("LA", "RGBA") and resample != NEAREST:
return (
self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
.transform(size, method, data, resample, fill, fillcolor)
.convert(self.mode)
)
if isinstance(method, ImageTransformHandler):
return method.transform(size, self, resample=resample, fill=fill)
if hasattr(method, "getdata"):
# compatibility w. old-style transform objects
method, data = method.getdata()
if data is None:
raise ValueError("missing method data")
im = new(self.mode, size, fillcolor)
if self.mode == "P" and self.palette:
im.palette = self.palette.copy()
im.info = self.info.copy()
if method == MESH:
# list of quads
for box, quad in data:
im.__transformer(box, self, QUAD, quad, resample, fillcolor is None)
else:
im.__transformer(
(0, 0) + size, self, method, data, resample, fillcolor is None
)
return im
def __transformer(self, box, image, method, data, resample=NEAREST, fill=1):
w = box[2] - box[0]
h = box[3] - box[1]
if method == AFFINE:
data = data[0:6]
elif method == EXTENT:
# convert extent to an affine transform
x0, y0, x1, y1 = data
xs = (x1 - x0) / w
ys = (y1 - y0) / h
method = AFFINE
data = (xs, 0, x0, 0, ys, y0)
elif method == PERSPECTIVE:
data = data[0:8]
elif method == QUAD:
# quadrilateral warp. data specifies the four corners
# given as NW, SW, SE, and NE.
nw = data[0:2]
sw = data[2:4]
se = data[4:6]
ne = data[6:8]
x0, y0 = nw
As = 1.0 / w
At = 1.0 / h
data = (
x0,
(ne[0] - x0) * As,
(sw[0] - x0) * At,
(se[0] - sw[0] - ne[0] + x0) * As * At,
y0,
(ne[1] - y0) * As,
(sw[1] - y0) * At,
(se[1] - sw[1] - ne[1] + y0) * As * At,
)
else:
raise ValueError("unknown transformation method")
if resample not in (NEAREST, BILINEAR, BICUBIC):
if resample in (BOX, HAMMING, LANCZOS):
message = {
BOX: "Image.BOX",
HAMMING: "Image.HAMMING",
LANCZOS: "Image.LANCZOS/Image.ANTIALIAS",
}[resample] + f" ({resample}) cannot be used."
else:
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
image.load()
self.load()
if image.mode in ("1", "P"):
resample = NEAREST
self.im.transform2(box, image.im, method, data, resample, fill)
def transpose(self, method):
"""
Transpose image (flip or rotate in 90 degree steps)
:param method: One of :py:data:`PIL.Image.FLIP_LEFT_RIGHT`,
:py:data:`PIL.Image.FLIP_TOP_BOTTOM`, :py:data:`PIL.Image.ROTATE_90`,
:py:data:`PIL.Image.ROTATE_180`, :py:data:`PIL.Image.ROTATE_270`,
:py:data:`PIL.Image.TRANSPOSE` or :py:data:`PIL.Image.TRANSVERSE`.
:returns: Returns a flipped or rotated copy of this image.
"""
self.load()
return self._new(self.im.transpose(method))
def effect_spread(self, distance):
"""
Randomly spread pixels in an image.
:param distance: Distance to spread pixels.
"""
self.load()
return self._new(self.im.effect_spread(distance))
def toqimage(self):
"""Returns a QImage copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqimage(self)
def toqpixmap(self):
"""Returns a QPixmap copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqpixmap(self)
The provided code snippet includes necessary dependencies for implementing the `linear_gradient` function. Write a Python function `def linear_gradient(mode)` to solve the following problem:
Generate 256x256 linear gradient from black to white, top to bottom. :param mode: Input mode.
Here is the function:
def linear_gradient(mode):
"""
Generate 256x256 linear gradient from black to white, top to bottom.
:param mode: Input mode.
"""
return Image()._new(core.linear_gradient(mode)) | Generate 256x256 linear gradient from black to white, top to bottom. :param mode: Input mode. |
167,779 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
class Image:
"""
This class represents an image object. To create
:py:class:`~PIL.Image.Image` objects, use the appropriate factory
functions. There's hardly ever any reason to call the Image constructor
directly.
* :py:func:`~PIL.Image.open`
* :py:func:`~PIL.Image.new`
* :py:func:`~PIL.Image.frombytes`
"""
format = None
format_description = None
_close_exclusive_fp_after_loading = True
def __init__(self):
# FIXME: take "new" parameters / other image?
# FIXME: turn mode and size into delegating properties?
self.im = None
self.mode = ""
self._size = (0, 0)
self.palette = None
self.info = {}
self._category = 0
self.readonly = 0
self.pyaccess = None
self._exif = None
def __getattr__(self, name):
if name == "category":
warnings.warn(
"Image categories are deprecated and will be removed in Pillow 10 "
"(2023-07-01). Use is_animated instead.",
DeprecationWarning,
stacklevel=2,
)
return self._category
raise AttributeError(name)
def width(self):
return self.size[0]
def height(self):
return self.size[1]
def size(self):
return self._size
def _new(self, im):
new = Image()
new.im = im
new.mode = im.mode
new._size = im.size
if im.mode in ("P", "PA"):
if self.palette:
new.palette = self.palette.copy()
else:
from . import ImagePalette
new.palette = ImagePalette.ImagePalette()
new.info = self.info.copy()
return new
# Context manager support
def __enter__(self):
return self
def __exit__(self, *args):
if hasattr(self, "fp") and getattr(self, "_exclusive_fp", False):
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
def close(self):
"""
Closes the file pointer, if possible.
This operation will destroy the image core and release its memory.
The image data will be unusable afterward.
This function is required to close images that have multiple frames or
have not had their file read and closed by the
:py:meth:`~PIL.Image.Image.load` method. See :ref:`file-handling` for
more information.
"""
try:
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
except Exception as msg:
logger.debug("Error closing: %s", msg)
if getattr(self, "map", None):
self.map = None
# Instead of simply setting to None, we're setting up a
# deferred error that will better explain that the core image
# object is gone.
self.im = deferred_error(ValueError("Operation on closed image"))
def _copy(self):
self.load()
self.im = self.im.copy()
self.pyaccess = None
self.readonly = 0
def _ensure_mutable(self):
if self.readonly:
self._copy()
else:
self.load()
def _dump(self, file=None, format=None, **options):
suffix = ""
if format:
suffix = "." + format
if not file:
f, filename = tempfile.mkstemp(suffix)
os.close(f)
else:
filename = file
if not filename.endswith(suffix):
filename = filename + suffix
self.load()
if not format or format == "PPM":
self.im.save_ppm(filename)
else:
self.save(filename, format, **options)
return filename
def __eq__(self, other):
return (
self.__class__ is other.__class__
and self.mode == other.mode
and self.size == other.size
and self.info == other.info
and self._category == other._category
and self.readonly == other.readonly
and self.getpalette() == other.getpalette()
and self.tobytes() == other.tobytes()
)
def __repr__(self):
return "<%s.%s image mode=%s size=%dx%d at 0x%X>" % (
self.__class__.__module__,
self.__class__.__name__,
self.mode,
self.size[0],
self.size[1],
id(self),
)
def _repr_png_(self):
"""iPython display hook support
:returns: png version of the image as bytes
"""
b = io.BytesIO()
try:
self.save(b, "PNG")
except Exception as e:
raise ValueError("Could not save to PNG for display") from e
return b.getvalue()
class _ArrayData:
def __init__(self, new):
self.__array_interface__ = new
def __array__(self, dtype=None):
# numpy array interface support
import numpy as np
new = {}
shape, typestr = _conv_type_shape(self)
new["shape"] = shape
new["typestr"] = typestr
new["version"] = 3
if self.mode == "1":
# Binary images need to be extended from bits to bytes
# See: https://github.com/python-pillow/Pillow/issues/350
new["data"] = self.tobytes("raw", "L")
else:
new["data"] = self.tobytes()
return np.array(self._ArrayData(new), dtype)
def __getstate__(self):
return [self.info, self.mode, self.size, self.getpalette(), self.tobytes()]
def __setstate__(self, state):
Image.__init__(self)
self.tile = []
info, mode, size, palette, data = state
self.info = info
self.mode = mode
self._size = size
self.im = core.new(mode, size)
if mode in ("L", "LA", "P", "PA") and palette:
self.putpalette(palette)
self.frombytes(data)
def tobytes(self, encoder_name="raw", *args):
"""
Return image as a bytes object.
.. warning::
This method returns the raw image data from the internal
storage. For compressed image data (e.g. PNG, JPEG) use
:meth:`~.save`, with a BytesIO parameter for in-memory
data.
:param encoder_name: What encoder to use. The default is to
use the standard "raw" encoder.
:param args: Extra arguments to the encoder.
:returns: A :py:class:`bytes` object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
if encoder_name == "raw" and args == ():
args = self.mode
self.load()
# unpack data
e = _getencoder(self.mode, encoder_name, args)
e.setimage(self.im)
bufsize = max(65536, self.size[0] * 4) # see RawEncode.c
data = []
while True:
l, s, d = e.encode(bufsize)
data.append(d)
if s:
break
if s < 0:
raise RuntimeError(f"encoder error {s} in tobytes")
return b"".join(data)
def tobitmap(self, name="image"):
"""
Returns the image converted to an X11 bitmap.
.. note:: This method only works for mode "1" images.
:param name: The name prefix to use for the bitmap variables.
:returns: A string containing an X11 bitmap.
:raises ValueError: If the mode is not "1"
"""
self.load()
if self.mode != "1":
raise ValueError("not a bitmap")
data = self.tobytes("xbm")
return b"".join(
[
f"#define {name}_width {self.size[0]}\n".encode("ascii"),
f"#define {name}_height {self.size[1]}\n".encode("ascii"),
f"static char {name}_bits[] = {{\n".encode("ascii"),
data,
b"};",
]
)
def frombytes(self, data, decoder_name="raw", *args):
"""
Loads this image with pixel data from a bytes object.
This method is similar to the :py:func:`~PIL.Image.frombytes` function,
but loads data into this image instead of creating a new image object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
# default format
if decoder_name == "raw" and args == ():
args = self.mode
# unpack data
d = _getdecoder(self.mode, decoder_name, args)
d.setimage(self.im)
s = d.decode(data)
if s[0] >= 0:
raise ValueError("not enough image data")
if s[1] != 0:
raise ValueError("cannot decode image data")
def load(self):
"""
Allocates storage for the image and loads the pixel data. In
normal cases, you don't need to call this method, since the
Image class automatically loads an opened image when it is
accessed for the first time.
If the file associated with the image was opened by Pillow, then this
method will close it. The exception to this is if the image has
multiple frames, in which case the file will be left open for seek
operations. See :ref:`file-handling` for more information.
:returns: An image access object.
:rtype: :ref:`PixelAccess` or :py:class:`PIL.PyAccess`
"""
if self.im and self.palette and self.palette.dirty:
# realize palette
mode, arr = self.palette.getdata()
if mode == "RGBA":
mode = "RGB"
self.info["transparency"] = arr[3::4]
arr = bytes(
value for (index, value) in enumerate(arr) if index % 4 != 3
)
palette_length = self.im.putpalette(mode, arr)
self.palette.dirty = 0
self.palette.rawmode = None
if "transparency" in self.info and mode in ("LA", "PA"):
if isinstance(self.info["transparency"], int):
self.im.putpalettealpha(self.info["transparency"], 0)
else:
self.im.putpalettealphas(self.info["transparency"])
self.palette.mode = "RGBA"
else:
self.palette.mode = "RGB"
self.palette.palette = self.im.getpalette()[: palette_length * 3]
if self.im:
if cffi and USE_CFFI_ACCESS:
if self.pyaccess:
return self.pyaccess
from . import PyAccess
self.pyaccess = PyAccess.new(self, self.readonly)
if self.pyaccess:
return self.pyaccess
return self.im.pixel_access(self.readonly)
def verify(self):
"""
Verifies the contents of a file. For data read from a file, this
method attempts to determine if the file is broken, without
actually decoding the image data. If this method finds any
problems, it raises suitable exceptions. If you need to load
the image after using this method, you must reopen the image
file.
"""
pass
def convert(self, mode=None, matrix=None, dither=None, palette=WEB, colors=256):
"""
Returns a converted copy of this image. For the "P" mode, this
method translates pixels through the palette. If mode is
omitted, a mode is chosen so that all information in the image
and the palette can be represented without a palette.
The current version supports all possible conversions between
"L", "RGB" and "CMYK." The ``matrix`` argument only supports "L"
and "RGB".
When translating a color image to greyscale (mode "L"),
the library uses the ITU-R 601-2 luma transform::
L = R * 299/1000 + G * 587/1000 + B * 114/1000
The default method of converting a greyscale ("L") or "RGB"
image into a bilevel (mode "1") image uses Floyd-Steinberg
dither to approximate the original image luminosity levels. If
dither is :data:`NONE`, all values larger than 127 are set to 255 (white),
all other values to 0 (black). To use other thresholds, use the
:py:meth:`~PIL.Image.Image.point` method.
When converting from "RGBA" to "P" without a ``matrix`` argument,
this passes the operation to :py:meth:`~PIL.Image.Image.quantize`,
and ``dither`` and ``palette`` are ignored.
:param mode: The requested mode. See: :ref:`concept-modes`.
:param matrix: An optional conversion matrix. If given, this
should be 4- or 12-tuple containing floating point values.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Note that this is not used when ``matrix`` is supplied.
:param palette: Palette to use when converting from mode "RGB"
to "P". Available palettes are :data:`WEB` or :data:`ADAPTIVE`.
:param colors: Number of colors to use for the :data:`ADAPTIVE` palette.
Defaults to 256.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
has_transparency = self.info.get("transparency") is not None
if not mode and self.mode == "P":
# determine default mode
if self.palette:
mode = self.palette.mode
else:
mode = "RGB"
if mode == "RGB" and has_transparency:
mode = "RGBA"
if not mode or (mode == self.mode and not matrix):
return self.copy()
if matrix:
# matrix conversion
if mode not in ("L", "RGB"):
raise ValueError("illegal conversion")
im = self.im.convert_matrix(mode, matrix)
new = self._new(im)
if has_transparency and self.im.bands == 3:
transparency = new.info["transparency"]
def convert_transparency(m, v):
v = m[0] * v[0] + m[1] * v[1] + m[2] * v[2] + m[3] * 0.5
return max(0, min(255, int(v)))
if mode == "L":
transparency = convert_transparency(matrix, transparency)
elif len(mode) == 3:
transparency = tuple(
convert_transparency(matrix[i * 4 : i * 4 + 4], transparency)
for i in range(0, len(transparency))
)
new.info["transparency"] = transparency
return new
if mode == "P" and self.mode == "RGBA":
return self.quantize(colors)
trns = None
delete_trns = False
# transparency handling
if has_transparency:
if self.mode in ("1", "L", "I", "RGB") and mode == "RGBA":
# Use transparent conversion to promote from transparent
# color to an alpha channel.
new_im = self._new(
self.im.convert_transparent(mode, self.info["transparency"])
)
del new_im.info["transparency"]
return new_im
elif self.mode in ("L", "RGB", "P") and mode in ("L", "RGB", "P"):
t = self.info["transparency"]
if isinstance(t, bytes):
# Dragons. This can't be represented by a single color
warnings.warn(
"Palette images with Transparency expressed in bytes should be "
"converted to RGBA images"
)
delete_trns = True
else:
# get the new transparency color.
# use existing conversions
trns_im = Image()._new(core.new(self.mode, (1, 1)))
if self.mode == "P":
trns_im.putpalette(self.palette)
if isinstance(t, tuple):
err = "Couldn't allocate a palette color for transparency"
try:
t = trns_im.palette.getcolor(t, self)
except ValueError as e:
if str(e) == "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
t = None
else:
raise ValueError(err) from e
if t is None:
trns = None
else:
trns_im.putpixel((0, 0), t)
if mode in ("L", "RGB"):
trns_im = trns_im.convert(mode)
else:
# can't just retrieve the palette number, got to do it
# after quantization.
trns_im = trns_im.convert("RGB")
trns = trns_im.getpixel((0, 0))
elif self.mode == "P" and mode in ("LA", "PA", "RGBA"):
t = self.info["transparency"]
delete_trns = True
if isinstance(t, bytes):
self.im.putpalettealphas(t)
elif isinstance(t, int):
self.im.putpalettealpha(t, 0)
else:
raise ValueError("Transparency for P mode should be bytes or int")
if mode == "P" and palette == ADAPTIVE:
im = self.im.quantize(colors)
new = self._new(im)
from . import ImagePalette
new.palette = ImagePalette.ImagePalette("RGB", new.im.getpalette("RGB"))
if delete_trns:
# This could possibly happen if we requantize to fewer colors.
# The transparency would be totally off in that case.
del new.info["transparency"]
if trns is not None:
try:
new.info["transparency"] = new.palette.getcolor(trns, new)
except Exception:
# if we can't make a transparent color, don't leave the old
# transparency hanging around to mess us up.
del new.info["transparency"]
warnings.warn("Couldn't allocate palette entry for transparency")
return new
# colorspace conversion
if dither is None:
dither = FLOYDSTEINBERG
try:
im = self.im.convert(mode, dither)
except ValueError:
try:
# normalize source image and try again
im = self.im.convert(getmodebase(self.mode))
im = im.convert(mode, dither)
except KeyError as e:
raise ValueError("illegal conversion") from e
new_im = self._new(im)
if mode == "P" and palette != ADAPTIVE:
from . import ImagePalette
new_im.palette = ImagePalette.ImagePalette("RGB", list(range(256)) * 3)
if delete_trns:
# crash fail if we leave a bytes transparency in an rgb/l mode.
del new_im.info["transparency"]
if trns is not None:
if new_im.mode == "P":
try:
new_im.info["transparency"] = new_im.palette.getcolor(trns, new_im)
except ValueError as e:
del new_im.info["transparency"]
if str(e) != "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
warnings.warn(
"Couldn't allocate palette entry for transparency"
)
else:
new_im.info["transparency"] = trns
return new_im
def quantize(self, colors=256, method=None, kmeans=0, palette=None, dither=1):
"""
Convert the image to 'P' mode with the specified number
of colors.
:param colors: The desired number of colors, <= 256
:param method: :data:`MEDIANCUT` (median cut),
:data:`MAXCOVERAGE` (maximum coverage),
:data:`FASTOCTREE` (fast octree),
:data:`LIBIMAGEQUANT` (libimagequant; check support using
:py:func:`PIL.features.check_feature`
with ``feature="libimagequant"``).
By default, :data:`MEDIANCUT` will be used.
The exception to this is RGBA images. :data:`MEDIANCUT` and
:data:`MAXCOVERAGE` do not support RGBA images, so
:data:`FASTOCTREE` is used by default instead.
:param kmeans: Integer
:param palette: Quantize to the palette of given
:py:class:`PIL.Image.Image`.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Default: 1 (legacy setting)
:returns: A new image
"""
self.load()
if method is None:
# defaults:
method = MEDIANCUT
if self.mode == "RGBA":
method = FASTOCTREE
if self.mode == "RGBA" and method not in (FASTOCTREE, LIBIMAGEQUANT):
# Caller specified an invalid mode.
raise ValueError(
"Fast Octree (method == 2) and libimagequant (method == 3) "
"are the only valid methods for quantizing RGBA images"
)
if palette:
# use palette from reference image
palette.load()
if palette.mode != "P":
raise ValueError("bad mode for palette image")
if self.mode != "RGB" and self.mode != "L":
raise ValueError(
"only RGB or L mode images can be quantized to a palette"
)
im = self.im.convert("P", dither, palette.im)
new_im = self._new(im)
new_im.palette = palette.palette.copy()
return new_im
im = self._new(self.im.quantize(colors, method, kmeans))
from . import ImagePalette
mode = im.im.getpalettemode()
palette = im.im.getpalette(mode, mode)[: colors * len(mode)]
im.palette = ImagePalette.ImagePalette(mode, palette)
return im
def copy(self):
"""
Copies this image. Use this method if you wish to paste things
into an image, but still retain the original.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
return self._new(self.im.copy())
__copy__ = copy
def crop(self, box=None):
"""
Returns a rectangular region from this image. The box is a
4-tuple defining the left, upper, right, and lower pixel
coordinate. See :ref:`coordinate-system`.
Note: Prior to Pillow 3.4.0, this was a lazy operation.
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if box is None:
return self.copy()
self.load()
return self._new(self._crop(self.im, box))
def _crop(self, im, box):
"""
Returns a rectangular region from the core image object im.
This is equivalent to calling im.crop((x0, y0, x1, y1)), but
includes additional sanity checks.
:param im: a core image object
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:returns: A core image object.
"""
x0, y0, x1, y1 = map(int, map(round, box))
absolute_values = (abs(x1 - x0), abs(y1 - y0))
_decompression_bomb_check(absolute_values)
return im.crop((x0, y0, x1, y1))
def draft(self, mode, size):
"""
Configures the image file loader so it returns a version of the
image that as closely as possible matches the given mode and
size. For example, you can use this method to convert a color
JPEG to greyscale while loading it.
If any changes are made, returns a tuple with the chosen ``mode`` and
``box`` with coordinates of the original image within the altered one.
Note that this method modifies the :py:class:`~PIL.Image.Image` object
in place. If the image has already been loaded, this method has no
effect.
Note: This method is not implemented for most images. It is
currently implemented only for JPEG and MPO images.
:param mode: The requested mode.
:param size: The requested size.
"""
pass
def _expand(self, xmargin, ymargin=None):
if ymargin is None:
ymargin = xmargin
self.load()
return self._new(self.im.expand(xmargin, ymargin, 0))
def filter(self, filter):
"""
Filters this image using the given filter. For a list of
available filters, see the :py:mod:`~PIL.ImageFilter` module.
:param filter: Filter kernel.
:returns: An :py:class:`~PIL.Image.Image` object."""
from . import ImageFilter
self.load()
if isinstance(filter, Callable):
filter = filter()
if not hasattr(filter, "filter"):
raise TypeError(
"filter argument should be ImageFilter.Filter instance or class"
)
multiband = isinstance(filter, ImageFilter.MultibandFilter)
if self.im.bands == 1 or multiband:
return self._new(filter.filter(self.im))
ims = []
for c in range(self.im.bands):
ims.append(self._new(filter.filter(self.im.getband(c))))
return merge(self.mode, ims)
def getbands(self):
"""
Returns a tuple containing the name of each band in this image.
For example, ``getbands`` on an RGB image returns ("R", "G", "B").
:returns: A tuple containing band names.
:rtype: tuple
"""
return ImageMode.getmode(self.mode).bands
def getbbox(self):
"""
Calculates the bounding box of the non-zero regions in the
image.
:returns: The bounding box is returned as a 4-tuple defining the
left, upper, right, and lower pixel coordinate. See
:ref:`coordinate-system`. If the image is completely empty, this
method returns None.
"""
self.load()
return self.im.getbbox()
def getcolors(self, maxcolors=256):
"""
Returns a list of colors used in this image.
The colors will be in the image's mode. For example, an RGB image will
return a tuple of (red, green, blue) color values, and a P image will
return the index of the color in the palette.
:param maxcolors: Maximum number of colors. If this number is
exceeded, this method returns None. The default limit is
256 colors.
:returns: An unsorted list of (count, pixel) values.
"""
self.load()
if self.mode in ("1", "L", "P"):
h = self.im.histogram()
out = []
for i in range(256):
if h[i]:
out.append((h[i], i))
if len(out) > maxcolors:
return None
return out
return self.im.getcolors(maxcolors)
def getdata(self, band=None):
"""
Returns the contents of this image as a sequence object
containing pixel values. The sequence object is flattened, so
that values for line one follow directly after the values of
line zero, and so on.
Note that the sequence object returned by this method is an
internal PIL data type, which only supports certain sequence
operations. To convert it to an ordinary sequence (e.g. for
printing), use ``list(im.getdata())``.
:param band: What band to return. The default is to return
all bands. To return a single band, pass in the index
value (e.g. 0 to get the "R" band from an "RGB" image).
:returns: A sequence-like object.
"""
self.load()
if band is not None:
return self.im.getband(band)
return self.im # could be abused
def getextrema(self):
"""
Gets the the minimum and maximum pixel values for each band in
the image.
:returns: For a single-band image, a 2-tuple containing the
minimum and maximum pixel value. For a multi-band image,
a tuple containing one 2-tuple for each band.
"""
self.load()
if self.im.bands > 1:
extrema = []
for i in range(self.im.bands):
extrema.append(self.im.getband(i).getextrema())
return tuple(extrema)
return self.im.getextrema()
def _getxmp(self, xmp_tags):
def get_name(tag):
return tag.split("}")[1]
def get_value(element):
value = {get_name(k): v for k, v in element.attrib.items()}
children = list(element)
if children:
for child in children:
name = get_name(child.tag)
child_value = get_value(child)
if name in value:
if not isinstance(value[name], list):
value[name] = [value[name]]
value[name].append(child_value)
else:
value[name] = child_value
elif value:
if element.text:
value["text"] = element.text
else:
return element.text
return value
if ElementTree is None:
warnings.warn("XMP data cannot be read without defusedxml dependency")
return {}
else:
root = ElementTree.fromstring(xmp_tags)
return {get_name(root.tag): get_value(root)}
def getexif(self):
if self._exif is None:
self._exif = Exif()
exif_info = self.info.get("exif")
if exif_info is None:
if "Raw profile type exif" in self.info:
exif_info = bytes.fromhex(
"".join(self.info["Raw profile type exif"].split("\n")[3:])
)
elif hasattr(self, "tag_v2"):
self._exif.endian = self.tag_v2._endian
self._exif.load_from_fp(self.fp, self.tag_v2._offset)
if exif_info is not None:
self._exif.load(exif_info)
# XMP tags
if 0x0112 not in self._exif:
xmp_tags = self.info.get("XML:com.adobe.xmp")
if xmp_tags:
match = re.search(r'tiff:Orientation="([0-9])"', xmp_tags)
if match:
self._exif[0x0112] = int(match[1])
return self._exif
def getim(self):
"""
Returns a capsule that points to the internal image memory.
:returns: A capsule object.
"""
self.load()
return self.im.ptr
def getpalette(self):
"""
Returns the image palette as a list.
:returns: A list of color values [r, g, b, ...], or None if the
image has no palette.
"""
self.load()
try:
return list(self.im.getpalette())
except ValueError:
return None # no palette
def getpixel(self, xy):
"""
Returns the pixel value at a given position.
:param xy: The coordinate, given as (x, y). See
:ref:`coordinate-system`.
:returns: The pixel value. If the image is a multi-layer image,
this method returns a tuple.
"""
self.load()
if self.pyaccess:
return self.pyaccess.getpixel(xy)
return self.im.getpixel(xy)
def getprojection(self):
"""
Get projection to x and y axes
:returns: Two sequences, indicating where there are non-zero
pixels along the X-axis and the Y-axis, respectively.
"""
self.load()
x, y = self.im.getprojection()
return list(x), list(y)
def histogram(self, mask=None, extrema=None):
"""
Returns a histogram for the image. The histogram is returned as
a list of pixel counts, one for each pixel value in the source
image. If the image has more than one band, the histograms for
all bands are concatenated (for example, the histogram for an
"RGB" image contains 768 values).
A bilevel image (mode "1") is treated as a greyscale ("L") image
by this method.
If a mask is provided, the method returns a histogram for those
parts of the image where the mask image is non-zero. The mask
image must have the same size as the image, and be either a
bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A list containing pixel counts.
"""
self.load()
if mask:
mask.load()
return self.im.histogram((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.histogram(extrema)
return self.im.histogram()
def entropy(self, mask=None, extrema=None):
"""
Calculates and returns the entropy for the image.
A bilevel image (mode "1") is treated as a greyscale ("L")
image by this method.
If a mask is provided, the method employs the histogram for
those parts of the image where the mask image is non-zero.
The mask image must have the same size as the image, and be
either a bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A float value representing the image entropy
"""
self.load()
if mask:
mask.load()
return self.im.entropy((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.entropy(extrema)
return self.im.entropy()
def paste(self, im, box=None, mask=None):
"""
Pastes another image into this image. The box argument is either
a 2-tuple giving the upper left corner, a 4-tuple defining the
left, upper, right, and lower pixel coordinate, or None (same as
(0, 0)). See :ref:`coordinate-system`. If a 4-tuple is given, the size
of the pasted image must match the size of the region.
If the modes don't match, the pasted image is converted to the mode of
this image (see the :py:meth:`~PIL.Image.Image.convert` method for
details).
Instead of an image, the source can be a integer or tuple
containing pixel values. The method then fills the region
with the given color. When creating RGB images, you can
also use color strings as supported by the ImageColor module.
If a mask is given, this method updates only the regions
indicated by the mask. You can use either "1", "L" or "RGBA"
images (in the latter case, the alpha band is used as mask).
Where the mask is 255, the given image is copied as is. Where
the mask is 0, the current value is preserved. Intermediate
values will mix the two images together, including their alpha
channels if they have them.
See :py:meth:`~PIL.Image.Image.alpha_composite` if you want to
combine images with respect to their alpha channels.
:param im: Source image or pixel value (integer or tuple).
:param box: An optional 4-tuple giving the region to paste into.
If a 2-tuple is used instead, it's treated as the upper left
corner. If omitted or None, the source is pasted into the
upper left corner.
If an image is given as the second argument and there is no
third, the box defaults to (0, 0), and the second argument
is interpreted as a mask image.
:param mask: An optional mask image.
"""
if isImageType(box) and mask is None:
# abbreviated paste(im, mask) syntax
mask = box
box = None
if box is None:
box = (0, 0)
if len(box) == 2:
# upper left corner given; get size from image or mask
if isImageType(im):
size = im.size
elif isImageType(mask):
size = mask.size
else:
# FIXME: use self.size here?
raise ValueError("cannot determine region size; use 4-item box")
box += (box[0] + size[0], box[1] + size[1])
if isinstance(im, str):
from . import ImageColor
im = ImageColor.getcolor(im, self.mode)
elif isImageType(im):
im.load()
if self.mode != im.mode:
if self.mode != "RGB" or im.mode not in ("RGBA", "RGBa"):
# should use an adapter for this!
im = im.convert(self.mode)
im = im.im
self._ensure_mutable()
if mask:
mask.load()
self.im.paste(im, box, mask.im)
else:
self.im.paste(im, box)
def alpha_composite(self, im, dest=(0, 0), source=(0, 0)):
"""'In-place' analog of Image.alpha_composite. Composites an image
onto this image.
:param im: image to composite over this one
:param dest: Optional 2 tuple (left, top) specifying the upper
left corner in this (destination) image.
:param source: Optional 2 (left, top) tuple for the upper left
corner in the overlay source image, or 4 tuple (left, top, right,
bottom) for the bounds of the source rectangle
Performance Note: Not currently implemented in-place in the core layer.
"""
if not isinstance(source, (list, tuple)):
raise ValueError("Source must be a tuple")
if not isinstance(dest, (list, tuple)):
raise ValueError("Destination must be a tuple")
if not len(source) in (2, 4):
raise ValueError("Source must be a 2 or 4-tuple")
if not len(dest) == 2:
raise ValueError("Destination must be a 2-tuple")
if min(source) < 0:
raise ValueError("Source must be non-negative")
if len(source) == 2:
source = source + im.size
# over image, crop if it's not the whole thing.
if source == (0, 0) + im.size:
overlay = im
else:
overlay = im.crop(source)
# target for the paste
box = dest + (dest[0] + overlay.width, dest[1] + overlay.height)
# destination image. don't copy if we're using the whole image.
if box == (0, 0) + self.size:
background = self
else:
background = self.crop(box)
result = alpha_composite(background, overlay)
self.paste(result, box)
def point(self, lut, mode=None):
"""
Maps this image through a lookup table or function.
:param lut: A lookup table, containing 256 (or 65536 if
self.mode=="I" and mode == "L") values per band in the
image. A function can be used instead, it should take a
single argument. The function is called once for each
possible pixel value, and the resulting table is applied to
all bands of the image.
It may also be an :py:class:`~PIL.Image.ImagePointHandler`
object::
class Example(Image.ImagePointHandler):
def point(self, data):
# Return result
:param mode: Output mode (default is same as input). In the
current version, this can only be used if the source image
has mode "L" or "P", and the output has mode "1" or the
source image mode is "I" and the output mode is "L".
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
if isinstance(lut, ImagePointHandler):
return lut.point(self)
if callable(lut):
# if it isn't a list, it should be a function
if self.mode in ("I", "I;16", "F"):
# check if the function can be used with point_transform
# UNDONE wiredfool -- I think this prevents us from ever doing
# a gamma function point transform on > 8bit images.
scale, offset = _getscaleoffset(lut)
return self._new(self.im.point_transform(scale, offset))
# for other modes, convert the function to a table
lut = [lut(i) for i in range(256)] * self.im.bands
if self.mode == "F":
# FIXME: _imaging returns a confusing error message for this case
raise ValueError("point operation not supported for this mode")
return self._new(self.im.point(lut, mode))
def putalpha(self, alpha):
"""
Adds or replaces the alpha layer in this image. If the image
does not have an alpha layer, it's converted to "LA" or "RGBA".
The new layer must be either "L" or "1".
:param alpha: The new alpha layer. This can either be an "L" or "1"
image having the same size as this image, or an integer or
other color value.
"""
self._ensure_mutable()
if self.mode not in ("LA", "PA", "RGBA"):
# attempt to promote self to a matching alpha mode
try:
mode = getmodebase(self.mode) + "A"
try:
self.im.setmode(mode)
except (AttributeError, ValueError) as e:
# do things the hard way
im = self.im.convert(mode)
if im.mode not in ("LA", "PA", "RGBA"):
raise ValueError from e # sanity check
self.im = im
self.pyaccess = None
self.mode = self.im.mode
except KeyError as e:
raise ValueError("illegal image mode") from e
if self.mode in ("LA", "PA"):
band = 1
else:
band = 3
if isImageType(alpha):
# alpha layer
if alpha.mode not in ("1", "L"):
raise ValueError("illegal image mode")
alpha.load()
if alpha.mode == "1":
alpha = alpha.convert("L")
else:
# constant alpha
try:
self.im.fillband(band, alpha)
except (AttributeError, ValueError):
# do things the hard way
alpha = new("L", self.size, alpha)
else:
return
self.im.putband(alpha.im, band)
def putdata(self, data, scale=1.0, offset=0.0):
"""
Copies pixel data from a flattened sequence object into the image. The
values should start at the upper left corner (0, 0), continue to the
end of the line, followed directly by the first value of the second
line, and so on. Data will be read until either the image or the
sequence ends. The scale and offset values are used to adjust the
sequence values: **pixel = value*scale + offset**.
:param data: A flattened sequence object.
:param scale: An optional scale value. The default is 1.0.
:param offset: An optional offset value. The default is 0.0.
"""
self._ensure_mutable()
self.im.putdata(data, scale, offset)
def putpalette(self, data, rawmode="RGB"):
"""
Attaches a palette to this image. The image must be a "P", "PA", "L"
or "LA" image.
The palette sequence must contain at most 256 colors, made up of one
integer value for each channel in the raw mode.
For example, if the raw mode is "RGB", then it can contain at most 768
values, made up of red, green and blue values for the corresponding pixel
index in the 256 colors.
If the raw mode is "RGBA", then it can contain at most 1024 values,
containing red, green, blue and alpha values.
Alternatively, an 8-bit string may be used instead of an integer sequence.
:param data: A palette sequence (either a list or a string).
:param rawmode: The raw mode of the palette. Either "RGB", "RGBA", or a
mode that can be transformed to "RGB" (e.g. "R", "BGR;15", "RGBA;L").
"""
from . import ImagePalette
if self.mode not in ("L", "LA", "P", "PA"):
raise ValueError("illegal image mode")
if isinstance(data, ImagePalette.ImagePalette):
palette = ImagePalette.raw(data.rawmode, data.palette)
else:
if not isinstance(data, bytes):
data = bytes(data)
palette = ImagePalette.raw(rawmode, data)
self.mode = "PA" if "A" in self.mode else "P"
self.palette = palette
self.palette.mode = "RGB"
self.load() # install new palette
def putpixel(self, xy, value):
"""
Modifies the pixel at the given position. The color is given as
a single numerical value for single-band images, and a tuple for
multi-band images. In addition to this, RGB and RGBA tuples are
accepted for P images.
Note that this method is relatively slow. For more extensive changes,
use :py:meth:`~PIL.Image.Image.paste` or the :py:mod:`~PIL.ImageDraw`
module instead.
See:
* :py:meth:`~PIL.Image.Image.paste`
* :py:meth:`~PIL.Image.Image.putdata`
* :py:mod:`~PIL.ImageDraw`
:param xy: The pixel coordinate, given as (x, y). See
:ref:`coordinate-system`.
:param value: The pixel value.
"""
if self.readonly:
self._copy()
self.load()
if self.pyaccess:
return self.pyaccess.putpixel(xy, value)
if (
self.mode == "P"
and isinstance(value, (list, tuple))
and len(value) in [3, 4]
):
# RGB or RGBA value for a P image
value = self.palette.getcolor(value, self)
return self.im.putpixel(xy, value)
def remap_palette(self, dest_map, source_palette=None):
"""
Rewrites the image to reorder the palette.
:param dest_map: A list of indexes into the original palette.
e.g. ``[1,0]`` would swap a two item palette, and ``list(range(256))``
is the identity transform.
:param source_palette: Bytes or None.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
from . import ImagePalette
if self.mode not in ("L", "P"):
raise ValueError("illegal image mode")
if source_palette is None:
if self.mode == "P":
self.load()
source_palette = self.im.getpalette("RGB")[:768]
else: # L-mode
source_palette = bytearray(i // 3 for i in range(768))
palette_bytes = b""
new_positions = [0] * 256
# pick only the used colors from the palette
for i, oldPosition in enumerate(dest_map):
palette_bytes += source_palette[oldPosition * 3 : oldPosition * 3 + 3]
new_positions[oldPosition] = i
# replace the palette color id of all pixel with the new id
# Palette images are [0..255], mapped through a 1 or 3
# byte/color map. We need to remap the whole image
# from palette 1 to palette 2. New_positions is
# an array of indexes into palette 1. Palette 2 is
# palette 1 with any holes removed.
# We're going to leverage the convert mechanism to use the
# C code to remap the image from palette 1 to palette 2,
# by forcing the source image into 'L' mode and adding a
# mapping 'L' mode palette, then converting back to 'L'
# sans palette thus converting the image bytes, then
# assigning the optimized RGB palette.
# perf reference, 9500x4000 gif, w/~135 colors
# 14 sec prepatch, 1 sec postpatch with optimization forced.
mapping_palette = bytearray(new_positions)
m_im = self.copy()
m_im.mode = "P"
m_im.palette = ImagePalette.ImagePalette("RGB", palette=mapping_palette * 3)
# possibly set palette dirty, then
# m_im.putpalette(mapping_palette, 'L') # converts to 'P'
# or just force it.
# UNDONE -- this is part of the general issue with palettes
m_im.im.putpalette("RGB;L", m_im.palette.tobytes())
m_im = m_im.convert("L")
# Internally, we require 768 bytes for a palette.
new_palette_bytes = palette_bytes + (768 - len(palette_bytes)) * b"\x00"
m_im.putpalette(new_palette_bytes)
m_im.palette = ImagePalette.ImagePalette("RGB", palette=palette_bytes)
return m_im
def _get_safe_box(self, size, resample, box):
"""Expands the box so it includes adjacent pixels
that may be used by resampling with the given resampling filter.
"""
filter_support = _filters_support[resample] - 0.5
scale_x = (box[2] - box[0]) / size[0]
scale_y = (box[3] - box[1]) / size[1]
support_x = filter_support * scale_x
support_y = filter_support * scale_y
return (
max(0, int(box[0] - support_x)),
max(0, int(box[1] - support_y)),
min(self.size[0], math.ceil(box[2] + support_x)),
min(self.size[1], math.ceil(box[3] + support_y)),
)
def resize(self, size, resample=None, box=None, reducing_gap=None):
"""
Returns a resized copy of this image.
:param size: The requested size in pixels, as a 2-tuple:
(width, height).
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If the image has mode "1" or "P", it is always set to
:py:data:`PIL.Image.NEAREST`.
If the image mode specifies a number of bits, such as "I;16", then the
default filter is :py:data:`PIL.Image.NEAREST`.
Otherwise, the default filter is :py:data:`PIL.Image.BICUBIC`.
See: :ref:`concept-filters`.
:param box: An optional 4-tuple of floats providing
the source image region to be scaled.
The values must be within (0, 0, width, height) rectangle.
If omitted or None, the entire source is used.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce`.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is None (no optimization).
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if resample is None:
type_special = ";" in self.mode
resample = NEAREST if type_special else BICUBIC
elif resample not in (NEAREST, BILINEAR, BICUBIC, LANCZOS, BOX, HAMMING):
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(LANCZOS, "Image.LANCZOS"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
(BOX, "Image.BOX"),
(HAMMING, "Image.HAMMING"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
if reducing_gap is not None and reducing_gap < 1.0:
raise ValueError("reducing_gap must be 1.0 or greater")
size = tuple(size)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if self.size == size and box == (0, 0) + self.size:
return self.copy()
if self.mode in ("1", "P"):
resample = NEAREST
if self.mode in ["LA", "RGBA"] and resample != NEAREST:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.resize(size, resample, box)
return im.convert(self.mode)
self.load()
if reducing_gap is not None and resample != NEAREST:
factor_x = int((box[2] - box[0]) / size[0] / reducing_gap) or 1
factor_y = int((box[3] - box[1]) / size[1] / reducing_gap) or 1
if factor_x > 1 or factor_y > 1:
reduce_box = self._get_safe_box(size, resample, box)
factor = (factor_x, factor_y)
if callable(self.reduce):
self = self.reduce(factor, box=reduce_box)
else:
self = Image.reduce(self, factor, box=reduce_box)
box = (
(box[0] - reduce_box[0]) / factor_x,
(box[1] - reduce_box[1]) / factor_y,
(box[2] - reduce_box[0]) / factor_x,
(box[3] - reduce_box[1]) / factor_y,
)
return self._new(self.im.resize(size, resample, box))
def reduce(self, factor, box=None):
"""
Returns a copy of the image reduced ``factor`` times.
If the size of the image is not dividable by ``factor``,
the resulting size will be rounded up.
:param factor: A greater than 0 integer or tuple of two integers
for width and height separately.
:param box: An optional 4-tuple of ints providing
the source image region to be reduced.
The values must be within ``(0, 0, width, height)`` rectangle.
If omitted or ``None``, the entire source is used.
"""
if not isinstance(factor, (list, tuple)):
factor = (factor, factor)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if factor == (1, 1) and box == (0, 0) + self.size:
return self.copy()
if self.mode in ["LA", "RGBA"]:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.reduce(factor, box)
return im.convert(self.mode)
self.load()
return self._new(self.im.reduce(factor, box))
def rotate(
self,
angle,
resample=NEAREST,
expand=0,
center=None,
translate=None,
fillcolor=None,
):
"""
Returns a rotated copy of this image. This method returns a
copy of this image, rotated the given number of degrees counter
clockwise around its centre.
:param angle: In degrees counter clockwise.
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC`
(cubic spline interpolation in a 4x4 environment).
If omitted, or if the image has mode "1" or "P", it is
set to :py:data:`PIL.Image.NEAREST`. See :ref:`concept-filters`.
:param expand: Optional expansion flag. If true, expands the output
image to make it large enough to hold the entire rotated image.
If false or omitted, make the output image the same size as the
input image. Note that the expand flag assumes rotation around
the center and no translation.
:param center: Optional center of rotation (a 2-tuple). Origin is
the upper left corner. Default is the center of the image.
:param translate: An optional post-rotate translation (a 2-tuple).
:param fillcolor: An optional color for area outside the rotated image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
angle = angle % 360.0
# Fast paths regardless of filter, as long as we're not
# translating or changing the center.
if not (center or translate):
if angle == 0:
return self.copy()
if angle == 180:
return self.transpose(ROTATE_180)
if angle in (90, 270) and (expand or self.width == self.height):
return self.transpose(ROTATE_90 if angle == 90 else ROTATE_270)
# Calculate the affine matrix. Note that this is the reverse
# transformation (from destination image to source) because we
# want to interpolate the (discrete) destination pixel from
# the local area around the (floating) source pixel.
# The matrix we actually want (note that it operates from the right):
# (1, 0, tx) (1, 0, cx) ( cos a, sin a, 0) (1, 0, -cx)
# (0, 1, ty) * (0, 1, cy) * (-sin a, cos a, 0) * (0, 1, -cy)
# (0, 0, 1) (0, 0, 1) ( 0, 0, 1) (0, 0, 1)
# The reverse matrix is thus:
# (1, 0, cx) ( cos -a, sin -a, 0) (1, 0, -cx) (1, 0, -tx)
# (0, 1, cy) * (-sin -a, cos -a, 0) * (0, 1, -cy) * (0, 1, -ty)
# (0, 0, 1) ( 0, 0, 1) (0, 0, 1) (0, 0, 1)
# In any case, the final translation may be updated at the end to
# compensate for the expand flag.
w, h = self.size
if translate is None:
post_trans = (0, 0)
else:
post_trans = translate
if center is None:
# FIXME These should be rounded to ints?
rotn_center = (w / 2.0, h / 2.0)
else:
rotn_center = center
angle = -math.radians(angle)
matrix = [
round(math.cos(angle), 15),
round(math.sin(angle), 15),
0.0,
round(-math.sin(angle), 15),
round(math.cos(angle), 15),
0.0,
]
def transform(x, y, matrix):
(a, b, c, d, e, f) = matrix
return a * x + b * y + c, d * x + e * y + f
matrix[2], matrix[5] = transform(
-rotn_center[0] - post_trans[0], -rotn_center[1] - post_trans[1], matrix
)
matrix[2] += rotn_center[0]
matrix[5] += rotn_center[1]
if expand:
# calculate output size
xx = []
yy = []
for x, y in ((0, 0), (w, 0), (w, h), (0, h)):
x, y = transform(x, y, matrix)
xx.append(x)
yy.append(y)
nw = math.ceil(max(xx)) - math.floor(min(xx))
nh = math.ceil(max(yy)) - math.floor(min(yy))
# We multiply a translation matrix from the right. Because of its
# special form, this is the same as taking the image of the
# translation vector as new translation vector.
matrix[2], matrix[5] = transform(-(nw - w) / 2.0, -(nh - h) / 2.0, matrix)
w, h = nw, nh
return self.transform((w, h), AFFINE, matrix, resample, fillcolor=fillcolor)
def save(self, fp, format=None, **params):
"""
Saves this image under the given filename. If no format is
specified, the format to use is determined from the filename
extension, if possible.
Keyword options can be used to provide additional instructions
to the writer. If a writer doesn't recognise an option, it is
silently ignored. The available options are described in the
:doc:`image format documentation
<../handbook/image-file-formats>` for each writer.
You can use a file object instead of a filename. In this case,
you must always specify the format. The file object must
implement the ``seek``, ``tell``, and ``write``
methods, and be opened in binary mode.
:param fp: A filename (string), pathlib.Path object or file object.
:param format: Optional format override. If omitted, the
format to use is determined from the filename extension.
If a file object was used instead of a filename, this
parameter should always be used.
:param params: Extra parameters to the image writer.
:returns: None
:exception ValueError: If the output format could not be determined
from the file name. Use the format option to solve this.
:exception OSError: If the file could not be written. The file
may have been created, and may contain partial data.
"""
filename = ""
open_fp = False
if isinstance(fp, Path):
filename = str(fp)
open_fp = True
elif isPath(fp):
filename = fp
open_fp = True
elif fp == sys.stdout:
try:
fp = sys.stdout.buffer
except AttributeError:
pass
if not filename and hasattr(fp, "name") and isPath(fp.name):
# only set the name for metadata purposes
filename = fp.name
# may mutate self!
self._ensure_mutable()
save_all = params.pop("save_all", False)
self.encoderinfo = params
self.encoderconfig = ()
preinit()
ext = os.path.splitext(filename)[1].lower()
if not format:
if ext not in EXTENSION:
init()
try:
format = EXTENSION[ext]
except KeyError as e:
raise ValueError(f"unknown file extension: {ext}") from e
if format.upper() not in SAVE:
init()
if save_all:
save_handler = SAVE_ALL[format.upper()]
else:
save_handler = SAVE[format.upper()]
if open_fp:
if params.get("append", False):
# Open also for reading ("+"), because TIFF save_all
# writer needs to go back and edit the written data.
fp = builtins.open(filename, "r+b")
else:
fp = builtins.open(filename, "w+b")
try:
save_handler(self, fp, filename)
finally:
# do what we can to clean up
if open_fp:
fp.close()
def seek(self, frame):
"""
Seeks to the given frame in this sequence file. If you seek
beyond the end of the sequence, the method raises an
``EOFError`` exception. When a sequence file is opened, the
library automatically seeks to frame 0.
See :py:meth:`~PIL.Image.Image.tell`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:param frame: Frame number, starting at 0.
:exception EOFError: If the call attempts to seek beyond the end
of the sequence.
"""
# overridden by file handlers
if frame != 0:
raise EOFError
def show(self, title=None):
"""
Displays this image. This method is mainly intended for debugging purposes.
This method calls :py:func:`PIL.ImageShow.show` internally. You can use
:py:func:`PIL.ImageShow.register` to override its default behaviour.
The image is first saved to a temporary file. By default, it will be in
PNG format.
On Unix, the image is then opened using the **display**, **eog** or
**xv** utility, depending on which one can be found.
On macOS, the image is opened with the native Preview application.
On Windows, the image is opened with the standard PNG display utility.
:param title: Optional title to use for the image window, where possible.
"""
_show(self, title=title)
def split(self):
"""
Split this image into individual bands. This method returns a
tuple of individual image bands from an image. For example,
splitting an "RGB" image creates three new images each
containing a copy of one of the original bands (red, green,
blue).
If you need only one band, :py:meth:`~PIL.Image.Image.getchannel`
method can be more convenient and faster.
:returns: A tuple containing bands.
"""
self.load()
if self.im.bands == 1:
ims = [self.copy()]
else:
ims = map(self._new, self.im.split())
return tuple(ims)
def getchannel(self, channel):
"""
Returns an image containing a single channel of the source image.
:param channel: What channel to return. Could be index
(0 for "R" channel of "RGB") or channel name
("A" for alpha channel of "RGBA").
:returns: An image in "L" mode.
.. versionadded:: 4.3.0
"""
self.load()
if isinstance(channel, str):
try:
channel = self.getbands().index(channel)
except ValueError as e:
raise ValueError(f'The image has no channel "{channel}"') from e
return self._new(self.im.getband(channel))
def tell(self):
"""
Returns the current frame number. See :py:meth:`~PIL.Image.Image.seek`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:returns: Frame number, starting with 0.
"""
return 0
def thumbnail(self, size, resample=BICUBIC, reducing_gap=2.0):
"""
Make this image into a thumbnail. This method modifies the
image to contain a thumbnail version of itself, no larger than
the given size. This method calculates an appropriate thumbnail
size to preserve the aspect of the image, calls the
:py:meth:`~PIL.Image.Image.draft` method to configure the file reader
(where applicable), and finally resizes the image.
Note that this function modifies the :py:class:`~PIL.Image.Image`
object in place. If you need to use the full resolution image as well,
apply this method to a :py:meth:`~PIL.Image.Image.copy` of the original
image.
:param size: Requested size.
:param resample: Optional resampling filter. This can be one
of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If omitted, it defaults to :py:data:`PIL.Image.BICUBIC`.
(was :py:data:`PIL.Image.NEAREST` prior to version 2.5.0).
See: :ref:`concept-filters`.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce` or
:py:meth:`~PIL.Image.Image.draft` for JPEG images.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is 2.0 (very close to fair resampling
while still being faster in many cases).
:returns: None
"""
x, y = map(math.floor, size)
if x >= self.width and y >= self.height:
return
def round_aspect(number, key):
return max(min(math.floor(number), math.ceil(number), key=key), 1)
# preserve aspect ratio
aspect = self.width / self.height
if x / y >= aspect:
x = round_aspect(y * aspect, key=lambda n: abs(aspect - n / y))
else:
y = round_aspect(
x / aspect, key=lambda n: 0 if n == 0 else abs(aspect - x / n)
)
size = (x, y)
box = None
if reducing_gap is not None:
res = self.draft(None, (size[0] * reducing_gap, size[1] * reducing_gap))
if res is not None:
box = res[1]
if self.size != size:
im = self.resize(size, resample, box=box, reducing_gap=reducing_gap)
self.im = im.im
self._size = size
self.mode = self.im.mode
self.readonly = 0
self.pyaccess = None
# FIXME: the different transform methods need further explanation
# instead of bloating the method docs, add a separate chapter.
def transform(
self, size, method, data=None, resample=NEAREST, fill=1, fillcolor=None
):
"""
Transforms this image. This method creates a new image with the
given size, and the same mode as the original, and copies data
to the new image using the given transform.
:param size: The output size.
:param method: The transformation method. This is one of
:py:data:`PIL.Image.EXTENT` (cut out a rectangular subregion),
:py:data:`PIL.Image.AFFINE` (affine transform),
:py:data:`PIL.Image.PERSPECTIVE` (perspective transform),
:py:data:`PIL.Image.QUAD` (map a quadrilateral to a rectangle), or
:py:data:`PIL.Image.MESH` (map a number of source quadrilaterals
in one operation).
It may also be an :py:class:`~PIL.Image.ImageTransformHandler`
object::
class Example(Image.ImageTransformHandler):
def transform(self, size, data, resample, fill=1):
# Return result
It may also be an object with a ``method.getdata`` method
that returns a tuple supplying new ``method`` and ``data`` values::
class Example:
def getdata(self):
method = Image.EXTENT
data = (0, 0, 100, 100)
return method, data
:param data: Extra data to the transformation method.
:param resample: Optional resampling filter. It can be one of
:py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC` (cubic spline
interpolation in a 4x4 environment). If omitted, or if the image
has mode "1" or "P", it is set to :py:data:`PIL.Image.NEAREST`.
See: :ref:`concept-filters`.
:param fill: If ``method`` is an
:py:class:`~PIL.Image.ImageTransformHandler` object, this is one of
the arguments passed to it. Otherwise, it is unused.
:param fillcolor: Optional fill color for the area outside the
transform in the output image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if self.mode in ("LA", "RGBA") and resample != NEAREST:
return (
self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
.transform(size, method, data, resample, fill, fillcolor)
.convert(self.mode)
)
if isinstance(method, ImageTransformHandler):
return method.transform(size, self, resample=resample, fill=fill)
if hasattr(method, "getdata"):
# compatibility w. old-style transform objects
method, data = method.getdata()
if data is None:
raise ValueError("missing method data")
im = new(self.mode, size, fillcolor)
if self.mode == "P" and self.palette:
im.palette = self.palette.copy()
im.info = self.info.copy()
if method == MESH:
# list of quads
for box, quad in data:
im.__transformer(box, self, QUAD, quad, resample, fillcolor is None)
else:
im.__transformer(
(0, 0) + size, self, method, data, resample, fillcolor is None
)
return im
def __transformer(self, box, image, method, data, resample=NEAREST, fill=1):
w = box[2] - box[0]
h = box[3] - box[1]
if method == AFFINE:
data = data[0:6]
elif method == EXTENT:
# convert extent to an affine transform
x0, y0, x1, y1 = data
xs = (x1 - x0) / w
ys = (y1 - y0) / h
method = AFFINE
data = (xs, 0, x0, 0, ys, y0)
elif method == PERSPECTIVE:
data = data[0:8]
elif method == QUAD:
# quadrilateral warp. data specifies the four corners
# given as NW, SW, SE, and NE.
nw = data[0:2]
sw = data[2:4]
se = data[4:6]
ne = data[6:8]
x0, y0 = nw
As = 1.0 / w
At = 1.0 / h
data = (
x0,
(ne[0] - x0) * As,
(sw[0] - x0) * At,
(se[0] - sw[0] - ne[0] + x0) * As * At,
y0,
(ne[1] - y0) * As,
(sw[1] - y0) * At,
(se[1] - sw[1] - ne[1] + y0) * As * At,
)
else:
raise ValueError("unknown transformation method")
if resample not in (NEAREST, BILINEAR, BICUBIC):
if resample in (BOX, HAMMING, LANCZOS):
message = {
BOX: "Image.BOX",
HAMMING: "Image.HAMMING",
LANCZOS: "Image.LANCZOS/Image.ANTIALIAS",
}[resample] + f" ({resample}) cannot be used."
else:
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
image.load()
self.load()
if image.mode in ("1", "P"):
resample = NEAREST
self.im.transform2(box, image.im, method, data, resample, fill)
def transpose(self, method):
"""
Transpose image (flip or rotate in 90 degree steps)
:param method: One of :py:data:`PIL.Image.FLIP_LEFT_RIGHT`,
:py:data:`PIL.Image.FLIP_TOP_BOTTOM`, :py:data:`PIL.Image.ROTATE_90`,
:py:data:`PIL.Image.ROTATE_180`, :py:data:`PIL.Image.ROTATE_270`,
:py:data:`PIL.Image.TRANSPOSE` or :py:data:`PIL.Image.TRANSVERSE`.
:returns: Returns a flipped or rotated copy of this image.
"""
self.load()
return self._new(self.im.transpose(method))
def effect_spread(self, distance):
"""
Randomly spread pixels in an image.
:param distance: Distance to spread pixels.
"""
self.load()
return self._new(self.im.effect_spread(distance))
def toqimage(self):
"""Returns a QImage copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqimage(self)
def toqpixmap(self):
"""Returns a QPixmap copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqpixmap(self)
The provided code snippet includes necessary dependencies for implementing the `radial_gradient` function. Write a Python function `def radial_gradient(mode)` to solve the following problem:
Generate 256x256 radial gradient from black to white, centre to edge. :param mode: Input mode.
Here is the function:
def radial_gradient(mode):
"""
Generate 256x256 radial gradient from black to white, centre to edge.
:param mode: Input mode.
"""
return Image()._new(core.radial_gradient(mode)) | Generate 256x256 radial gradient from black to white, centre to edge. :param mode: Input mode. |
167,780 | import atexit
import builtins
import io
import logging
import math
import numbers
import os
import re
import struct
import sys
import tempfile
import warnings
from collections.abc import Callable, MutableMapping
from pathlib import Path
from . import ImageMode, TiffTags, UnidentifiedImageError, __version__, _plugins
from ._binary import i32le
from ._util import deferred_error, isPath
def _apply_env_variables(env=None):
if env is None:
env = os.environ
for var_name, setter in [
("PILLOW_ALIGNMENT", core.set_alignment),
("PILLOW_BLOCK_SIZE", core.set_block_size),
("PILLOW_BLOCKS_MAX", core.set_blocks_max),
]:
if var_name not in env:
continue
var = env[var_name].lower()
units = 1
for postfix, mul in [("k", 1024), ("m", 1024 * 1024)]:
if var.endswith(postfix):
units = mul
var = var[: -len(postfix)]
try:
var = int(var) * units
except ValueError:
warnings.warn(f"{var_name} is not int")
continue
try:
setter(var)
except ValueError as e:
warnings.warn(f"{var_name}: {e}") | null |
167,781 | import olefile
from . import Image, ImageFile
from ._binary import i32le as i32
def _accept(prefix):
return prefix[:8] == olefile.MAGIC | null |
167,782 | import collections
import os
import sys
import warnings
import PIL
from . import Image
def get_supported_modules():
"""
:returns: A list of all supported modules.
"""
return [f for f in modules if check_module(f)]
def get_supported_codecs():
"""
:returns: A list of all supported codecs.
"""
return [f for f in codecs if check_codec(f)]
def get_supported_features():
"""
:returns: A list of all supported features.
"""
return [f for f in features if check_feature(f)]
The provided code snippet includes necessary dependencies for implementing the `get_supported` function. Write a Python function `def get_supported()` to solve the following problem:
:returns: A list of all supported modules, features, and codecs.
Here is the function:
def get_supported():
"""
:returns: A list of all supported modules, features, and codecs.
"""
ret = get_supported_modules()
ret.extend(get_supported_features())
ret.extend(get_supported_codecs())
return ret | :returns: A list of all supported modules, features, and codecs. |
167,783 | import collections
import os
import sys
import warnings
import PIL
from . import Image
features = {
"webp_anim": ("PIL._webp", "HAVE_WEBPANIM", None),
"webp_mux": ("PIL._webp", "HAVE_WEBPMUX", None),
"transp_webp": ("PIL._webp", "HAVE_TRANSPARENCY", None),
"raqm": ("PIL._imagingft", "HAVE_RAQM", "raqm_version"),
"fribidi": ("PIL._imagingft", "HAVE_FRIBIDI", "fribidi_version"),
"harfbuzz": ("PIL._imagingft", "HAVE_HARFBUZZ", "harfbuzz_version"),
"libjpeg_turbo": ("PIL._imaging", "HAVE_LIBJPEGTURBO", "libjpeg_turbo_version"),
"libimagequant": ("PIL._imaging", "HAVE_LIBIMAGEQUANT", "imagequant_version"),
"xcb": ("PIL._imaging", "HAVE_XCB", None),
}
def check_feature(feature):
"""
Checks if a feature is available.
:param feature: The feature to check for.
:returns: ``True`` if available, ``False`` if unavailable, ``None`` if unknown.
:raises ValueError: If the feature is not defined in this version of Pillow.
"""
if feature not in features:
raise ValueError(f"Unknown feature {feature}")
module, flag, ver = features[feature]
try:
imported_module = __import__(module, fromlist=["PIL"])
return getattr(imported_module, flag)
except ImportError:
return None
def version_feature(feature):
"""
:param feature: The feature to check for.
:returns: The version number as a string, or ``None`` if not available.
:raises ValueError: If the feature is not defined in this version of Pillow.
"""
if not check_feature(feature):
return None
module, flag, ver = features[feature]
if ver is None:
return None
return getattr(__import__(module, fromlist=[ver]), ver)
def check(feature):
"""
:param feature: A module, codec, or feature name.
:returns:
``True`` if the module, codec, or feature is available,
``False`` or ``None`` otherwise.
"""
if feature in modules:
return check_module(feature)
if feature in codecs:
return check_codec(feature)
if feature in features:
return check_feature(feature)
warnings.warn(f"Unknown feature '{feature}'.", stacklevel=2)
return False
def version(feature):
"""
:param feature:
The module, codec, or feature to check for.
:returns:
The version number as a string, or ``None`` if unknown or not available.
"""
if feature in modules:
return version_module(feature)
if feature in codecs:
return version_codec(feature)
if feature in features:
return version_feature(feature)
return None
class Image:
"""
This class represents an image object. To create
:py:class:`~PIL.Image.Image` objects, use the appropriate factory
functions. There's hardly ever any reason to call the Image constructor
directly.
* :py:func:`~PIL.Image.open`
* :py:func:`~PIL.Image.new`
* :py:func:`~PIL.Image.frombytes`
"""
format = None
format_description = None
_close_exclusive_fp_after_loading = True
def __init__(self):
# FIXME: take "new" parameters / other image?
# FIXME: turn mode and size into delegating properties?
self.im = None
self.mode = ""
self._size = (0, 0)
self.palette = None
self.info = {}
self._category = 0
self.readonly = 0
self.pyaccess = None
self._exif = None
def __getattr__(self, name):
if name == "category":
warnings.warn(
"Image categories are deprecated and will be removed in Pillow 10 "
"(2023-07-01). Use is_animated instead.",
DeprecationWarning,
stacklevel=2,
)
return self._category
raise AttributeError(name)
def width(self):
return self.size[0]
def height(self):
return self.size[1]
def size(self):
return self._size
def _new(self, im):
new = Image()
new.im = im
new.mode = im.mode
new._size = im.size
if im.mode in ("P", "PA"):
if self.palette:
new.palette = self.palette.copy()
else:
from . import ImagePalette
new.palette = ImagePalette.ImagePalette()
new.info = self.info.copy()
return new
# Context manager support
def __enter__(self):
return self
def __exit__(self, *args):
if hasattr(self, "fp") and getattr(self, "_exclusive_fp", False):
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
def close(self):
"""
Closes the file pointer, if possible.
This operation will destroy the image core and release its memory.
The image data will be unusable afterward.
This function is required to close images that have multiple frames or
have not had their file read and closed by the
:py:meth:`~PIL.Image.Image.load` method. See :ref:`file-handling` for
more information.
"""
try:
if hasattr(self, "_close__fp"):
self._close__fp()
if self.fp:
self.fp.close()
self.fp = None
except Exception as msg:
logger.debug("Error closing: %s", msg)
if getattr(self, "map", None):
self.map = None
# Instead of simply setting to None, we're setting up a
# deferred error that will better explain that the core image
# object is gone.
self.im = deferred_error(ValueError("Operation on closed image"))
def _copy(self):
self.load()
self.im = self.im.copy()
self.pyaccess = None
self.readonly = 0
def _ensure_mutable(self):
if self.readonly:
self._copy()
else:
self.load()
def _dump(self, file=None, format=None, **options):
suffix = ""
if format:
suffix = "." + format
if not file:
f, filename = tempfile.mkstemp(suffix)
os.close(f)
else:
filename = file
if not filename.endswith(suffix):
filename = filename + suffix
self.load()
if not format or format == "PPM":
self.im.save_ppm(filename)
else:
self.save(filename, format, **options)
return filename
def __eq__(self, other):
return (
self.__class__ is other.__class__
and self.mode == other.mode
and self.size == other.size
and self.info == other.info
and self._category == other._category
and self.readonly == other.readonly
and self.getpalette() == other.getpalette()
and self.tobytes() == other.tobytes()
)
def __repr__(self):
return "<%s.%s image mode=%s size=%dx%d at 0x%X>" % (
self.__class__.__module__,
self.__class__.__name__,
self.mode,
self.size[0],
self.size[1],
id(self),
)
def _repr_png_(self):
"""iPython display hook support
:returns: png version of the image as bytes
"""
b = io.BytesIO()
try:
self.save(b, "PNG")
except Exception as e:
raise ValueError("Could not save to PNG for display") from e
return b.getvalue()
class _ArrayData:
def __init__(self, new):
self.__array_interface__ = new
def __array__(self, dtype=None):
# numpy array interface support
import numpy as np
new = {}
shape, typestr = _conv_type_shape(self)
new["shape"] = shape
new["typestr"] = typestr
new["version"] = 3
if self.mode == "1":
# Binary images need to be extended from bits to bytes
# See: https://github.com/python-pillow/Pillow/issues/350
new["data"] = self.tobytes("raw", "L")
else:
new["data"] = self.tobytes()
return np.array(self._ArrayData(new), dtype)
def __getstate__(self):
return [self.info, self.mode, self.size, self.getpalette(), self.tobytes()]
def __setstate__(self, state):
Image.__init__(self)
self.tile = []
info, mode, size, palette, data = state
self.info = info
self.mode = mode
self._size = size
self.im = core.new(mode, size)
if mode in ("L", "LA", "P", "PA") and palette:
self.putpalette(palette)
self.frombytes(data)
def tobytes(self, encoder_name="raw", *args):
"""
Return image as a bytes object.
.. warning::
This method returns the raw image data from the internal
storage. For compressed image data (e.g. PNG, JPEG) use
:meth:`~.save`, with a BytesIO parameter for in-memory
data.
:param encoder_name: What encoder to use. The default is to
use the standard "raw" encoder.
:param args: Extra arguments to the encoder.
:returns: A :py:class:`bytes` object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
if encoder_name == "raw" and args == ():
args = self.mode
self.load()
# unpack data
e = _getencoder(self.mode, encoder_name, args)
e.setimage(self.im)
bufsize = max(65536, self.size[0] * 4) # see RawEncode.c
data = []
while True:
l, s, d = e.encode(bufsize)
data.append(d)
if s:
break
if s < 0:
raise RuntimeError(f"encoder error {s} in tobytes")
return b"".join(data)
def tobitmap(self, name="image"):
"""
Returns the image converted to an X11 bitmap.
.. note:: This method only works for mode "1" images.
:param name: The name prefix to use for the bitmap variables.
:returns: A string containing an X11 bitmap.
:raises ValueError: If the mode is not "1"
"""
self.load()
if self.mode != "1":
raise ValueError("not a bitmap")
data = self.tobytes("xbm")
return b"".join(
[
f"#define {name}_width {self.size[0]}\n".encode("ascii"),
f"#define {name}_height {self.size[1]}\n".encode("ascii"),
f"static char {name}_bits[] = {{\n".encode("ascii"),
data,
b"};",
]
)
def frombytes(self, data, decoder_name="raw", *args):
"""
Loads this image with pixel data from a bytes object.
This method is similar to the :py:func:`~PIL.Image.frombytes` function,
but loads data into this image instead of creating a new image object.
"""
# may pass tuple instead of argument list
if len(args) == 1 and isinstance(args[0], tuple):
args = args[0]
# default format
if decoder_name == "raw" and args == ():
args = self.mode
# unpack data
d = _getdecoder(self.mode, decoder_name, args)
d.setimage(self.im)
s = d.decode(data)
if s[0] >= 0:
raise ValueError("not enough image data")
if s[1] != 0:
raise ValueError("cannot decode image data")
def load(self):
"""
Allocates storage for the image and loads the pixel data. In
normal cases, you don't need to call this method, since the
Image class automatically loads an opened image when it is
accessed for the first time.
If the file associated with the image was opened by Pillow, then this
method will close it. The exception to this is if the image has
multiple frames, in which case the file will be left open for seek
operations. See :ref:`file-handling` for more information.
:returns: An image access object.
:rtype: :ref:`PixelAccess` or :py:class:`PIL.PyAccess`
"""
if self.im and self.palette and self.palette.dirty:
# realize palette
mode, arr = self.palette.getdata()
if mode == "RGBA":
mode = "RGB"
self.info["transparency"] = arr[3::4]
arr = bytes(
value for (index, value) in enumerate(arr) if index % 4 != 3
)
palette_length = self.im.putpalette(mode, arr)
self.palette.dirty = 0
self.palette.rawmode = None
if "transparency" in self.info and mode in ("LA", "PA"):
if isinstance(self.info["transparency"], int):
self.im.putpalettealpha(self.info["transparency"], 0)
else:
self.im.putpalettealphas(self.info["transparency"])
self.palette.mode = "RGBA"
else:
self.palette.mode = "RGB"
self.palette.palette = self.im.getpalette()[: palette_length * 3]
if self.im:
if cffi and USE_CFFI_ACCESS:
if self.pyaccess:
return self.pyaccess
from . import PyAccess
self.pyaccess = PyAccess.new(self, self.readonly)
if self.pyaccess:
return self.pyaccess
return self.im.pixel_access(self.readonly)
def verify(self):
"""
Verifies the contents of a file. For data read from a file, this
method attempts to determine if the file is broken, without
actually decoding the image data. If this method finds any
problems, it raises suitable exceptions. If you need to load
the image after using this method, you must reopen the image
file.
"""
pass
def convert(self, mode=None, matrix=None, dither=None, palette=WEB, colors=256):
"""
Returns a converted copy of this image. For the "P" mode, this
method translates pixels through the palette. If mode is
omitted, a mode is chosen so that all information in the image
and the palette can be represented without a palette.
The current version supports all possible conversions between
"L", "RGB" and "CMYK." The ``matrix`` argument only supports "L"
and "RGB".
When translating a color image to greyscale (mode "L"),
the library uses the ITU-R 601-2 luma transform::
L = R * 299/1000 + G * 587/1000 + B * 114/1000
The default method of converting a greyscale ("L") or "RGB"
image into a bilevel (mode "1") image uses Floyd-Steinberg
dither to approximate the original image luminosity levels. If
dither is :data:`NONE`, all values larger than 127 are set to 255 (white),
all other values to 0 (black). To use other thresholds, use the
:py:meth:`~PIL.Image.Image.point` method.
When converting from "RGBA" to "P" without a ``matrix`` argument,
this passes the operation to :py:meth:`~PIL.Image.Image.quantize`,
and ``dither`` and ``palette`` are ignored.
:param mode: The requested mode. See: :ref:`concept-modes`.
:param matrix: An optional conversion matrix. If given, this
should be 4- or 12-tuple containing floating point values.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Note that this is not used when ``matrix`` is supplied.
:param palette: Palette to use when converting from mode "RGB"
to "P". Available palettes are :data:`WEB` or :data:`ADAPTIVE`.
:param colors: Number of colors to use for the :data:`ADAPTIVE` palette.
Defaults to 256.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
has_transparency = self.info.get("transparency") is not None
if not mode and self.mode == "P":
# determine default mode
if self.palette:
mode = self.palette.mode
else:
mode = "RGB"
if mode == "RGB" and has_transparency:
mode = "RGBA"
if not mode or (mode == self.mode and not matrix):
return self.copy()
if matrix:
# matrix conversion
if mode not in ("L", "RGB"):
raise ValueError("illegal conversion")
im = self.im.convert_matrix(mode, matrix)
new = self._new(im)
if has_transparency and self.im.bands == 3:
transparency = new.info["transparency"]
def convert_transparency(m, v):
v = m[0] * v[0] + m[1] * v[1] + m[2] * v[2] + m[3] * 0.5
return max(0, min(255, int(v)))
if mode == "L":
transparency = convert_transparency(matrix, transparency)
elif len(mode) == 3:
transparency = tuple(
convert_transparency(matrix[i * 4 : i * 4 + 4], transparency)
for i in range(0, len(transparency))
)
new.info["transparency"] = transparency
return new
if mode == "P" and self.mode == "RGBA":
return self.quantize(colors)
trns = None
delete_trns = False
# transparency handling
if has_transparency:
if self.mode in ("1", "L", "I", "RGB") and mode == "RGBA":
# Use transparent conversion to promote from transparent
# color to an alpha channel.
new_im = self._new(
self.im.convert_transparent(mode, self.info["transparency"])
)
del new_im.info["transparency"]
return new_im
elif self.mode in ("L", "RGB", "P") and mode in ("L", "RGB", "P"):
t = self.info["transparency"]
if isinstance(t, bytes):
# Dragons. This can't be represented by a single color
warnings.warn(
"Palette images with Transparency expressed in bytes should be "
"converted to RGBA images"
)
delete_trns = True
else:
# get the new transparency color.
# use existing conversions
trns_im = Image()._new(core.new(self.mode, (1, 1)))
if self.mode == "P":
trns_im.putpalette(self.palette)
if isinstance(t, tuple):
err = "Couldn't allocate a palette color for transparency"
try:
t = trns_im.palette.getcolor(t, self)
except ValueError as e:
if str(e) == "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
t = None
else:
raise ValueError(err) from e
if t is None:
trns = None
else:
trns_im.putpixel((0, 0), t)
if mode in ("L", "RGB"):
trns_im = trns_im.convert(mode)
else:
# can't just retrieve the palette number, got to do it
# after quantization.
trns_im = trns_im.convert("RGB")
trns = trns_im.getpixel((0, 0))
elif self.mode == "P" and mode in ("LA", "PA", "RGBA"):
t = self.info["transparency"]
delete_trns = True
if isinstance(t, bytes):
self.im.putpalettealphas(t)
elif isinstance(t, int):
self.im.putpalettealpha(t, 0)
else:
raise ValueError("Transparency for P mode should be bytes or int")
if mode == "P" and palette == ADAPTIVE:
im = self.im.quantize(colors)
new = self._new(im)
from . import ImagePalette
new.palette = ImagePalette.ImagePalette("RGB", new.im.getpalette("RGB"))
if delete_trns:
# This could possibly happen if we requantize to fewer colors.
# The transparency would be totally off in that case.
del new.info["transparency"]
if trns is not None:
try:
new.info["transparency"] = new.palette.getcolor(trns, new)
except Exception:
# if we can't make a transparent color, don't leave the old
# transparency hanging around to mess us up.
del new.info["transparency"]
warnings.warn("Couldn't allocate palette entry for transparency")
return new
# colorspace conversion
if dither is None:
dither = FLOYDSTEINBERG
try:
im = self.im.convert(mode, dither)
except ValueError:
try:
# normalize source image and try again
im = self.im.convert(getmodebase(self.mode))
im = im.convert(mode, dither)
except KeyError as e:
raise ValueError("illegal conversion") from e
new_im = self._new(im)
if mode == "P" and palette != ADAPTIVE:
from . import ImagePalette
new_im.palette = ImagePalette.ImagePalette("RGB", list(range(256)) * 3)
if delete_trns:
# crash fail if we leave a bytes transparency in an rgb/l mode.
del new_im.info["transparency"]
if trns is not None:
if new_im.mode == "P":
try:
new_im.info["transparency"] = new_im.palette.getcolor(trns, new_im)
except ValueError as e:
del new_im.info["transparency"]
if str(e) != "cannot allocate more than 256 colors":
# If all 256 colors are in use,
# then there is no need for transparency
warnings.warn(
"Couldn't allocate palette entry for transparency"
)
else:
new_im.info["transparency"] = trns
return new_im
def quantize(self, colors=256, method=None, kmeans=0, palette=None, dither=1):
"""
Convert the image to 'P' mode with the specified number
of colors.
:param colors: The desired number of colors, <= 256
:param method: :data:`MEDIANCUT` (median cut),
:data:`MAXCOVERAGE` (maximum coverage),
:data:`FASTOCTREE` (fast octree),
:data:`LIBIMAGEQUANT` (libimagequant; check support using
:py:func:`PIL.features.check_feature`
with ``feature="libimagequant"``).
By default, :data:`MEDIANCUT` will be used.
The exception to this is RGBA images. :data:`MEDIANCUT` and
:data:`MAXCOVERAGE` do not support RGBA images, so
:data:`FASTOCTREE` is used by default instead.
:param kmeans: Integer
:param palette: Quantize to the palette of given
:py:class:`PIL.Image.Image`.
:param dither: Dithering method, used when converting from
mode "RGB" to "P" or from "RGB" or "L" to "1".
Available methods are :data:`NONE` or :data:`FLOYDSTEINBERG` (default).
Default: 1 (legacy setting)
:returns: A new image
"""
self.load()
if method is None:
# defaults:
method = MEDIANCUT
if self.mode == "RGBA":
method = FASTOCTREE
if self.mode == "RGBA" and method not in (FASTOCTREE, LIBIMAGEQUANT):
# Caller specified an invalid mode.
raise ValueError(
"Fast Octree (method == 2) and libimagequant (method == 3) "
"are the only valid methods for quantizing RGBA images"
)
if palette:
# use palette from reference image
palette.load()
if palette.mode != "P":
raise ValueError("bad mode for palette image")
if self.mode != "RGB" and self.mode != "L":
raise ValueError(
"only RGB or L mode images can be quantized to a palette"
)
im = self.im.convert("P", dither, palette.im)
new_im = self._new(im)
new_im.palette = palette.palette.copy()
return new_im
im = self._new(self.im.quantize(colors, method, kmeans))
from . import ImagePalette
mode = im.im.getpalettemode()
palette = im.im.getpalette(mode, mode)[: colors * len(mode)]
im.palette = ImagePalette.ImagePalette(mode, palette)
return im
def copy(self):
"""
Copies this image. Use this method if you wish to paste things
into an image, but still retain the original.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
return self._new(self.im.copy())
__copy__ = copy
def crop(self, box=None):
"""
Returns a rectangular region from this image. The box is a
4-tuple defining the left, upper, right, and lower pixel
coordinate. See :ref:`coordinate-system`.
Note: Prior to Pillow 3.4.0, this was a lazy operation.
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:rtype: :py:class:`~PIL.Image.Image`
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if box is None:
return self.copy()
self.load()
return self._new(self._crop(self.im, box))
def _crop(self, im, box):
"""
Returns a rectangular region from the core image object im.
This is equivalent to calling im.crop((x0, y0, x1, y1)), but
includes additional sanity checks.
:param im: a core image object
:param box: The crop rectangle, as a (left, upper, right, lower)-tuple.
:returns: A core image object.
"""
x0, y0, x1, y1 = map(int, map(round, box))
absolute_values = (abs(x1 - x0), abs(y1 - y0))
_decompression_bomb_check(absolute_values)
return im.crop((x0, y0, x1, y1))
def draft(self, mode, size):
"""
Configures the image file loader so it returns a version of the
image that as closely as possible matches the given mode and
size. For example, you can use this method to convert a color
JPEG to greyscale while loading it.
If any changes are made, returns a tuple with the chosen ``mode`` and
``box`` with coordinates of the original image within the altered one.
Note that this method modifies the :py:class:`~PIL.Image.Image` object
in place. If the image has already been loaded, this method has no
effect.
Note: This method is not implemented for most images. It is
currently implemented only for JPEG and MPO images.
:param mode: The requested mode.
:param size: The requested size.
"""
pass
def _expand(self, xmargin, ymargin=None):
if ymargin is None:
ymargin = xmargin
self.load()
return self._new(self.im.expand(xmargin, ymargin, 0))
def filter(self, filter):
"""
Filters this image using the given filter. For a list of
available filters, see the :py:mod:`~PIL.ImageFilter` module.
:param filter: Filter kernel.
:returns: An :py:class:`~PIL.Image.Image` object."""
from . import ImageFilter
self.load()
if isinstance(filter, Callable):
filter = filter()
if not hasattr(filter, "filter"):
raise TypeError(
"filter argument should be ImageFilter.Filter instance or class"
)
multiband = isinstance(filter, ImageFilter.MultibandFilter)
if self.im.bands == 1 or multiband:
return self._new(filter.filter(self.im))
ims = []
for c in range(self.im.bands):
ims.append(self._new(filter.filter(self.im.getband(c))))
return merge(self.mode, ims)
def getbands(self):
"""
Returns a tuple containing the name of each band in this image.
For example, ``getbands`` on an RGB image returns ("R", "G", "B").
:returns: A tuple containing band names.
:rtype: tuple
"""
return ImageMode.getmode(self.mode).bands
def getbbox(self):
"""
Calculates the bounding box of the non-zero regions in the
image.
:returns: The bounding box is returned as a 4-tuple defining the
left, upper, right, and lower pixel coordinate. See
:ref:`coordinate-system`. If the image is completely empty, this
method returns None.
"""
self.load()
return self.im.getbbox()
def getcolors(self, maxcolors=256):
"""
Returns a list of colors used in this image.
The colors will be in the image's mode. For example, an RGB image will
return a tuple of (red, green, blue) color values, and a P image will
return the index of the color in the palette.
:param maxcolors: Maximum number of colors. If this number is
exceeded, this method returns None. The default limit is
256 colors.
:returns: An unsorted list of (count, pixel) values.
"""
self.load()
if self.mode in ("1", "L", "P"):
h = self.im.histogram()
out = []
for i in range(256):
if h[i]:
out.append((h[i], i))
if len(out) > maxcolors:
return None
return out
return self.im.getcolors(maxcolors)
def getdata(self, band=None):
"""
Returns the contents of this image as a sequence object
containing pixel values. The sequence object is flattened, so
that values for line one follow directly after the values of
line zero, and so on.
Note that the sequence object returned by this method is an
internal PIL data type, which only supports certain sequence
operations. To convert it to an ordinary sequence (e.g. for
printing), use ``list(im.getdata())``.
:param band: What band to return. The default is to return
all bands. To return a single band, pass in the index
value (e.g. 0 to get the "R" band from an "RGB" image).
:returns: A sequence-like object.
"""
self.load()
if band is not None:
return self.im.getband(band)
return self.im # could be abused
def getextrema(self):
"""
Gets the the minimum and maximum pixel values for each band in
the image.
:returns: For a single-band image, a 2-tuple containing the
minimum and maximum pixel value. For a multi-band image,
a tuple containing one 2-tuple for each band.
"""
self.load()
if self.im.bands > 1:
extrema = []
for i in range(self.im.bands):
extrema.append(self.im.getband(i).getextrema())
return tuple(extrema)
return self.im.getextrema()
def _getxmp(self, xmp_tags):
def get_name(tag):
return tag.split("}")[1]
def get_value(element):
value = {get_name(k): v for k, v in element.attrib.items()}
children = list(element)
if children:
for child in children:
name = get_name(child.tag)
child_value = get_value(child)
if name in value:
if not isinstance(value[name], list):
value[name] = [value[name]]
value[name].append(child_value)
else:
value[name] = child_value
elif value:
if element.text:
value["text"] = element.text
else:
return element.text
return value
if ElementTree is None:
warnings.warn("XMP data cannot be read without defusedxml dependency")
return {}
else:
root = ElementTree.fromstring(xmp_tags)
return {get_name(root.tag): get_value(root)}
def getexif(self):
if self._exif is None:
self._exif = Exif()
exif_info = self.info.get("exif")
if exif_info is None:
if "Raw profile type exif" in self.info:
exif_info = bytes.fromhex(
"".join(self.info["Raw profile type exif"].split("\n")[3:])
)
elif hasattr(self, "tag_v2"):
self._exif.endian = self.tag_v2._endian
self._exif.load_from_fp(self.fp, self.tag_v2._offset)
if exif_info is not None:
self._exif.load(exif_info)
# XMP tags
if 0x0112 not in self._exif:
xmp_tags = self.info.get("XML:com.adobe.xmp")
if xmp_tags:
match = re.search(r'tiff:Orientation="([0-9])"', xmp_tags)
if match:
self._exif[0x0112] = int(match[1])
return self._exif
def getim(self):
"""
Returns a capsule that points to the internal image memory.
:returns: A capsule object.
"""
self.load()
return self.im.ptr
def getpalette(self):
"""
Returns the image palette as a list.
:returns: A list of color values [r, g, b, ...], or None if the
image has no palette.
"""
self.load()
try:
return list(self.im.getpalette())
except ValueError:
return None # no palette
def getpixel(self, xy):
"""
Returns the pixel value at a given position.
:param xy: The coordinate, given as (x, y). See
:ref:`coordinate-system`.
:returns: The pixel value. If the image is a multi-layer image,
this method returns a tuple.
"""
self.load()
if self.pyaccess:
return self.pyaccess.getpixel(xy)
return self.im.getpixel(xy)
def getprojection(self):
"""
Get projection to x and y axes
:returns: Two sequences, indicating where there are non-zero
pixels along the X-axis and the Y-axis, respectively.
"""
self.load()
x, y = self.im.getprojection()
return list(x), list(y)
def histogram(self, mask=None, extrema=None):
"""
Returns a histogram for the image. The histogram is returned as
a list of pixel counts, one for each pixel value in the source
image. If the image has more than one band, the histograms for
all bands are concatenated (for example, the histogram for an
"RGB" image contains 768 values).
A bilevel image (mode "1") is treated as a greyscale ("L") image
by this method.
If a mask is provided, the method returns a histogram for those
parts of the image where the mask image is non-zero. The mask
image must have the same size as the image, and be either a
bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A list containing pixel counts.
"""
self.load()
if mask:
mask.load()
return self.im.histogram((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.histogram(extrema)
return self.im.histogram()
def entropy(self, mask=None, extrema=None):
"""
Calculates and returns the entropy for the image.
A bilevel image (mode "1") is treated as a greyscale ("L")
image by this method.
If a mask is provided, the method employs the histogram for
those parts of the image where the mask image is non-zero.
The mask image must have the same size as the image, and be
either a bi-level image (mode "1") or a greyscale image ("L").
:param mask: An optional mask.
:param extrema: An optional tuple of manually-specified extrema.
:returns: A float value representing the image entropy
"""
self.load()
if mask:
mask.load()
return self.im.entropy((0, 0), mask.im)
if self.mode in ("I", "F"):
if extrema is None:
extrema = self.getextrema()
return self.im.entropy(extrema)
return self.im.entropy()
def paste(self, im, box=None, mask=None):
"""
Pastes another image into this image. The box argument is either
a 2-tuple giving the upper left corner, a 4-tuple defining the
left, upper, right, and lower pixel coordinate, or None (same as
(0, 0)). See :ref:`coordinate-system`. If a 4-tuple is given, the size
of the pasted image must match the size of the region.
If the modes don't match, the pasted image is converted to the mode of
this image (see the :py:meth:`~PIL.Image.Image.convert` method for
details).
Instead of an image, the source can be a integer or tuple
containing pixel values. The method then fills the region
with the given color. When creating RGB images, you can
also use color strings as supported by the ImageColor module.
If a mask is given, this method updates only the regions
indicated by the mask. You can use either "1", "L" or "RGBA"
images (in the latter case, the alpha band is used as mask).
Where the mask is 255, the given image is copied as is. Where
the mask is 0, the current value is preserved. Intermediate
values will mix the two images together, including their alpha
channels if they have them.
See :py:meth:`~PIL.Image.Image.alpha_composite` if you want to
combine images with respect to their alpha channels.
:param im: Source image or pixel value (integer or tuple).
:param box: An optional 4-tuple giving the region to paste into.
If a 2-tuple is used instead, it's treated as the upper left
corner. If omitted or None, the source is pasted into the
upper left corner.
If an image is given as the second argument and there is no
third, the box defaults to (0, 0), and the second argument
is interpreted as a mask image.
:param mask: An optional mask image.
"""
if isImageType(box) and mask is None:
# abbreviated paste(im, mask) syntax
mask = box
box = None
if box is None:
box = (0, 0)
if len(box) == 2:
# upper left corner given; get size from image or mask
if isImageType(im):
size = im.size
elif isImageType(mask):
size = mask.size
else:
# FIXME: use self.size here?
raise ValueError("cannot determine region size; use 4-item box")
box += (box[0] + size[0], box[1] + size[1])
if isinstance(im, str):
from . import ImageColor
im = ImageColor.getcolor(im, self.mode)
elif isImageType(im):
im.load()
if self.mode != im.mode:
if self.mode != "RGB" or im.mode not in ("RGBA", "RGBa"):
# should use an adapter for this!
im = im.convert(self.mode)
im = im.im
self._ensure_mutable()
if mask:
mask.load()
self.im.paste(im, box, mask.im)
else:
self.im.paste(im, box)
def alpha_composite(self, im, dest=(0, 0), source=(0, 0)):
"""'In-place' analog of Image.alpha_composite. Composites an image
onto this image.
:param im: image to composite over this one
:param dest: Optional 2 tuple (left, top) specifying the upper
left corner in this (destination) image.
:param source: Optional 2 (left, top) tuple for the upper left
corner in the overlay source image, or 4 tuple (left, top, right,
bottom) for the bounds of the source rectangle
Performance Note: Not currently implemented in-place in the core layer.
"""
if not isinstance(source, (list, tuple)):
raise ValueError("Source must be a tuple")
if not isinstance(dest, (list, tuple)):
raise ValueError("Destination must be a tuple")
if not len(source) in (2, 4):
raise ValueError("Source must be a 2 or 4-tuple")
if not len(dest) == 2:
raise ValueError("Destination must be a 2-tuple")
if min(source) < 0:
raise ValueError("Source must be non-negative")
if len(source) == 2:
source = source + im.size
# over image, crop if it's not the whole thing.
if source == (0, 0) + im.size:
overlay = im
else:
overlay = im.crop(source)
# target for the paste
box = dest + (dest[0] + overlay.width, dest[1] + overlay.height)
# destination image. don't copy if we're using the whole image.
if box == (0, 0) + self.size:
background = self
else:
background = self.crop(box)
result = alpha_composite(background, overlay)
self.paste(result, box)
def point(self, lut, mode=None):
"""
Maps this image through a lookup table or function.
:param lut: A lookup table, containing 256 (or 65536 if
self.mode=="I" and mode == "L") values per band in the
image. A function can be used instead, it should take a
single argument. The function is called once for each
possible pixel value, and the resulting table is applied to
all bands of the image.
It may also be an :py:class:`~PIL.Image.ImagePointHandler`
object::
class Example(Image.ImagePointHandler):
def point(self, data):
# Return result
:param mode: Output mode (default is same as input). In the
current version, this can only be used if the source image
has mode "L" or "P", and the output has mode "1" or the
source image mode is "I" and the output mode is "L".
:returns: An :py:class:`~PIL.Image.Image` object.
"""
self.load()
if isinstance(lut, ImagePointHandler):
return lut.point(self)
if callable(lut):
# if it isn't a list, it should be a function
if self.mode in ("I", "I;16", "F"):
# check if the function can be used with point_transform
# UNDONE wiredfool -- I think this prevents us from ever doing
# a gamma function point transform on > 8bit images.
scale, offset = _getscaleoffset(lut)
return self._new(self.im.point_transform(scale, offset))
# for other modes, convert the function to a table
lut = [lut(i) for i in range(256)] * self.im.bands
if self.mode == "F":
# FIXME: _imaging returns a confusing error message for this case
raise ValueError("point operation not supported for this mode")
return self._new(self.im.point(lut, mode))
def putalpha(self, alpha):
"""
Adds or replaces the alpha layer in this image. If the image
does not have an alpha layer, it's converted to "LA" or "RGBA".
The new layer must be either "L" or "1".
:param alpha: The new alpha layer. This can either be an "L" or "1"
image having the same size as this image, or an integer or
other color value.
"""
self._ensure_mutable()
if self.mode not in ("LA", "PA", "RGBA"):
# attempt to promote self to a matching alpha mode
try:
mode = getmodebase(self.mode) + "A"
try:
self.im.setmode(mode)
except (AttributeError, ValueError) as e:
# do things the hard way
im = self.im.convert(mode)
if im.mode not in ("LA", "PA", "RGBA"):
raise ValueError from e # sanity check
self.im = im
self.pyaccess = None
self.mode = self.im.mode
except KeyError as e:
raise ValueError("illegal image mode") from e
if self.mode in ("LA", "PA"):
band = 1
else:
band = 3
if isImageType(alpha):
# alpha layer
if alpha.mode not in ("1", "L"):
raise ValueError("illegal image mode")
alpha.load()
if alpha.mode == "1":
alpha = alpha.convert("L")
else:
# constant alpha
try:
self.im.fillband(band, alpha)
except (AttributeError, ValueError):
# do things the hard way
alpha = new("L", self.size, alpha)
else:
return
self.im.putband(alpha.im, band)
def putdata(self, data, scale=1.0, offset=0.0):
"""
Copies pixel data from a flattened sequence object into the image. The
values should start at the upper left corner (0, 0), continue to the
end of the line, followed directly by the first value of the second
line, and so on. Data will be read until either the image or the
sequence ends. The scale and offset values are used to adjust the
sequence values: **pixel = value*scale + offset**.
:param data: A flattened sequence object.
:param scale: An optional scale value. The default is 1.0.
:param offset: An optional offset value. The default is 0.0.
"""
self._ensure_mutable()
self.im.putdata(data, scale, offset)
def putpalette(self, data, rawmode="RGB"):
"""
Attaches a palette to this image. The image must be a "P", "PA", "L"
or "LA" image.
The palette sequence must contain at most 256 colors, made up of one
integer value for each channel in the raw mode.
For example, if the raw mode is "RGB", then it can contain at most 768
values, made up of red, green and blue values for the corresponding pixel
index in the 256 colors.
If the raw mode is "RGBA", then it can contain at most 1024 values,
containing red, green, blue and alpha values.
Alternatively, an 8-bit string may be used instead of an integer sequence.
:param data: A palette sequence (either a list or a string).
:param rawmode: The raw mode of the palette. Either "RGB", "RGBA", or a
mode that can be transformed to "RGB" (e.g. "R", "BGR;15", "RGBA;L").
"""
from . import ImagePalette
if self.mode not in ("L", "LA", "P", "PA"):
raise ValueError("illegal image mode")
if isinstance(data, ImagePalette.ImagePalette):
palette = ImagePalette.raw(data.rawmode, data.palette)
else:
if not isinstance(data, bytes):
data = bytes(data)
palette = ImagePalette.raw(rawmode, data)
self.mode = "PA" if "A" in self.mode else "P"
self.palette = palette
self.palette.mode = "RGB"
self.load() # install new palette
def putpixel(self, xy, value):
"""
Modifies the pixel at the given position. The color is given as
a single numerical value for single-band images, and a tuple for
multi-band images. In addition to this, RGB and RGBA tuples are
accepted for P images.
Note that this method is relatively slow. For more extensive changes,
use :py:meth:`~PIL.Image.Image.paste` or the :py:mod:`~PIL.ImageDraw`
module instead.
See:
* :py:meth:`~PIL.Image.Image.paste`
* :py:meth:`~PIL.Image.Image.putdata`
* :py:mod:`~PIL.ImageDraw`
:param xy: The pixel coordinate, given as (x, y). See
:ref:`coordinate-system`.
:param value: The pixel value.
"""
if self.readonly:
self._copy()
self.load()
if self.pyaccess:
return self.pyaccess.putpixel(xy, value)
if (
self.mode == "P"
and isinstance(value, (list, tuple))
and len(value) in [3, 4]
):
# RGB or RGBA value for a P image
value = self.palette.getcolor(value, self)
return self.im.putpixel(xy, value)
def remap_palette(self, dest_map, source_palette=None):
"""
Rewrites the image to reorder the palette.
:param dest_map: A list of indexes into the original palette.
e.g. ``[1,0]`` would swap a two item palette, and ``list(range(256))``
is the identity transform.
:param source_palette: Bytes or None.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
from . import ImagePalette
if self.mode not in ("L", "P"):
raise ValueError("illegal image mode")
if source_palette is None:
if self.mode == "P":
self.load()
source_palette = self.im.getpalette("RGB")[:768]
else: # L-mode
source_palette = bytearray(i // 3 for i in range(768))
palette_bytes = b""
new_positions = [0] * 256
# pick only the used colors from the palette
for i, oldPosition in enumerate(dest_map):
palette_bytes += source_palette[oldPosition * 3 : oldPosition * 3 + 3]
new_positions[oldPosition] = i
# replace the palette color id of all pixel with the new id
# Palette images are [0..255], mapped through a 1 or 3
# byte/color map. We need to remap the whole image
# from palette 1 to palette 2. New_positions is
# an array of indexes into palette 1. Palette 2 is
# palette 1 with any holes removed.
# We're going to leverage the convert mechanism to use the
# C code to remap the image from palette 1 to palette 2,
# by forcing the source image into 'L' mode and adding a
# mapping 'L' mode palette, then converting back to 'L'
# sans palette thus converting the image bytes, then
# assigning the optimized RGB palette.
# perf reference, 9500x4000 gif, w/~135 colors
# 14 sec prepatch, 1 sec postpatch with optimization forced.
mapping_palette = bytearray(new_positions)
m_im = self.copy()
m_im.mode = "P"
m_im.palette = ImagePalette.ImagePalette("RGB", palette=mapping_palette * 3)
# possibly set palette dirty, then
# m_im.putpalette(mapping_palette, 'L') # converts to 'P'
# or just force it.
# UNDONE -- this is part of the general issue with palettes
m_im.im.putpalette("RGB;L", m_im.palette.tobytes())
m_im = m_im.convert("L")
# Internally, we require 768 bytes for a palette.
new_palette_bytes = palette_bytes + (768 - len(palette_bytes)) * b"\x00"
m_im.putpalette(new_palette_bytes)
m_im.palette = ImagePalette.ImagePalette("RGB", palette=palette_bytes)
return m_im
def _get_safe_box(self, size, resample, box):
"""Expands the box so it includes adjacent pixels
that may be used by resampling with the given resampling filter.
"""
filter_support = _filters_support[resample] - 0.5
scale_x = (box[2] - box[0]) / size[0]
scale_y = (box[3] - box[1]) / size[1]
support_x = filter_support * scale_x
support_y = filter_support * scale_y
return (
max(0, int(box[0] - support_x)),
max(0, int(box[1] - support_y)),
min(self.size[0], math.ceil(box[2] + support_x)),
min(self.size[1], math.ceil(box[3] + support_y)),
)
def resize(self, size, resample=None, box=None, reducing_gap=None):
"""
Returns a resized copy of this image.
:param size: The requested size in pixels, as a 2-tuple:
(width, height).
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If the image has mode "1" or "P", it is always set to
:py:data:`PIL.Image.NEAREST`.
If the image mode specifies a number of bits, such as "I;16", then the
default filter is :py:data:`PIL.Image.NEAREST`.
Otherwise, the default filter is :py:data:`PIL.Image.BICUBIC`.
See: :ref:`concept-filters`.
:param box: An optional 4-tuple of floats providing
the source image region to be scaled.
The values must be within (0, 0, width, height) rectangle.
If omitted or None, the entire source is used.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce`.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is None (no optimization).
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if resample is None:
type_special = ";" in self.mode
resample = NEAREST if type_special else BICUBIC
elif resample not in (NEAREST, BILINEAR, BICUBIC, LANCZOS, BOX, HAMMING):
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(LANCZOS, "Image.LANCZOS"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
(BOX, "Image.BOX"),
(HAMMING, "Image.HAMMING"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
if reducing_gap is not None and reducing_gap < 1.0:
raise ValueError("reducing_gap must be 1.0 or greater")
size = tuple(size)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if self.size == size and box == (0, 0) + self.size:
return self.copy()
if self.mode in ("1", "P"):
resample = NEAREST
if self.mode in ["LA", "RGBA"] and resample != NEAREST:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.resize(size, resample, box)
return im.convert(self.mode)
self.load()
if reducing_gap is not None and resample != NEAREST:
factor_x = int((box[2] - box[0]) / size[0] / reducing_gap) or 1
factor_y = int((box[3] - box[1]) / size[1] / reducing_gap) or 1
if factor_x > 1 or factor_y > 1:
reduce_box = self._get_safe_box(size, resample, box)
factor = (factor_x, factor_y)
if callable(self.reduce):
self = self.reduce(factor, box=reduce_box)
else:
self = Image.reduce(self, factor, box=reduce_box)
box = (
(box[0] - reduce_box[0]) / factor_x,
(box[1] - reduce_box[1]) / factor_y,
(box[2] - reduce_box[0]) / factor_x,
(box[3] - reduce_box[1]) / factor_y,
)
return self._new(self.im.resize(size, resample, box))
def reduce(self, factor, box=None):
"""
Returns a copy of the image reduced ``factor`` times.
If the size of the image is not dividable by ``factor``,
the resulting size will be rounded up.
:param factor: A greater than 0 integer or tuple of two integers
for width and height separately.
:param box: An optional 4-tuple of ints providing
the source image region to be reduced.
The values must be within ``(0, 0, width, height)`` rectangle.
If omitted or ``None``, the entire source is used.
"""
if not isinstance(factor, (list, tuple)):
factor = (factor, factor)
if box is None:
box = (0, 0) + self.size
else:
box = tuple(box)
if factor == (1, 1) and box == (0, 0) + self.size:
return self.copy()
if self.mode in ["LA", "RGBA"]:
im = self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
im = im.reduce(factor, box)
return im.convert(self.mode)
self.load()
return self._new(self.im.reduce(factor, box))
def rotate(
self,
angle,
resample=NEAREST,
expand=0,
center=None,
translate=None,
fillcolor=None,
):
"""
Returns a rotated copy of this image. This method returns a
copy of this image, rotated the given number of degrees counter
clockwise around its centre.
:param angle: In degrees counter clockwise.
:param resample: An optional resampling filter. This can be
one of :py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC`
(cubic spline interpolation in a 4x4 environment).
If omitted, or if the image has mode "1" or "P", it is
set to :py:data:`PIL.Image.NEAREST`. See :ref:`concept-filters`.
:param expand: Optional expansion flag. If true, expands the output
image to make it large enough to hold the entire rotated image.
If false or omitted, make the output image the same size as the
input image. Note that the expand flag assumes rotation around
the center and no translation.
:param center: Optional center of rotation (a 2-tuple). Origin is
the upper left corner. Default is the center of the image.
:param translate: An optional post-rotate translation (a 2-tuple).
:param fillcolor: An optional color for area outside the rotated image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
angle = angle % 360.0
# Fast paths regardless of filter, as long as we're not
# translating or changing the center.
if not (center or translate):
if angle == 0:
return self.copy()
if angle == 180:
return self.transpose(ROTATE_180)
if angle in (90, 270) and (expand or self.width == self.height):
return self.transpose(ROTATE_90 if angle == 90 else ROTATE_270)
# Calculate the affine matrix. Note that this is the reverse
# transformation (from destination image to source) because we
# want to interpolate the (discrete) destination pixel from
# the local area around the (floating) source pixel.
# The matrix we actually want (note that it operates from the right):
# (1, 0, tx) (1, 0, cx) ( cos a, sin a, 0) (1, 0, -cx)
# (0, 1, ty) * (0, 1, cy) * (-sin a, cos a, 0) * (0, 1, -cy)
# (0, 0, 1) (0, 0, 1) ( 0, 0, 1) (0, 0, 1)
# The reverse matrix is thus:
# (1, 0, cx) ( cos -a, sin -a, 0) (1, 0, -cx) (1, 0, -tx)
# (0, 1, cy) * (-sin -a, cos -a, 0) * (0, 1, -cy) * (0, 1, -ty)
# (0, 0, 1) ( 0, 0, 1) (0, 0, 1) (0, 0, 1)
# In any case, the final translation may be updated at the end to
# compensate for the expand flag.
w, h = self.size
if translate is None:
post_trans = (0, 0)
else:
post_trans = translate
if center is None:
# FIXME These should be rounded to ints?
rotn_center = (w / 2.0, h / 2.0)
else:
rotn_center = center
angle = -math.radians(angle)
matrix = [
round(math.cos(angle), 15),
round(math.sin(angle), 15),
0.0,
round(-math.sin(angle), 15),
round(math.cos(angle), 15),
0.0,
]
def transform(x, y, matrix):
(a, b, c, d, e, f) = matrix
return a * x + b * y + c, d * x + e * y + f
matrix[2], matrix[5] = transform(
-rotn_center[0] - post_trans[0], -rotn_center[1] - post_trans[1], matrix
)
matrix[2] += rotn_center[0]
matrix[5] += rotn_center[1]
if expand:
# calculate output size
xx = []
yy = []
for x, y in ((0, 0), (w, 0), (w, h), (0, h)):
x, y = transform(x, y, matrix)
xx.append(x)
yy.append(y)
nw = math.ceil(max(xx)) - math.floor(min(xx))
nh = math.ceil(max(yy)) - math.floor(min(yy))
# We multiply a translation matrix from the right. Because of its
# special form, this is the same as taking the image of the
# translation vector as new translation vector.
matrix[2], matrix[5] = transform(-(nw - w) / 2.0, -(nh - h) / 2.0, matrix)
w, h = nw, nh
return self.transform((w, h), AFFINE, matrix, resample, fillcolor=fillcolor)
def save(self, fp, format=None, **params):
"""
Saves this image under the given filename. If no format is
specified, the format to use is determined from the filename
extension, if possible.
Keyword options can be used to provide additional instructions
to the writer. If a writer doesn't recognise an option, it is
silently ignored. The available options are described in the
:doc:`image format documentation
<../handbook/image-file-formats>` for each writer.
You can use a file object instead of a filename. In this case,
you must always specify the format. The file object must
implement the ``seek``, ``tell``, and ``write``
methods, and be opened in binary mode.
:param fp: A filename (string), pathlib.Path object or file object.
:param format: Optional format override. If omitted, the
format to use is determined from the filename extension.
If a file object was used instead of a filename, this
parameter should always be used.
:param params: Extra parameters to the image writer.
:returns: None
:exception ValueError: If the output format could not be determined
from the file name. Use the format option to solve this.
:exception OSError: If the file could not be written. The file
may have been created, and may contain partial data.
"""
filename = ""
open_fp = False
if isinstance(fp, Path):
filename = str(fp)
open_fp = True
elif isPath(fp):
filename = fp
open_fp = True
elif fp == sys.stdout:
try:
fp = sys.stdout.buffer
except AttributeError:
pass
if not filename and hasattr(fp, "name") and isPath(fp.name):
# only set the name for metadata purposes
filename = fp.name
# may mutate self!
self._ensure_mutable()
save_all = params.pop("save_all", False)
self.encoderinfo = params
self.encoderconfig = ()
preinit()
ext = os.path.splitext(filename)[1].lower()
if not format:
if ext not in EXTENSION:
init()
try:
format = EXTENSION[ext]
except KeyError as e:
raise ValueError(f"unknown file extension: {ext}") from e
if format.upper() not in SAVE:
init()
if save_all:
save_handler = SAVE_ALL[format.upper()]
else:
save_handler = SAVE[format.upper()]
if open_fp:
if params.get("append", False):
# Open also for reading ("+"), because TIFF save_all
# writer needs to go back and edit the written data.
fp = builtins.open(filename, "r+b")
else:
fp = builtins.open(filename, "w+b")
try:
save_handler(self, fp, filename)
finally:
# do what we can to clean up
if open_fp:
fp.close()
def seek(self, frame):
"""
Seeks to the given frame in this sequence file. If you seek
beyond the end of the sequence, the method raises an
``EOFError`` exception. When a sequence file is opened, the
library automatically seeks to frame 0.
See :py:meth:`~PIL.Image.Image.tell`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:param frame: Frame number, starting at 0.
:exception EOFError: If the call attempts to seek beyond the end
of the sequence.
"""
# overridden by file handlers
if frame != 0:
raise EOFError
def show(self, title=None):
"""
Displays this image. This method is mainly intended for debugging purposes.
This method calls :py:func:`PIL.ImageShow.show` internally. You can use
:py:func:`PIL.ImageShow.register` to override its default behaviour.
The image is first saved to a temporary file. By default, it will be in
PNG format.
On Unix, the image is then opened using the **display**, **eog** or
**xv** utility, depending on which one can be found.
On macOS, the image is opened with the native Preview application.
On Windows, the image is opened with the standard PNG display utility.
:param title: Optional title to use for the image window, where possible.
"""
_show(self, title=title)
def split(self):
"""
Split this image into individual bands. This method returns a
tuple of individual image bands from an image. For example,
splitting an "RGB" image creates three new images each
containing a copy of one of the original bands (red, green,
blue).
If you need only one band, :py:meth:`~PIL.Image.Image.getchannel`
method can be more convenient and faster.
:returns: A tuple containing bands.
"""
self.load()
if self.im.bands == 1:
ims = [self.copy()]
else:
ims = map(self._new, self.im.split())
return tuple(ims)
def getchannel(self, channel):
"""
Returns an image containing a single channel of the source image.
:param channel: What channel to return. Could be index
(0 for "R" channel of "RGB") or channel name
("A" for alpha channel of "RGBA").
:returns: An image in "L" mode.
.. versionadded:: 4.3.0
"""
self.load()
if isinstance(channel, str):
try:
channel = self.getbands().index(channel)
except ValueError as e:
raise ValueError(f'The image has no channel "{channel}"') from e
return self._new(self.im.getband(channel))
def tell(self):
"""
Returns the current frame number. See :py:meth:`~PIL.Image.Image.seek`.
If defined, :attr:`~PIL.Image.Image.n_frames` refers to the
number of available frames.
:returns: Frame number, starting with 0.
"""
return 0
def thumbnail(self, size, resample=BICUBIC, reducing_gap=2.0):
"""
Make this image into a thumbnail. This method modifies the
image to contain a thumbnail version of itself, no larger than
the given size. This method calculates an appropriate thumbnail
size to preserve the aspect of the image, calls the
:py:meth:`~PIL.Image.Image.draft` method to configure the file reader
(where applicable), and finally resizes the image.
Note that this function modifies the :py:class:`~PIL.Image.Image`
object in place. If you need to use the full resolution image as well,
apply this method to a :py:meth:`~PIL.Image.Image.copy` of the original
image.
:param size: Requested size.
:param resample: Optional resampling filter. This can be one
of :py:data:`PIL.Image.NEAREST`, :py:data:`PIL.Image.BOX`,
:py:data:`PIL.Image.BILINEAR`, :py:data:`PIL.Image.HAMMING`,
:py:data:`PIL.Image.BICUBIC` or :py:data:`PIL.Image.LANCZOS`.
If omitted, it defaults to :py:data:`PIL.Image.BICUBIC`.
(was :py:data:`PIL.Image.NEAREST` prior to version 2.5.0).
See: :ref:`concept-filters`.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce` or
:py:meth:`~PIL.Image.Image.draft` for JPEG images.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is 2.0 (very close to fair resampling
while still being faster in many cases).
:returns: None
"""
x, y = map(math.floor, size)
if x >= self.width and y >= self.height:
return
def round_aspect(number, key):
return max(min(math.floor(number), math.ceil(number), key=key), 1)
# preserve aspect ratio
aspect = self.width / self.height
if x / y >= aspect:
x = round_aspect(y * aspect, key=lambda n: abs(aspect - n / y))
else:
y = round_aspect(
x / aspect, key=lambda n: 0 if n == 0 else abs(aspect - x / n)
)
size = (x, y)
box = None
if reducing_gap is not None:
res = self.draft(None, (size[0] * reducing_gap, size[1] * reducing_gap))
if res is not None:
box = res[1]
if self.size != size:
im = self.resize(size, resample, box=box, reducing_gap=reducing_gap)
self.im = im.im
self._size = size
self.mode = self.im.mode
self.readonly = 0
self.pyaccess = None
# FIXME: the different transform methods need further explanation
# instead of bloating the method docs, add a separate chapter.
def transform(
self, size, method, data=None, resample=NEAREST, fill=1, fillcolor=None
):
"""
Transforms this image. This method creates a new image with the
given size, and the same mode as the original, and copies data
to the new image using the given transform.
:param size: The output size.
:param method: The transformation method. This is one of
:py:data:`PIL.Image.EXTENT` (cut out a rectangular subregion),
:py:data:`PIL.Image.AFFINE` (affine transform),
:py:data:`PIL.Image.PERSPECTIVE` (perspective transform),
:py:data:`PIL.Image.QUAD` (map a quadrilateral to a rectangle), or
:py:data:`PIL.Image.MESH` (map a number of source quadrilaterals
in one operation).
It may also be an :py:class:`~PIL.Image.ImageTransformHandler`
object::
class Example(Image.ImageTransformHandler):
def transform(self, size, data, resample, fill=1):
# Return result
It may also be an object with a ``method.getdata`` method
that returns a tuple supplying new ``method`` and ``data`` values::
class Example:
def getdata(self):
method = Image.EXTENT
data = (0, 0, 100, 100)
return method, data
:param data: Extra data to the transformation method.
:param resample: Optional resampling filter. It can be one of
:py:data:`PIL.Image.NEAREST` (use nearest neighbour),
:py:data:`PIL.Image.BILINEAR` (linear interpolation in a 2x2
environment), or :py:data:`PIL.Image.BICUBIC` (cubic spline
interpolation in a 4x4 environment). If omitted, or if the image
has mode "1" or "P", it is set to :py:data:`PIL.Image.NEAREST`.
See: :ref:`concept-filters`.
:param fill: If ``method`` is an
:py:class:`~PIL.Image.ImageTransformHandler` object, this is one of
the arguments passed to it. Otherwise, it is unused.
:param fillcolor: Optional fill color for the area outside the
transform in the output image.
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if self.mode in ("LA", "RGBA") and resample != NEAREST:
return (
self.convert({"LA": "La", "RGBA": "RGBa"}[self.mode])
.transform(size, method, data, resample, fill, fillcolor)
.convert(self.mode)
)
if isinstance(method, ImageTransformHandler):
return method.transform(size, self, resample=resample, fill=fill)
if hasattr(method, "getdata"):
# compatibility w. old-style transform objects
method, data = method.getdata()
if data is None:
raise ValueError("missing method data")
im = new(self.mode, size, fillcolor)
if self.mode == "P" and self.palette:
im.palette = self.palette.copy()
im.info = self.info.copy()
if method == MESH:
# list of quads
for box, quad in data:
im.__transformer(box, self, QUAD, quad, resample, fillcolor is None)
else:
im.__transformer(
(0, 0) + size, self, method, data, resample, fillcolor is None
)
return im
def __transformer(self, box, image, method, data, resample=NEAREST, fill=1):
w = box[2] - box[0]
h = box[3] - box[1]
if method == AFFINE:
data = data[0:6]
elif method == EXTENT:
# convert extent to an affine transform
x0, y0, x1, y1 = data
xs = (x1 - x0) / w
ys = (y1 - y0) / h
method = AFFINE
data = (xs, 0, x0, 0, ys, y0)
elif method == PERSPECTIVE:
data = data[0:8]
elif method == QUAD:
# quadrilateral warp. data specifies the four corners
# given as NW, SW, SE, and NE.
nw = data[0:2]
sw = data[2:4]
se = data[4:6]
ne = data[6:8]
x0, y0 = nw
As = 1.0 / w
At = 1.0 / h
data = (
x0,
(ne[0] - x0) * As,
(sw[0] - x0) * At,
(se[0] - sw[0] - ne[0] + x0) * As * At,
y0,
(ne[1] - y0) * As,
(sw[1] - y0) * At,
(se[1] - sw[1] - ne[1] + y0) * As * At,
)
else:
raise ValueError("unknown transformation method")
if resample not in (NEAREST, BILINEAR, BICUBIC):
if resample in (BOX, HAMMING, LANCZOS):
message = {
BOX: "Image.BOX",
HAMMING: "Image.HAMMING",
LANCZOS: "Image.LANCZOS/Image.ANTIALIAS",
}[resample] + f" ({resample}) cannot be used."
else:
message = f"Unknown resampling filter ({resample})."
filters = [
f"{filter[1]} ({filter[0]})"
for filter in (
(NEAREST, "Image.NEAREST"),
(BILINEAR, "Image.BILINEAR"),
(BICUBIC, "Image.BICUBIC"),
)
]
raise ValueError(
message + " Use " + ", ".join(filters[:-1]) + " or " + filters[-1]
)
image.load()
self.load()
if image.mode in ("1", "P"):
resample = NEAREST
self.im.transform2(box, image.im, method, data, resample, fill)
def transpose(self, method):
"""
Transpose image (flip or rotate in 90 degree steps)
:param method: One of :py:data:`PIL.Image.FLIP_LEFT_RIGHT`,
:py:data:`PIL.Image.FLIP_TOP_BOTTOM`, :py:data:`PIL.Image.ROTATE_90`,
:py:data:`PIL.Image.ROTATE_180`, :py:data:`PIL.Image.ROTATE_270`,
:py:data:`PIL.Image.TRANSPOSE` or :py:data:`PIL.Image.TRANSVERSE`.
:returns: Returns a flipped or rotated copy of this image.
"""
self.load()
return self._new(self.im.transpose(method))
def effect_spread(self, distance):
"""
Randomly spread pixels in an image.
:param distance: Distance to spread pixels.
"""
self.load()
return self._new(self.im.effect_spread(distance))
def toqimage(self):
"""Returns a QImage copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqimage(self)
def toqpixmap(self):
"""Returns a QPixmap copy of this image"""
from . import ImageQt
if not ImageQt.qt_is_installed:
raise ImportError("Qt bindings are not installed")
return ImageQt.toqpixmap(self)
The provided code snippet includes necessary dependencies for implementing the `pilinfo` function. Write a Python function `def pilinfo(out=None, supported_formats=True)` to solve the following problem:
Prints information about this installation of Pillow. This function can be called with ``python3 -m PIL``. :param out: The output stream to print to. Defaults to ``sys.stdout`` if ``None``. :param supported_formats: If ``True``, a list of all supported image file formats will be printed.
Here is the function:
def pilinfo(out=None, supported_formats=True):
"""
Prints information about this installation of Pillow.
This function can be called with ``python3 -m PIL``.
:param out:
The output stream to print to. Defaults to ``sys.stdout`` if ``None``.
:param supported_formats:
If ``True``, a list of all supported image file formats will be printed.
"""
if out is None:
out = sys.stdout
Image.init()
print("-" * 68, file=out)
print(f"Pillow {PIL.__version__}", file=out)
py_version = sys.version.splitlines()
print(f"Python {py_version[0].strip()}", file=out)
for py_version in py_version[1:]:
print(f" {py_version.strip()}", file=out)
print("-" * 68, file=out)
print(
f"Python modules loaded from {os.path.dirname(Image.__file__)}",
file=out,
)
print(
f"Binary modules loaded from {os.path.dirname(Image.core.__file__)}",
file=out,
)
print("-" * 68, file=out)
for name, feature in [
("pil", "PIL CORE"),
("tkinter", "TKINTER"),
("freetype2", "FREETYPE2"),
("littlecms2", "LITTLECMS2"),
("webp", "WEBP"),
("transp_webp", "WEBP Transparency"),
("webp_mux", "WEBPMUX"),
("webp_anim", "WEBP Animation"),
("jpg", "JPEG"),
("jpg_2000", "OPENJPEG (JPEG2000)"),
("zlib", "ZLIB (PNG/ZIP)"),
("libtiff", "LIBTIFF"),
("raqm", "RAQM (Bidirectional Text)"),
("libimagequant", "LIBIMAGEQUANT (Quantization method)"),
("xcb", "XCB (X protocol)"),
]:
if check(name):
if name == "jpg" and check_feature("libjpeg_turbo"):
v = "libjpeg-turbo " + version_feature("libjpeg_turbo")
else:
v = version(name)
if v is not None:
version_static = name in ("pil", "jpg")
if name == "littlecms2":
# this check is also in src/_imagingcms.c:setup_module()
version_static = tuple(int(x) for x in v.split(".")) < (2, 7)
t = "compiled for" if version_static else "loaded"
if name == "raqm":
for f in ("fribidi", "harfbuzz"):
v2 = version_feature(f)
if v2 is not None:
v += f", {f} {v2}"
print("---", feature, "support ok,", t, v, file=out)
else:
print("---", feature, "support ok", file=out)
else:
print("***", feature, "support not installed", file=out)
print("-" * 68, file=out)
if supported_formats:
extensions = collections.defaultdict(list)
for ext, i in Image.EXTENSION.items():
extensions[i].append(ext)
for i in sorted(Image.ID):
line = f"{i}"
if i in Image.MIME:
line = f"{line} {Image.MIME[i]}"
print(line, file=out)
if i in extensions:
print(
"Extensions: {}".format(", ".join(sorted(extensions[i]))), file=out
)
features = []
if i in Image.OPEN:
features.append("open")
if i in Image.SAVE:
features.append("save")
if i in Image.SAVE_ALL:
features.append("save_all")
if i in Image.DECODERS:
features.append("decode")
if i in Image.ENCODERS:
features.append("encode")
print("Features: {}".format(", ".join(features)), file=out)
print("-" * 68, file=out) | Prints information about this installation of Pillow. This function can be called with ``python3 -m PIL``. :param out: The output stream to print to. Defaults to ``sys.stdout`` if ``None``. :param supported_formats: If ``True``, a list of all supported image file formats will be printed. |
167,784 | from inspect import signature
from typing import List, Type
from beanie.migrations.controllers.base import BaseMigrationController
from beanie.odm.documents import Document
class BaseMigrationController(ABC):
def __init__(self, function):
self.function = function
async def run(self, session):
pass
def models(self) -> List[Type[Document]]:
pass
class Document(
LazyModel,
SettersInterface,
InheritanceInterface,
FindInterface,
AggregateInterface,
OtherGettersInterface,
):
"""
Document Mapping class.
Fields:
- `id` - MongoDB document ObjectID "_id" field.
Mapped to the PydanticObjectId class
"""
if IS_PYDANTIC_V2:
model_config = ConfigDict(
json_schema_extra=json_schema_extra,
populate_by_name=True,
alias_generator=document_alias_generator,
)
else:
class Config:
json_encoders = {ObjectId: str}
allow_population_by_field_name = True
fields = {"id": "_id"}
schema_extra = staticmethod(json_schema_extra)
id: Optional[PydanticObjectId] = Field(
default=None, description="MongoDB document ObjectID"
)
# State
revision_id: Optional[UUID] = Field(default=None, exclude=True)
_saved_state: Optional[Dict[str, Any]] = PrivateAttr(default=None)
_previous_saved_state: Optional[Dict[str, Any]] = PrivateAttr(default=None)
# Relations
_link_fields: ClassVar[Optional[Dict[str, LinkInfo]]] = None
# Cache
_cache: ClassVar[Optional[LRUCache]] = None
# Settings
_document_settings: ClassVar[Optional[DocumentSettings]] = None
# Database
_database_major_version: ClassVar[int] = 4
def __init__(self, *args, **kwargs) -> None:
super(Document, self).__init__(*args, **kwargs)
self.get_motor_collection()
def _fill_back_refs(cls, values):
if cls._link_fields:
for field_name, link_info in cls._link_fields.items():
if (
link_info.link_type
in [LinkTypes.BACK_DIRECT, LinkTypes.OPTIONAL_BACK_DIRECT]
and field_name not in values
):
values[field_name] = BackLink[link_info.document_class](
link_info.document_class
)
if (
link_info.link_type
in [LinkTypes.BACK_LIST, LinkTypes.OPTIONAL_BACK_LIST]
and field_name not in values
):
values[field_name] = [
BackLink[link_info.document_class](
link_info.document_class
)
]
return values
if IS_PYDANTIC_V2:
def fill_back_refs(cls, values):
return cls._fill_back_refs(values)
else:
def fill_back_refs(cls, values):
return cls._fill_back_refs(values)
async def get(
cls: Type["DocType"],
document_id: Any,
session: Optional[ClientSession] = None,
ignore_cache: bool = False,
fetch_links: bool = False,
with_children: bool = False,
nesting_depth: Optional[int] = None,
nesting_depths_per_field: Optional[Dict[str, int]] = None,
**pymongo_kwargs,
) -> Optional["DocType"]:
"""
Get document by id, returns None if document does not exist
:param document_id: PydanticObjectId - document id
:param session: Optional[ClientSession] - pymongo session
:param ignore_cache: bool - ignore cache (if it is turned on)
:param **pymongo_kwargs: pymongo native parameters for find operation
:return: Union["Document", None]
"""
if not isinstance(
document_id,
extract_id_class(get_field_type(get_model_fields(cls)["id"])),
):
document_id = parse_object_as(
get_field_type(get_model_fields(cls)["id"]), document_id
)
return await cls.find_one(
{"_id": document_id},
session=session,
ignore_cache=ignore_cache,
fetch_links=fetch_links,
with_children=with_children,
nesting_depth=nesting_depth,
nesting_depths_per_field=nesting_depths_per_field,
**pymongo_kwargs,
)
async def sync(self, merge_strategy: MergeStrategy = MergeStrategy.remote):
"""
Sync the document with the database
:param merge_strategy: MergeStrategy - how to merge the document
:return: None
"""
if (
merge_strategy == MergeStrategy.local
and self.get_settings().use_state_management is False
):
raise ValueError(
"State management must be turned on to use local merge strategy"
)
if self.id is None:
raise DocumentWasNotSaved
document = await self.find_one({"_id": self.id})
if document is None:
raise DocumentNotFound
if merge_strategy == MergeStrategy.local:
original_changes = self.get_changes()
new_state = document.get_saved_state()
if new_state is None:
raise DocumentWasNotSaved
changes_to_apply = self._collect_updates(
new_state, original_changes
)
merge_models(self, document)
apply_changes(changes_to_apply, self)
elif merge_strategy == MergeStrategy.remote:
merge_models(self, document)
else:
raise ValueError("Invalid merge strategy")
async def insert(
self: DocType,
*,
link_rule: WriteRules = WriteRules.DO_NOTHING,
session: Optional[ClientSession] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> DocType:
"""
Insert the document (self) to the collection
:return: Document
"""
if self.get_settings().use_revision:
self.revision_id = uuid4()
if link_rule == WriteRules.WRITE:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
]:
if isinstance(value, Document):
await value.save(link_rule=WriteRules.WRITE)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.save(link_rule=WriteRules.WRITE)
for obj in value
if isinstance(obj, Document)
]
)
result = await self.get_motor_collection().insert_one(
get_dict(
self, to_db=True, keep_nulls=self.get_settings().keep_nulls
),
session=session,
)
new_id = result.inserted_id
if not isinstance(
new_id,
extract_id_class(get_field_type(get_model_fields(self)["id"])),
):
new_id = parse_object_as(
get_field_type(get_model_fields(self)["id"]), new_id
)
self.id = new_id
return self
async def create(
self: DocType,
session: Optional[ClientSession] = None,
) -> DocType:
"""
The same as self.insert()
:return: Document
"""
return await self.insert(session=session)
async def insert_one(
cls: Type[DocType],
document: DocType,
session: Optional[ClientSession] = None,
bulk_writer: Optional["BulkWriter"] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
) -> Optional[DocType]:
"""
Insert one document to the collection
:param document: Document - document to insert
:param session: ClientSession - pymongo session
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param link_rule: InsertRules - hot to manage link fields
:return: DocType
"""
if not isinstance(document, cls):
raise TypeError(
"Inserting document must be of the original document class"
)
if bulk_writer is None:
return await document.insert(link_rule=link_rule, session=session)
else:
if link_rule == WriteRules.WRITE:
raise NotSupported(
"Cascade insert with bulk writing not supported"
)
bulk_writer.add_operation(
Operation(
operation=InsertOne,
first_query=get_dict(
document,
to_db=True,
keep_nulls=document.get_settings().keep_nulls,
),
object_class=type(document),
)
)
return None
async def insert_many(
cls: Type[DocType],
documents: Iterable[DocType],
session: Optional[ClientSession] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
**pymongo_kwargs,
) -> InsertManyResult:
"""
Insert many documents to the collection
:param documents: List["Document"] - documents to insert
:param session: ClientSession - pymongo session
:param link_rule: InsertRules - how to manage link fields
:return: InsertManyResult
"""
if link_rule == WriteRules.WRITE:
raise NotSupported(
"Cascade insert not supported for insert many method"
)
documents_list = [
get_dict(
document,
to_db=True,
keep_nulls=document.get_settings().keep_nulls,
)
for document in documents
]
return await cls.get_motor_collection().insert_many(
documents_list, session=session, **pymongo_kwargs
)
async def replace(
self: DocType,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> DocType:
"""
Fully update the document in the database
:param session: Optional[ClientSession] - pymongo session.
:param ignore_revision: bool - do force replace.
Used when revision based protection is turned on.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:return: self
"""
if self.id is None:
raise ValueError("Document must have an id")
if bulk_writer is not None and link_rule != WriteRules.DO_NOTHING:
raise NotSupported
if link_rule == WriteRules.WRITE:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if isinstance(value, Document):
await value.replace(
link_rule=link_rule,
bulk_writer=bulk_writer,
ignore_revision=ignore_revision,
session=session,
)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.replace(
link_rule=link_rule,
bulk_writer=bulk_writer,
ignore_revision=ignore_revision,
session=session,
)
for obj in value
if isinstance(obj, Document)
]
)
use_revision_id = self.get_settings().use_revision
find_query: Dict[str, Any] = {"_id": self.id}
if use_revision_id and not ignore_revision:
find_query["revision_id"] = self.revision_id
self.revision_id = uuid4()
try:
await self.find_one(find_query).replace_one(
self,
session=session,
bulk_writer=bulk_writer,
)
except DocumentNotFound:
if use_revision_id and not ignore_revision:
raise RevisionIdWasChanged
else:
raise DocumentNotFound
return self
async def save(
self: DocType,
session: Optional[ClientSession] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
ignore_revision: bool = False,
**kwargs,
) -> None:
"""
Update an existing model in the database or
insert it if it does not yet exist.
:param session: Optional[ClientSession] - pymongo session.
:param link_rule: WriteRules - rules how to deal with links on writing
:param ignore_revision: bool - do force save.
:return: None
"""
if link_rule == WriteRules.WRITE:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if isinstance(value, Document):
await value.save(
link_rule=link_rule, session=session
)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.save(
link_rule=link_rule, session=session
)
for obj in value
if isinstance(obj, Document)
]
)
if self.get_settings().keep_nulls is False:
return await self.update(
SetOperator(
get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
)
),
Unset(get_top_level_nones(self)),
session=session,
ignore_revision=ignore_revision,
upsert=True,
**kwargs,
)
else:
return await self.update(
SetOperator(
get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
)
),
session=session,
ignore_revision=ignore_revision,
upsert=True,
**kwargs,
)
async def save_changes(
self,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> None:
"""
Save changes.
State management usage must be turned on
:param ignore_revision: bool - ignore revision id, if revision is turned on
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:return: None
"""
if not self.is_changed:
return None
changes = self.get_changes()
if self.get_settings().keep_nulls is False:
return await self.update(
SetOperator(changes),
Unset(get_top_level_nones(self)),
ignore_revision=ignore_revision,
session=session,
bulk_writer=bulk_writer,
)
else:
return await self.set(
changes, # type: ignore #TODO fix typing
ignore_revision=ignore_revision,
session=session,
bulk_writer=bulk_writer,
)
async def replace_many(
cls: Type[DocType],
documents: List[DocType],
session: Optional[ClientSession] = None,
) -> None:
"""
Replace list of documents
:param documents: List["Document"]
:param session: Optional[ClientSession] - pymongo session.
:return: None
"""
ids_list = [document.id for document in documents]
if await cls.find(In(cls.id, ids_list)).count() != len(ids_list):
raise ReplaceError(
"Some of the documents are not exist in the collection"
)
async with BulkWriter(session=session) as bulk_writer:
for document in documents:
await document.replace(
bulk_writer=bulk_writer, session=session
)
async def update(
self,
*args,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
skip_sync: Optional[bool] = None,
**pymongo_kwargs,
) -> DocType:
"""
Partially update the document in the database
:param args: *Union[dict, Mapping] - the modifications to apply.
:param session: ClientSession - pymongo session.
:param ignore_revision: bool - force update. Will update even if revision id is not the same, as stored
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param pymongo_kwargs: pymongo native parameters for update operation
:return: None
"""
arguments = list(args)
if skip_sync is not None:
raise DeprecationWarning(
"skip_sync parameter is not supported. The document get synced always using atomic operation."
)
use_revision_id = self.get_settings().use_revision
if self.id is not None:
find_query: Dict[str, Any] = {"_id": self.id}
else:
find_query = {"_id": PydanticObjectId()}
if use_revision_id and not ignore_revision:
find_query["revision_id"] = self.revision_id
if use_revision_id:
new_revision_id = uuid4()
arguments.append(SetRevisionId(new_revision_id))
try:
result = await self.find_one(find_query).update(
*arguments,
session=session,
response_type=UpdateResponse.NEW_DOCUMENT,
bulk_writer=bulk_writer,
**pymongo_kwargs,
)
except DuplicateKeyError:
raise RevisionIdWasChanged
if bulk_writer is None:
if use_revision_id and not ignore_revision and result is None:
raise RevisionIdWasChanged
merge_models(self, result)
return self
def update_all(
cls,
*args: Union[dict, Mapping],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
**pymongo_kwargs,
) -> UpdateMany:
"""
Partially update all the documents
:param args: *Union[dict, Mapping] - the modifications to apply.
:param session: ClientSession - pymongo session.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param **pymongo_kwargs: pymongo native parameters for find operation
:return: UpdateMany query
"""
return cls.find_all().update_many(
*args, session=session, bulk_writer=bulk_writer, **pymongo_kwargs
)
def set(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
"""
Set values
Example:
```python
class Sample(Document):
one: int
await Document.find(Sample.one == 1).set({Sample.one: 100})
```
Uses [Set operator](operators/update.md#set)
:param expression: Dict[Union[ExpressionField, str], Any] - keys and
values to set
:param session: Optional[ClientSession] - pymongo session
:param bulk_writer: Optional[BulkWriter] - bulk writer
:param skip_sync: bool - skip doc syncing. Available for the direct instances only
:return: self
"""
return self.update(
SetOperator(expression),
session=session,
bulk_writer=bulk_writer,
skip_sync=skip_sync,
**kwargs,
)
def current_date(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
"""
Set current date
Uses [CurrentDate operator](operators/update.md#currentdate)
:param expression: Dict[Union[ExpressionField, str], Any]
:param session: Optional[ClientSession] - pymongo session
:param bulk_writer: Optional[BulkWriter] - bulk writer
:param skip_sync: bool - skip doc syncing. Available for the direct instances only
:return: self
"""
return self.update(
CurrentDate(expression),
session=session,
bulk_writer=bulk_writer,
skip_sync=skip_sync,
**kwargs,
)
def inc(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
"""
Increment
Example:
```python
class Sample(Document):
one: int
await Document.find(Sample.one == 1).inc({Sample.one: 100})
```
Uses [Inc operator](operators/update.md#inc)
:param expression: Dict[Union[ExpressionField, str], Any]
:param session: Optional[ClientSession] - pymongo session
:param bulk_writer: Optional[BulkWriter] - bulk writer
:param skip_sync: bool - skip doc syncing. Available for the direct instances only
:return: self
"""
return self.update(
Inc(expression),
session=session,
bulk_writer=bulk_writer,
skip_sync=skip_sync,
**kwargs,
)
async def delete(
self,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
link_rule: DeleteRules = DeleteRules.DO_NOTHING,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
**pymongo_kwargs,
) -> Optional[DeleteResult]:
"""
Delete the document
:param session: Optional[ClientSession] - pymongo session.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param link_rule: DeleteRules - rules for link fields
:param **pymongo_kwargs: pymongo native parameters for delete operation
:return: Optional[DeleteResult] - pymongo DeleteResult instance.
"""
if link_rule == DeleteRules.DELETE_LINKS:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if isinstance(value, Document):
await value.delete(
link_rule=DeleteRules.DELETE_LINKS,
**pymongo_kwargs,
)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.delete(
link_rule=DeleteRules.DELETE_LINKS,
**pymongo_kwargs,
)
for obj in value
if isinstance(obj, Document)
]
)
return await self.find_one({"_id": self.id}).delete(
session=session, bulk_writer=bulk_writer, **pymongo_kwargs
)
async def delete_all(
cls,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
**pymongo_kwargs,
) -> Optional[DeleteResult]:
"""
Delete all the documents
:param session: Optional[ClientSession] - pymongo session.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param **pymongo_kwargs: pymongo native parameters for delete operation
:return: Optional[DeleteResult] - pymongo DeleteResult instance.
"""
return await cls.find_all().delete(
session=session, bulk_writer=bulk_writer, **pymongo_kwargs
)
# State management
def use_state_management(cls) -> bool:
"""
Is state management turned on
:return: bool
"""
return cls.get_settings().use_state_management
def state_management_save_previous(cls) -> bool:
"""
Should we save the previous state after a commit to database
:return: bool
"""
return cls.get_settings().state_management_save_previous
def state_management_replace_objects(cls) -> bool:
"""
Should objects be replaced when using state management
:return: bool
"""
return cls.get_settings().state_management_replace_objects
def _save_state(self) -> None:
"""
Save current document state. Internal method
:return: None
"""
if self.use_state_management() and self.id is not None:
if self.state_management_save_previous():
self._previous_saved_state = self._saved_state
self._saved_state = get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
exclude={"revision_id"},
)
def get_saved_state(self) -> Optional[Dict[str, Any]]:
"""
Saved state getter. It is protected property.
:return: Optional[Dict[str, Any]] - saved state
"""
return self._saved_state
def get_previous_saved_state(self) -> Optional[Dict[str, Any]]:
"""
Previous state getter. It is a protected property.
:return: Optional[Dict[str, Any]] - previous state
"""
return self._previous_saved_state
def is_changed(self) -> bool:
if self._saved_state == get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
exclude={"revision_id"},
):
return False
return True
def has_changed(self) -> bool:
if (
self._previous_saved_state is None
or self._previous_saved_state == self._saved_state
):
return False
return True
def _collect_updates(
self, old_dict: Dict[str, Any], new_dict: Dict[str, Any]
) -> Dict[str, Any]:
"""
Compares old_dict with new_dict and returns field paths that have been updated
Args:
old_dict: dict1
new_dict: dict2
Returns: dictionary with updates
"""
updates = {}
if old_dict.keys() - new_dict.keys():
updates = new_dict
else:
for field_name, field_value in new_dict.items():
if field_value != old_dict.get(field_name):
if not self.state_management_replace_objects() and (
isinstance(field_value, dict)
and isinstance(old_dict.get(field_name), dict)
):
if old_dict.get(field_name) is None:
updates[field_name] = field_value
elif isinstance(field_value, dict) and isinstance(
old_dict.get(field_name), dict
):
field_data = self._collect_updates(
old_dict.get(field_name), # type: ignore
field_value,
)
for k, v in field_data.items():
updates[f"{field_name}.{k}"] = v
else:
updates[field_name] = field_value
return updates
def get_changes(self) -> Dict[str, Any]:
return self._collect_updates(
self._saved_state, # type: ignore
get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
exclude={"revision_id"},
),
)
def get_previous_changes(self) -> Dict[str, Any]:
if self._previous_saved_state is None:
return {}
return self._collect_updates(
self._previous_saved_state,
self._saved_state, # type: ignore
)
def rollback(self) -> None:
if self.is_changed:
for key, value in self._saved_state.items(): # type: ignore
if key == "_id":
setattr(self, "id", value)
else:
setattr(self, key, value)
# Other
def get_settings(cls) -> DocumentSettings:
"""
Get document settings, which was created on
the initialization step
:return: DocumentSettings class
"""
if cls._document_settings is None:
raise CollectionWasNotInitialized
return cls._document_settings
async def inspect_collection(
cls, session: Optional[ClientSession] = None
) -> InspectionResult:
"""
Check, if documents, stored in the MongoDB collection
are compatible with the Document schema
:return: InspectionResult
"""
inspection_result = InspectionResult()
async for json_document in cls.get_motor_collection().find(
{}, session=session
):
try:
parse_model(cls, json_document)
except ValidationError as e:
if inspection_result.status == InspectionStatuses.OK:
inspection_result.status = InspectionStatuses.FAIL
inspection_result.errors.append(
InspectionError(
document_id=json_document["_id"], error=str(e)
)
)
return inspection_result
def check_hidden_fields(cls):
hidden_fields = [
(name, field)
for name, field in get_model_fields(cls).items()
if get_extra_field_info(field, "hidden") is True
]
if not hidden_fields:
return
warnings.warn(
f"{cls.__name__}: 'hidden=True' is deprecated, please use 'exclude=True'",
DeprecationWarning,
)
if IS_PYDANTIC_V2:
for name, field in hidden_fields:
field.exclude = True
del field.json_schema_extra["hidden"]
cls.model_rebuild(force=True)
else:
for name, field in hidden_fields:
field.field_info.exclude = True
del field.field_info.extra["hidden"]
cls.__exclude_fields__[name] = True
async def validate_self(self, *args, **kwargs):
# TODO: it can be sync, but needs some actions controller improvements
if self.get_settings().validate_on_save:
new_model = parse_model(self.__class__, get_model_dump(self))
merge_models(self, new_model)
def to_ref(self):
if self.id is None:
raise DocumentWasNotSaved("Can not create dbref without id")
return DBRef(self.get_motor_collection().name, self.id)
async def fetch_link(self, field: Union[str, Any]):
ref_obj = getattr(self, field, None)
if isinstance(ref_obj, Link):
value = await ref_obj.fetch(fetch_links=True)
setattr(self, field, value)
if isinstance(ref_obj, list) and ref_obj:
values = await Link.fetch_list(ref_obj, fetch_links=True)
setattr(self, field, values)
async def fetch_all_links(self):
coros = []
link_fields = self.get_link_fields()
if link_fields is not None:
for ref in link_fields.values():
coros.append(self.fetch_link(ref.field_name)) # TODO lists
await asyncio.gather(*coros)
def get_link_fields(cls) -> Optional[Dict[str, LinkInfo]]:
return cls._link_fields
def get_model_type(cls) -> ModelType:
return ModelType.Document
async def distinct(
cls,
key: str,
filter: Optional[Mapping[str, Any]] = None,
session: Optional[ClientSession] = None,
**kwargs: Any,
) -> list:
return await cls.get_motor_collection().distinct(
key, filter, session, **kwargs
)
def link_from_id(cls, id: Any):
ref = DBRef(id=id, collection=cls.get_collection_name())
return Link(ref, document_class=cls)
def free_fall_migration(document_models: List[Type[Document]]):
class FreeFallMigrationController(BaseMigrationController):
def __init__(self, function):
self.function = function
self.function_signature = signature(function)
self.document_models = document_models
def __call__(self, *args, **kwargs):
pass
@property
def models(self) -> List[Type[Document]]:
return self.document_models
async def run(self, session):
function_kwargs = {"session": session}
if "self" in self.function_signature.parameters:
function_kwargs["self"] = None
await self.function(**function_kwargs)
return FreeFallMigrationController | null |
167,785 | import asyncio
from inspect import isclass, signature
from typing import List, Optional, Type, Union
from beanie.migrations.controllers.base import BaseMigrationController
from beanie.migrations.utils import update_dict
from beanie.odm.documents import Document
from beanie.odm.utils.pydantic import parse_model
class DummyOutput:
def __init__(self):
super(DummyOutput, self).__setattr__("_internal_structure_dict", {})
def __setattr__(self, key, value):
self._internal_structure_dict[key] = value
def __getattr__(self, item):
try:
return self._internal_structure_dict[item]
except KeyError:
self._internal_structure_dict[item] = DummyOutput()
return self._internal_structure_dict[item]
def dict(self, to_parse: Optional[Union[dict, "DummyOutput"]] = None):
if to_parse is None:
to_parse = self
input_dict = (
to_parse._internal_structure_dict
if isinstance(to_parse, DummyOutput)
else to_parse
)
result_dict = {}
for key, value in input_dict.items():
if isinstance(value, (DummyOutput, dict)):
result_dict[key] = self.dict(to_parse=value)
else:
result_dict[key] = value
return result_dict
class BaseMigrationController(ABC):
def __init__(self, function):
self.function = function
async def run(self, session):
pass
def models(self) -> List[Type[Document]]:
pass
def update_dict(d, u):
for k, v in u.items():
if isinstance(v, dict):
d[k] = update_dict(d.get(k, {}), v)
else:
d[k] = v
return d
class Document(
LazyModel,
SettersInterface,
InheritanceInterface,
FindInterface,
AggregateInterface,
OtherGettersInterface,
):
"""
Document Mapping class.
Fields:
- `id` - MongoDB document ObjectID "_id" field.
Mapped to the PydanticObjectId class
"""
if IS_PYDANTIC_V2:
model_config = ConfigDict(
json_schema_extra=json_schema_extra,
populate_by_name=True,
alias_generator=document_alias_generator,
)
else:
class Config:
json_encoders = {ObjectId: str}
allow_population_by_field_name = True
fields = {"id": "_id"}
schema_extra = staticmethod(json_schema_extra)
id: Optional[PydanticObjectId] = Field(
default=None, description="MongoDB document ObjectID"
)
# State
revision_id: Optional[UUID] = Field(default=None, exclude=True)
_saved_state: Optional[Dict[str, Any]] = PrivateAttr(default=None)
_previous_saved_state: Optional[Dict[str, Any]] = PrivateAttr(default=None)
# Relations
_link_fields: ClassVar[Optional[Dict[str, LinkInfo]]] = None
# Cache
_cache: ClassVar[Optional[LRUCache]] = None
# Settings
_document_settings: ClassVar[Optional[DocumentSettings]] = None
# Database
_database_major_version: ClassVar[int] = 4
def __init__(self, *args, **kwargs) -> None:
super(Document, self).__init__(*args, **kwargs)
self.get_motor_collection()
def _fill_back_refs(cls, values):
if cls._link_fields:
for field_name, link_info in cls._link_fields.items():
if (
link_info.link_type
in [LinkTypes.BACK_DIRECT, LinkTypes.OPTIONAL_BACK_DIRECT]
and field_name not in values
):
values[field_name] = BackLink[link_info.document_class](
link_info.document_class
)
if (
link_info.link_type
in [LinkTypes.BACK_LIST, LinkTypes.OPTIONAL_BACK_LIST]
and field_name not in values
):
values[field_name] = [
BackLink[link_info.document_class](
link_info.document_class
)
]
return values
if IS_PYDANTIC_V2:
def fill_back_refs(cls, values):
return cls._fill_back_refs(values)
else:
def fill_back_refs(cls, values):
return cls._fill_back_refs(values)
async def get(
cls: Type["DocType"],
document_id: Any,
session: Optional[ClientSession] = None,
ignore_cache: bool = False,
fetch_links: bool = False,
with_children: bool = False,
nesting_depth: Optional[int] = None,
nesting_depths_per_field: Optional[Dict[str, int]] = None,
**pymongo_kwargs,
) -> Optional["DocType"]:
"""
Get document by id, returns None if document does not exist
:param document_id: PydanticObjectId - document id
:param session: Optional[ClientSession] - pymongo session
:param ignore_cache: bool - ignore cache (if it is turned on)
:param **pymongo_kwargs: pymongo native parameters for find operation
:return: Union["Document", None]
"""
if not isinstance(
document_id,
extract_id_class(get_field_type(get_model_fields(cls)["id"])),
):
document_id = parse_object_as(
get_field_type(get_model_fields(cls)["id"]), document_id
)
return await cls.find_one(
{"_id": document_id},
session=session,
ignore_cache=ignore_cache,
fetch_links=fetch_links,
with_children=with_children,
nesting_depth=nesting_depth,
nesting_depths_per_field=nesting_depths_per_field,
**pymongo_kwargs,
)
async def sync(self, merge_strategy: MergeStrategy = MergeStrategy.remote):
"""
Sync the document with the database
:param merge_strategy: MergeStrategy - how to merge the document
:return: None
"""
if (
merge_strategy == MergeStrategy.local
and self.get_settings().use_state_management is False
):
raise ValueError(
"State management must be turned on to use local merge strategy"
)
if self.id is None:
raise DocumentWasNotSaved
document = await self.find_one({"_id": self.id})
if document is None:
raise DocumentNotFound
if merge_strategy == MergeStrategy.local:
original_changes = self.get_changes()
new_state = document.get_saved_state()
if new_state is None:
raise DocumentWasNotSaved
changes_to_apply = self._collect_updates(
new_state, original_changes
)
merge_models(self, document)
apply_changes(changes_to_apply, self)
elif merge_strategy == MergeStrategy.remote:
merge_models(self, document)
else:
raise ValueError("Invalid merge strategy")
async def insert(
self: DocType,
*,
link_rule: WriteRules = WriteRules.DO_NOTHING,
session: Optional[ClientSession] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> DocType:
"""
Insert the document (self) to the collection
:return: Document
"""
if self.get_settings().use_revision:
self.revision_id = uuid4()
if link_rule == WriteRules.WRITE:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
]:
if isinstance(value, Document):
await value.save(link_rule=WriteRules.WRITE)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.save(link_rule=WriteRules.WRITE)
for obj in value
if isinstance(obj, Document)
]
)
result = await self.get_motor_collection().insert_one(
get_dict(
self, to_db=True, keep_nulls=self.get_settings().keep_nulls
),
session=session,
)
new_id = result.inserted_id
if not isinstance(
new_id,
extract_id_class(get_field_type(get_model_fields(self)["id"])),
):
new_id = parse_object_as(
get_field_type(get_model_fields(self)["id"]), new_id
)
self.id = new_id
return self
async def create(
self: DocType,
session: Optional[ClientSession] = None,
) -> DocType:
"""
The same as self.insert()
:return: Document
"""
return await self.insert(session=session)
async def insert_one(
cls: Type[DocType],
document: DocType,
session: Optional[ClientSession] = None,
bulk_writer: Optional["BulkWriter"] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
) -> Optional[DocType]:
"""
Insert one document to the collection
:param document: Document - document to insert
:param session: ClientSession - pymongo session
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param link_rule: InsertRules - hot to manage link fields
:return: DocType
"""
if not isinstance(document, cls):
raise TypeError(
"Inserting document must be of the original document class"
)
if bulk_writer is None:
return await document.insert(link_rule=link_rule, session=session)
else:
if link_rule == WriteRules.WRITE:
raise NotSupported(
"Cascade insert with bulk writing not supported"
)
bulk_writer.add_operation(
Operation(
operation=InsertOne,
first_query=get_dict(
document,
to_db=True,
keep_nulls=document.get_settings().keep_nulls,
),
object_class=type(document),
)
)
return None
async def insert_many(
cls: Type[DocType],
documents: Iterable[DocType],
session: Optional[ClientSession] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
**pymongo_kwargs,
) -> InsertManyResult:
"""
Insert many documents to the collection
:param documents: List["Document"] - documents to insert
:param session: ClientSession - pymongo session
:param link_rule: InsertRules - how to manage link fields
:return: InsertManyResult
"""
if link_rule == WriteRules.WRITE:
raise NotSupported(
"Cascade insert not supported for insert many method"
)
documents_list = [
get_dict(
document,
to_db=True,
keep_nulls=document.get_settings().keep_nulls,
)
for document in documents
]
return await cls.get_motor_collection().insert_many(
documents_list, session=session, **pymongo_kwargs
)
async def replace(
self: DocType,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> DocType:
"""
Fully update the document in the database
:param session: Optional[ClientSession] - pymongo session.
:param ignore_revision: bool - do force replace.
Used when revision based protection is turned on.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:return: self
"""
if self.id is None:
raise ValueError("Document must have an id")
if bulk_writer is not None and link_rule != WriteRules.DO_NOTHING:
raise NotSupported
if link_rule == WriteRules.WRITE:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if isinstance(value, Document):
await value.replace(
link_rule=link_rule,
bulk_writer=bulk_writer,
ignore_revision=ignore_revision,
session=session,
)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.replace(
link_rule=link_rule,
bulk_writer=bulk_writer,
ignore_revision=ignore_revision,
session=session,
)
for obj in value
if isinstance(obj, Document)
]
)
use_revision_id = self.get_settings().use_revision
find_query: Dict[str, Any] = {"_id": self.id}
if use_revision_id and not ignore_revision:
find_query["revision_id"] = self.revision_id
self.revision_id = uuid4()
try:
await self.find_one(find_query).replace_one(
self,
session=session,
bulk_writer=bulk_writer,
)
except DocumentNotFound:
if use_revision_id and not ignore_revision:
raise RevisionIdWasChanged
else:
raise DocumentNotFound
return self
async def save(
self: DocType,
session: Optional[ClientSession] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
ignore_revision: bool = False,
**kwargs,
) -> None:
"""
Update an existing model in the database or
insert it if it does not yet exist.
:param session: Optional[ClientSession] - pymongo session.
:param link_rule: WriteRules - rules how to deal with links on writing
:param ignore_revision: bool - do force save.
:return: None
"""
if link_rule == WriteRules.WRITE:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if isinstance(value, Document):
await value.save(
link_rule=link_rule, session=session
)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.save(
link_rule=link_rule, session=session
)
for obj in value
if isinstance(obj, Document)
]
)
if self.get_settings().keep_nulls is False:
return await self.update(
SetOperator(
get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
)
),
Unset(get_top_level_nones(self)),
session=session,
ignore_revision=ignore_revision,
upsert=True,
**kwargs,
)
else:
return await self.update(
SetOperator(
get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
)
),
session=session,
ignore_revision=ignore_revision,
upsert=True,
**kwargs,
)
async def save_changes(
self,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> None:
"""
Save changes.
State management usage must be turned on
:param ignore_revision: bool - ignore revision id, if revision is turned on
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:return: None
"""
if not self.is_changed:
return None
changes = self.get_changes()
if self.get_settings().keep_nulls is False:
return await self.update(
SetOperator(changes),
Unset(get_top_level_nones(self)),
ignore_revision=ignore_revision,
session=session,
bulk_writer=bulk_writer,
)
else:
return await self.set(
changes, # type: ignore #TODO fix typing
ignore_revision=ignore_revision,
session=session,
bulk_writer=bulk_writer,
)
async def replace_many(
cls: Type[DocType],
documents: List[DocType],
session: Optional[ClientSession] = None,
) -> None:
"""
Replace list of documents
:param documents: List["Document"]
:param session: Optional[ClientSession] - pymongo session.
:return: None
"""
ids_list = [document.id for document in documents]
if await cls.find(In(cls.id, ids_list)).count() != len(ids_list):
raise ReplaceError(
"Some of the documents are not exist in the collection"
)
async with BulkWriter(session=session) as bulk_writer:
for document in documents:
await document.replace(
bulk_writer=bulk_writer, session=session
)
async def update(
self,
*args,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
skip_sync: Optional[bool] = None,
**pymongo_kwargs,
) -> DocType:
"""
Partially update the document in the database
:param args: *Union[dict, Mapping] - the modifications to apply.
:param session: ClientSession - pymongo session.
:param ignore_revision: bool - force update. Will update even if revision id is not the same, as stored
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param pymongo_kwargs: pymongo native parameters for update operation
:return: None
"""
arguments = list(args)
if skip_sync is not None:
raise DeprecationWarning(
"skip_sync parameter is not supported. The document get synced always using atomic operation."
)
use_revision_id = self.get_settings().use_revision
if self.id is not None:
find_query: Dict[str, Any] = {"_id": self.id}
else:
find_query = {"_id": PydanticObjectId()}
if use_revision_id and not ignore_revision:
find_query["revision_id"] = self.revision_id
if use_revision_id:
new_revision_id = uuid4()
arguments.append(SetRevisionId(new_revision_id))
try:
result = await self.find_one(find_query).update(
*arguments,
session=session,
response_type=UpdateResponse.NEW_DOCUMENT,
bulk_writer=bulk_writer,
**pymongo_kwargs,
)
except DuplicateKeyError:
raise RevisionIdWasChanged
if bulk_writer is None:
if use_revision_id and not ignore_revision and result is None:
raise RevisionIdWasChanged
merge_models(self, result)
return self
def update_all(
cls,
*args: Union[dict, Mapping],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
**pymongo_kwargs,
) -> UpdateMany:
"""
Partially update all the documents
:param args: *Union[dict, Mapping] - the modifications to apply.
:param session: ClientSession - pymongo session.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param **pymongo_kwargs: pymongo native parameters for find operation
:return: UpdateMany query
"""
return cls.find_all().update_many(
*args, session=session, bulk_writer=bulk_writer, **pymongo_kwargs
)
def set(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
"""
Set values
Example:
```python
class Sample(Document):
one: int
await Document.find(Sample.one == 1).set({Sample.one: 100})
```
Uses [Set operator](operators/update.md#set)
:param expression: Dict[Union[ExpressionField, str], Any] - keys and
values to set
:param session: Optional[ClientSession] - pymongo session
:param bulk_writer: Optional[BulkWriter] - bulk writer
:param skip_sync: bool - skip doc syncing. Available for the direct instances only
:return: self
"""
return self.update(
SetOperator(expression),
session=session,
bulk_writer=bulk_writer,
skip_sync=skip_sync,
**kwargs,
)
def current_date(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
"""
Set current date
Uses [CurrentDate operator](operators/update.md#currentdate)
:param expression: Dict[Union[ExpressionField, str], Any]
:param session: Optional[ClientSession] - pymongo session
:param bulk_writer: Optional[BulkWriter] - bulk writer
:param skip_sync: bool - skip doc syncing. Available for the direct instances only
:return: self
"""
return self.update(
CurrentDate(expression),
session=session,
bulk_writer=bulk_writer,
skip_sync=skip_sync,
**kwargs,
)
def inc(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
"""
Increment
Example:
```python
class Sample(Document):
one: int
await Document.find(Sample.one == 1).inc({Sample.one: 100})
```
Uses [Inc operator](operators/update.md#inc)
:param expression: Dict[Union[ExpressionField, str], Any]
:param session: Optional[ClientSession] - pymongo session
:param bulk_writer: Optional[BulkWriter] - bulk writer
:param skip_sync: bool - skip doc syncing. Available for the direct instances only
:return: self
"""
return self.update(
Inc(expression),
session=session,
bulk_writer=bulk_writer,
skip_sync=skip_sync,
**kwargs,
)
async def delete(
self,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
link_rule: DeleteRules = DeleteRules.DO_NOTHING,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
**pymongo_kwargs,
) -> Optional[DeleteResult]:
"""
Delete the document
:param session: Optional[ClientSession] - pymongo session.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param link_rule: DeleteRules - rules for link fields
:param **pymongo_kwargs: pymongo native parameters for delete operation
:return: Optional[DeleteResult] - pymongo DeleteResult instance.
"""
if link_rule == DeleteRules.DELETE_LINKS:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if isinstance(value, Document):
await value.delete(
link_rule=DeleteRules.DELETE_LINKS,
**pymongo_kwargs,
)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.delete(
link_rule=DeleteRules.DELETE_LINKS,
**pymongo_kwargs,
)
for obj in value
if isinstance(obj, Document)
]
)
return await self.find_one({"_id": self.id}).delete(
session=session, bulk_writer=bulk_writer, **pymongo_kwargs
)
async def delete_all(
cls,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
**pymongo_kwargs,
) -> Optional[DeleteResult]:
"""
Delete all the documents
:param session: Optional[ClientSession] - pymongo session.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param **pymongo_kwargs: pymongo native parameters for delete operation
:return: Optional[DeleteResult] - pymongo DeleteResult instance.
"""
return await cls.find_all().delete(
session=session, bulk_writer=bulk_writer, **pymongo_kwargs
)
# State management
def use_state_management(cls) -> bool:
"""
Is state management turned on
:return: bool
"""
return cls.get_settings().use_state_management
def state_management_save_previous(cls) -> bool:
"""
Should we save the previous state after a commit to database
:return: bool
"""
return cls.get_settings().state_management_save_previous
def state_management_replace_objects(cls) -> bool:
"""
Should objects be replaced when using state management
:return: bool
"""
return cls.get_settings().state_management_replace_objects
def _save_state(self) -> None:
"""
Save current document state. Internal method
:return: None
"""
if self.use_state_management() and self.id is not None:
if self.state_management_save_previous():
self._previous_saved_state = self._saved_state
self._saved_state = get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
exclude={"revision_id"},
)
def get_saved_state(self) -> Optional[Dict[str, Any]]:
"""
Saved state getter. It is protected property.
:return: Optional[Dict[str, Any]] - saved state
"""
return self._saved_state
def get_previous_saved_state(self) -> Optional[Dict[str, Any]]:
"""
Previous state getter. It is a protected property.
:return: Optional[Dict[str, Any]] - previous state
"""
return self._previous_saved_state
def is_changed(self) -> bool:
if self._saved_state == get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
exclude={"revision_id"},
):
return False
return True
def has_changed(self) -> bool:
if (
self._previous_saved_state is None
or self._previous_saved_state == self._saved_state
):
return False
return True
def _collect_updates(
self, old_dict: Dict[str, Any], new_dict: Dict[str, Any]
) -> Dict[str, Any]:
"""
Compares old_dict with new_dict and returns field paths that have been updated
Args:
old_dict: dict1
new_dict: dict2
Returns: dictionary with updates
"""
updates = {}
if old_dict.keys() - new_dict.keys():
updates = new_dict
else:
for field_name, field_value in new_dict.items():
if field_value != old_dict.get(field_name):
if not self.state_management_replace_objects() and (
isinstance(field_value, dict)
and isinstance(old_dict.get(field_name), dict)
):
if old_dict.get(field_name) is None:
updates[field_name] = field_value
elif isinstance(field_value, dict) and isinstance(
old_dict.get(field_name), dict
):
field_data = self._collect_updates(
old_dict.get(field_name), # type: ignore
field_value,
)
for k, v in field_data.items():
updates[f"{field_name}.{k}"] = v
else:
updates[field_name] = field_value
return updates
def get_changes(self) -> Dict[str, Any]:
return self._collect_updates(
self._saved_state, # type: ignore
get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
exclude={"revision_id"},
),
)
def get_previous_changes(self) -> Dict[str, Any]:
if self._previous_saved_state is None:
return {}
return self._collect_updates(
self._previous_saved_state,
self._saved_state, # type: ignore
)
def rollback(self) -> None:
if self.is_changed:
for key, value in self._saved_state.items(): # type: ignore
if key == "_id":
setattr(self, "id", value)
else:
setattr(self, key, value)
# Other
def get_settings(cls) -> DocumentSettings:
"""
Get document settings, which was created on
the initialization step
:return: DocumentSettings class
"""
if cls._document_settings is None:
raise CollectionWasNotInitialized
return cls._document_settings
async def inspect_collection(
cls, session: Optional[ClientSession] = None
) -> InspectionResult:
"""
Check, if documents, stored in the MongoDB collection
are compatible with the Document schema
:return: InspectionResult
"""
inspection_result = InspectionResult()
async for json_document in cls.get_motor_collection().find(
{}, session=session
):
try:
parse_model(cls, json_document)
except ValidationError as e:
if inspection_result.status == InspectionStatuses.OK:
inspection_result.status = InspectionStatuses.FAIL
inspection_result.errors.append(
InspectionError(
document_id=json_document["_id"], error=str(e)
)
)
return inspection_result
def check_hidden_fields(cls):
hidden_fields = [
(name, field)
for name, field in get_model_fields(cls).items()
if get_extra_field_info(field, "hidden") is True
]
if not hidden_fields:
return
warnings.warn(
f"{cls.__name__}: 'hidden=True' is deprecated, please use 'exclude=True'",
DeprecationWarning,
)
if IS_PYDANTIC_V2:
for name, field in hidden_fields:
field.exclude = True
del field.json_schema_extra["hidden"]
cls.model_rebuild(force=True)
else:
for name, field in hidden_fields:
field.field_info.exclude = True
del field.field_info.extra["hidden"]
cls.__exclude_fields__[name] = True
async def validate_self(self, *args, **kwargs):
# TODO: it can be sync, but needs some actions controller improvements
if self.get_settings().validate_on_save:
new_model = parse_model(self.__class__, get_model_dump(self))
merge_models(self, new_model)
def to_ref(self):
if self.id is None:
raise DocumentWasNotSaved("Can not create dbref without id")
return DBRef(self.get_motor_collection().name, self.id)
async def fetch_link(self, field: Union[str, Any]):
ref_obj = getattr(self, field, None)
if isinstance(ref_obj, Link):
value = await ref_obj.fetch(fetch_links=True)
setattr(self, field, value)
if isinstance(ref_obj, list) and ref_obj:
values = await Link.fetch_list(ref_obj, fetch_links=True)
setattr(self, field, values)
async def fetch_all_links(self):
coros = []
link_fields = self.get_link_fields()
if link_fields is not None:
for ref in link_fields.values():
coros.append(self.fetch_link(ref.field_name)) # TODO lists
await asyncio.gather(*coros)
def get_link_fields(cls) -> Optional[Dict[str, LinkInfo]]:
return cls._link_fields
def get_model_type(cls) -> ModelType:
return ModelType.Document
async def distinct(
cls,
key: str,
filter: Optional[Mapping[str, Any]] = None,
session: Optional[ClientSession] = None,
**kwargs: Any,
) -> list:
return await cls.get_motor_collection().distinct(
key, filter, session, **kwargs
)
def link_from_id(cls, id: Any):
ref = DBRef(id=id, collection=cls.get_collection_name())
return Link(ref, document_class=cls)
def parse_model(model_type: Type[BaseModel], data: Any):
if IS_PYDANTIC_V2:
return model_type.model_validate(data)
else:
return model_type.parse_obj(data)
def iterative_migration(
document_models: Optional[List[Type[Document]]] = None,
batch_size: int = 10000,
):
class IterativeMigration(BaseMigrationController):
def __init__(self, function):
self.function = function
self.function_signature = signature(function)
input_signature = self.function_signature.parameters.get(
"input_document"
)
if input_signature is None:
raise RuntimeError("input_signature must not be None")
self.input_document_model: Type[
Document
] = input_signature.annotation
output_signature = self.function_signature.parameters.get(
"output_document"
)
if output_signature is None:
raise RuntimeError("output_signature must not be None")
self.output_document_model: Type[
Document
] = output_signature.annotation
if (
not isclass(self.input_document_model)
or not issubclass(self.input_document_model, Document)
or not isclass(self.output_document_model)
or not issubclass(self.output_document_model, Document)
):
raise TypeError(
"input_document and output_document "
"must have annotation of Document subclass"
)
self.batch_size = batch_size
def __call__(self, *args, **kwargs):
pass
@property
def models(self) -> List[Type[Document]]:
preset_models = document_models
if preset_models is None:
preset_models = []
return preset_models + [
self.input_document_model,
self.output_document_model,
]
async def run(self, session):
output_documents = []
all_migration_ops = []
async for input_document in self.input_document_model.find_all(
session=session
):
output = DummyOutput()
function_kwargs = {
"input_document": input_document,
"output_document": output,
}
if "self" in self.function_signature.parameters:
function_kwargs["self"] = None
await self.function(**function_kwargs)
output_dict = input_document.dict()
update_dict(output_dict, output.dict())
output_document = parse_model(
self.output_document_model, output_dict
)
output_documents.append(output_document)
if len(output_documents) == self.batch_size:
all_migration_ops.append(
self.output_document_model.replace_many(
documents=output_documents, session=session
)
)
output_documents = []
if output_documents:
all_migration_ops.append(
self.output_document_model.replace_many(
documents=output_documents, session=session
)
)
await asyncio.gather(*all_migration_ops)
return IterativeMigration | null |
167,786 | import pydantic
def is_second_version() -> bool:
return int(pydantic.VERSION.split(".")[0]) >= 2 | null |
167,787 | import asyncio
import logging
import os
import shutil
from datetime import datetime
from pathlib import Path
from typing import Any
import click
import toml
from beanie.migrations import template
from beanie.migrations.database import DBHandler
from beanie.migrations.models import RunningDirections, RunningMode
from beanie.migrations.runner import MigrationNode
def migrations():
pass | null |
167,788 | import asyncio
import logging
import os
import shutil
from datetime import datetime
from pathlib import Path
from typing import Any
import click
import toml
from beanie.migrations import template
from beanie.migrations.database import DBHandler
from beanie.migrations.models import RunningDirections, RunningMode
from beanie.migrations.runner import MigrationNode
class MigrationSettings:
def __init__(self, **kwargs):
def get_env_value(field_name) -> Any:
def get_from_toml(field_name) -> Any:
async def run_migrate(settings: MigrationSettings):
def migrate(
direction,
distance,
connection_uri,
database_name,
path,
allow_index_dropping,
use_transaction,
):
settings_kwargs = {}
if direction:
settings_kwargs["direction"] = direction
if distance:
settings_kwargs["distance"] = distance
if connection_uri:
settings_kwargs["connection_uri"] = connection_uri
if database_name:
settings_kwargs["database_name"] = database_name
if path:
settings_kwargs["path"] = path
if allow_index_dropping:
settings_kwargs["allow_index_dropping"] = allow_index_dropping
settings_kwargs["use_transaction"] = use_transaction
settings = MigrationSettings(**settings_kwargs)
asyncio.run(run_migrate(settings)) | null |
167,789 | import asyncio
import logging
import os
import shutil
from datetime import datetime
from pathlib import Path
from typing import Any
import click
import toml
from beanie.migrations import template
from beanie.migrations.database import DBHandler
from beanie.migrations.models import RunningDirections, RunningMode
from beanie.migrations.runner import MigrationNode
def new_migration(name, path):
path = Path(path)
ts_string = datetime.now().strftime("%Y%m%d%H%M%S")
file_name = f"{ts_string}_{name}.py"
shutil.copy(template.__file__, path / file_name) | null |
167,790 | import asyncio
import inspect
from enum import Enum
from functools import wraps
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Type,
Union,
)
class EventTypes(str, Enum):
INSERT = "INSERT"
REPLACE = "REPLACE"
SAVE = "SAVE"
SAVE_CHANGES = "SAVE_CHANGES"
VALIDATE_ON_SAVE = "VALIDATE_ON_SAVE"
DELETE = "DELETE"
UPDATE = "UPDATE"
class ActionDirections(str, Enum): # TODO think about this name
BEFORE = "BEFORE"
AFTER = "AFTER"
def register_action(
event_types: Tuple[Union[List[EventTypes], EventTypes]],
action_direction: ActionDirections,
):
"""
Decorator. Base registration method.
Used inside `before_event` and `after_event`
:param event_types: Union[List[EventTypes], EventTypes] - event types
:param action_direction: ActionDirections - before or after
:return:
"""
final_event_types = []
for event_type in event_types:
if isinstance(event_type, list):
final_event_types.extend(event_type)
else:
final_event_types.append(event_type)
def decorator(f):
f.has_action = True
f.event_types = final_event_types
f.action_direction = action_direction
return f
return decorator
The provided code snippet includes necessary dependencies for implementing the `before_event` function. Write a Python function `def before_event(*args: Union[List[EventTypes], EventTypes])` to solve the following problem:
Decorator. It adds action, which should run before mentioned one or many events happen :param args: Union[List[EventTypes], EventTypes] - event types :return: None
Here is the function:
def before_event(*args: Union[List[EventTypes], EventTypes]):
"""
Decorator. It adds action, which should run before mentioned one
or many events happen
:param args: Union[List[EventTypes], EventTypes] - event types
:return: None
"""
return register_action(
action_direction=ActionDirections.BEFORE, event_types=args # type: ignore
) | Decorator. It adds action, which should run before mentioned one or many events happen :param args: Union[List[EventTypes], EventTypes] - event types :return: None |
167,791 | import asyncio
import inspect
from enum import Enum
from functools import wraps
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Type,
Union,
)
class EventTypes(str, Enum):
INSERT = "INSERT"
REPLACE = "REPLACE"
SAVE = "SAVE"
SAVE_CHANGES = "SAVE_CHANGES"
VALIDATE_ON_SAVE = "VALIDATE_ON_SAVE"
DELETE = "DELETE"
UPDATE = "UPDATE"
class ActionDirections(str, Enum): # TODO think about this name
BEFORE = "BEFORE"
AFTER = "AFTER"
def register_action(
event_types: Tuple[Union[List[EventTypes], EventTypes]],
action_direction: ActionDirections,
):
"""
Decorator. Base registration method.
Used inside `before_event` and `after_event`
:param event_types: Union[List[EventTypes], EventTypes] - event types
:param action_direction: ActionDirections - before or after
:return:
"""
final_event_types = []
for event_type in event_types:
if isinstance(event_type, list):
final_event_types.extend(event_type)
else:
final_event_types.append(event_type)
def decorator(f):
f.has_action = True
f.event_types = final_event_types
f.action_direction = action_direction
return f
return decorator
The provided code snippet includes necessary dependencies for implementing the `after_event` function. Write a Python function `def after_event(*args: Union[List[EventTypes], EventTypes])` to solve the following problem:
Decorator. It adds action, which should run after mentioned one or many events happen :param args: Union[List[EventTypes], EventTypes] - event types :return: None
Here is the function:
def after_event(*args: Union[List[EventTypes], EventTypes]):
"""
Decorator. It adds action, which should run after mentioned one
or many events happen
:param args: Union[List[EventTypes], EventTypes] - event types
:return: None
"""
return register_action(
action_direction=ActionDirections.AFTER, event_types=args # type: ignore
) | Decorator. It adds action, which should run after mentioned one or many events happen :param args: Union[List[EventTypes], EventTypes] - event types :return: None |
167,792 | import asyncio
import inspect
from enum import Enum
from functools import wraps
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Type,
Union,
)
class EventTypes(str, Enum):
INSERT = "INSERT"
REPLACE = "REPLACE"
SAVE = "SAVE"
SAVE_CHANGES = "SAVE_CHANGES"
VALIDATE_ON_SAVE = "VALIDATE_ON_SAVE"
DELETE = "DELETE"
UPDATE = "UPDATE"
class ActionDirections(str, Enum): # TODO think about this name
BEFORE = "BEFORE"
AFTER = "AFTER"
class ActionRegistry:
_actions: Dict[
Type["Document"],
Dict[EventTypes, Dict[ActionDirections, List[Callable[..., Any]]]],
] = {}
def clean_actions(cls, document_class: Type["Document"]):
if cls._actions.get(document_class) is not None:
del cls._actions[document_class]
def add_action(
cls,
document_class: Type["Document"],
event_types: List[EventTypes],
action_direction: ActionDirections,
funct: Callable,
):
"""
Add action to the action registry
:param document_class: document class
:param event_types: List[EventTypes]
:param action_direction: ActionDirections - before or after
:param funct: Callable - function
"""
if cls._actions.get(document_class) is None:
cls._actions[document_class] = {
action_type: {
action_direction: []
for action_direction in ActionDirections
}
for action_type in EventTypes
}
for event_type in event_types:
cls._actions[document_class][event_type][action_direction].append(
funct
)
def get_action_list(
cls,
document_class: Type["Document"],
event_type: EventTypes,
action_direction: ActionDirections,
) -> List[Callable]:
"""
Get stored action list
:param document_class: Type - document class
:param event_type: EventTypes - type of needed event
:param action_direction: ActionDirections - before or after
:return: List[Callable] - list of stored methods
"""
if document_class not in cls._actions:
return []
return cls._actions[document_class][event_type][action_direction]
async def run_actions(
cls,
instance: "Document",
event_type: EventTypes,
action_direction: ActionDirections,
exclude: List[Union[ActionDirections, str]],
):
"""
Run actions
:param instance: Document - object of the Document subclass
:param event_type: EventTypes - event types
:param action_direction: ActionDirections - before or after
"""
if action_direction in exclude:
return
document_class = instance.__class__
actions_list = cls.get_action_list(
document_class, event_type, action_direction
)
coros = []
for action in actions_list:
if action.__name__ in exclude:
continue
if inspect.iscoroutinefunction(action):
coros.append(action(instance))
elif inspect.isfunction(action):
action(instance)
await asyncio.gather(*coros)
The provided code snippet includes necessary dependencies for implementing the `wrap_with_actions` function. Write a Python function `def wrap_with_actions(event_type: EventTypes)` to solve the following problem:
Helper function to wrap Document methods with before and after event listeners :param event_type: EventTypes - event types :return: None
Here is the function:
def wrap_with_actions(event_type: EventTypes):
"""
Helper function to wrap Document methods with
before and after event listeners
:param event_type: EventTypes - event types
:return: None
"""
def decorator(f: Callable):
@wraps(f)
async def wrapper(
self,
*args,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
**kwargs,
):
if skip_actions is None:
skip_actions = []
await ActionRegistry.run_actions(
self,
event_type=event_type,
action_direction=ActionDirections.BEFORE,
exclude=skip_actions,
)
result = await f(self, *args, skip_actions=skip_actions, **kwargs)
await ActionRegistry.run_actions(
self,
event_type=event_type,
action_direction=ActionDirections.AFTER,
exclude=skip_actions,
)
return result
return wrapper
return decorator | Helper function to wrap Document methods with before and after event listeners :param event_type: EventTypes - event types :return: None |
167,793 | from typing import Any
import bson
import pydantic
from typing_extensions import Annotated
from beanie.odm.utils.pydantic import IS_PYDANTIC_V2
def _to_bson_binary(value: Any) -> bson.Binary:
return value if isinstance(value, bson.Binary) else bson.Binary(value) | null |
167,794 | import asyncio
import warnings
from enum import Enum
from typing import (
Any,
ClassVar,
Dict,
Iterable,
List,
Mapping,
Optional,
Type,
TypeVar,
Union,
)
from uuid import UUID, uuid4
from bson import DBRef, ObjectId
from lazy_model import LazyModel
from pydantic import (
ConfigDict,
Field,
PrivateAttr,
ValidationError,
)
from pydantic.class_validators import root_validator
from pydantic.main import BaseModel
from pymongo import InsertOne
from pymongo.client_session import ClientSession
from pymongo.errors import DuplicateKeyError
from pymongo.results import (
DeleteResult,
InsertManyResult,
)
from beanie.exceptions import (
CollectionWasNotInitialized,
DocumentNotFound,
DocumentWasNotSaved,
NotSupported,
ReplaceError,
RevisionIdWasChanged,
)
from beanie.odm.actions import (
ActionDirections,
EventTypes,
wrap_with_actions,
)
from beanie.odm.bulk import BulkWriter, Operation
from beanie.odm.cache import LRUCache
from beanie.odm.fields import (
BackLink,
DeleteRules,
ExpressionField,
Link,
LinkInfo,
LinkTypes,
PydanticObjectId,
WriteRules,
)
from beanie.odm.interfaces.aggregate import AggregateInterface
from beanie.odm.interfaces.detector import ModelType
from beanie.odm.interfaces.find import FindInterface
from beanie.odm.interfaces.getters import OtherGettersInterface
from beanie.odm.interfaces.inheritance import InheritanceInterface
from beanie.odm.interfaces.setters import SettersInterface
from beanie.odm.models import (
InspectionError,
InspectionResult,
InspectionStatuses,
)
from beanie.odm.operators.find.comparison import In
from beanie.odm.operators.update.general import (
CurrentDate,
Inc,
SetRevisionId,
Unset,
)
from beanie.odm.operators.update.general import (
Set as SetOperator,
)
from beanie.odm.queries.update import UpdateMany, UpdateResponse
from beanie.odm.settings.document import DocumentSettings
from beanie.odm.utils.dump import get_dict, get_top_level_nones
from beanie.odm.utils.parsing import apply_changes, merge_models
from beanie.odm.utils.pydantic import (
IS_PYDANTIC_V2,
get_extra_field_info,
get_field_type,
get_model_dump,
get_model_fields,
parse_model,
parse_object_as,
)
from beanie.odm.utils.self_validation import validate_self_before
from beanie.odm.utils.state import (
previous_saved_state_needed,
save_state_after,
saved_state_needed,
)
from beanie.odm.utils.typing import extract_id_class
if IS_PYDANTIC_V2:
from pydantic import model_validator
IS_PYDANTIC_V2 = int(pydantic.VERSION.split(".")[0]) >= 2
if IS_PYDANTIC_V2:
from pydantic import TypeAdapter
else:
from pydantic import parse_obj_as
def get_model_fields(model):
if IS_PYDANTIC_V2:
return model.model_fields
else:
return model.__fields__
def json_schema_extra(schema: Dict[str, Any], model: Type["Document"]) -> None:
# remove excluded fields from the json schema
properties = schema.get("properties")
if not properties:
return
for k, field in get_model_fields(model).items():
k = field.alias or k
if k not in properties:
continue
field_info = field if IS_PYDANTIC_V2 else field.field_info
if field_info.exclude:
del properties[k] | null |
167,795 | import asyncio
import warnings
from enum import Enum
from typing import (
Any,
ClassVar,
Dict,
Iterable,
List,
Mapping,
Optional,
Type,
TypeVar,
Union,
)
from uuid import UUID, uuid4
from bson import DBRef, ObjectId
from lazy_model import LazyModel
from pydantic import (
ConfigDict,
Field,
PrivateAttr,
ValidationError,
)
from pydantic.class_validators import root_validator
from pydantic.main import BaseModel
from pymongo import InsertOne
from pymongo.client_session import ClientSession
from pymongo.errors import DuplicateKeyError
from pymongo.results import (
DeleteResult,
InsertManyResult,
)
from beanie.exceptions import (
CollectionWasNotInitialized,
DocumentNotFound,
DocumentWasNotSaved,
NotSupported,
ReplaceError,
RevisionIdWasChanged,
)
from beanie.odm.actions import (
ActionDirections,
EventTypes,
wrap_with_actions,
)
from beanie.odm.bulk import BulkWriter, Operation
from beanie.odm.cache import LRUCache
from beanie.odm.fields import (
BackLink,
DeleteRules,
ExpressionField,
Link,
LinkInfo,
LinkTypes,
PydanticObjectId,
WriteRules,
)
from beanie.odm.interfaces.aggregate import AggregateInterface
from beanie.odm.interfaces.detector import ModelType
from beanie.odm.interfaces.find import FindInterface
from beanie.odm.interfaces.getters import OtherGettersInterface
from beanie.odm.interfaces.inheritance import InheritanceInterface
from beanie.odm.interfaces.setters import SettersInterface
from beanie.odm.models import (
InspectionError,
InspectionResult,
InspectionStatuses,
)
from beanie.odm.operators.find.comparison import In
from beanie.odm.operators.update.general import (
CurrentDate,
Inc,
SetRevisionId,
Unset,
)
from beanie.odm.operators.update.general import (
Set as SetOperator,
)
from beanie.odm.queries.update import UpdateMany, UpdateResponse
from beanie.odm.settings.document import DocumentSettings
from beanie.odm.utils.dump import get_dict, get_top_level_nones
from beanie.odm.utils.parsing import apply_changes, merge_models
from beanie.odm.utils.pydantic import (
IS_PYDANTIC_V2,
get_extra_field_info,
get_field_type,
get_model_dump,
get_model_fields,
parse_model,
parse_object_as,
)
from beanie.odm.utils.self_validation import validate_self_before
from beanie.odm.utils.state import (
previous_saved_state_needed,
save_state_after,
saved_state_needed,
)
from beanie.odm.utils.typing import extract_id_class
def document_alias_generator(s: str) -> str:
if s == "id":
return "_id"
return s | null |
167,796 | import asyncio
import sys
from collections import OrderedDict
from dataclasses import dataclass
from enum import Enum
from typing import (
TYPE_CHECKING,
Any,
Dict,
Generic,
List,
Optional,
Type,
TypeVar,
Union,
)
from typing import OrderedDict as OrderedDictType
from typing import Tuple
from bson import DBRef, ObjectId
from bson.errors import InvalidId
from pydantic import BaseModel
from pymongo import ASCENDING, IndexModel
from beanie.odm.enums import SortDirection
from beanie.odm.operators.find.comparison import (
GT,
GTE,
LT,
LTE,
NE,
Eq,
In,
)
from beanie.odm.registry import DocsRegistry
from beanie.odm.utils.parsing import parse_obj
from beanie.odm.utils.pydantic import (
IS_PYDANTIC_V2,
get_field_type,
get_model_fields,
parse_object_as,
)
if IS_PYDANTIC_V2:
from pydantic import (
GetCoreSchemaHandler,
GetJsonSchemaHandler,
TypeAdapter,
)
from pydantic.json_schema import JsonSchemaValue
from pydantic_core import CoreSchema, core_schema
from pydantic_core.core_schema import (
ValidationInfo,
simple_ser_schema,
str_schema,
)
else:
from pydantic.fields import ModelField # type: ignore
from pydantic.json import ENCODERS_BY_TYPE
class IndexedAnnotation:
_indexed: Tuple[int, Dict[str, Any]]
if not IS_PYDANTIC_V2:
ENCODERS_BY_TYPE[
PydanticObjectId
] = str # it is a workaround to force pydantic make json schema for this field
if not IS_PYDANTIC_V2:
ENCODERS_BY_TYPE[Link] = lambda o: o.to_dict()
if not IS_PYDANTIC_V2:
ENCODERS_BY_TYPE[BackLink] = lambda o: o.to_dict()
IS_PYDANTIC_V2 = int(pydantic.VERSION.split(".")[0]) >= 2
if IS_PYDANTIC_V2:
from pydantic import TypeAdapter
else:
from pydantic import parse_obj_as
The provided code snippet includes necessary dependencies for implementing the `Indexed` function. Write a Python function `def Indexed(typ=None, index_type=ASCENDING, **kwargs)` to solve the following problem:
If `typ` is defined, returns a subclass of `typ` with an extra attribute `_indexed` as a tuple: - Index 0: `index_type` such as `pymongo.ASCENDING` - Index 1: `kwargs` passed to `IndexModel` When instantiated the type of the result will actually be `typ`. When `typ` is not defined, returns an `IndexedAnnotation` instance, to be used as metadata in `Annotated` fields. Example: ```py # Both fields would have the same behavior class MyModel(BaseModel): field1: Indexed(str, unique=True) field2: Annotated[str, Indexed(unique=True)] ```
Here is the function:
def Indexed(typ=None, index_type=ASCENDING, **kwargs):
"""
If `typ` is defined, returns a subclass of `typ` with an extra attribute
`_indexed` as a tuple:
- Index 0: `index_type` such as `pymongo.ASCENDING`
- Index 1: `kwargs` passed to `IndexModel`
When instantiated the type of the result will actually be `typ`.
When `typ` is not defined, returns an `IndexedAnnotation` instance, to be
used as metadata in `Annotated` fields.
Example:
```py
# Both fields would have the same behavior
class MyModel(BaseModel):
field1: Indexed(str, unique=True)
field2: Annotated[str, Indexed(unique=True)]
```
"""
if typ is None:
return IndexedAnnotation(_indexed=(index_type, kwargs))
class NewType(typ):
_indexed = (index_type, kwargs)
def __new__(cls, *args, **kwargs):
return typ.__new__(typ, *args, **kwargs)
if IS_PYDANTIC_V2:
@classmethod
def __get_pydantic_core_schema__(
cls, _source_type: Any, _handler: GetCoreSchemaHandler
) -> core_schema.CoreSchema:
custom_type = getattr(
typ, "__get_pydantic_core_schema__", None
)
if custom_type is not None:
return custom_type(_source_type, _handler)
return core_schema.no_info_after_validator_function(
lambda v: v,
simple_ser_schema(typ.__name__),
)
NewType.__name__ = f"Indexed {typ.__name__}"
return NewType | If `typ` is defined, returns a subclass of `typ` with an extra attribute `_indexed` as a tuple: - Index 0: `index_type` such as `pymongo.ASCENDING` - Index 1: `kwargs` passed to `IndexModel` When instantiated the type of the result will actually be `typ`. When `typ` is not defined, returns an `IndexedAnnotation` instance, to be used as metadata in `Annotated` fields. Example: ```py # Both fields would have the same behavior class MyModel(BaseModel): field1: Indexed(str, unique=True) field2: Annotated[str, Indexed(unique=True)] ``` |
167,797 | from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Type
from beanie.odm.fields import LinkInfo, LinkTypes
def construct_query(
link_info: LinkInfo,
queries: List,
database_major_version: int,
current_depth: Optional[int] = None,
):
if link_info.is_fetchable is False or (
current_depth is not None and current_depth <= 0
):
return
if link_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
]:
if database_major_version >= 5 or link_info.nested_links is None:
lookup_steps = [
{
"$lookup": {
"from": link_info.document_class.get_motor_collection().name, # type: ignore
"localField": f"{link_info.lookup_field_name}.$id",
"foreignField": "_id",
"as": f"_link_{link_info.field_name}",
}
},
{
"$unwind": {
"path": f"$_link_{link_info.field_name}",
"preserveNullAndEmptyArrays": True,
}
},
{
"$set": {
link_info.field_name: {
"$cond": {
"if": {
"$ifNull": [
f"$_link_{link_info.field_name}",
False,
]
},
"then": f"$_link_{link_info.field_name}",
"else": f"${link_info.field_name}",
}
}
}
},
{"$unset": f"_link_{link_info.field_name}"},
] # type: ignore
new_depth = (
current_depth - 1 if current_depth is not None else None
)
if link_info.nested_links is not None:
lookup_steps[0]["$lookup"]["pipeline"] = [] # type: ignore
for nested_link in link_info.nested_links:
construct_query(
link_info=link_info.nested_links[nested_link],
queries=lookup_steps[0]["$lookup"]["pipeline"], # type: ignore
database_major_version=database_major_version,
current_depth=new_depth,
)
queries += lookup_steps
else:
lookup_steps = [
{
"$lookup": {
"from": link_info.document_class.get_motor_collection().name, # type: ignore
"let": {
"link_id": f"${link_info.lookup_field_name}.$id"
},
"as": f"_link_{link_info.field_name}",
"pipeline": [
{
"$match": {
"$expr": {"$eq": ["$_id", "$$link_id"]}
}
},
],
}
},
{
"$unwind": {
"path": f"$_link_{link_info.field_name}",
"preserveNullAndEmptyArrays": True,
}
},
{
"$set": {
link_info.field_name: {
"$cond": {
"if": {
"$ifNull": [
f"$_link_{link_info.field_name}",
False,
]
},
"then": f"$_link_{link_info.field_name}",
"else": f"${link_info.field_name}",
}
}
}
},
{"$unset": f"_link_{link_info.field_name}"},
]
new_depth = (
current_depth - 1 if current_depth is not None else None
)
for nested_link in link_info.nested_links:
construct_query(
link_info=link_info.nested_links[nested_link],
queries=lookup_steps[0]["$lookup"]["pipeline"], # type: ignore
database_major_version=database_major_version,
current_depth=new_depth,
)
queries += lookup_steps
elif link_info.link_type in [
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if database_major_version >= 5 or link_info.nested_links is None:
lookup_steps = [
{
"$lookup": {
"from": link_info.document_class.get_motor_collection().name, # type: ignore
"localField": "_id",
"foreignField": f"{link_info.lookup_field_name}.$id",
"as": f"_link_{link_info.field_name}",
}
},
{
"$unwind": {
"path": f"$_link_{link_info.field_name}",
"preserveNullAndEmptyArrays": True,
}
},
{
"$set": {
link_info.field_name: {
"$cond": {
"if": {
"$ifNull": [
f"$_link_{link_info.field_name}",
False,
]
},
"then": f"$_link_{link_info.field_name}",
"else": f"${link_info.field_name}",
}
}
}
},
{"$unset": f"_link_{link_info.field_name}"},
] # type: ignore
new_depth = (
current_depth - 1 if current_depth is not None else None
)
if link_info.nested_links is not None:
lookup_steps[0]["$lookup"]["pipeline"] = [] # type: ignore
for nested_link in link_info.nested_links:
construct_query(
link_info=link_info.nested_links[nested_link],
queries=lookup_steps[0]["$lookup"]["pipeline"], # type: ignore
database_major_version=database_major_version,
current_depth=new_depth,
)
queries += lookup_steps
else:
lookup_steps = [
{
"$lookup": {
"from": link_info.document_class.get_motor_collection().name, # type: ignore
"let": {"link_id": "$_id"},
"as": f"_link_{link_info.field_name}",
"pipeline": [
{
"$match": {
"$expr": {
"$eq": [
f"${link_info.lookup_field_name}.$id",
"$$link_id",
]
}
}
},
],
}
},
{
"$unwind": {
"path": f"$_link_{link_info.field_name}",
"preserveNullAndEmptyArrays": True,
}
},
{
"$set": {
link_info.field_name: {
"$cond": {
"if": {
"$ifNull": [
f"$_link_{link_info.field_name}",
False,
]
},
"then": f"$_link_{link_info.field_name}",
"else": f"${link_info.field_name}",
}
}
}
},
{"$unset": f"_link_{link_info.field_name}"},
]
new_depth = (
current_depth - 1 if current_depth is not None else None
)
for nested_link in link_info.nested_links:
construct_query(
link_info=link_info.nested_links[nested_link],
queries=lookup_steps[0]["$lookup"]["pipeline"], # type: ignore
database_major_version=database_major_version,
current_depth=new_depth,
)
queries += lookup_steps
elif link_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
]:
if database_major_version >= 5 or link_info.nested_links is None:
queries.append(
{
"$lookup": {
"from": link_info.document_class.get_motor_collection().name, # type: ignore
"localField": f"{link_info.lookup_field_name}.$id",
"foreignField": "_id",
"as": link_info.field_name,
}
}
)
new_depth = (
current_depth - 1 if current_depth is not None else None
)
if link_info.nested_links is not None:
queries[-1]["$lookup"]["pipeline"] = []
for nested_link in link_info.nested_links:
construct_query(
link_info=link_info.nested_links[nested_link],
queries=queries[-1]["$lookup"]["pipeline"],
database_major_version=database_major_version,
current_depth=new_depth,
)
else:
lookup_step = {
"$lookup": {
"from": link_info.document_class.get_motor_collection().name, # type: ignore
"let": {"link_id": f"${link_info.lookup_field_name}.$id"},
"as": link_info.field_name,
"pipeline": [
{"$match": {"$expr": {"$in": ["$_id", "$$link_id"]}}},
],
}
}
new_depth = (
current_depth - 1 if current_depth is not None else None
)
for nested_link in link_info.nested_links:
construct_query(
link_info=link_info.nested_links[nested_link],
queries=lookup_step["$lookup"]["pipeline"],
database_major_version=database_major_version,
current_depth=new_depth,
)
queries.append(lookup_step)
elif link_info.link_type in [
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if database_major_version >= 5 or link_info.nested_links is None:
queries.append(
{
"$lookup": {
"from": link_info.document_class.get_motor_collection().name, # type: ignore
"localField": "_id",
"foreignField": f"{link_info.lookup_field_name}.$id",
"as": link_info.field_name,
}
}
)
new_depth = (
current_depth - 1 if current_depth is not None else None
)
if link_info.nested_links is not None:
queries[-1]["$lookup"]["pipeline"] = []
for nested_link in link_info.nested_links:
construct_query(
link_info=link_info.nested_links[nested_link],
queries=queries[-1]["$lookup"]["pipeline"],
database_major_version=database_major_version,
current_depth=new_depth,
)
else:
lookup_step = {
"$lookup": {
"from": link_info.document_class.get_motor_collection().name, # type: ignore
"let": {"link_id": "$_id"},
"as": link_info.field_name,
"pipeline": [
{
"$match": {
"$expr": {
"$in": [
"$$link_id",
f"${link_info.lookup_field_name}.$id",
]
}
}
}
],
}
}
new_depth = (
current_depth - 1 if current_depth is not None else None
)
for nested_link in link_info.nested_links:
construct_query(
link_info=link_info.nested_links[nested_link],
queries=lookup_step["$lookup"]["pipeline"],
database_major_version=database_major_version,
current_depth=new_depth,
)
queries.append(lookup_step)
return queries
def construct_lookup_queries(
cls: Type["Document"],
nesting_depth: Optional[int] = None,
nesting_depths_per_field: Optional[Dict[str, int]] = None,
) -> List[Dict[str, Any]]:
queries: List = []
link_fields = cls.get_link_fields()
if link_fields is not None:
for link_info in link_fields.values():
final_nesting_depth = (
nesting_depths_per_field.get(link_info.field_name, None)
if nesting_depths_per_field is not None
else None
)
if final_nesting_depth is None:
final_nesting_depth = nesting_depth
construct_query(
link_info=link_info,
queries=queries,
database_major_version=cls._database_major_version,
current_depth=final_nesting_depth,
)
return queries | null |
167,798 | from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Type
from beanie.odm.fields import LinkInfo, LinkTypes
The provided code snippet includes necessary dependencies for implementing the `split_text_query` function. Write a Python function `def split_text_query( query: Dict[str, Any] ) -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]]]` to solve the following problem:
Divide query into text and non-text matches :param query: Dict[str, Any] - query dict :return: Tuple[Dict[str, Any], Dict[str, Any]] - text and non-text queries, respectively
Here is the function:
def split_text_query(
query: Dict[str, Any]
) -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]]]:
"""Divide query into text and non-text matches
:param query: Dict[str, Any] - query dict
:return: Tuple[Dict[str, Any], Dict[str, Any]] - text and non-text queries,
respectively
"""
root_text_query_args: Dict[str, Any] = query.get("$text", None)
root_non_text_queries: Dict[str, Any] = {
k: v for k, v in query.items() if k not in {"$text", "$and"}
}
text_queries: List[Dict[str, Any]] = (
[{"$text": root_text_query_args}] if root_text_query_args else []
)
non_text_queries: List[Dict[str, Any]] = (
[root_non_text_queries] if root_non_text_queries else []
)
for match_case in query.get("$and", []):
if "$text" in match_case:
text_queries.append(match_case)
else:
non_text_queries.append(match_case)
return text_queries, non_text_queries | Divide query into text and non-text matches :param query: Dict[str, Any] - query dict :return: Tuple[Dict[str, Any], Dict[str, Any]] - text and non-text queries, respectively |
167,799 | import asyncio
import sys
from beanie.odm.utils.pydantic import (
IS_PYDANTIC_V2,
get_extra_field_info,
get_model_fields,
parse_model,
)
from beanie.odm.utils.typing import get_index_attributes
import importlib
import inspect
from typing import ( # type: ignore
List,
Optional,
Type,
Union,
_GenericAlias,
)
from motor.motor_asyncio import AsyncIOMotorClient, AsyncIOMotorDatabase
from pydantic import BaseModel
from pydantic.fields import FieldInfo
from pymongo import IndexModel
from beanie.exceptions import Deprecation, MongoDBVersionError
from beanie.odm.actions import ActionRegistry
from beanie.odm.cache import LRUCache
from beanie.odm.documents import DocType, Document
from beanie.odm.fields import (
BackLink,
ExpressionField,
Link,
LinkInfo,
LinkTypes,
)
from beanie.odm.interfaces.detector import ModelType
from beanie.odm.registry import DocsRegistry
from beanie.odm.settings.document import DocumentSettings, IndexModelField
from beanie.odm.settings.union_doc import UnionDocSettings
from beanie.odm.settings.view import ViewSettings
from beanie.odm.union_doc import UnionDoc
from beanie.odm.views import View
class Initializer:
def __init__(
self,
database: AsyncIOMotorDatabase = None,
connection_string: Optional[str] = None,
document_models: Optional[
List[Union[Type["DocType"], Type["View"], str]]
] = None,
allow_index_dropping: bool = False,
recreate_views: bool = False,
multiprocessing_mode: bool = False,
):
"""
Beanie initializer
:param database: AsyncIOMotorDatabase - motor database instance
:param connection_string: str - MongoDB connection string
:param document_models: List[Union[Type[DocType], str]] - model classes
or strings with dot separated paths
:param allow_index_dropping: bool - if index dropping is allowed.
Default False
:param recreate_views: bool - if views should be recreated. Default False
:param multiprocessing_mode: bool - if multiprocessing mode is on
it will patch the motor client to use process's event loop.
:return: None
"""
self.inited_classes: List[Type] = []
self.allow_index_dropping = allow_index_dropping
self.recreate_views = recreate_views
self.models_with_updated_forward_refs: List[Type[BaseModel]] = []
if (connection_string is None and database is None) or (
connection_string is not None and database is not None
):
raise ValueError(
"connection_string parameter or database parameter must be set"
)
if document_models is None:
raise ValueError("document_models parameter must be set")
if connection_string is not None:
database = AsyncIOMotorClient(
connection_string
).get_default_database()
self.database: AsyncIOMotorDatabase = database
if multiprocessing_mode:
self.database.client.get_io_loop = asyncio.get_running_loop
sort_order = {
ModelType.UnionDoc: 0,
ModelType.Document: 1,
ModelType.View: 2,
}
self.document_models: List[Union[Type[DocType], Type[View]]] = [
self.get_model(model) if isinstance(model, str) else model
for model in document_models
]
self.fill_docs_registry()
self.document_models.sort(
key=lambda val: sort_order[val.get_model_type()]
)
def __await__(self):
for model in self.document_models:
yield from self.init_class(model).__await__()
# General
def fill_docs_registry(self):
for model in self.document_models:
module = inspect.getmodule(model)
members = inspect.getmembers(module)
for name, obj in members:
if inspect.isclass(obj) and issubclass(obj, BaseModel):
DocsRegistry.register(name, obj)
def get_model(dot_path: str) -> Type["DocType"]:
"""
Get the model by the path in format bar.foo.Model
:param dot_path: str - dot seprated path to the model
:return: Type[DocType] - class of the model
"""
module_name, class_name = None, None
try:
module_name, class_name = dot_path.rsplit(".", 1)
return getattr(importlib.import_module(module_name), class_name)
except ValueError:
raise ValueError(
f"'{dot_path}' doesn't have '.' path, eg. path.to.your.model.class"
)
except AttributeError:
raise AttributeError(
f"module '{module_name}' has no class called '{class_name}'"
)
def init_settings(
self, cls: Union[Type[Document], Type[View], Type[UnionDoc]]
):
"""
Init Settings
:param cls: Union[Type[Document], Type[View], Type[UnionDoc]] - Class
to init settings
:return: None
"""
settings_class = getattr(cls, "Settings", None)
settings_vars = (
{} if settings_class is None else dict(vars(settings_class))
)
if issubclass(cls, Document):
cls._document_settings = parse_model(
DocumentSettings, settings_vars
)
if issubclass(cls, View):
cls._settings = parse_model(ViewSettings, settings_vars)
if issubclass(cls, UnionDoc):
cls._settings = parse_model(UnionDocSettings, settings_vars)
if not IS_PYDANTIC_V2:
def update_forward_refs(self, cls: Type[BaseModel]):
"""
Update forward refs
:param cls: Type[BaseModel] - class to update forward refs
:return: None
"""
if cls not in self.models_with_updated_forward_refs:
cls.update_forward_refs()
self.models_with_updated_forward_refs.append(cls)
# General. Relations
def detect_link(
self, field: FieldInfo, field_name: str
) -> Optional[LinkInfo]:
"""
It detects link and returns LinkInfo if any found.
:param field: ModelField
:return: Optional[LinkInfo]
"""
origin = get_origin(field.annotation)
args = get_args(field.annotation)
classes = [
Link,
BackLink,
]
for cls in classes:
# Check if annotation is one of the custom classes
if (
isinstance(field.annotation, _GenericAlias)
and field.annotation.__origin__ is cls
):
if cls is Link:
return LinkInfo(
field_name=field_name,
lookup_field_name=field_name,
document_class=DocsRegistry.evaluate_fr(args[0]), # type: ignore
link_type=LinkTypes.DIRECT,
)
if cls is BackLink:
return LinkInfo(
field_name=field_name,
lookup_field_name=get_extra_field_info(
field, "original_field"
), # type: ignore
document_class=DocsRegistry.evaluate_fr(args[0]), # type: ignore
link_type=LinkTypes.BACK_DIRECT,
)
# Check if annotation is List[custom class]
elif (
(origin is List or origin is list)
and len(args) == 1
and isinstance(args[0], _GenericAlias)
and args[0].__origin__ is cls
):
if cls is Link:
return LinkInfo(
field_name=field_name,
lookup_field_name=field_name,
document_class=DocsRegistry.evaluate_fr(get_args(args[0])[0]), # type: ignore
link_type=LinkTypes.LIST,
)
if cls is BackLink:
return LinkInfo(
field_name=field_name,
lookup_field_name=get_extra_field_info( # type: ignore
field, "original_field"
),
document_class=DocsRegistry.evaluate_fr(get_args(args[0])[0]), # type: ignore
link_type=LinkTypes.BACK_LIST,
)
# Check if annotation is Optional[custom class] or Optional[List[custom class]]
elif origin is Union and len(args) == 2 and args[1] is type(None):
optional_origin = get_origin(args[0])
optional_args = get_args(args[0])
if (
isinstance(args[0], _GenericAlias)
and args[0].__origin__ is cls
):
if cls is Link:
return LinkInfo(
field_name=field_name,
lookup_field_name=field_name,
document_class=DocsRegistry.evaluate_fr(optional_args[0]), # type: ignore
link_type=LinkTypes.OPTIONAL_DIRECT,
)
if cls is BackLink:
return LinkInfo(
field_name=field_name,
lookup_field_name=get_extra_field_info(
field, "original_field"
),
document_class=DocsRegistry.evaluate_fr(optional_args[0]), # type: ignore
link_type=LinkTypes.OPTIONAL_BACK_DIRECT,
)
elif (
(optional_origin is List or optional_origin is list)
and len(optional_args) == 1
and isinstance(optional_args[0], _GenericAlias)
and optional_args[0].__origin__ is cls
):
if cls is Link:
return LinkInfo(
field_name=field_name,
lookup_field_name=field_name,
document_class=DocsRegistry.evaluate_fr(get_args(optional_args[0])[0]), # type: ignore
link_type=LinkTypes.OPTIONAL_LIST,
)
if cls is BackLink:
return LinkInfo(
field_name=field_name,
lookup_field_name=get_extra_field_info(
field, "original_field"
),
document_class=DocsRegistry.evaluate_fr(get_args(optional_args[0])[0]), # type: ignore
link_type=LinkTypes.OPTIONAL_BACK_LIST,
)
return None
def check_nested_links(self, link_info: LinkInfo, current_depth: int):
if current_depth == 1:
return
for k, v in get_model_fields(link_info.document_class).items():
nested_link_info = self.detect_link(v, k)
if nested_link_info is None:
continue
if link_info.nested_links is None:
link_info.nested_links = {}
link_info.nested_links[k] = nested_link_info
new_depth = (
current_depth - 1 if current_depth is not None else None
)
self.check_nested_links(nested_link_info, current_depth=new_depth)
# Document
def set_default_class_vars(cls: Type[Document]):
"""
Set default class variables.
:param cls: Union[Type[Document], Type[View], Type[UnionDoc]] - Class
to init settings
:return:
"""
cls._children = dict()
cls._parent = None
cls._inheritance_inited = False
cls._class_id = None
cls._link_fields = None
def init_cache(cls) -> None:
"""
Init model's cache
:return: None
"""
if cls.get_settings().use_cache:
cls._cache = LRUCache(
capacity=cls.get_settings().cache_capacity,
expiration_time=cls.get_settings().cache_expiration_time,
)
def init_document_fields(self, cls) -> None:
"""
Init class fields
:return: None
"""
if not IS_PYDANTIC_V2:
self.update_forward_refs(cls)
if cls._link_fields is None:
cls._link_fields = {}
for k, v in get_model_fields(cls).items():
path = v.alias or k
setattr(cls, k, ExpressionField(path))
link_info = self.detect_link(v, k)
depth_level = cls.get_settings().max_nesting_depths_per_field.get(
k, None
)
if depth_level is None:
depth_level = cls.get_settings().max_nesting_depth
if link_info is not None:
if depth_level > 0 or depth_level is None:
cls._link_fields[k] = link_info
self.check_nested_links(
link_info, current_depth=depth_level
)
elif depth_level <= 0:
link_info.is_fetchable = False
cls._link_fields[k] = link_info
cls.check_hidden_fields()
def init_actions(cls):
"""
Init event-based actions
"""
ActionRegistry.clean_actions(cls)
for attr in dir(cls):
f = getattr(cls, attr)
if inspect.isfunction(f):
if hasattr(f, "has_action"):
ActionRegistry.add_action(
document_class=cls,
event_types=f.event_types, # type: ignore
action_direction=f.action_direction, # type: ignore
funct=f,
)
async def init_document_collection(self, cls):
"""
Init collection for the Document-based class
:param cls:
:return:
"""
cls.set_database(self.database)
document_settings = cls.get_settings()
# register in the Union Doc
if document_settings.union_doc is not None:
name = cls.get_settings().name or cls.__name__
document_settings.name = document_settings.union_doc.register_doc(
name, cls
)
document_settings.union_doc_alias = name
# set a name
if not document_settings.name:
document_settings.name = cls.__name__
# check mongodb version fits
if (
document_settings.timeseries is not None
and cls._database_major_version < 5
):
raise MongoDBVersionError(
"Timeseries are supported by MongoDB version 5 and higher"
)
# create motor collection
if (
document_settings.timeseries is not None
and document_settings.name
not in await self.database.list_collection_names(
authorizedCollections=True, nameOnly=True
)
):
collection = await self.database.create_collection(
**document_settings.timeseries.build_query(
document_settings.name
)
)
else:
collection = self.database[document_settings.name]
cls.set_collection(collection)
async def init_indexes(self, cls, allow_index_dropping: bool = False):
"""
Async indexes initializer
"""
collection = cls.get_motor_collection()
document_settings = cls.get_settings()
index_information = await collection.index_information()
old_indexes = IndexModelField.from_motor_index_information(
index_information
)
new_indexes = []
# Indexed field wrapped with Indexed()
indexed_fields = (
(k, fvalue, get_index_attributes(fvalue))
for k, fvalue in get_model_fields(cls).items()
)
found_indexes = [
IndexModelField(
IndexModel(
[
(
fvalue.alias or k,
indexed_attrs[0],
)
],
**indexed_attrs[1],
)
)
for k, fvalue, indexed_attrs in indexed_fields
if indexed_attrs is not None
]
if document_settings.merge_indexes:
result: List[IndexModelField] = []
for subclass in reversed(cls.mro()):
if issubclass(subclass, Document) and not subclass == Document:
if (
subclass not in self.inited_classes
and not subclass == cls
):
await self.init_class(subclass)
if subclass.get_settings().indexes:
result = IndexModelField.merge_indexes(
result, subclass.get_settings().indexes
)
found_indexes = IndexModelField.merge_indexes(
found_indexes, result
)
else:
if document_settings.indexes:
found_indexes = IndexModelField.merge_indexes(
found_indexes, document_settings.indexes
)
new_indexes += found_indexes
# delete indexes
# Only drop indexes if the user specifically allows for it
if allow_index_dropping:
for index in IndexModelField.list_difference(
old_indexes, new_indexes
):
await collection.drop_index(index.name)
# create indices
if found_indexes:
new_indexes += await collection.create_indexes(
IndexModelField.list_to_index_model(new_indexes)
)
async def init_document(self, cls: Type[Document]) -> Optional[Output]:
"""
Init Document-based class
:param cls:
:return:
"""
if cls is Document:
return None
# get db version
build_info = await self.database.command({"buildInfo": 1})
mongo_version = build_info["version"]
cls._database_major_version = int(mongo_version.split(".")[0])
if cls not in self.inited_classes:
self.set_default_class_vars(cls)
self.init_settings(cls)
bases = [b for b in cls.__bases__ if issubclass(b, Document)]
if len(bases) > 1:
return None
parent = bases[0]
output = await self.init_document(parent)
if cls.get_settings().is_root and (
parent is Document or not parent.get_settings().is_root
):
if cls.get_collection_name() is None:
cls.set_collection_name(cls.__name__)
output = Output(
class_name=cls.__name__,
collection_name=cls.get_collection_name(),
)
cls._class_id = cls.__name__
cls._inheritance_inited = True
elif output is not None:
output.class_name = f"{output.class_name}.{cls.__name__}"
cls._class_id = output.class_name
cls.set_collection_name(output.collection_name)
parent.add_child(cls._class_id, cls)
cls._parent = parent
cls._inheritance_inited = True
await self.init_document_collection(cls)
await self.init_indexes(cls, self.allow_index_dropping)
self.init_document_fields(cls)
self.init_cache(cls)
self.init_actions(cls)
self.inited_classes.append(cls)
return output
else:
if cls._inheritance_inited is True:
return Output(
class_name=cls._class_id,
collection_name=cls.get_collection_name(),
)
else:
return None
# Views
def init_view_fields(self, cls) -> None:
"""
Init class fields
:return: None
"""
if cls._link_fields is None:
cls._link_fields = {}
for k, v in get_model_fields(cls).items():
path = v.alias or k
setattr(cls, k, ExpressionField(path))
link_info = self.detect_link(v, k)
depth_level = cls.get_settings().max_nesting_depths_per_field.get(
k, None
)
if depth_level is None:
depth_level = cls.get_settings().max_nesting_depth
if link_info is not None:
if depth_level > 0:
cls._link_fields[k] = link_info
self.check_nested_links(
link_info, current_depth=depth_level
)
elif depth_level <= 0:
link_info.is_fetchable = False
cls._link_fields[k] = link_info
def init_view_collection(self, cls):
"""
Init collection for View
:param cls:
:return:
"""
view_settings = cls.get_settings()
if view_settings.name is None:
view_settings.name = cls.__name__
if inspect.isclass(view_settings.source):
view_settings.source = view_settings.source.get_collection_name()
view_settings.motor_db = self.database
view_settings.motor_collection = self.database[view_settings.name]
async def init_view(self, cls: Type[View]):
"""
Init View-based class
:param cls:
:return:
"""
self.init_settings(cls)
self.init_view_collection(cls)
self.init_view_fields(cls)
self.init_cache(cls)
collection_names = await self.database.list_collection_names(
authorizedCollections=True, nameOnly=True
)
if self.recreate_views or cls._settings.name not in collection_names:
if cls._settings.name in collection_names:
await cls.get_motor_collection().drop()
await self.database.command(
{
"create": cls.get_settings().name,
"viewOn": cls.get_settings().source,
"pipeline": cls.get_settings().pipeline,
}
)
# Union Doc
async def init_union_doc(self, cls: Type[UnionDoc]):
"""
Init Union Doc based class
:param cls:
:return:
"""
self.init_settings(cls)
if cls._settings.name is None:
cls._settings.name = cls.__name__
cls._settings.motor_db = self.database
cls._settings.motor_collection = self.database[cls._settings.name]
cls._is_inited = True
# Deprecations
def check_deprecations(
cls: Union[Type[Document], Type[View], Type[UnionDoc]]
):
if hasattr(cls, "Collection"):
raise Deprecation(
"Collection inner class is not supported more. "
"Please use Settings instead. "
"https://beanie-odm.dev/tutorial/defining-a-document/#settings"
)
# Final
async def init_class(
self, cls: Union[Type[Document], Type[View], Type[UnionDoc]]
):
"""
Init Document, View or UnionDoc based class.
:param cls:
:return:
"""
self.check_deprecations(cls)
if issubclass(cls, Document):
await self.init_document(cls)
if issubclass(cls, View):
await self.init_view(cls)
if issubclass(cls, UnionDoc):
await self.init_union_doc(cls)
if hasattr(cls, "custom_init"):
await cls.custom_init() # type: ignore
class Document(
LazyModel,
SettersInterface,
InheritanceInterface,
FindInterface,
AggregateInterface,
OtherGettersInterface,
):
"""
Document Mapping class.
Fields:
- `id` - MongoDB document ObjectID "_id" field.
Mapped to the PydanticObjectId class
"""
if IS_PYDANTIC_V2:
model_config = ConfigDict(
json_schema_extra=json_schema_extra,
populate_by_name=True,
alias_generator=document_alias_generator,
)
else:
class Config:
json_encoders = {ObjectId: str}
allow_population_by_field_name = True
fields = {"id": "_id"}
schema_extra = staticmethod(json_schema_extra)
id: Optional[PydanticObjectId] = Field(
default=None, description="MongoDB document ObjectID"
)
# State
revision_id: Optional[UUID] = Field(default=None, exclude=True)
_saved_state: Optional[Dict[str, Any]] = PrivateAttr(default=None)
_previous_saved_state: Optional[Dict[str, Any]] = PrivateAttr(default=None)
# Relations
_link_fields: ClassVar[Optional[Dict[str, LinkInfo]]] = None
# Cache
_cache: ClassVar[Optional[LRUCache]] = None
# Settings
_document_settings: ClassVar[Optional[DocumentSettings]] = None
# Database
_database_major_version: ClassVar[int] = 4
def __init__(self, *args, **kwargs) -> None:
super(Document, self).__init__(*args, **kwargs)
self.get_motor_collection()
def _fill_back_refs(cls, values):
if cls._link_fields:
for field_name, link_info in cls._link_fields.items():
if (
link_info.link_type
in [LinkTypes.BACK_DIRECT, LinkTypes.OPTIONAL_BACK_DIRECT]
and field_name not in values
):
values[field_name] = BackLink[link_info.document_class](
link_info.document_class
)
if (
link_info.link_type
in [LinkTypes.BACK_LIST, LinkTypes.OPTIONAL_BACK_LIST]
and field_name not in values
):
values[field_name] = [
BackLink[link_info.document_class](
link_info.document_class
)
]
return values
if IS_PYDANTIC_V2:
def fill_back_refs(cls, values):
return cls._fill_back_refs(values)
else:
def fill_back_refs(cls, values):
return cls._fill_back_refs(values)
async def get(
cls: Type["DocType"],
document_id: Any,
session: Optional[ClientSession] = None,
ignore_cache: bool = False,
fetch_links: bool = False,
with_children: bool = False,
nesting_depth: Optional[int] = None,
nesting_depths_per_field: Optional[Dict[str, int]] = None,
**pymongo_kwargs,
) -> Optional["DocType"]:
"""
Get document by id, returns None if document does not exist
:param document_id: PydanticObjectId - document id
:param session: Optional[ClientSession] - pymongo session
:param ignore_cache: bool - ignore cache (if it is turned on)
:param **pymongo_kwargs: pymongo native parameters for find operation
:return: Union["Document", None]
"""
if not isinstance(
document_id,
extract_id_class(get_field_type(get_model_fields(cls)["id"])),
):
document_id = parse_object_as(
get_field_type(get_model_fields(cls)["id"]), document_id
)
return await cls.find_one(
{"_id": document_id},
session=session,
ignore_cache=ignore_cache,
fetch_links=fetch_links,
with_children=with_children,
nesting_depth=nesting_depth,
nesting_depths_per_field=nesting_depths_per_field,
**pymongo_kwargs,
)
async def sync(self, merge_strategy: MergeStrategy = MergeStrategy.remote):
"""
Sync the document with the database
:param merge_strategy: MergeStrategy - how to merge the document
:return: None
"""
if (
merge_strategy == MergeStrategy.local
and self.get_settings().use_state_management is False
):
raise ValueError(
"State management must be turned on to use local merge strategy"
)
if self.id is None:
raise DocumentWasNotSaved
document = await self.find_one({"_id": self.id})
if document is None:
raise DocumentNotFound
if merge_strategy == MergeStrategy.local:
original_changes = self.get_changes()
new_state = document.get_saved_state()
if new_state is None:
raise DocumentWasNotSaved
changes_to_apply = self._collect_updates(
new_state, original_changes
)
merge_models(self, document)
apply_changes(changes_to_apply, self)
elif merge_strategy == MergeStrategy.remote:
merge_models(self, document)
else:
raise ValueError("Invalid merge strategy")
async def insert(
self: DocType,
*,
link_rule: WriteRules = WriteRules.DO_NOTHING,
session: Optional[ClientSession] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> DocType:
"""
Insert the document (self) to the collection
:return: Document
"""
if self.get_settings().use_revision:
self.revision_id = uuid4()
if link_rule == WriteRules.WRITE:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
]:
if isinstance(value, Document):
await value.save(link_rule=WriteRules.WRITE)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.save(link_rule=WriteRules.WRITE)
for obj in value
if isinstance(obj, Document)
]
)
result = await self.get_motor_collection().insert_one(
get_dict(
self, to_db=True, keep_nulls=self.get_settings().keep_nulls
),
session=session,
)
new_id = result.inserted_id
if not isinstance(
new_id,
extract_id_class(get_field_type(get_model_fields(self)["id"])),
):
new_id = parse_object_as(
get_field_type(get_model_fields(self)["id"]), new_id
)
self.id = new_id
return self
async def create(
self: DocType,
session: Optional[ClientSession] = None,
) -> DocType:
"""
The same as self.insert()
:return: Document
"""
return await self.insert(session=session)
async def insert_one(
cls: Type[DocType],
document: DocType,
session: Optional[ClientSession] = None,
bulk_writer: Optional["BulkWriter"] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
) -> Optional[DocType]:
"""
Insert one document to the collection
:param document: Document - document to insert
:param session: ClientSession - pymongo session
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param link_rule: InsertRules - hot to manage link fields
:return: DocType
"""
if not isinstance(document, cls):
raise TypeError(
"Inserting document must be of the original document class"
)
if bulk_writer is None:
return await document.insert(link_rule=link_rule, session=session)
else:
if link_rule == WriteRules.WRITE:
raise NotSupported(
"Cascade insert with bulk writing not supported"
)
bulk_writer.add_operation(
Operation(
operation=InsertOne,
first_query=get_dict(
document,
to_db=True,
keep_nulls=document.get_settings().keep_nulls,
),
object_class=type(document),
)
)
return None
async def insert_many(
cls: Type[DocType],
documents: Iterable[DocType],
session: Optional[ClientSession] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
**pymongo_kwargs,
) -> InsertManyResult:
"""
Insert many documents to the collection
:param documents: List["Document"] - documents to insert
:param session: ClientSession - pymongo session
:param link_rule: InsertRules - how to manage link fields
:return: InsertManyResult
"""
if link_rule == WriteRules.WRITE:
raise NotSupported(
"Cascade insert not supported for insert many method"
)
documents_list = [
get_dict(
document,
to_db=True,
keep_nulls=document.get_settings().keep_nulls,
)
for document in documents
]
return await cls.get_motor_collection().insert_many(
documents_list, session=session, **pymongo_kwargs
)
async def replace(
self: DocType,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> DocType:
"""
Fully update the document in the database
:param session: Optional[ClientSession] - pymongo session.
:param ignore_revision: bool - do force replace.
Used when revision based protection is turned on.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:return: self
"""
if self.id is None:
raise ValueError("Document must have an id")
if bulk_writer is not None and link_rule != WriteRules.DO_NOTHING:
raise NotSupported
if link_rule == WriteRules.WRITE:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if isinstance(value, Document):
await value.replace(
link_rule=link_rule,
bulk_writer=bulk_writer,
ignore_revision=ignore_revision,
session=session,
)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.replace(
link_rule=link_rule,
bulk_writer=bulk_writer,
ignore_revision=ignore_revision,
session=session,
)
for obj in value
if isinstance(obj, Document)
]
)
use_revision_id = self.get_settings().use_revision
find_query: Dict[str, Any] = {"_id": self.id}
if use_revision_id and not ignore_revision:
find_query["revision_id"] = self.revision_id
self.revision_id = uuid4()
try:
await self.find_one(find_query).replace_one(
self,
session=session,
bulk_writer=bulk_writer,
)
except DocumentNotFound:
if use_revision_id and not ignore_revision:
raise RevisionIdWasChanged
else:
raise DocumentNotFound
return self
async def save(
self: DocType,
session: Optional[ClientSession] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
ignore_revision: bool = False,
**kwargs,
) -> None:
"""
Update an existing model in the database or
insert it if it does not yet exist.
:param session: Optional[ClientSession] - pymongo session.
:param link_rule: WriteRules - rules how to deal with links on writing
:param ignore_revision: bool - do force save.
:return: None
"""
if link_rule == WriteRules.WRITE:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if isinstance(value, Document):
await value.save(
link_rule=link_rule, session=session
)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.save(
link_rule=link_rule, session=session
)
for obj in value
if isinstance(obj, Document)
]
)
if self.get_settings().keep_nulls is False:
return await self.update(
SetOperator(
get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
)
),
Unset(get_top_level_nones(self)),
session=session,
ignore_revision=ignore_revision,
upsert=True,
**kwargs,
)
else:
return await self.update(
SetOperator(
get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
)
),
session=session,
ignore_revision=ignore_revision,
upsert=True,
**kwargs,
)
async def save_changes(
self,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> None:
"""
Save changes.
State management usage must be turned on
:param ignore_revision: bool - ignore revision id, if revision is turned on
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:return: None
"""
if not self.is_changed:
return None
changes = self.get_changes()
if self.get_settings().keep_nulls is False:
return await self.update(
SetOperator(changes),
Unset(get_top_level_nones(self)),
ignore_revision=ignore_revision,
session=session,
bulk_writer=bulk_writer,
)
else:
return await self.set(
changes, # type: ignore #TODO fix typing
ignore_revision=ignore_revision,
session=session,
bulk_writer=bulk_writer,
)
async def replace_many(
cls: Type[DocType],
documents: List[DocType],
session: Optional[ClientSession] = None,
) -> None:
"""
Replace list of documents
:param documents: List["Document"]
:param session: Optional[ClientSession] - pymongo session.
:return: None
"""
ids_list = [document.id for document in documents]
if await cls.find(In(cls.id, ids_list)).count() != len(ids_list):
raise ReplaceError(
"Some of the documents are not exist in the collection"
)
async with BulkWriter(session=session) as bulk_writer:
for document in documents:
await document.replace(
bulk_writer=bulk_writer, session=session
)
async def update(
self,
*args,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
skip_sync: Optional[bool] = None,
**pymongo_kwargs,
) -> DocType:
"""
Partially update the document in the database
:param args: *Union[dict, Mapping] - the modifications to apply.
:param session: ClientSession - pymongo session.
:param ignore_revision: bool - force update. Will update even if revision id is not the same, as stored
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param pymongo_kwargs: pymongo native parameters for update operation
:return: None
"""
arguments = list(args)
if skip_sync is not None:
raise DeprecationWarning(
"skip_sync parameter is not supported. The document get synced always using atomic operation."
)
use_revision_id = self.get_settings().use_revision
if self.id is not None:
find_query: Dict[str, Any] = {"_id": self.id}
else:
find_query = {"_id": PydanticObjectId()}
if use_revision_id and not ignore_revision:
find_query["revision_id"] = self.revision_id
if use_revision_id:
new_revision_id = uuid4()
arguments.append(SetRevisionId(new_revision_id))
try:
result = await self.find_one(find_query).update(
*arguments,
session=session,
response_type=UpdateResponse.NEW_DOCUMENT,
bulk_writer=bulk_writer,
**pymongo_kwargs,
)
except DuplicateKeyError:
raise RevisionIdWasChanged
if bulk_writer is None:
if use_revision_id and not ignore_revision and result is None:
raise RevisionIdWasChanged
merge_models(self, result)
return self
def update_all(
cls,
*args: Union[dict, Mapping],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
**pymongo_kwargs,
) -> UpdateMany:
"""
Partially update all the documents
:param args: *Union[dict, Mapping] - the modifications to apply.
:param session: ClientSession - pymongo session.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param **pymongo_kwargs: pymongo native parameters for find operation
:return: UpdateMany query
"""
return cls.find_all().update_many(
*args, session=session, bulk_writer=bulk_writer, **pymongo_kwargs
)
def set(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
"""
Set values
Example:
```python
class Sample(Document):
one: int
await Document.find(Sample.one == 1).set({Sample.one: 100})
```
Uses [Set operator](operators/update.md#set)
:param expression: Dict[Union[ExpressionField, str], Any] - keys and
values to set
:param session: Optional[ClientSession] - pymongo session
:param bulk_writer: Optional[BulkWriter] - bulk writer
:param skip_sync: bool - skip doc syncing. Available for the direct instances only
:return: self
"""
return self.update(
SetOperator(expression),
session=session,
bulk_writer=bulk_writer,
skip_sync=skip_sync,
**kwargs,
)
def current_date(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
"""
Set current date
Uses [CurrentDate operator](operators/update.md#currentdate)
:param expression: Dict[Union[ExpressionField, str], Any]
:param session: Optional[ClientSession] - pymongo session
:param bulk_writer: Optional[BulkWriter] - bulk writer
:param skip_sync: bool - skip doc syncing. Available for the direct instances only
:return: self
"""
return self.update(
CurrentDate(expression),
session=session,
bulk_writer=bulk_writer,
skip_sync=skip_sync,
**kwargs,
)
def inc(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
"""
Increment
Example:
```python
class Sample(Document):
one: int
await Document.find(Sample.one == 1).inc({Sample.one: 100})
```
Uses [Inc operator](operators/update.md#inc)
:param expression: Dict[Union[ExpressionField, str], Any]
:param session: Optional[ClientSession] - pymongo session
:param bulk_writer: Optional[BulkWriter] - bulk writer
:param skip_sync: bool - skip doc syncing. Available for the direct instances only
:return: self
"""
return self.update(
Inc(expression),
session=session,
bulk_writer=bulk_writer,
skip_sync=skip_sync,
**kwargs,
)
async def delete(
self,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
link_rule: DeleteRules = DeleteRules.DO_NOTHING,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
**pymongo_kwargs,
) -> Optional[DeleteResult]:
"""
Delete the document
:param session: Optional[ClientSession] - pymongo session.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param link_rule: DeleteRules - rules for link fields
:param **pymongo_kwargs: pymongo native parameters for delete operation
:return: Optional[DeleteResult] - pymongo DeleteResult instance.
"""
if link_rule == DeleteRules.DELETE_LINKS:
link_fields = self.get_link_fields()
if link_fields is not None:
for field_info in link_fields.values():
value = getattr(self, field_info.field_name)
if field_info.link_type in [
LinkTypes.DIRECT,
LinkTypes.OPTIONAL_DIRECT,
LinkTypes.BACK_DIRECT,
LinkTypes.OPTIONAL_BACK_DIRECT,
]:
if isinstance(value, Document):
await value.delete(
link_rule=DeleteRules.DELETE_LINKS,
**pymongo_kwargs,
)
if field_info.link_type in [
LinkTypes.LIST,
LinkTypes.OPTIONAL_LIST,
LinkTypes.BACK_LIST,
LinkTypes.OPTIONAL_BACK_LIST,
]:
if isinstance(value, List):
await asyncio.gather(
*[
obj.delete(
link_rule=DeleteRules.DELETE_LINKS,
**pymongo_kwargs,
)
for obj in value
if isinstance(obj, Document)
]
)
return await self.find_one({"_id": self.id}).delete(
session=session, bulk_writer=bulk_writer, **pymongo_kwargs
)
async def delete_all(
cls,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
**pymongo_kwargs,
) -> Optional[DeleteResult]:
"""
Delete all the documents
:param session: Optional[ClientSession] - pymongo session.
:param bulk_writer: "BulkWriter" - Beanie bulk writer
:param **pymongo_kwargs: pymongo native parameters for delete operation
:return: Optional[DeleteResult] - pymongo DeleteResult instance.
"""
return await cls.find_all().delete(
session=session, bulk_writer=bulk_writer, **pymongo_kwargs
)
# State management
def use_state_management(cls) -> bool:
"""
Is state management turned on
:return: bool
"""
return cls.get_settings().use_state_management
def state_management_save_previous(cls) -> bool:
"""
Should we save the previous state after a commit to database
:return: bool
"""
return cls.get_settings().state_management_save_previous
def state_management_replace_objects(cls) -> bool:
"""
Should objects be replaced when using state management
:return: bool
"""
return cls.get_settings().state_management_replace_objects
def _save_state(self) -> None:
"""
Save current document state. Internal method
:return: None
"""
if self.use_state_management() and self.id is not None:
if self.state_management_save_previous():
self._previous_saved_state = self._saved_state
self._saved_state = get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
exclude={"revision_id"},
)
def get_saved_state(self) -> Optional[Dict[str, Any]]:
"""
Saved state getter. It is protected property.
:return: Optional[Dict[str, Any]] - saved state
"""
return self._saved_state
def get_previous_saved_state(self) -> Optional[Dict[str, Any]]:
"""
Previous state getter. It is a protected property.
:return: Optional[Dict[str, Any]] - previous state
"""
return self._previous_saved_state
def is_changed(self) -> bool:
if self._saved_state == get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
exclude={"revision_id"},
):
return False
return True
def has_changed(self) -> bool:
if (
self._previous_saved_state is None
or self._previous_saved_state == self._saved_state
):
return False
return True
def _collect_updates(
self, old_dict: Dict[str, Any], new_dict: Dict[str, Any]
) -> Dict[str, Any]:
"""
Compares old_dict with new_dict and returns field paths that have been updated
Args:
old_dict: dict1
new_dict: dict2
Returns: dictionary with updates
"""
updates = {}
if old_dict.keys() - new_dict.keys():
updates = new_dict
else:
for field_name, field_value in new_dict.items():
if field_value != old_dict.get(field_name):
if not self.state_management_replace_objects() and (
isinstance(field_value, dict)
and isinstance(old_dict.get(field_name), dict)
):
if old_dict.get(field_name) is None:
updates[field_name] = field_value
elif isinstance(field_value, dict) and isinstance(
old_dict.get(field_name), dict
):
field_data = self._collect_updates(
old_dict.get(field_name), # type: ignore
field_value,
)
for k, v in field_data.items():
updates[f"{field_name}.{k}"] = v
else:
updates[field_name] = field_value
return updates
def get_changes(self) -> Dict[str, Any]:
return self._collect_updates(
self._saved_state, # type: ignore
get_dict(
self,
to_db=True,
keep_nulls=self.get_settings().keep_nulls,
exclude={"revision_id"},
),
)
def get_previous_changes(self) -> Dict[str, Any]:
if self._previous_saved_state is None:
return {}
return self._collect_updates(
self._previous_saved_state,
self._saved_state, # type: ignore
)
def rollback(self) -> None:
if self.is_changed:
for key, value in self._saved_state.items(): # type: ignore
if key == "_id":
setattr(self, "id", value)
else:
setattr(self, key, value)
# Other
def get_settings(cls) -> DocumentSettings:
"""
Get document settings, which was created on
the initialization step
:return: DocumentSettings class
"""
if cls._document_settings is None:
raise CollectionWasNotInitialized
return cls._document_settings
async def inspect_collection(
cls, session: Optional[ClientSession] = None
) -> InspectionResult:
"""
Check, if documents, stored in the MongoDB collection
are compatible with the Document schema
:return: InspectionResult
"""
inspection_result = InspectionResult()
async for json_document in cls.get_motor_collection().find(
{}, session=session
):
try:
parse_model(cls, json_document)
except ValidationError as e:
if inspection_result.status == InspectionStatuses.OK:
inspection_result.status = InspectionStatuses.FAIL
inspection_result.errors.append(
InspectionError(
document_id=json_document["_id"], error=str(e)
)
)
return inspection_result
def check_hidden_fields(cls):
hidden_fields = [
(name, field)
for name, field in get_model_fields(cls).items()
if get_extra_field_info(field, "hidden") is True
]
if not hidden_fields:
return
warnings.warn(
f"{cls.__name__}: 'hidden=True' is deprecated, please use 'exclude=True'",
DeprecationWarning,
)
if IS_PYDANTIC_V2:
for name, field in hidden_fields:
field.exclude = True
del field.json_schema_extra["hidden"]
cls.model_rebuild(force=True)
else:
for name, field in hidden_fields:
field.field_info.exclude = True
del field.field_info.extra["hidden"]
cls.__exclude_fields__[name] = True
async def validate_self(self, *args, **kwargs):
# TODO: it can be sync, but needs some actions controller improvements
if self.get_settings().validate_on_save:
new_model = parse_model(self.__class__, get_model_dump(self))
merge_models(self, new_model)
def to_ref(self):
if self.id is None:
raise DocumentWasNotSaved("Can not create dbref without id")
return DBRef(self.get_motor_collection().name, self.id)
async def fetch_link(self, field: Union[str, Any]):
ref_obj = getattr(self, field, None)
if isinstance(ref_obj, Link):
value = await ref_obj.fetch(fetch_links=True)
setattr(self, field, value)
if isinstance(ref_obj, list) and ref_obj:
values = await Link.fetch_list(ref_obj, fetch_links=True)
setattr(self, field, values)
async def fetch_all_links(self):
coros = []
link_fields = self.get_link_fields()
if link_fields is not None:
for ref in link_fields.values():
coros.append(self.fetch_link(ref.field_name)) # TODO lists
await asyncio.gather(*coros)
def get_link_fields(cls) -> Optional[Dict[str, LinkInfo]]:
return cls._link_fields
def get_model_type(cls) -> ModelType:
return ModelType.Document
async def distinct(
cls,
key: str,
filter: Optional[Mapping[str, Any]] = None,
session: Optional[ClientSession] = None,
**kwargs: Any,
) -> list:
return await cls.get_motor_collection().distinct(
key, filter, session, **kwargs
)
def link_from_id(cls, id: Any):
ref = DBRef(id=id, collection=cls.get_collection_name())
return Link(ref, document_class=cls)
The provided code snippet includes necessary dependencies for implementing the `init_beanie` function. Write a Python function `async def init_beanie( database: AsyncIOMotorDatabase = None, connection_string: Optional[str] = None, document_models: Optional[ List[Union[Type[Document], Type["View"], str]] ] = None, allow_index_dropping: bool = False, recreate_views: bool = False, multiprocessing_mode: bool = False, )` to solve the following problem:
Beanie initialization :param database: AsyncIOMotorDatabase - motor database instance :param connection_string: str - MongoDB connection string :param document_models: List[Union[Type[DocType], str]] - model classes or strings with dot separated paths :param allow_index_dropping: bool - if index dropping is allowed. Default False :param recreate_views: bool - if views should be recreated. Default False :param multiprocessing_mode: bool - if multiprocessing mode is on it will patch the motor client to use process's event loop. Default False :return: None
Here is the function:
async def init_beanie(
database: AsyncIOMotorDatabase = None,
connection_string: Optional[str] = None,
document_models: Optional[
List[Union[Type[Document], Type["View"], str]]
] = None,
allow_index_dropping: bool = False,
recreate_views: bool = False,
multiprocessing_mode: bool = False,
):
"""
Beanie initialization
:param database: AsyncIOMotorDatabase - motor database instance
:param connection_string: str - MongoDB connection string
:param document_models: List[Union[Type[DocType], str]] - model classes
or strings with dot separated paths
:param allow_index_dropping: bool - if index dropping is allowed.
Default False
:param recreate_views: bool - if views should be recreated. Default False
:param multiprocessing_mode: bool - if multiprocessing mode is on
it will patch the motor client to use process's event loop. Default False
:return: None
"""
await Initializer(
database=database,
connection_string=connection_string,
document_models=document_models,
allow_index_dropping=allow_index_dropping,
recreate_views=recreate_views,
multiprocessing_mode=multiprocessing_mode,
) | Beanie initialization :param database: AsyncIOMotorDatabase - motor database instance :param connection_string: str - MongoDB connection string :param document_models: List[Union[Type[DocType], str]] - model classes or strings with dot separated paths :param allow_index_dropping: bool - if index dropping is allowed. Default False :param recreate_views: bool - if views should be recreated. Default False :param multiprocessing_mode: bool - if multiprocessing mode is on it will patch the motor client to use process's event loop. Default False :return: None |
167,800 | import inspect
import sys
from typing import Any, Dict, Optional, Tuple, Type
from beanie.odm.fields import IndexedAnnotation
from .pydantic import IS_PYDANTIC_V2, get_field_type
def extract_id_class(annotation) -> Type[Any]:
if get_origin(annotation) is not None:
try:
annotation = next(
arg for arg in get_args(annotation) if arg is not type(None)
)
except StopIteration:
annotation = None
if inspect.isclass(annotation):
return annotation
raise ValueError("Unknown annotation: {}".format(annotation)) | null |
167,801 | import inspect
import sys
from typing import Any, Dict, Optional, Tuple, Type
from beanie.odm.fields import IndexedAnnotation
from .pydantic import IS_PYDANTIC_V2, get_field_type
class IndexedAnnotation:
_indexed: Tuple[int, Dict[str, Any]]
IS_PYDANTIC_V2 = int(pydantic.VERSION.split(".")[0]) >= 2
if IS_PYDANTIC_V2:
from pydantic import TypeAdapter
else:
from pydantic import parse_obj_as
def get_field_type(field):
if IS_PYDANTIC_V2:
return field.annotation
else:
return field.outer_type_
The provided code snippet includes necessary dependencies for implementing the `get_index_attributes` function. Write a Python function `def get_index_attributes(field) -> Optional[Tuple[int, Dict[str, Any]]]` to solve the following problem:
Gets the index attributes from the field, if it is indexed. :param field: The field to get the index attributes from. :return: The index attributes, if the field is indexed. Otherwise, None.
Here is the function:
def get_index_attributes(field) -> Optional[Tuple[int, Dict[str, Any]]]:
"""Gets the index attributes from the field, if it is indexed.
:param field: The field to get the index attributes from.
:return: The index attributes, if the field is indexed. Otherwise, None.
"""
# For fields that are directly typed with `Indexed()`, the type will have
# an `_indexed` attribute.
field_type = get_field_type(field)
if hasattr(field_type, "_indexed"):
return getattr(field_type, "_indexed", None)
# For fields that are use `Indexed` within `Annotated`, the field will have
# metadata that might contain an `IndexedAnnotation` instance.
if IS_PYDANTIC_V2:
# In Pydantic 2, the field has a `metadata` attribute with
# the annotations.
metadata = getattr(field, "metadata", None)
elif hasattr(field, "annotation") and hasattr(
field.annotation, "__metadata__"
):
# In Pydantic 1, the field has an `annotation` attribute with the
# type assigned to the field. If the type is annotated, it will
# have a `__metadata__` attribute with the annotations.
metadata = field.annotation.__metadata__
else:
return None
if metadata is None:
return None
try:
iter(metadata)
except TypeError:
return None
indexed_annotation = next(
(
annotation
for annotation in metadata
if isinstance(annotation, IndexedAnnotation)
),
None,
)
return getattr(indexed_annotation, "_indexed", None) | Gets the index attributes from the field, if it is indexed. :param field: The field to get the index attributes from. :return: The index attributes, if the field is indexed. Otherwise, None. |
167,802 | from collections.abc import Mapping
from typing import TYPE_CHECKING, Any, Dict
from typing import Mapping as MappingType
from beanie.odm.fields import (
ExpressionField,
)
class ExpressionField(str):
def __getitem__(self, item):
def __getattr__(self, item):
def __hash__(self):
def __eq__(self, other):
def __gt__(self, other):
def __ge__(self, other):
def __lt__(self, other):
def __le__(self, other):
def __ne__(self, other):
def __pos__(self):
def __neg__(self):
def __copy__(self):
def __deepcopy__(self, memo):
def convert_ids(
query: MappingType[str, Any], doc: "Document", fetch_links: bool
) -> Dict[str, Any]:
# TODO add all the cases
new_query = {}
for k, v in query.items():
k_splitted = k.split(".")
if (
isinstance(k, ExpressionField)
and doc.get_link_fields() is not None
and len(k_splitted) == 2
and k_splitted[0] in doc.get_link_fields().keys() # type: ignore
and k_splitted[1] == "id"
):
if fetch_links:
new_k = f"{k_splitted[0]}._id"
else:
new_k = f"{k_splitted[0]}.$id"
else:
new_k = k
new_v: Any
if isinstance(v, Mapping):
new_v = convert_ids(v, doc, fetch_links)
elif isinstance(v, list):
new_v = [
convert_ids(ele, doc, fetch_links)
if isinstance(ele, Mapping)
else ele
for ele in v
]
else:
new_v = v
new_query[new_k] = new_v
return new_query | null |
167,803 | from typing import Any, Type
import pydantic
from pydantic import BaseModel
IS_PYDANTIC_V2 = int(pydantic.VERSION.split(".")[0]) >= 2
if IS_PYDANTIC_V2:
from pydantic import TypeAdapter
else:
from pydantic import parse_obj_as
def parse_object_as(object_type: Type, data: Any):
if IS_PYDANTIC_V2:
return TypeAdapter(object_type).validate_python(data)
else:
return parse_obj_as(object_type, data) | null |
167,804 | from typing import Any, Type
import pydantic
from pydantic import BaseModel
IS_PYDANTIC_V2 = int(pydantic.VERSION.split(".")[0]) >= 2
if IS_PYDANTIC_V2:
from pydantic import TypeAdapter
else:
from pydantic import parse_obj_as
def get_extra_field_info(field, parameter: str):
if IS_PYDANTIC_V2:
if field.json_schema_extra is not None:
return field.json_schema_extra.get(parameter)
return None
else:
return field.field_info.extra.get(parameter) | null |
167,805 | from typing import Any, Type
import pydantic
from pydantic import BaseModel
IS_PYDANTIC_V2 = int(pydantic.VERSION.split(".")[0]) >= 2
if IS_PYDANTIC_V2:
from pydantic import TypeAdapter
else:
from pydantic import parse_obj_as
def get_model_dump(model, *args, **kwargs):
if IS_PYDANTIC_V2:
return model.model_dump(*args, **kwargs)
else:
return model.dict(*args, **kwargs) | null |
167,806 | from typing import TYPE_CHECKING, Any, Dict, Type, Union
from pydantic import BaseModel
from beanie.exceptions import (
ApplyChangesException,
DocWasNotRegisteredInUnionClass,
UnionHasNoRegisteredDocs,
)
from beanie.odm.interfaces.detector import ModelType
from beanie.odm.utils.pydantic import get_config_value, parse_model
def get_config_value(model, parameter: str):
if IS_PYDANTIC_V2:
return model.model_config.get(parameter)
else:
return getattr(model.Config, parameter, None)
class Link(Generic[T]):
def __init__(self, ref: DBRef, document_class: Type[T]):
self.ref = ref
self.document_class = document_class
async def fetch(self, fetch_links: bool = False) -> Union[T, "Link"]:
result = await self.document_class.get( # type: ignore
self.ref.id, with_children=True, fetch_links=fetch_links
)
return result or self
async def fetch_one(cls, link: "Link"):
return await link.fetch()
async def fetch_list(
cls, links: List[Union["Link", "DocType"]], fetch_links: bool = False
):
"""
Fetch list that contains links and documents
:param links:
:param fetch_links:
:return:
"""
data = Link.repack_links(links) # type: ignore
ids_to_fetch = []
document_class = None
for doc_id, link in data.items():
if isinstance(link, Link):
if document_class is None:
document_class = link.document_class
else:
if document_class != link.document_class:
raise ValueError(
"All the links must have the same model class"
)
ids_to_fetch.append(link.ref.id)
if ids_to_fetch:
fetched_models = await document_class.find( # type: ignore
In("_id", ids_to_fetch),
with_children=True,
fetch_links=fetch_links,
).to_list()
for model in fetched_models:
data[model.id] = model
return list(data.values())
def repack_links(
links: List[Union["Link", "DocType"]]
) -> OrderedDictType[Any, Any]:
result = OrderedDict()
for link in links:
if isinstance(link, Link):
result[link.ref.id] = link
else:
result[link.id] = link
return result
async def fetch_many(cls, links: List["Link"]):
coros = []
for link in links:
coros.append(link.fetch())
return await asyncio.gather(*coros)
if IS_PYDANTIC_V2:
def serialize(value: Union["Link", BaseModel]):
if isinstance(value, Link):
return value.to_dict()
return value.model_dump()
def build_validation(cls, handler, source_type):
def validate(v: Union[DBRef, T], validation_info: ValidationInfo):
document_class = DocsRegistry.evaluate_fr(get_args(source_type)[0]) # type: ignore # noqa: F821
if isinstance(v, DBRef):
return cls(ref=v, document_class=document_class)
if isinstance(v, Link):
return v
if isinstance(v, dict) and v.keys() == {"id", "collection"}:
return cls(
ref=DBRef(
collection=v["collection"],
id=TypeAdapter(
document_class.model_fields["id"].annotation
).validate_python(v["id"]),
),
document_class=document_class,
)
if isinstance(v, dict) or isinstance(v, BaseModel):
return parse_obj(document_class, v)
new_id = TypeAdapter(
document_class.model_fields["id"].annotation
).validate_python(v)
ref = DBRef(
collection=document_class.get_collection_name(), id=new_id
)
return cls(ref=ref, document_class=document_class)
return validate
def __get_pydantic_core_schema__(
cls, source_type: Any, handler: GetCoreSchemaHandler
) -> CoreSchema: # type: ignore
return core_schema.json_or_python_schema(
python_schema=core_schema.general_plain_validator_function(
cls.build_validation(handler, source_type)
),
json_schema=core_schema.typed_dict_schema(
{
"id": core_schema.typed_dict_field(
core_schema.str_schema()
),
"collection": core_schema.typed_dict_field(
core_schema.str_schema()
),
}
),
serialization=core_schema.plain_serializer_function_ser_schema( # type: ignore
lambda instance: cls.serialize(instance) # type: ignore
),
)
return core_schema.general_plain_validator_function(
cls.build_validation(handler, source_type)
)
else:
def __get_validators__(cls):
yield cls.validate
def validate(cls, v: Union[DBRef, T], field: ModelField):
document_class = field.sub_fields[0].type_ # type: ignore
if isinstance(v, DBRef):
return cls(ref=v, document_class=document_class)
if isinstance(v, Link):
return v
if isinstance(v, dict) or isinstance(v, BaseModel):
return parse_obj(document_class, v)
new_id = parse_object_as(
get_field_type(get_model_fields(document_class)["id"]), v
)
ref = DBRef(
collection=document_class.get_collection_name(), id=new_id
)
return cls(ref=ref, document_class=document_class)
def to_ref(self):
return self.ref
def to_dict(self):
return {"id": str(self.ref.id), "collection": self.ref.collection}
The provided code snippet includes necessary dependencies for implementing the `merge_models` function. Write a Python function `def merge_models(left: BaseModel, right: BaseModel) -> None` to solve the following problem:
Merge two models :param left: left model :param right: right model :return: None
Here is the function:
def merge_models(left: BaseModel, right: BaseModel) -> None:
"""
Merge two models
:param left: left model
:param right: right model
:return: None
"""
from beanie.odm.fields import Link
for k, right_value in right.__iter__():
left_value = getattr(left, k)
if isinstance(right_value, BaseModel) and isinstance(
left_value, BaseModel
):
if get_config_value(left_value, "frozen"):
left.__setattr__(k, right_value)
else:
merge_models(left_value, right_value)
continue
if isinstance(right_value, list):
links_found = False
for i in right_value:
if isinstance(i, Link):
links_found = True
break
if links_found:
continue
left.__setattr__(k, right_value)
elif not isinstance(right_value, Link):
left.__setattr__(k, right_value) | Merge two models :param left: left model :param right: right model :return: None |
167,807 | from typing import TYPE_CHECKING, Any, Dict, Type, Union
from pydantic import BaseModel
from beanie.exceptions import (
ApplyChangesException,
DocWasNotRegisteredInUnionClass,
UnionHasNoRegisteredDocs,
)
from beanie.odm.interfaces.detector import ModelType
from beanie.odm.utils.pydantic import get_config_value, parse_model
class ApplyChangesException(Exception):
pass
def apply_changes(
changes: Dict[str, Any], target: Union[BaseModel, Dict[str, Any]]
):
for key, value in changes.items():
if "." in key:
key_parts = key.split(".")
current_target = target
try:
for part in key_parts[:-1]:
if isinstance(current_target, dict):
current_target = current_target[part]
elif isinstance(current_target, BaseModel):
current_target = getattr(current_target, part)
else:
raise ApplyChangesException(
f"Unexpected type of target: {type(target)}"
)
final_key = key_parts[-1]
if isinstance(current_target, dict):
current_target[final_key] = value
elif isinstance(current_target, BaseModel):
setattr(current_target, final_key, value)
else:
raise ApplyChangesException(
f"Unexpected type of target: {type(target)}"
)
except (KeyError, AttributeError) as e:
raise ApplyChangesException(
f"Failed to apply change for key '{key}': {e}"
)
else:
if isinstance(target, dict):
target[key] = value
elif isinstance(target, BaseModel):
setattr(target, key, value)
else:
raise ApplyChangesException(
f"Unexpected type of target: {type(target)}"
) | null |
167,808 | from typing import TYPE_CHECKING, Any, Dict, Type, Union
from pydantic import BaseModel
from beanie.exceptions import (
ApplyChangesException,
DocWasNotRegisteredInUnionClass,
UnionHasNoRegisteredDocs,
)
from beanie.odm.interfaces.detector import ModelType
from beanie.odm.utils.pydantic import get_config_value, parse_model
def save_state(item: BaseModel): # type: ignore
class UnionHasNoRegisteredDocs(Exception):
class DocWasNotRegisteredInUnionClass(Exception):
class ModelType(str, Enum):
def parse_model(model_type: Type[BaseModel], data: Any):
class Document(
LazyModel,
SettersInterface,
InheritanceInterface,
FindInterface,
AggregateInterface,
OtherGettersInterface,
):
def __init__(self, *args, **kwargs) -> None:
def _fill_back_refs(cls, values):
def fill_back_refs(cls, values):
def fill_back_refs(cls, values):
async def get(
cls: Type["DocType"],
document_id: Any,
session: Optional[ClientSession] = None,
ignore_cache: bool = False,
fetch_links: bool = False,
with_children: bool = False,
nesting_depth: Optional[int] = None,
nesting_depths_per_field: Optional[Dict[str, int]] = None,
**pymongo_kwargs,
) -> Optional["DocType"]:
async def sync(self, merge_strategy: MergeStrategy = MergeStrategy.remote):
async def insert(
self: DocType,
*,
link_rule: WriteRules = WriteRules.DO_NOTHING,
session: Optional[ClientSession] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> DocType:
async def create(
self: DocType,
session: Optional[ClientSession] = None,
) -> DocType:
async def insert_one(
cls: Type[DocType],
document: DocType,
session: Optional[ClientSession] = None,
bulk_writer: Optional["BulkWriter"] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
) -> Optional[DocType]:
async def insert_many(
cls: Type[DocType],
documents: Iterable[DocType],
session: Optional[ClientSession] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
**pymongo_kwargs,
) -> InsertManyResult:
async def replace(
self: DocType,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> DocType:
async def save(
self: DocType,
session: Optional[ClientSession] = None,
link_rule: WriteRules = WriteRules.DO_NOTHING,
ignore_revision: bool = False,
**kwargs,
) -> None:
async def save_changes(
self,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
) -> None:
async def replace_many(
cls: Type[DocType],
documents: List[DocType],
session: Optional[ClientSession] = None,
) -> None:
async def update(
self,
*args,
ignore_revision: bool = False,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
skip_sync: Optional[bool] = None,
**pymongo_kwargs,
) -> DocType:
def update_all(
cls,
*args: Union[dict, Mapping],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
**pymongo_kwargs,
) -> UpdateMany:
def set(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
def current_date(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
def inc(
self,
expression: Dict[Union[ExpressionField, str], Any],
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
skip_sync: Optional[bool] = None,
**kwargs,
):
async def delete(
self,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
link_rule: DeleteRules = DeleteRules.DO_NOTHING,
skip_actions: Optional[List[Union[ActionDirections, str]]] = None,
**pymongo_kwargs,
) -> Optional[DeleteResult]:
async def delete_all(
cls,
session: Optional[ClientSession] = None,
bulk_writer: Optional[BulkWriter] = None,
**pymongo_kwargs,
) -> Optional[DeleteResult]:
def use_state_management(cls) -> bool:
def state_management_save_previous(cls) -> bool:
def state_management_replace_objects(cls) -> bool:
def _save_state(self) -> None:
def get_saved_state(self) -> Optional[Dict[str, Any]]:
def get_previous_saved_state(self) -> Optional[Dict[str, Any]]:
def is_changed(self) -> bool:
def has_changed(self) -> bool:
def _collect_updates(
self, old_dict: Dict[str, Any], new_dict: Dict[str, Any]
) -> Dict[str, Any]:
def get_changes(self) -> Dict[str, Any]:
def get_previous_changes(self) -> Dict[str, Any]:
def rollback(self) -> None:
def get_settings(cls) -> DocumentSettings:
async def inspect_collection(
cls, session: Optional[ClientSession] = None
) -> InspectionResult:
def check_hidden_fields(cls):
async def validate_self(self, *args, **kwargs):
def to_ref(self):
async def fetch_link(self, field: Union[str, Any]):
async def fetch_all_links(self):
def get_link_fields(cls) -> Optional[Dict[str, LinkInfo]]:
def get_model_type(cls) -> ModelType:
async def distinct(
cls,
key: str,
filter: Optional[Mapping[str, Any]] = None,
session: Optional[ClientSession] = None,
**kwargs: Any,
) -> list:
def link_from_id(cls, id: Any):
def parse_obj(
model: Union[Type[BaseModel], Type["Document"]],
data: Any,
lazy_parse: bool = False,
) -> BaseModel:
if (
hasattr(model, "get_model_type")
and model.get_model_type() == ModelType.UnionDoc # type: ignore
):
if model._document_models is None: # type: ignore
raise UnionHasNoRegisteredDocs
if isinstance(data, dict):
class_name = data[model.get_settings().class_id] # type: ignore
else:
class_name = data._class_id
if class_name not in model._document_models: # type: ignore
raise DocWasNotRegisteredInUnionClass
return parse_obj(
model=model._document_models[class_name], # type: ignore
data=data,
lazy_parse=lazy_parse,
) # type: ignore
if (
hasattr(model, "get_model_type")
and model.get_model_type() == ModelType.Document # type: ignore
and model._inheritance_inited # type: ignore
):
if isinstance(data, dict):
class_name = data.get(model.get_settings().class_id) # type: ignore
elif hasattr(data, model.get_settings().class_id): # type: ignore
class_name = data._class_id
else:
class_name = None
if model._children and class_name in model._children: # type: ignore
return parse_obj(
model=model._children[class_name], # type: ignore
data=data,
lazy_parse=lazy_parse,
) # type: ignore
if (
lazy_parse
and hasattr(model, "get_model_type")
and model.get_model_type() == ModelType.Document # type: ignore
):
o = model.lazy_parse(data, {"_id"}) # type: ignore
o._saved_state = {"_id": o.id}
return o
result = parse_model(model, data)
save_state(result)
return result | null |
167,809 | from typing import TYPE_CHECKING, Optional, Set
from beanie.odm.utils.encoder import Encoder
def get_dict(
document: "Document",
to_db: bool = False,
exclude: Optional[Set[str]] = None,
keep_nulls: bool = True,
):
if exclude is None:
exclude = set()
if document.id is None:
exclude.add("_id")
if not document.get_settings().use_revision:
exclude.add("revision_id")
encoder = Encoder(exclude=exclude, to_db=to_db, keep_nulls=keep_nulls)
return encoder.encode(document)
def filter_none(d):
result = {}
for k, v in d.items():
if isinstance(v, dict):
filtered = filter_none(v)
if filtered:
result[k] = filtered
elif v is None:
result[k] = v
return result
def get_nulls(
document: "Document",
exclude: Optional[Set[str]] = None,
):
dictionary = get_dict(document, exclude=exclude, keep_nulls=True)
return filter_none(dictionary) | null |
167,810 | from typing import TYPE_CHECKING, Optional, Set
from beanie.odm.utils.encoder import Encoder
def get_dict(
document: "Document",
to_db: bool = False,
exclude: Optional[Set[str]] = None,
keep_nulls: bool = True,
):
if exclude is None:
exclude = set()
if document.id is None:
exclude.add("_id")
if not document.get_settings().use_revision:
exclude.add("revision_id")
encoder = Encoder(exclude=exclude, to_db=to_db, keep_nulls=keep_nulls)
return encoder.encode(document)
def get_top_level_nones(
document: "Document",
exclude: Optional[Set[str]] = None,
):
dictionary = get_dict(document, exclude=exclude, keep_nulls=True)
return {k: v for k, v in dictionary.items() if v is None} | null |
167,811 | from typing import Dict, Optional, Type, TypeVar
from pydantic import BaseModel
from beanie.odm.interfaces.detector import ModelType
from beanie.odm.utils.pydantic import get_config_value, get_model_fields
ProjectionModelType = TypeVar("ProjectionModelType", bound=BaseModel)
class ModelType(str, Enum):
def get_model_fields(model):
def get_config_value(model, parameter: str):
def get_projection(
model: Type[ProjectionModelType],
) -> Optional[Dict[str, int]]:
if hasattr(model, "get_model_type") and (
model.get_model_type() == ModelType.UnionDoc # type: ignore
or ( # type: ignore
model.get_model_type() == ModelType.Document # type: ignore
and model._inheritance_inited # type: ignore
)
): # type: ignore
return None
if hasattr(model, "Settings"): # MyPy checks
settings = getattr(model, "Settings")
if hasattr(settings, "projection"):
return getattr(settings, "projection")
if get_config_value(model, "extra") == "allow":
return None
document_projection: Dict[str, int] = {}
for name, field in get_model_fields(model).items():
document_projection[field.alias or name] = 1
return document_projection | null |
167,812 | from functools import wraps
from typing import TYPE_CHECKING, Callable
def validate_self_before(f: Callable):
@wraps(f)
async def wrapper(self: "DocType", *args, **kwargs):
await self.validate_self(*args, **kwargs)
return await f(self, *args, **kwargs)
return wrapper | null |
167,813 | import inspect
from functools import wraps
from typing import TYPE_CHECKING, Callable
from beanie.exceptions import StateManagementIsTurnedOff, StateNotSaved
def check_if_state_saved(self: "DocType"):
if not self.use_state_management():
raise StateManagementIsTurnedOff(
"State management is turned off for this document"
)
if self._saved_state is None:
raise StateNotSaved("No state was saved")
def saved_state_needed(f: Callable):
@wraps(f)
def sync_wrapper(self: "DocType", *args, **kwargs):
check_if_state_saved(self)
return f(self, *args, **kwargs)
@wraps(f)
async def async_wrapper(self: "DocType", *args, **kwargs):
check_if_state_saved(self)
return await f(self, *args, **kwargs)
if inspect.iscoroutinefunction(f):
return async_wrapper
return sync_wrapper | null |
167,814 | import inspect
from functools import wraps
from typing import TYPE_CHECKING, Callable
from beanie.exceptions import StateManagementIsTurnedOff, StateNotSaved
def check_if_previous_state_saved(self: "DocType"):
if not self.use_state_management():
raise StateManagementIsTurnedOff(
"State management is turned off for this document"
)
if not self.state_management_save_previous():
raise StateManagementIsTurnedOff(
"State management's option to save previous state is turned off for this document"
)
def previous_saved_state_needed(f: Callable):
@wraps(f)
def sync_wrapper(self: "DocType", *args, **kwargs):
check_if_previous_state_saved(self)
return f(self, *args, **kwargs)
@wraps(f)
async def async_wrapper(self: "DocType", *args, **kwargs):
check_if_previous_state_saved(self)
return await f(self, *args, **kwargs)
if inspect.iscoroutinefunction(f):
return async_wrapper
return sync_wrapper | null |
167,815 | import inspect
from functools import wraps
from typing import TYPE_CHECKING, Callable
from beanie.exceptions import StateManagementIsTurnedOff, StateNotSaved
def save_state_after(f: Callable):
@wraps(f)
async def wrapper(self: "DocType", *args, **kwargs):
result = await f(self, *args, **kwargs)
self._save_state()
return result
return wrapper | null |
167,816 | import dataclasses as dc
import datetime
import decimal
import enum
import ipaddress
import operator
import pathlib
import re
import uuid
from enum import Enum
from typing import (
Any,
Callable,
Container,
Iterable,
Mapping,
MutableMapping,
Optional,
Tuple,
)
import bson
import pydantic
import beanie
from beanie.odm.fields import Link, LinkTypes
from beanie.odm.utils.pydantic import IS_PYDANTIC_V2, get_model_fields
SingleArgCallable = Callable[[Any], Any]
def _get_encoder(
obj: Any, custom_encoders: Mapping[type, SingleArgCallable]
) -> Optional[SingleArgCallable]:
encoder = custom_encoders.get(type(obj))
if encoder is not None:
return encoder
for cls, encoder in custom_encoders.items():
if isinstance(obj, cls):
return encoder
return None | null |
167,817 | from typing import Optional
from fastapi import Depends, HTTPException, Path, Query
from starlette import status
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.db.errors import EntityDoesNotExist
from app.db.repositories.articles import ArticlesRepository
from app.models.domain.articles import Article
from app.models.domain.users import User
from app.models.schemas.articles import (
DEFAULT_ARTICLES_LIMIT,
DEFAULT_ARTICLES_OFFSET,
ArticlesFilters,
)
from app.resources import strings
from app.services.articles import check_user_can_modify_article
async def get_article_by_slug_from_path(
slug: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> Article:
try:
return await articles_repo.get_article_by_slug(slug=slug, requested_user=user)
except EntityDoesNotExist:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=strings.ARTICLE_DOES_NOT_EXIST_ERROR,
)
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
class Article(IDModelMixin, DateTimeModelMixin, RWModel):
slug: str
title: str
description: str
body: str
tags: List[str]
author: Profile
favorited: bool
favorites_count: int
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
def check_user_can_modify_article(article: Article, user: User) -> bool:
return article.author.username == user.username
def check_article_modification_permissions(
current_article: Article = Depends(get_article_by_slug_from_path),
user: User = Depends(get_current_user_authorizer()),
) -> None:
if not check_user_can_modify_article(current_article, user):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=strings.USER_IS_NOT_AUTHOR_OF_ARTICLE,
) | null |
167,818 | from typing import Optional
from fastapi import Depends, HTTPException, Path
from starlette import status
from app.api.dependencies import articles, authentication, database
from app.db.errors import EntityDoesNotExist
from app.db.repositories.comments import CommentsRepository
from app.models.domain.articles import Article
from app.models.domain.comments import Comment
from app.models.domain.users import User
from app.resources import strings
from app.services.comments import check_user_can_modify_comment
async def get_comment_by_id_from_path(
comment_id: int = Path(..., ge=1),
article: Article = Depends(articles.get_article_by_slug_from_path),
user: Optional[User] = Depends(
authentication.get_current_user_authorizer(required=False),
),
comments_repo: CommentsRepository = Depends(
database.get_repository(CommentsRepository),
),
) -> Comment:
try:
return await comments_repo.get_comment_by_id(
comment_id=comment_id,
article=article,
user=user,
)
except EntityDoesNotExist:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=strings.COMMENT_DOES_NOT_EXIST,
)
class Comment(IDModelMixin, DateTimeModelMixin, RWModel):
body: str
author: Profile
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
def check_user_can_modify_comment(comment: Comment, user: User) -> bool:
return comment.author.username == user.username
def check_comment_modification_permissions(
comment: Comment = Depends(get_comment_by_id_from_path),
user: User = Depends(authentication.get_current_user_authorizer()),
) -> None:
if not check_user_can_modify_comment(comment, user):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=strings.USER_IS_NOT_AUTHOR_OF_ARTICLE,
) | null |
167,819 | from fastapi import APIRouter, Depends
from app.api.dependencies.database import get_repository
from app.db.repositories.tags import TagsRepository
from app.models.schemas.tags import TagsInList
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
class TagsRepository(BaseRepository):
async def get_all_tags(self) -> List[str]:
tags_row = await queries.get_all_tags(self.connection)
return [tag[0] for tag in tags_row]
async def create_tags_that_dont_exist(self, *, tags: Sequence[str]) -> None:
await queries.create_new_tags(self.connection, [{"tag": tag} for tag in tags])
class TagsInList(BaseModel):
tags: List[str]
async def get_all_tags(
tags_repo: TagsRepository = Depends(get_repository(TagsRepository)),
) -> TagsInList:
tags = await tags_repo.get_all_tags()
return TagsInList(tags=tags) | null |
167,820 | from fastapi import APIRouter, Body, Depends, HTTPException
from starlette.status import HTTP_400_BAD_REQUEST
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.core.config import get_app_settings
from app.core.settings.app import AppSettings
from app.db.repositories.users import UsersRepository
from app.models.domain.users import User
from app.models.schemas.users import UserInResponse, UserInUpdate, UserWithToken
from app.resources import strings
from app.services import jwt
from app.services.authentication import check_email_is_taken, check_username_is_taken
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
def get_app_settings() -> AppSettings:
app_env = BaseAppSettings().app_env
config = environments[app_env]
return config()
class AppSettings(BaseAppSettings):
debug: bool = False
docs_url: str = "/docs"
openapi_prefix: str = ""
openapi_url: str = "/openapi.json"
redoc_url: str = "/redoc"
title: str = "FastAPI example application"
version: str = "0.0.0"
database_url: PostgresDsn
max_connection_count: int = 10
min_connection_count: int = 10
secret_key: SecretStr
api_prefix: str = "/api"
jwt_token_prefix: str = "Token"
allowed_hosts: List[str] = ["*"]
logging_level: int = logging.INFO
loggers: Tuple[str, str] = ("uvicorn.asgi", "uvicorn.access")
class Config:
validate_assignment = True
def fastapi_kwargs(self) -> Dict[str, Any]:
return {
"debug": self.debug,
"docs_url": self.docs_url,
"openapi_prefix": self.openapi_prefix,
"openapi_url": self.openapi_url,
"redoc_url": self.redoc_url,
"title": self.title,
"version": self.version,
}
def configure_logging(self) -> None:
logging.getLogger().handlers = [InterceptHandler()]
for logger_name in self.loggers:
logging_logger = logging.getLogger(logger_name)
logging_logger.handlers = [InterceptHandler(level=self.logging_level)]
logger.configure(handlers=[{"sink": sys.stderr, "level": self.logging_level}])
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
class UserWithToken(User):
token: str
class UserInResponse(RWSchema):
user: UserWithToken
import jwt
async def retrieve_current_user(
user: User = Depends(get_current_user_authorizer()),
settings: AppSettings = Depends(get_app_settings),
) -> UserInResponse:
token = jwt.create_access_token_for_user(
user,
str(settings.secret_key.get_secret_value()),
)
return UserInResponse(
user=UserWithToken(
username=user.username,
email=user.email,
bio=user.bio,
image=user.image,
token=token,
),
) | null |
167,821 | from fastapi import APIRouter, Body, Depends, HTTPException
from starlette.status import HTTP_400_BAD_REQUEST
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.core.config import get_app_settings
from app.core.settings.app import AppSettings
from app.db.repositories.users import UsersRepository
from app.models.domain.users import User
from app.models.schemas.users import UserInResponse, UserInUpdate, UserWithToken
from app.resources import strings
from app.services import jwt
from app.services.authentication import check_email_is_taken, check_username_is_taken
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
def get_app_settings() -> AppSettings:
app_env = BaseAppSettings().app_env
config = environments[app_env]
return config()
class AppSettings(BaseAppSettings):
debug: bool = False
docs_url: str = "/docs"
openapi_prefix: str = ""
openapi_url: str = "/openapi.json"
redoc_url: str = "/redoc"
title: str = "FastAPI example application"
version: str = "0.0.0"
database_url: PostgresDsn
max_connection_count: int = 10
min_connection_count: int = 10
secret_key: SecretStr
api_prefix: str = "/api"
jwt_token_prefix: str = "Token"
allowed_hosts: List[str] = ["*"]
logging_level: int = logging.INFO
loggers: Tuple[str, str] = ("uvicorn.asgi", "uvicorn.access")
class Config:
validate_assignment = True
def fastapi_kwargs(self) -> Dict[str, Any]:
return {
"debug": self.debug,
"docs_url": self.docs_url,
"openapi_prefix": self.openapi_prefix,
"openapi_url": self.openapi_url,
"redoc_url": self.redoc_url,
"title": self.title,
"version": self.version,
}
def configure_logging(self) -> None:
logging.getLogger().handlers = [InterceptHandler()]
for logger_name in self.loggers:
logging_logger = logging.getLogger(logger_name)
logging_logger.handlers = [InterceptHandler(level=self.logging_level)]
logger.configure(handlers=[{"sink": sys.stderr, "level": self.logging_level}])
class UsersRepository(BaseRepository):
async def get_user_by_email(self, *, email: str) -> UserInDB:
user_row = await queries.get_user_by_email(self.connection, email=email)
if user_row:
return UserInDB(**user_row)
raise EntityDoesNotExist("user with email {0} does not exist".format(email))
async def get_user_by_username(self, *, username: str) -> UserInDB:
user_row = await queries.get_user_by_username(
self.connection,
username=username,
)
if user_row:
return UserInDB(**user_row)
raise EntityDoesNotExist(
"user with username {0} does not exist".format(username),
)
async def create_user(
self,
*,
username: str,
email: str,
password: str,
) -> UserInDB:
user = UserInDB(username=username, email=email)
user.change_password(password)
async with self.connection.transaction():
user_row = await queries.create_new_user(
self.connection,
username=user.username,
email=user.email,
salt=user.salt,
hashed_password=user.hashed_password,
)
return user.copy(update=dict(user_row))
async def update_user( # noqa: WPS211
self,
*,
user: User,
username: Optional[str] = None,
email: Optional[str] = None,
password: Optional[str] = None,
bio: Optional[str] = None,
image: Optional[str] = None,
) -> UserInDB:
user_in_db = await self.get_user_by_username(username=user.username)
user_in_db.username = username or user_in_db.username
user_in_db.email = email or user_in_db.email
user_in_db.bio = bio or user_in_db.bio
user_in_db.image = image or user_in_db.image
if password:
user_in_db.change_password(password)
async with self.connection.transaction():
user_in_db.updated_at = await queries.update_user_by_username(
self.connection,
username=user.username,
new_username=user_in_db.username,
new_email=user_in_db.email,
new_salt=user_in_db.salt,
new_password=user_in_db.hashed_password,
new_bio=user_in_db.bio,
new_image=user_in_db.image,
)
return user_in_db
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
class UserInUpdate(BaseModel):
username: Optional[str] = None
email: Optional[EmailStr] = None
password: Optional[str] = None
bio: Optional[str] = None
image: Optional[HttpUrl] = None
class UserWithToken(User):
token: str
class UserInResponse(RWSchema):
user: UserWithToken
import jwt
async def check_username_is_taken(repo: UsersRepository, username: str) -> bool:
try:
await repo.get_user_by_username(username=username)
except EntityDoesNotExist:
return False
return True
async def check_email_is_taken(repo: UsersRepository, email: str) -> bool:
try:
await repo.get_user_by_email(email=email)
except EntityDoesNotExist:
return False
return True
async def update_current_user(
user_update: UserInUpdate = Body(..., embed=True, alias="user"),
current_user: User = Depends(get_current_user_authorizer()),
users_repo: UsersRepository = Depends(get_repository(UsersRepository)),
settings: AppSettings = Depends(get_app_settings),
) -> UserInResponse:
if user_update.username and user_update.username != current_user.username:
if await check_username_is_taken(users_repo, user_update.username):
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=strings.USERNAME_TAKEN,
)
if user_update.email and user_update.email != current_user.email:
if await check_email_is_taken(users_repo, user_update.email):
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=strings.EMAIL_TAKEN,
)
user = await users_repo.update_user(user=current_user, **user_update.dict())
token = jwt.create_access_token_for_user(
user,
str(settings.secret_key.get_secret_value()),
)
return UserInResponse(
user=UserWithToken(
username=user.username,
email=user.email,
bio=user.bio,
image=user.image,
token=token,
),
) | null |
167,822 | from fastapi import APIRouter, Depends, HTTPException
from starlette.status import HTTP_400_BAD_REQUEST
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.api.dependencies.profiles import get_profile_by_username_from_path
from app.db.repositories.profiles import ProfilesRepository
from app.models.domain.profiles import Profile
from app.models.domain.users import User
from app.models.schemas.profiles import ProfileInResponse
from app.resources import strings
async def get_profile_by_username_from_path(
username: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
profiles_repo: ProfilesRepository = Depends(get_repository(ProfilesRepository)),
) -> Profile:
try:
return await profiles_repo.get_profile_by_username(
username=username,
requested_user=user,
)
except EntityDoesNotExist:
raise HTTPException(
status_code=HTTP_404_NOT_FOUND,
detail=strings.USER_DOES_NOT_EXIST_ERROR,
)
class Profile(RWModel):
username: str
bio: str = ""
image: Optional[str] = None
following: bool = False
class ProfileInResponse(BaseModel):
profile: Profile
async def retrieve_profile_by_username(
profile: Profile = Depends(get_profile_by_username_from_path),
) -> ProfileInResponse:
return ProfileInResponse(profile=profile) | null |
167,823 | from fastapi import APIRouter, Depends, HTTPException
from starlette.status import HTTP_400_BAD_REQUEST
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.api.dependencies.profiles import get_profile_by_username_from_path
from app.db.repositories.profiles import ProfilesRepository
from app.models.domain.profiles import Profile
from app.models.domain.users import User
from app.models.schemas.profiles import ProfileInResponse
from app.resources import strings
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
async def get_profile_by_username_from_path(
username: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
profiles_repo: ProfilesRepository = Depends(get_repository(ProfilesRepository)),
) -> Profile:
try:
return await profiles_repo.get_profile_by_username(
username=username,
requested_user=user,
)
except EntityDoesNotExist:
raise HTTPException(
status_code=HTTP_404_NOT_FOUND,
detail=strings.USER_DOES_NOT_EXIST_ERROR,
)
class ProfilesRepository(BaseRepository):
def __init__(self, conn: Connection):
super().__init__(conn)
self._users_repo = UsersRepository(conn)
async def get_profile_by_username(
self,
*,
username: str,
requested_user: Optional[UserLike],
) -> Profile:
user = await self._users_repo.get_user_by_username(username=username)
profile = Profile(username=user.username, bio=user.bio, image=user.image)
if requested_user:
profile.following = await self.is_user_following_for_another_user(
target_user=user,
requested_user=requested_user,
)
return profile
async def is_user_following_for_another_user(
self,
*,
target_user: UserLike,
requested_user: UserLike,
) -> bool:
return (
await queries.is_user_following_for_another(
self.connection,
follower_username=requested_user.username,
following_username=target_user.username,
)
)["is_following"]
async def add_user_into_followers(
self,
*,
target_user: UserLike,
requested_user: UserLike,
) -> None:
async with self.connection.transaction():
await queries.subscribe_user_to_another(
self.connection,
follower_username=requested_user.username,
following_username=target_user.username,
)
async def remove_user_from_followers(
self,
*,
target_user: UserLike,
requested_user: UserLike,
) -> None:
async with self.connection.transaction():
await queries.unsubscribe_user_from_another(
self.connection,
follower_username=requested_user.username,
following_username=target_user.username,
)
class Profile(RWModel):
username: str
bio: str = ""
image: Optional[str] = None
following: bool = False
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
class ProfileInResponse(BaseModel):
profile: Profile
async def follow_for_user(
profile: Profile = Depends(get_profile_by_username_from_path),
user: User = Depends(get_current_user_authorizer()),
profiles_repo: ProfilesRepository = Depends(get_repository(ProfilesRepository)),
) -> ProfileInResponse:
if user.username == profile.username:
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=strings.UNABLE_TO_FOLLOW_YOURSELF,
)
if profile.following:
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=strings.USER_IS_ALREADY_FOLLOWED,
)
await profiles_repo.add_user_into_followers(
target_user=profile,
requested_user=user,
)
return ProfileInResponse(profile=profile.copy(update={"following": True})) | null |
167,824 | from fastapi import APIRouter, Depends, HTTPException
from starlette.status import HTTP_400_BAD_REQUEST
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.api.dependencies.profiles import get_profile_by_username_from_path
from app.db.repositories.profiles import ProfilesRepository
from app.models.domain.profiles import Profile
from app.models.domain.users import User
from app.models.schemas.profiles import ProfileInResponse
from app.resources import strings
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
async def get_profile_by_username_from_path(
username: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
profiles_repo: ProfilesRepository = Depends(get_repository(ProfilesRepository)),
) -> Profile:
try:
return await profiles_repo.get_profile_by_username(
username=username,
requested_user=user,
)
except EntityDoesNotExist:
raise HTTPException(
status_code=HTTP_404_NOT_FOUND,
detail=strings.USER_DOES_NOT_EXIST_ERROR,
)
class ProfilesRepository(BaseRepository):
def __init__(self, conn: Connection):
super().__init__(conn)
self._users_repo = UsersRepository(conn)
async def get_profile_by_username(
self,
*,
username: str,
requested_user: Optional[UserLike],
) -> Profile:
user = await self._users_repo.get_user_by_username(username=username)
profile = Profile(username=user.username, bio=user.bio, image=user.image)
if requested_user:
profile.following = await self.is_user_following_for_another_user(
target_user=user,
requested_user=requested_user,
)
return profile
async def is_user_following_for_another_user(
self,
*,
target_user: UserLike,
requested_user: UserLike,
) -> bool:
return (
await queries.is_user_following_for_another(
self.connection,
follower_username=requested_user.username,
following_username=target_user.username,
)
)["is_following"]
async def add_user_into_followers(
self,
*,
target_user: UserLike,
requested_user: UserLike,
) -> None:
async with self.connection.transaction():
await queries.subscribe_user_to_another(
self.connection,
follower_username=requested_user.username,
following_username=target_user.username,
)
async def remove_user_from_followers(
self,
*,
target_user: UserLike,
requested_user: UserLike,
) -> None:
async with self.connection.transaction():
await queries.unsubscribe_user_from_another(
self.connection,
follower_username=requested_user.username,
following_username=target_user.username,
)
class Profile(RWModel):
username: str
bio: str = ""
image: Optional[str] = None
following: bool = False
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
class ProfileInResponse(BaseModel):
profile: Profile
async def unsubscribe_from_user(
profile: Profile = Depends(get_profile_by_username_from_path),
user: User = Depends(get_current_user_authorizer()),
profiles_repo: ProfilesRepository = Depends(get_repository(ProfilesRepository)),
) -> ProfileInResponse:
if user.username == profile.username:
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=strings.UNABLE_TO_UNSUBSCRIBE_FROM_YOURSELF,
)
if not profile.following:
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=strings.USER_IS_NOT_FOLLOWED,
)
await profiles_repo.remove_user_from_followers(
target_user=profile,
requested_user=user,
)
return ProfileInResponse(profile=profile.copy(update={"following": False})) | null |
167,825 | from fastapi import APIRouter, Body, Depends, HTTPException
from starlette.status import HTTP_201_CREATED, HTTP_400_BAD_REQUEST
from app.api.dependencies.database import get_repository
from app.core.config import get_app_settings
from app.core.settings.app import AppSettings
from app.db.errors import EntityDoesNotExist
from app.db.repositories.users import UsersRepository
from app.models.schemas.users import (
UserInCreate,
UserInLogin,
UserInResponse,
UserWithToken,
)
from app.resources import strings
from app.services import jwt
from app.services.authentication import check_email_is_taken, check_username_is_taken
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
def get_app_settings() -> AppSettings:
app_env = BaseAppSettings().app_env
config = environments[app_env]
return config()
class AppSettings(BaseAppSettings):
debug: bool = False
docs_url: str = "/docs"
openapi_prefix: str = ""
openapi_url: str = "/openapi.json"
redoc_url: str = "/redoc"
title: str = "FastAPI example application"
version: str = "0.0.0"
database_url: PostgresDsn
max_connection_count: int = 10
min_connection_count: int = 10
secret_key: SecretStr
api_prefix: str = "/api"
jwt_token_prefix: str = "Token"
allowed_hosts: List[str] = ["*"]
logging_level: int = logging.INFO
loggers: Tuple[str, str] = ("uvicorn.asgi", "uvicorn.access")
class Config:
validate_assignment = True
def fastapi_kwargs(self) -> Dict[str, Any]:
return {
"debug": self.debug,
"docs_url": self.docs_url,
"openapi_prefix": self.openapi_prefix,
"openapi_url": self.openapi_url,
"redoc_url": self.redoc_url,
"title": self.title,
"version": self.version,
}
def configure_logging(self) -> None:
logging.getLogger().handlers = [InterceptHandler()]
for logger_name in self.loggers:
logging_logger = logging.getLogger(logger_name)
logging_logger.handlers = [InterceptHandler(level=self.logging_level)]
logger.configure(handlers=[{"sink": sys.stderr, "level": self.logging_level}])
class EntityDoesNotExist(Exception):
"""Raised when entity was not found in database."""
class UsersRepository(BaseRepository):
async def get_user_by_email(self, *, email: str) -> UserInDB:
user_row = await queries.get_user_by_email(self.connection, email=email)
if user_row:
return UserInDB(**user_row)
raise EntityDoesNotExist("user with email {0} does not exist".format(email))
async def get_user_by_username(self, *, username: str) -> UserInDB:
user_row = await queries.get_user_by_username(
self.connection,
username=username,
)
if user_row:
return UserInDB(**user_row)
raise EntityDoesNotExist(
"user with username {0} does not exist".format(username),
)
async def create_user(
self,
*,
username: str,
email: str,
password: str,
) -> UserInDB:
user = UserInDB(username=username, email=email)
user.change_password(password)
async with self.connection.transaction():
user_row = await queries.create_new_user(
self.connection,
username=user.username,
email=user.email,
salt=user.salt,
hashed_password=user.hashed_password,
)
return user.copy(update=dict(user_row))
async def update_user( # noqa: WPS211
self,
*,
user: User,
username: Optional[str] = None,
email: Optional[str] = None,
password: Optional[str] = None,
bio: Optional[str] = None,
image: Optional[str] = None,
) -> UserInDB:
user_in_db = await self.get_user_by_username(username=user.username)
user_in_db.username = username or user_in_db.username
user_in_db.email = email or user_in_db.email
user_in_db.bio = bio or user_in_db.bio
user_in_db.image = image or user_in_db.image
if password:
user_in_db.change_password(password)
async with self.connection.transaction():
user_in_db.updated_at = await queries.update_user_by_username(
self.connection,
username=user.username,
new_username=user_in_db.username,
new_email=user_in_db.email,
new_salt=user_in_db.salt,
new_password=user_in_db.hashed_password,
new_bio=user_in_db.bio,
new_image=user_in_db.image,
)
return user_in_db
class UserInLogin(RWSchema):
email: EmailStr
password: str
class UserWithToken(User):
token: str
class UserInResponse(RWSchema):
user: UserWithToken
import jwt
async def login(
user_login: UserInLogin = Body(..., embed=True, alias="user"),
users_repo: UsersRepository = Depends(get_repository(UsersRepository)),
settings: AppSettings = Depends(get_app_settings),
) -> UserInResponse:
wrong_login_error = HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=strings.INCORRECT_LOGIN_INPUT,
)
try:
user = await users_repo.get_user_by_email(email=user_login.email)
except EntityDoesNotExist as existence_error:
raise wrong_login_error from existence_error
if not user.check_password(user_login.password):
raise wrong_login_error
token = jwt.create_access_token_for_user(
user,
str(settings.secret_key.get_secret_value()),
)
return UserInResponse(
user=UserWithToken(
username=user.username,
email=user.email,
bio=user.bio,
image=user.image,
token=token,
),
) | null |
167,826 | from fastapi import APIRouter, Body, Depends, HTTPException
from starlette.status import HTTP_201_CREATED, HTTP_400_BAD_REQUEST
from app.api.dependencies.database import get_repository
from app.core.config import get_app_settings
from app.core.settings.app import AppSettings
from app.db.errors import EntityDoesNotExist
from app.db.repositories.users import UsersRepository
from app.models.schemas.users import (
UserInCreate,
UserInLogin,
UserInResponse,
UserWithToken,
)
from app.resources import strings
from app.services import jwt
from app.services.authentication import check_email_is_taken, check_username_is_taken
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
def get_app_settings() -> AppSettings:
app_env = BaseAppSettings().app_env
config = environments[app_env]
return config()
class AppSettings(BaseAppSettings):
debug: bool = False
docs_url: str = "/docs"
openapi_prefix: str = ""
openapi_url: str = "/openapi.json"
redoc_url: str = "/redoc"
title: str = "FastAPI example application"
version: str = "0.0.0"
database_url: PostgresDsn
max_connection_count: int = 10
min_connection_count: int = 10
secret_key: SecretStr
api_prefix: str = "/api"
jwt_token_prefix: str = "Token"
allowed_hosts: List[str] = ["*"]
logging_level: int = logging.INFO
loggers: Tuple[str, str] = ("uvicorn.asgi", "uvicorn.access")
class Config:
validate_assignment = True
def fastapi_kwargs(self) -> Dict[str, Any]:
return {
"debug": self.debug,
"docs_url": self.docs_url,
"openapi_prefix": self.openapi_prefix,
"openapi_url": self.openapi_url,
"redoc_url": self.redoc_url,
"title": self.title,
"version": self.version,
}
def configure_logging(self) -> None:
logging.getLogger().handlers = [InterceptHandler()]
for logger_name in self.loggers:
logging_logger = logging.getLogger(logger_name)
logging_logger.handlers = [InterceptHandler(level=self.logging_level)]
logger.configure(handlers=[{"sink": sys.stderr, "level": self.logging_level}])
class UsersRepository(BaseRepository):
async def get_user_by_email(self, *, email: str) -> UserInDB:
user_row = await queries.get_user_by_email(self.connection, email=email)
if user_row:
return UserInDB(**user_row)
raise EntityDoesNotExist("user with email {0} does not exist".format(email))
async def get_user_by_username(self, *, username: str) -> UserInDB:
user_row = await queries.get_user_by_username(
self.connection,
username=username,
)
if user_row:
return UserInDB(**user_row)
raise EntityDoesNotExist(
"user with username {0} does not exist".format(username),
)
async def create_user(
self,
*,
username: str,
email: str,
password: str,
) -> UserInDB:
user = UserInDB(username=username, email=email)
user.change_password(password)
async with self.connection.transaction():
user_row = await queries.create_new_user(
self.connection,
username=user.username,
email=user.email,
salt=user.salt,
hashed_password=user.hashed_password,
)
return user.copy(update=dict(user_row))
async def update_user( # noqa: WPS211
self,
*,
user: User,
username: Optional[str] = None,
email: Optional[str] = None,
password: Optional[str] = None,
bio: Optional[str] = None,
image: Optional[str] = None,
) -> UserInDB:
user_in_db = await self.get_user_by_username(username=user.username)
user_in_db.username = username or user_in_db.username
user_in_db.email = email or user_in_db.email
user_in_db.bio = bio or user_in_db.bio
user_in_db.image = image or user_in_db.image
if password:
user_in_db.change_password(password)
async with self.connection.transaction():
user_in_db.updated_at = await queries.update_user_by_username(
self.connection,
username=user.username,
new_username=user_in_db.username,
new_email=user_in_db.email,
new_salt=user_in_db.salt,
new_password=user_in_db.hashed_password,
new_bio=user_in_db.bio,
new_image=user_in_db.image,
)
return user_in_db
class UserInCreate(UserInLogin):
username: str
class UserWithToken(User):
token: str
class UserInResponse(RWSchema):
user: UserWithToken
import jwt
async def check_username_is_taken(repo: UsersRepository, username: str) -> bool:
try:
await repo.get_user_by_username(username=username)
except EntityDoesNotExist:
return False
return True
async def check_email_is_taken(repo: UsersRepository, email: str) -> bool:
try:
await repo.get_user_by_email(email=email)
except EntityDoesNotExist:
return False
return True
async def register(
user_create: UserInCreate = Body(..., embed=True, alias="user"),
users_repo: UsersRepository = Depends(get_repository(UsersRepository)),
settings: AppSettings = Depends(get_app_settings),
) -> UserInResponse:
if await check_username_is_taken(users_repo, user_create.username):
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=strings.USERNAME_TAKEN,
)
if await check_email_is_taken(users_repo, user_create.email):
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail=strings.EMAIL_TAKEN,
)
user = await users_repo.create_user(**user_create.dict())
token = jwt.create_access_token_for_user(
user,
str(settings.secret_key.get_secret_value()),
)
return UserInResponse(
user=UserWithToken(
username=user.username,
email=user.email,
bio=user.bio,
image=user.image,
token=token,
),
) | null |
167,827 | from typing import Optional
from fastapi import APIRouter, Body, Depends, HTTPException, Response
from starlette import status
from app.api.dependencies.articles import (
check_article_modification_permissions,
get_article_by_slug_from_path,
get_articles_filters,
)
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.db.repositories.articles import ArticlesRepository
from app.models.domain.articles import Article
from app.models.domain.users import User
from app.models.schemas.articles import (
ArticleForResponse,
ArticleInCreate,
ArticleInResponse,
ArticleInUpdate,
ArticlesFilters,
ListOfArticlesInResponse,
)
from app.resources import strings
from app.services.articles import check_article_exists, get_slug_for_article
def get_articles_filters(
tag: Optional[str] = None,
author: Optional[str] = None,
favorited: Optional[str] = None,
limit: int = Query(DEFAULT_ARTICLES_LIMIT, ge=1),
offset: int = Query(DEFAULT_ARTICLES_OFFSET, ge=0),
) -> ArticlesFilters:
return ArticlesFilters(
tag=tag,
author=author,
favorited=favorited,
limit=limit,
offset=offset,
)
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
class ArticlesRepository(BaseRepository): # noqa: WPS214
def __init__(self, conn: Connection) -> None:
super().__init__(conn)
self._profiles_repo = ProfilesRepository(conn)
self._tags_repo = TagsRepository(conn)
async def create_article( # noqa: WPS211
self,
*,
slug: str,
title: str,
description: str,
body: str,
author: User,
tags: Optional[Sequence[str]] = None,
) -> Article:
async with self.connection.transaction():
article_row = await queries.create_new_article(
self.connection,
slug=slug,
title=title,
description=description,
body=body,
author_username=author.username,
)
if tags:
await self._tags_repo.create_tags_that_dont_exist(tags=tags)
await self._link_article_with_tags(slug=slug, tags=tags)
return await self._get_article_from_db_record(
article_row=article_row,
slug=slug,
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=author,
)
async def update_article( # noqa: WPS211
self,
*,
article: Article,
slug: Optional[str] = None,
title: Optional[str] = None,
body: Optional[str] = None,
description: Optional[str] = None,
) -> Article:
updated_article = article.copy(deep=True)
updated_article.slug = slug or updated_article.slug
updated_article.title = title or article.title
updated_article.body = body or article.body
updated_article.description = description or article.description
async with self.connection.transaction():
updated_article.updated_at = await queries.update_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
new_slug=updated_article.slug,
new_title=updated_article.title,
new_body=updated_article.body,
new_description=updated_article.description,
)
return updated_article
async def delete_article(self, *, article: Article) -> None:
async with self.connection.transaction():
await queries.delete_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
)
async def filter_articles( # noqa: WPS211
self,
*,
tag: Optional[str] = None,
author: Optional[str] = None,
favorited: Optional[str] = None,
limit: int = 20,
offset: int = 0,
requested_user: Optional[User] = None,
) -> List[Article]:
query_params: List[Union[str, int]] = []
query_params_count = 0
# fmt: off
query = Query.from_(
articles,
).select(
articles.id,
articles.slug,
articles.title,
articles.description,
articles.body,
articles.created_at,
articles.updated_at,
Query.from_(
users,
).where(
users.id == articles.author_id,
).select(
users.username,
).as_(
AUTHOR_USERNAME_ALIAS,
),
)
# fmt: on
if tag:
query_params.append(tag)
query_params_count += 1
# fmt: off
query = query.join(
articles_to_tags,
).on(
(articles.id == articles_to_tags.article_id) & (
articles_to_tags.tag == Query.from_(
tags_table,
).where(
tags_table.tag == Parameter(query_params_count),
).select(
tags_table.tag,
)
),
)
# fmt: on
if author:
query_params.append(author)
query_params_count += 1
# fmt: off
query = query.join(
users,
).on(
(articles.author_id == users.id) & (
users.id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
if favorited:
query_params.append(favorited)
query_params_count += 1
# fmt: off
query = query.join(
favorites,
).on(
(articles.id == favorites.article_id) & (
favorites.user_id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
query = query.limit(Parameter(query_params_count + 1)).offset(
Parameter(query_params_count + 2),
)
query_params.extend([limit, offset])
articles_rows = await self.connection.fetch(query.get_sql(), *query_params)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
for article_row in articles_rows
]
async def get_articles_for_user_feed(
self,
*,
user: User,
limit: int = 20,
offset: int = 0,
) -> List[Article]:
articles_rows = await queries.get_articles_for_feed(
self.connection,
follower_username=user.username,
limit=limit,
offset=offset,
)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=user,
)
for article_row in articles_rows
]
async def get_article_by_slug(
self,
*,
slug: str,
requested_user: Optional[User] = None,
) -> Article:
article_row = await queries.get_article_by_slug(self.connection, slug=slug)
if article_row:
return await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
raise EntityDoesNotExist("article with slug {0} does not exist".format(slug))
async def get_tags_for_article_by_slug(self, *, slug: str) -> List[str]:
tag_rows = await queries.get_tags_for_article_by_slug(
self.connection,
slug=slug,
)
return [row["tag"] for row in tag_rows]
async def get_favorites_count_for_article_by_slug(self, *, slug: str) -> int:
return (
await queries.get_favorites_count_for_article(self.connection, slug=slug)
)["favorites_count"]
async def is_article_favorited_by_user(self, *, slug: str, user: User) -> bool:
return (
await queries.is_article_in_favorites(
self.connection,
username=user.username,
slug=slug,
)
)["favorited"]
async def add_article_into_favorites(self, *, article: Article, user: User) -> None:
await queries.add_article_to_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def remove_article_from_favorites(
self,
*,
article: Article,
user: User,
) -> None:
await queries.remove_article_from_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def _get_article_from_db_record(
self,
*,
article_row: Record,
slug: str,
author_username: str,
requested_user: Optional[User],
) -> Article:
return Article(
id_=article_row["id"],
slug=slug,
title=article_row["title"],
description=article_row["description"],
body=article_row["body"],
author=await self._profiles_repo.get_profile_by_username(
username=author_username,
requested_user=requested_user,
),
tags=await self.get_tags_for_article_by_slug(slug=slug),
favorites_count=await self.get_favorites_count_for_article_by_slug(
slug=slug,
),
favorited=await self.is_article_favorited_by_user(
slug=slug,
user=requested_user,
)
if requested_user
else False,
created_at=article_row["created_at"],
updated_at=article_row["updated_at"],
)
async def _link_article_with_tags(self, *, slug: str, tags: Sequence[str]) -> None:
await queries.add_tags_to_article(
self.connection,
[{SLUG_ALIAS: slug, "tag": tag} for tag in tags],
)
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
class ArticleForResponse(RWSchema, Article):
tags: List[str] = Field(..., alias="tagList")
class ListOfArticlesInResponse(RWSchema):
articles: List[ArticleForResponse]
articles_count: int
class ArticlesFilters(BaseModel):
tag: Optional[str] = None
author: Optional[str] = None
favorited: Optional[str] = None
limit: int = Field(DEFAULT_ARTICLES_LIMIT, ge=1)
offset: int = Field(DEFAULT_ARTICLES_OFFSET, ge=0)
async def list_articles(
articles_filters: ArticlesFilters = Depends(get_articles_filters),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> ListOfArticlesInResponse:
articles = await articles_repo.filter_articles(
tag=articles_filters.tag,
author=articles_filters.author,
favorited=articles_filters.favorited,
limit=articles_filters.limit,
offset=articles_filters.offset,
requested_user=user,
)
articles_for_response = [
ArticleForResponse.from_orm(article) for article in articles
]
return ListOfArticlesInResponse(
articles=articles_for_response,
articles_count=len(articles),
) | null |
167,828 | from typing import Optional
from fastapi import APIRouter, Body, Depends, HTTPException, Response
from starlette import status
from app.api.dependencies.articles import (
check_article_modification_permissions,
get_article_by_slug_from_path,
get_articles_filters,
)
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.db.repositories.articles import ArticlesRepository
from app.models.domain.articles import Article
from app.models.domain.users import User
from app.models.schemas.articles import (
ArticleForResponse,
ArticleInCreate,
ArticleInResponse,
ArticleInUpdate,
ArticlesFilters,
ListOfArticlesInResponse,
)
from app.resources import strings
from app.services.articles import check_article_exists, get_slug_for_article
def get_current_user_authorizer(*, required: bool = True) -> Callable:
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
class ArticlesRepository(BaseRepository):
def __init__(self, conn: Connection) -> None:
async def create_article( # noqa: WPS211
self,
*,
slug: str,
title: str,
description: str,
body: str,
author: User,
tags: Optional[Sequence[str]] = None,
) -> Article:
async def update_article( # noqa: WPS211
self,
*,
article: Article,
slug: Optional[str] = None,
title: Optional[str] = None,
body: Optional[str] = None,
description: Optional[str] = None,
) -> Article:
async def delete_article(self, *, article: Article) -> None:
async def filter_articles( # noqa: WPS211
self,
*,
tag: Optional[str] = None,
author: Optional[str] = None,
favorited: Optional[str] = None,
limit: int = 20,
offset: int = 0,
requested_user: Optional[User] = None,
) -> List[Article]:
async def get_articles_for_user_feed(
self,
*,
user: User,
limit: int = 20,
offset: int = 0,
) -> List[Article]:
async def get_article_by_slug(
self,
*,
slug: str,
requested_user: Optional[User] = None,
) -> Article:
async def get_tags_for_article_by_slug(self, *, slug: str) -> List[str]:
async def get_favorites_count_for_article_by_slug(self, *, slug: str) -> int:
async def is_article_favorited_by_user(self, *, slug: str, user: User) -> bool:
async def add_article_into_favorites(self, *, article: Article, user: User) -> None:
async def remove_article_from_favorites(
self,
*,
article: Article,
user: User,
) -> None:
async def _get_article_from_db_record(
self,
*,
article_row: Record,
slug: str,
author_username: str,
requested_user: Optional[User],
) -> Article:
async def _link_article_with_tags(self, *, slug: str, tags: Sequence[str]) -> None:
class User(RWModel):
class ArticleForResponse(RWSchema, Article):
class ArticleInResponse(RWSchema):
class ArticleInCreate(RWSchema):
async def check_article_exists(articles_repo: ArticlesRepository, slug: str) -> bool:
def get_slug_for_article(title: str) -> str:
async def create_new_article(
article_create: ArticleInCreate = Body(..., embed=True, alias="article"),
user: User = Depends(get_current_user_authorizer()),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> ArticleInResponse:
slug = get_slug_for_article(article_create.title)
if await check_article_exists(articles_repo, slug):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=strings.ARTICLE_ALREADY_EXISTS,
)
article = await articles_repo.create_article(
slug=slug,
title=article_create.title,
description=article_create.description,
body=article_create.body,
author=user,
tags=article_create.tags,
)
return ArticleInResponse(article=ArticleForResponse.from_orm(article)) | null |
167,829 | from typing import Optional
from fastapi import APIRouter, Body, Depends, HTTPException, Response
from starlette import status
from app.api.dependencies.articles import (
check_article_modification_permissions,
get_article_by_slug_from_path,
get_articles_filters,
)
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.db.repositories.articles import ArticlesRepository
from app.models.domain.articles import Article
from app.models.domain.users import User
from app.models.schemas.articles import (
ArticleForResponse,
ArticleInCreate,
ArticleInResponse,
ArticleInUpdate,
ArticlesFilters,
ListOfArticlesInResponse,
)
from app.resources import strings
from app.services.articles import check_article_exists, get_slug_for_article
async def get_article_by_slug_from_path(
slug: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> Article:
try:
return await articles_repo.get_article_by_slug(slug=slug, requested_user=user)
except EntityDoesNotExist:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=strings.ARTICLE_DOES_NOT_EXIST_ERROR,
)
class Article(IDModelMixin, DateTimeModelMixin, RWModel):
slug: str
title: str
description: str
body: str
tags: List[str]
author: Profile
favorited: bool
favorites_count: int
class ArticleForResponse(RWSchema, Article):
tags: List[str] = Field(..., alias="tagList")
class ArticleInResponse(RWSchema):
article: ArticleForResponse
async def retrieve_article_by_slug(
article: Article = Depends(get_article_by_slug_from_path),
) -> ArticleInResponse:
return ArticleInResponse(article=ArticleForResponse.from_orm(article)) | null |
167,830 | from typing import Optional
from fastapi import APIRouter, Body, Depends, HTTPException, Response
from starlette import status
from app.api.dependencies.articles import (
check_article_modification_permissions,
get_article_by_slug_from_path,
get_articles_filters,
)
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.db.repositories.articles import ArticlesRepository
from app.models.domain.articles import Article
from app.models.domain.users import User
from app.models.schemas.articles import (
ArticleForResponse,
ArticleInCreate,
ArticleInResponse,
ArticleInUpdate,
ArticlesFilters,
ListOfArticlesInResponse,
)
from app.resources import strings
from app.services.articles import check_article_exists, get_slug_for_article
async def get_article_by_slug_from_path(
slug: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> Article:
try:
return await articles_repo.get_article_by_slug(slug=slug, requested_user=user)
except EntityDoesNotExist:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=strings.ARTICLE_DOES_NOT_EXIST_ERROR,
)
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
class ArticlesRepository(BaseRepository): # noqa: WPS214
def __init__(self, conn: Connection) -> None:
super().__init__(conn)
self._profiles_repo = ProfilesRepository(conn)
self._tags_repo = TagsRepository(conn)
async def create_article( # noqa: WPS211
self,
*,
slug: str,
title: str,
description: str,
body: str,
author: User,
tags: Optional[Sequence[str]] = None,
) -> Article:
async with self.connection.transaction():
article_row = await queries.create_new_article(
self.connection,
slug=slug,
title=title,
description=description,
body=body,
author_username=author.username,
)
if tags:
await self._tags_repo.create_tags_that_dont_exist(tags=tags)
await self._link_article_with_tags(slug=slug, tags=tags)
return await self._get_article_from_db_record(
article_row=article_row,
slug=slug,
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=author,
)
async def update_article( # noqa: WPS211
self,
*,
article: Article,
slug: Optional[str] = None,
title: Optional[str] = None,
body: Optional[str] = None,
description: Optional[str] = None,
) -> Article:
updated_article = article.copy(deep=True)
updated_article.slug = slug or updated_article.slug
updated_article.title = title or article.title
updated_article.body = body or article.body
updated_article.description = description or article.description
async with self.connection.transaction():
updated_article.updated_at = await queries.update_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
new_slug=updated_article.slug,
new_title=updated_article.title,
new_body=updated_article.body,
new_description=updated_article.description,
)
return updated_article
async def delete_article(self, *, article: Article) -> None:
async with self.connection.transaction():
await queries.delete_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
)
async def filter_articles( # noqa: WPS211
self,
*,
tag: Optional[str] = None,
author: Optional[str] = None,
favorited: Optional[str] = None,
limit: int = 20,
offset: int = 0,
requested_user: Optional[User] = None,
) -> List[Article]:
query_params: List[Union[str, int]] = []
query_params_count = 0
# fmt: off
query = Query.from_(
articles,
).select(
articles.id,
articles.slug,
articles.title,
articles.description,
articles.body,
articles.created_at,
articles.updated_at,
Query.from_(
users,
).where(
users.id == articles.author_id,
).select(
users.username,
).as_(
AUTHOR_USERNAME_ALIAS,
),
)
# fmt: on
if tag:
query_params.append(tag)
query_params_count += 1
# fmt: off
query = query.join(
articles_to_tags,
).on(
(articles.id == articles_to_tags.article_id) & (
articles_to_tags.tag == Query.from_(
tags_table,
).where(
tags_table.tag == Parameter(query_params_count),
).select(
tags_table.tag,
)
),
)
# fmt: on
if author:
query_params.append(author)
query_params_count += 1
# fmt: off
query = query.join(
users,
).on(
(articles.author_id == users.id) & (
users.id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
if favorited:
query_params.append(favorited)
query_params_count += 1
# fmt: off
query = query.join(
favorites,
).on(
(articles.id == favorites.article_id) & (
favorites.user_id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
query = query.limit(Parameter(query_params_count + 1)).offset(
Parameter(query_params_count + 2),
)
query_params.extend([limit, offset])
articles_rows = await self.connection.fetch(query.get_sql(), *query_params)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
for article_row in articles_rows
]
async def get_articles_for_user_feed(
self,
*,
user: User,
limit: int = 20,
offset: int = 0,
) -> List[Article]:
articles_rows = await queries.get_articles_for_feed(
self.connection,
follower_username=user.username,
limit=limit,
offset=offset,
)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=user,
)
for article_row in articles_rows
]
async def get_article_by_slug(
self,
*,
slug: str,
requested_user: Optional[User] = None,
) -> Article:
article_row = await queries.get_article_by_slug(self.connection, slug=slug)
if article_row:
return await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
raise EntityDoesNotExist("article with slug {0} does not exist".format(slug))
async def get_tags_for_article_by_slug(self, *, slug: str) -> List[str]:
tag_rows = await queries.get_tags_for_article_by_slug(
self.connection,
slug=slug,
)
return [row["tag"] for row in tag_rows]
async def get_favorites_count_for_article_by_slug(self, *, slug: str) -> int:
return (
await queries.get_favorites_count_for_article(self.connection, slug=slug)
)["favorites_count"]
async def is_article_favorited_by_user(self, *, slug: str, user: User) -> bool:
return (
await queries.is_article_in_favorites(
self.connection,
username=user.username,
slug=slug,
)
)["favorited"]
async def add_article_into_favorites(self, *, article: Article, user: User) -> None:
await queries.add_article_to_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def remove_article_from_favorites(
self,
*,
article: Article,
user: User,
) -> None:
await queries.remove_article_from_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def _get_article_from_db_record(
self,
*,
article_row: Record,
slug: str,
author_username: str,
requested_user: Optional[User],
) -> Article:
return Article(
id_=article_row["id"],
slug=slug,
title=article_row["title"],
description=article_row["description"],
body=article_row["body"],
author=await self._profiles_repo.get_profile_by_username(
username=author_username,
requested_user=requested_user,
),
tags=await self.get_tags_for_article_by_slug(slug=slug),
favorites_count=await self.get_favorites_count_for_article_by_slug(
slug=slug,
),
favorited=await self.is_article_favorited_by_user(
slug=slug,
user=requested_user,
)
if requested_user
else False,
created_at=article_row["created_at"],
updated_at=article_row["updated_at"],
)
async def _link_article_with_tags(self, *, slug: str, tags: Sequence[str]) -> None:
await queries.add_tags_to_article(
self.connection,
[{SLUG_ALIAS: slug, "tag": tag} for tag in tags],
)
class Article(IDModelMixin, DateTimeModelMixin, RWModel):
slug: str
title: str
description: str
body: str
tags: List[str]
author: Profile
favorited: bool
favorites_count: int
class ArticleForResponse(RWSchema, Article):
tags: List[str] = Field(..., alias="tagList")
class ArticleInResponse(RWSchema):
article: ArticleForResponse
class ArticleInUpdate(RWSchema):
title: Optional[str] = None
description: Optional[str] = None
body: Optional[str] = None
def get_slug_for_article(title: str) -> str:
return slugify(title)
async def update_article_by_slug(
article_update: ArticleInUpdate = Body(..., embed=True, alias="article"),
current_article: Article = Depends(get_article_by_slug_from_path),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> ArticleInResponse:
slug = get_slug_for_article(article_update.title) if article_update.title else None
article = await articles_repo.update_article(
article=current_article,
slug=slug,
**article_update.dict(),
)
return ArticleInResponse(article=ArticleForResponse.from_orm(article)) | null |
167,831 | from typing import Optional
from fastapi import APIRouter, Body, Depends, HTTPException, Response
from starlette import status
from app.api.dependencies.articles import (
check_article_modification_permissions,
get_article_by_slug_from_path,
get_articles_filters,
)
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.db.repositories.articles import ArticlesRepository
from app.models.domain.articles import Article
from app.models.domain.users import User
from app.models.schemas.articles import (
ArticleForResponse,
ArticleInCreate,
ArticleInResponse,
ArticleInUpdate,
ArticlesFilters,
ListOfArticlesInResponse,
)
from app.resources import strings
from app.services.articles import check_article_exists, get_slug_for_article
async def get_article_by_slug_from_path(
slug: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> Article:
try:
return await articles_repo.get_article_by_slug(slug=slug, requested_user=user)
except EntityDoesNotExist:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=strings.ARTICLE_DOES_NOT_EXIST_ERROR,
)
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
class ArticlesRepository(BaseRepository): # noqa: WPS214
def __init__(self, conn: Connection) -> None:
super().__init__(conn)
self._profiles_repo = ProfilesRepository(conn)
self._tags_repo = TagsRepository(conn)
async def create_article( # noqa: WPS211
self,
*,
slug: str,
title: str,
description: str,
body: str,
author: User,
tags: Optional[Sequence[str]] = None,
) -> Article:
async with self.connection.transaction():
article_row = await queries.create_new_article(
self.connection,
slug=slug,
title=title,
description=description,
body=body,
author_username=author.username,
)
if tags:
await self._tags_repo.create_tags_that_dont_exist(tags=tags)
await self._link_article_with_tags(slug=slug, tags=tags)
return await self._get_article_from_db_record(
article_row=article_row,
slug=slug,
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=author,
)
async def update_article( # noqa: WPS211
self,
*,
article: Article,
slug: Optional[str] = None,
title: Optional[str] = None,
body: Optional[str] = None,
description: Optional[str] = None,
) -> Article:
updated_article = article.copy(deep=True)
updated_article.slug = slug or updated_article.slug
updated_article.title = title or article.title
updated_article.body = body or article.body
updated_article.description = description or article.description
async with self.connection.transaction():
updated_article.updated_at = await queries.update_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
new_slug=updated_article.slug,
new_title=updated_article.title,
new_body=updated_article.body,
new_description=updated_article.description,
)
return updated_article
async def delete_article(self, *, article: Article) -> None:
async with self.connection.transaction():
await queries.delete_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
)
async def filter_articles( # noqa: WPS211
self,
*,
tag: Optional[str] = None,
author: Optional[str] = None,
favorited: Optional[str] = None,
limit: int = 20,
offset: int = 0,
requested_user: Optional[User] = None,
) -> List[Article]:
query_params: List[Union[str, int]] = []
query_params_count = 0
# fmt: off
query = Query.from_(
articles,
).select(
articles.id,
articles.slug,
articles.title,
articles.description,
articles.body,
articles.created_at,
articles.updated_at,
Query.from_(
users,
).where(
users.id == articles.author_id,
).select(
users.username,
).as_(
AUTHOR_USERNAME_ALIAS,
),
)
# fmt: on
if tag:
query_params.append(tag)
query_params_count += 1
# fmt: off
query = query.join(
articles_to_tags,
).on(
(articles.id == articles_to_tags.article_id) & (
articles_to_tags.tag == Query.from_(
tags_table,
).where(
tags_table.tag == Parameter(query_params_count),
).select(
tags_table.tag,
)
),
)
# fmt: on
if author:
query_params.append(author)
query_params_count += 1
# fmt: off
query = query.join(
users,
).on(
(articles.author_id == users.id) & (
users.id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
if favorited:
query_params.append(favorited)
query_params_count += 1
# fmt: off
query = query.join(
favorites,
).on(
(articles.id == favorites.article_id) & (
favorites.user_id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
query = query.limit(Parameter(query_params_count + 1)).offset(
Parameter(query_params_count + 2),
)
query_params.extend([limit, offset])
articles_rows = await self.connection.fetch(query.get_sql(), *query_params)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
for article_row in articles_rows
]
async def get_articles_for_user_feed(
self,
*,
user: User,
limit: int = 20,
offset: int = 0,
) -> List[Article]:
articles_rows = await queries.get_articles_for_feed(
self.connection,
follower_username=user.username,
limit=limit,
offset=offset,
)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=user,
)
for article_row in articles_rows
]
async def get_article_by_slug(
self,
*,
slug: str,
requested_user: Optional[User] = None,
) -> Article:
article_row = await queries.get_article_by_slug(self.connection, slug=slug)
if article_row:
return await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
raise EntityDoesNotExist("article with slug {0} does not exist".format(slug))
async def get_tags_for_article_by_slug(self, *, slug: str) -> List[str]:
tag_rows = await queries.get_tags_for_article_by_slug(
self.connection,
slug=slug,
)
return [row["tag"] for row in tag_rows]
async def get_favorites_count_for_article_by_slug(self, *, slug: str) -> int:
return (
await queries.get_favorites_count_for_article(self.connection, slug=slug)
)["favorites_count"]
async def is_article_favorited_by_user(self, *, slug: str, user: User) -> bool:
return (
await queries.is_article_in_favorites(
self.connection,
username=user.username,
slug=slug,
)
)["favorited"]
async def add_article_into_favorites(self, *, article: Article, user: User) -> None:
await queries.add_article_to_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def remove_article_from_favorites(
self,
*,
article: Article,
user: User,
) -> None:
await queries.remove_article_from_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def _get_article_from_db_record(
self,
*,
article_row: Record,
slug: str,
author_username: str,
requested_user: Optional[User],
) -> Article:
return Article(
id_=article_row["id"],
slug=slug,
title=article_row["title"],
description=article_row["description"],
body=article_row["body"],
author=await self._profiles_repo.get_profile_by_username(
username=author_username,
requested_user=requested_user,
),
tags=await self.get_tags_for_article_by_slug(slug=slug),
favorites_count=await self.get_favorites_count_for_article_by_slug(
slug=slug,
),
favorited=await self.is_article_favorited_by_user(
slug=slug,
user=requested_user,
)
if requested_user
else False,
created_at=article_row["created_at"],
updated_at=article_row["updated_at"],
)
async def _link_article_with_tags(self, *, slug: str, tags: Sequence[str]) -> None:
await queries.add_tags_to_article(
self.connection,
[{SLUG_ALIAS: slug, "tag": tag} for tag in tags],
)
class Article(IDModelMixin, DateTimeModelMixin, RWModel):
slug: str
title: str
description: str
body: str
tags: List[str]
author: Profile
favorited: bool
favorites_count: int
async def delete_article_by_slug(
article: Article = Depends(get_article_by_slug_from_path),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> None:
await articles_repo.delete_article(article=article) | null |
167,832 | from fastapi import APIRouter, Depends, HTTPException, Query
from starlette import status
from app.api.dependencies.articles import get_article_by_slug_from_path
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.db.repositories.articles import ArticlesRepository
from app.models.domain.articles import Article
from app.models.domain.users import User
from app.models.schemas.articles import (
DEFAULT_ARTICLES_LIMIT,
DEFAULT_ARTICLES_OFFSET,
ArticleForResponse,
ArticleInResponse,
ListOfArticlesInResponse,
)
from app.resources import strings
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
class ArticlesRepository(BaseRepository): # noqa: WPS214
def __init__(self, conn: Connection) -> None:
super().__init__(conn)
self._profiles_repo = ProfilesRepository(conn)
self._tags_repo = TagsRepository(conn)
async def create_article( # noqa: WPS211
self,
*,
slug: str,
title: str,
description: str,
body: str,
author: User,
tags: Optional[Sequence[str]] = None,
) -> Article:
async with self.connection.transaction():
article_row = await queries.create_new_article(
self.connection,
slug=slug,
title=title,
description=description,
body=body,
author_username=author.username,
)
if tags:
await self._tags_repo.create_tags_that_dont_exist(tags=tags)
await self._link_article_with_tags(slug=slug, tags=tags)
return await self._get_article_from_db_record(
article_row=article_row,
slug=slug,
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=author,
)
async def update_article( # noqa: WPS211
self,
*,
article: Article,
slug: Optional[str] = None,
title: Optional[str] = None,
body: Optional[str] = None,
description: Optional[str] = None,
) -> Article:
updated_article = article.copy(deep=True)
updated_article.slug = slug or updated_article.slug
updated_article.title = title or article.title
updated_article.body = body or article.body
updated_article.description = description or article.description
async with self.connection.transaction():
updated_article.updated_at = await queries.update_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
new_slug=updated_article.slug,
new_title=updated_article.title,
new_body=updated_article.body,
new_description=updated_article.description,
)
return updated_article
async def delete_article(self, *, article: Article) -> None:
async with self.connection.transaction():
await queries.delete_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
)
async def filter_articles( # noqa: WPS211
self,
*,
tag: Optional[str] = None,
author: Optional[str] = None,
favorited: Optional[str] = None,
limit: int = 20,
offset: int = 0,
requested_user: Optional[User] = None,
) -> List[Article]:
query_params: List[Union[str, int]] = []
query_params_count = 0
# fmt: off
query = Query.from_(
articles,
).select(
articles.id,
articles.slug,
articles.title,
articles.description,
articles.body,
articles.created_at,
articles.updated_at,
Query.from_(
users,
).where(
users.id == articles.author_id,
).select(
users.username,
).as_(
AUTHOR_USERNAME_ALIAS,
),
)
# fmt: on
if tag:
query_params.append(tag)
query_params_count += 1
# fmt: off
query = query.join(
articles_to_tags,
).on(
(articles.id == articles_to_tags.article_id) & (
articles_to_tags.tag == Query.from_(
tags_table,
).where(
tags_table.tag == Parameter(query_params_count),
).select(
tags_table.tag,
)
),
)
# fmt: on
if author:
query_params.append(author)
query_params_count += 1
# fmt: off
query = query.join(
users,
).on(
(articles.author_id == users.id) & (
users.id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
if favorited:
query_params.append(favorited)
query_params_count += 1
# fmt: off
query = query.join(
favorites,
).on(
(articles.id == favorites.article_id) & (
favorites.user_id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
query = query.limit(Parameter(query_params_count + 1)).offset(
Parameter(query_params_count + 2),
)
query_params.extend([limit, offset])
articles_rows = await self.connection.fetch(query.get_sql(), *query_params)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
for article_row in articles_rows
]
async def get_articles_for_user_feed(
self,
*,
user: User,
limit: int = 20,
offset: int = 0,
) -> List[Article]:
articles_rows = await queries.get_articles_for_feed(
self.connection,
follower_username=user.username,
limit=limit,
offset=offset,
)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=user,
)
for article_row in articles_rows
]
async def get_article_by_slug(
self,
*,
slug: str,
requested_user: Optional[User] = None,
) -> Article:
article_row = await queries.get_article_by_slug(self.connection, slug=slug)
if article_row:
return await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
raise EntityDoesNotExist("article with slug {0} does not exist".format(slug))
async def get_tags_for_article_by_slug(self, *, slug: str) -> List[str]:
tag_rows = await queries.get_tags_for_article_by_slug(
self.connection,
slug=slug,
)
return [row["tag"] for row in tag_rows]
async def get_favorites_count_for_article_by_slug(self, *, slug: str) -> int:
return (
await queries.get_favorites_count_for_article(self.connection, slug=slug)
)["favorites_count"]
async def is_article_favorited_by_user(self, *, slug: str, user: User) -> bool:
return (
await queries.is_article_in_favorites(
self.connection,
username=user.username,
slug=slug,
)
)["favorited"]
async def add_article_into_favorites(self, *, article: Article, user: User) -> None:
await queries.add_article_to_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def remove_article_from_favorites(
self,
*,
article: Article,
user: User,
) -> None:
await queries.remove_article_from_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def _get_article_from_db_record(
self,
*,
article_row: Record,
slug: str,
author_username: str,
requested_user: Optional[User],
) -> Article:
return Article(
id_=article_row["id"],
slug=slug,
title=article_row["title"],
description=article_row["description"],
body=article_row["body"],
author=await self._profiles_repo.get_profile_by_username(
username=author_username,
requested_user=requested_user,
),
tags=await self.get_tags_for_article_by_slug(slug=slug),
favorites_count=await self.get_favorites_count_for_article_by_slug(
slug=slug,
),
favorited=await self.is_article_favorited_by_user(
slug=slug,
user=requested_user,
)
if requested_user
else False,
created_at=article_row["created_at"],
updated_at=article_row["updated_at"],
)
async def _link_article_with_tags(self, *, slug: str, tags: Sequence[str]) -> None:
await queries.add_tags_to_article(
self.connection,
[{SLUG_ALIAS: slug, "tag": tag} for tag in tags],
)
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
DEFAULT_ARTICLES_LIMIT = 20
DEFAULT_ARTICLES_OFFSET = 0
class ArticleForResponse(RWSchema, Article):
tags: List[str] = Field(..., alias="tagList")
class ListOfArticlesInResponse(RWSchema):
articles: List[ArticleForResponse]
articles_count: int
async def get_articles_for_user_feed(
limit: int = Query(DEFAULT_ARTICLES_LIMIT, ge=1),
offset: int = Query(DEFAULT_ARTICLES_OFFSET, ge=0),
user: User = Depends(get_current_user_authorizer()),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> ListOfArticlesInResponse:
articles = await articles_repo.get_articles_for_user_feed(
user=user,
limit=limit,
offset=offset,
)
articles_for_response = [
ArticleForResponse(**article.dict()) for article in articles
]
return ListOfArticlesInResponse(
articles=articles_for_response,
articles_count=len(articles),
) | null |
167,833 | from fastapi import APIRouter, Depends, HTTPException, Query
from starlette import status
from app.api.dependencies.articles import get_article_by_slug_from_path
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.db.repositories.articles import ArticlesRepository
from app.models.domain.articles import Article
from app.models.domain.users import User
from app.models.schemas.articles import (
DEFAULT_ARTICLES_LIMIT,
DEFAULT_ARTICLES_OFFSET,
ArticleForResponse,
ArticleInResponse,
ListOfArticlesInResponse,
)
from app.resources import strings
async def get_article_by_slug_from_path(
slug: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> Article:
try:
return await articles_repo.get_article_by_slug(slug=slug, requested_user=user)
except EntityDoesNotExist:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=strings.ARTICLE_DOES_NOT_EXIST_ERROR,
)
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
class ArticlesRepository(BaseRepository): # noqa: WPS214
def __init__(self, conn: Connection) -> None:
super().__init__(conn)
self._profiles_repo = ProfilesRepository(conn)
self._tags_repo = TagsRepository(conn)
async def create_article( # noqa: WPS211
self,
*,
slug: str,
title: str,
description: str,
body: str,
author: User,
tags: Optional[Sequence[str]] = None,
) -> Article:
async with self.connection.transaction():
article_row = await queries.create_new_article(
self.connection,
slug=slug,
title=title,
description=description,
body=body,
author_username=author.username,
)
if tags:
await self._tags_repo.create_tags_that_dont_exist(tags=tags)
await self._link_article_with_tags(slug=slug, tags=tags)
return await self._get_article_from_db_record(
article_row=article_row,
slug=slug,
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=author,
)
async def update_article( # noqa: WPS211
self,
*,
article: Article,
slug: Optional[str] = None,
title: Optional[str] = None,
body: Optional[str] = None,
description: Optional[str] = None,
) -> Article:
updated_article = article.copy(deep=True)
updated_article.slug = slug or updated_article.slug
updated_article.title = title or article.title
updated_article.body = body or article.body
updated_article.description = description or article.description
async with self.connection.transaction():
updated_article.updated_at = await queries.update_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
new_slug=updated_article.slug,
new_title=updated_article.title,
new_body=updated_article.body,
new_description=updated_article.description,
)
return updated_article
async def delete_article(self, *, article: Article) -> None:
async with self.connection.transaction():
await queries.delete_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
)
async def filter_articles( # noqa: WPS211
self,
*,
tag: Optional[str] = None,
author: Optional[str] = None,
favorited: Optional[str] = None,
limit: int = 20,
offset: int = 0,
requested_user: Optional[User] = None,
) -> List[Article]:
query_params: List[Union[str, int]] = []
query_params_count = 0
# fmt: off
query = Query.from_(
articles,
).select(
articles.id,
articles.slug,
articles.title,
articles.description,
articles.body,
articles.created_at,
articles.updated_at,
Query.from_(
users,
).where(
users.id == articles.author_id,
).select(
users.username,
).as_(
AUTHOR_USERNAME_ALIAS,
),
)
# fmt: on
if tag:
query_params.append(tag)
query_params_count += 1
# fmt: off
query = query.join(
articles_to_tags,
).on(
(articles.id == articles_to_tags.article_id) & (
articles_to_tags.tag == Query.from_(
tags_table,
).where(
tags_table.tag == Parameter(query_params_count),
).select(
tags_table.tag,
)
),
)
# fmt: on
if author:
query_params.append(author)
query_params_count += 1
# fmt: off
query = query.join(
users,
).on(
(articles.author_id == users.id) & (
users.id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
if favorited:
query_params.append(favorited)
query_params_count += 1
# fmt: off
query = query.join(
favorites,
).on(
(articles.id == favorites.article_id) & (
favorites.user_id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
query = query.limit(Parameter(query_params_count + 1)).offset(
Parameter(query_params_count + 2),
)
query_params.extend([limit, offset])
articles_rows = await self.connection.fetch(query.get_sql(), *query_params)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
for article_row in articles_rows
]
async def get_articles_for_user_feed(
self,
*,
user: User,
limit: int = 20,
offset: int = 0,
) -> List[Article]:
articles_rows = await queries.get_articles_for_feed(
self.connection,
follower_username=user.username,
limit=limit,
offset=offset,
)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=user,
)
for article_row in articles_rows
]
async def get_article_by_slug(
self,
*,
slug: str,
requested_user: Optional[User] = None,
) -> Article:
article_row = await queries.get_article_by_slug(self.connection, slug=slug)
if article_row:
return await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
raise EntityDoesNotExist("article with slug {0} does not exist".format(slug))
async def get_tags_for_article_by_slug(self, *, slug: str) -> List[str]:
tag_rows = await queries.get_tags_for_article_by_slug(
self.connection,
slug=slug,
)
return [row["tag"] for row in tag_rows]
async def get_favorites_count_for_article_by_slug(self, *, slug: str) -> int:
return (
await queries.get_favorites_count_for_article(self.connection, slug=slug)
)["favorites_count"]
async def is_article_favorited_by_user(self, *, slug: str, user: User) -> bool:
return (
await queries.is_article_in_favorites(
self.connection,
username=user.username,
slug=slug,
)
)["favorited"]
async def add_article_into_favorites(self, *, article: Article, user: User) -> None:
await queries.add_article_to_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def remove_article_from_favorites(
self,
*,
article: Article,
user: User,
) -> None:
await queries.remove_article_from_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def _get_article_from_db_record(
self,
*,
article_row: Record,
slug: str,
author_username: str,
requested_user: Optional[User],
) -> Article:
return Article(
id_=article_row["id"],
slug=slug,
title=article_row["title"],
description=article_row["description"],
body=article_row["body"],
author=await self._profiles_repo.get_profile_by_username(
username=author_username,
requested_user=requested_user,
),
tags=await self.get_tags_for_article_by_slug(slug=slug),
favorites_count=await self.get_favorites_count_for_article_by_slug(
slug=slug,
),
favorited=await self.is_article_favorited_by_user(
slug=slug,
user=requested_user,
)
if requested_user
else False,
created_at=article_row["created_at"],
updated_at=article_row["updated_at"],
)
async def _link_article_with_tags(self, *, slug: str, tags: Sequence[str]) -> None:
await queries.add_tags_to_article(
self.connection,
[{SLUG_ALIAS: slug, "tag": tag} for tag in tags],
)
class Article(IDModelMixin, DateTimeModelMixin, RWModel):
slug: str
title: str
description: str
body: str
tags: List[str]
author: Profile
favorited: bool
favorites_count: int
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
class ArticleForResponse(RWSchema, Article):
tags: List[str] = Field(..., alias="tagList")
class ArticleInResponse(RWSchema):
article: ArticleForResponse
async def mark_article_as_favorite(
article: Article = Depends(get_article_by_slug_from_path),
user: User = Depends(get_current_user_authorizer()),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> ArticleInResponse:
if not article.favorited:
await articles_repo.add_article_into_favorites(article=article, user=user)
return ArticleInResponse(
article=ArticleForResponse.from_orm(
article.copy(
update={
"favorited": True,
"favorites_count": article.favorites_count + 1,
},
),
),
)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=strings.ARTICLE_IS_ALREADY_FAVORITED,
) | null |
167,834 | from fastapi import APIRouter, Depends, HTTPException, Query
from starlette import status
from app.api.dependencies.articles import get_article_by_slug_from_path
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.database import get_repository
from app.db.repositories.articles import ArticlesRepository
from app.models.domain.articles import Article
from app.models.domain.users import User
from app.models.schemas.articles import (
DEFAULT_ARTICLES_LIMIT,
DEFAULT_ARTICLES_OFFSET,
ArticleForResponse,
ArticleInResponse,
ListOfArticlesInResponse,
)
from app.resources import strings
async def get_article_by_slug_from_path(
slug: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> Article:
try:
return await articles_repo.get_article_by_slug(slug=slug, requested_user=user)
except EntityDoesNotExist:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=strings.ARTICLE_DOES_NOT_EXIST_ERROR,
)
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
class ArticlesRepository(BaseRepository): # noqa: WPS214
def __init__(self, conn: Connection) -> None:
super().__init__(conn)
self._profiles_repo = ProfilesRepository(conn)
self._tags_repo = TagsRepository(conn)
async def create_article( # noqa: WPS211
self,
*,
slug: str,
title: str,
description: str,
body: str,
author: User,
tags: Optional[Sequence[str]] = None,
) -> Article:
async with self.connection.transaction():
article_row = await queries.create_new_article(
self.connection,
slug=slug,
title=title,
description=description,
body=body,
author_username=author.username,
)
if tags:
await self._tags_repo.create_tags_that_dont_exist(tags=tags)
await self._link_article_with_tags(slug=slug, tags=tags)
return await self._get_article_from_db_record(
article_row=article_row,
slug=slug,
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=author,
)
async def update_article( # noqa: WPS211
self,
*,
article: Article,
slug: Optional[str] = None,
title: Optional[str] = None,
body: Optional[str] = None,
description: Optional[str] = None,
) -> Article:
updated_article = article.copy(deep=True)
updated_article.slug = slug or updated_article.slug
updated_article.title = title or article.title
updated_article.body = body or article.body
updated_article.description = description or article.description
async with self.connection.transaction():
updated_article.updated_at = await queries.update_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
new_slug=updated_article.slug,
new_title=updated_article.title,
new_body=updated_article.body,
new_description=updated_article.description,
)
return updated_article
async def delete_article(self, *, article: Article) -> None:
async with self.connection.transaction():
await queries.delete_article(
self.connection,
slug=article.slug,
author_username=article.author.username,
)
async def filter_articles( # noqa: WPS211
self,
*,
tag: Optional[str] = None,
author: Optional[str] = None,
favorited: Optional[str] = None,
limit: int = 20,
offset: int = 0,
requested_user: Optional[User] = None,
) -> List[Article]:
query_params: List[Union[str, int]] = []
query_params_count = 0
# fmt: off
query = Query.from_(
articles,
).select(
articles.id,
articles.slug,
articles.title,
articles.description,
articles.body,
articles.created_at,
articles.updated_at,
Query.from_(
users,
).where(
users.id == articles.author_id,
).select(
users.username,
).as_(
AUTHOR_USERNAME_ALIAS,
),
)
# fmt: on
if tag:
query_params.append(tag)
query_params_count += 1
# fmt: off
query = query.join(
articles_to_tags,
).on(
(articles.id == articles_to_tags.article_id) & (
articles_to_tags.tag == Query.from_(
tags_table,
).where(
tags_table.tag == Parameter(query_params_count),
).select(
tags_table.tag,
)
),
)
# fmt: on
if author:
query_params.append(author)
query_params_count += 1
# fmt: off
query = query.join(
users,
).on(
(articles.author_id == users.id) & (
users.id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
if favorited:
query_params.append(favorited)
query_params_count += 1
# fmt: off
query = query.join(
favorites,
).on(
(articles.id == favorites.article_id) & (
favorites.user_id == Query.from_(
users,
).where(
users.username == Parameter(query_params_count),
).select(
users.id,
)
),
)
# fmt: on
query = query.limit(Parameter(query_params_count + 1)).offset(
Parameter(query_params_count + 2),
)
query_params.extend([limit, offset])
articles_rows = await self.connection.fetch(query.get_sql(), *query_params)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
for article_row in articles_rows
]
async def get_articles_for_user_feed(
self,
*,
user: User,
limit: int = 20,
offset: int = 0,
) -> List[Article]:
articles_rows = await queries.get_articles_for_feed(
self.connection,
follower_username=user.username,
limit=limit,
offset=offset,
)
return [
await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=user,
)
for article_row in articles_rows
]
async def get_article_by_slug(
self,
*,
slug: str,
requested_user: Optional[User] = None,
) -> Article:
article_row = await queries.get_article_by_slug(self.connection, slug=slug)
if article_row:
return await self._get_article_from_db_record(
article_row=article_row,
slug=article_row[SLUG_ALIAS],
author_username=article_row[AUTHOR_USERNAME_ALIAS],
requested_user=requested_user,
)
raise EntityDoesNotExist("article with slug {0} does not exist".format(slug))
async def get_tags_for_article_by_slug(self, *, slug: str) -> List[str]:
tag_rows = await queries.get_tags_for_article_by_slug(
self.connection,
slug=slug,
)
return [row["tag"] for row in tag_rows]
async def get_favorites_count_for_article_by_slug(self, *, slug: str) -> int:
return (
await queries.get_favorites_count_for_article(self.connection, slug=slug)
)["favorites_count"]
async def is_article_favorited_by_user(self, *, slug: str, user: User) -> bool:
return (
await queries.is_article_in_favorites(
self.connection,
username=user.username,
slug=slug,
)
)["favorited"]
async def add_article_into_favorites(self, *, article: Article, user: User) -> None:
await queries.add_article_to_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def remove_article_from_favorites(
self,
*,
article: Article,
user: User,
) -> None:
await queries.remove_article_from_favorites(
self.connection,
username=user.username,
slug=article.slug,
)
async def _get_article_from_db_record(
self,
*,
article_row: Record,
slug: str,
author_username: str,
requested_user: Optional[User],
) -> Article:
return Article(
id_=article_row["id"],
slug=slug,
title=article_row["title"],
description=article_row["description"],
body=article_row["body"],
author=await self._profiles_repo.get_profile_by_username(
username=author_username,
requested_user=requested_user,
),
tags=await self.get_tags_for_article_by_slug(slug=slug),
favorites_count=await self.get_favorites_count_for_article_by_slug(
slug=slug,
),
favorited=await self.is_article_favorited_by_user(
slug=slug,
user=requested_user,
)
if requested_user
else False,
created_at=article_row["created_at"],
updated_at=article_row["updated_at"],
)
async def _link_article_with_tags(self, *, slug: str, tags: Sequence[str]) -> None:
await queries.add_tags_to_article(
self.connection,
[{SLUG_ALIAS: slug, "tag": tag} for tag in tags],
)
class Article(IDModelMixin, DateTimeModelMixin, RWModel):
slug: str
title: str
description: str
body: str
tags: List[str]
author: Profile
favorited: bool
favorites_count: int
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
class ArticleForResponse(RWSchema, Article):
tags: List[str] = Field(..., alias="tagList")
class ArticleInResponse(RWSchema):
article: ArticleForResponse
async def remove_article_from_favorites(
article: Article = Depends(get_article_by_slug_from_path),
user: User = Depends(get_current_user_authorizer()),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> ArticleInResponse:
if article.favorited:
await articles_repo.remove_article_from_favorites(article=article, user=user)
return ArticleInResponse(
article=ArticleForResponse.from_orm(
article.copy(
update={
"favorited": False,
"favorites_count": article.favorites_count - 1,
},
),
),
)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=strings.ARTICLE_IS_NOT_FAVORITED,
) | null |
167,835 | from typing import Optional
from fastapi import APIRouter, Body, Depends, Response
from starlette import status
from app.api.dependencies.articles import get_article_by_slug_from_path
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.comments import (
check_comment_modification_permissions,
get_comment_by_id_from_path,
)
from app.api.dependencies.database import get_repository
from app.db.repositories.comments import CommentsRepository
from app.models.domain.articles import Article
from app.models.domain.comments import Comment
from app.models.domain.users import User
from app.models.schemas.comments import (
CommentInCreate,
CommentInResponse,
ListOfCommentsInResponse,
)
async def get_article_by_slug_from_path(
slug: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> Article:
def get_current_user_authorizer(*, required: bool = True) -> Callable:
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
class CommentsRepository(BaseRepository):
def __init__(self, conn: Connection) -> None:
async def get_comment_by_id(
self,
*,
comment_id: int,
article: Article,
user: Optional[User] = None,
) -> Comment:
async def get_comments_for_article(
self,
*,
article: Article,
user: Optional[User] = None,
) -> List[Comment]:
async def create_comment_for_article(
self,
*,
body: str,
article: Article,
user: User,
) -> Comment:
async def delete_comment(self, *, comment: Comment) -> None:
async def _get_comment_from_db_record(
self,
*,
comment_row: Record,
author_username: str,
requested_user: Optional[User],
) -> Comment:
class Article(IDModelMixin, DateTimeModelMixin, RWModel):
class User(RWModel):
class ListOfCommentsInResponse(RWSchema):
async def list_comments_for_article(
article: Article = Depends(get_article_by_slug_from_path),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
comments_repo: CommentsRepository = Depends(get_repository(CommentsRepository)),
) -> ListOfCommentsInResponse:
comments = await comments_repo.get_comments_for_article(article=article, user=user)
return ListOfCommentsInResponse(comments=comments) | null |
167,836 | from typing import Optional
from fastapi import APIRouter, Body, Depends, Response
from starlette import status
from app.api.dependencies.articles import get_article_by_slug_from_path
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.comments import (
check_comment_modification_permissions,
get_comment_by_id_from_path,
)
from app.api.dependencies.database import get_repository
from app.db.repositories.comments import CommentsRepository
from app.models.domain.articles import Article
from app.models.domain.comments import Comment
from app.models.domain.users import User
from app.models.schemas.comments import (
CommentInCreate,
CommentInResponse,
ListOfCommentsInResponse,
)
async def get_article_by_slug_from_path(
slug: str = Path(..., min_length=1),
user: Optional[User] = Depends(get_current_user_authorizer(required=False)),
articles_repo: ArticlesRepository = Depends(get_repository(ArticlesRepository)),
) -> Article:
try:
return await articles_repo.get_article_by_slug(slug=slug, requested_user=user)
except EntityDoesNotExist:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=strings.ARTICLE_DOES_NOT_EXIST_ERROR,
)
def get_current_user_authorizer(*, required: bool = True) -> Callable: # type: ignore
return _get_current_user if required else _get_current_user_optional
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
class CommentsRepository(BaseRepository):
def __init__(self, conn: Connection) -> None:
super().__init__(conn)
self._profiles_repo = ProfilesRepository(conn)
async def get_comment_by_id(
self,
*,
comment_id: int,
article: Article,
user: Optional[User] = None,
) -> Comment:
comment_row = await queries.get_comment_by_id_and_slug(
self.connection,
comment_id=comment_id,
article_slug=article.slug,
)
if comment_row:
return await self._get_comment_from_db_record(
comment_row=comment_row,
author_username=comment_row["author_username"],
requested_user=user,
)
raise EntityDoesNotExist(
"comment with id {0} does not exist".format(comment_id),
)
async def get_comments_for_article(
self,
*,
article: Article,
user: Optional[User] = None,
) -> List[Comment]:
comments_rows = await queries.get_comments_for_article_by_slug(
self.connection,
slug=article.slug,
)
return [
await self._get_comment_from_db_record(
comment_row=comment_row,
author_username=comment_row["author_username"],
requested_user=user,
)
for comment_row in comments_rows
]
async def create_comment_for_article(
self,
*,
body: str,
article: Article,
user: User,
) -> Comment:
comment_row = await queries.create_new_comment(
self.connection,
body=body,
article_slug=article.slug,
author_username=user.username,
)
return await self._get_comment_from_db_record(
comment_row=comment_row,
author_username=comment_row["author_username"],
requested_user=user,
)
async def delete_comment(self, *, comment: Comment) -> None:
await queries.delete_comment_by_id(
self.connection,
comment_id=comment.id_,
author_username=comment.author.username,
)
async def _get_comment_from_db_record(
self,
*,
comment_row: Record,
author_username: str,
requested_user: Optional[User],
) -> Comment:
return Comment(
id_=comment_row["id"],
body=comment_row["body"],
author=await self._profiles_repo.get_profile_by_username(
username=author_username,
requested_user=requested_user,
),
created_at=comment_row["created_at"],
updated_at=comment_row["updated_at"],
)
class Article(IDModelMixin, DateTimeModelMixin, RWModel):
slug: str
title: str
description: str
body: str
tags: List[str]
author: Profile
favorited: bool
favorites_count: int
class User(RWModel):
username: str
email: str
bio: str = ""
image: Optional[str] = None
class CommentInResponse(RWSchema):
comment: Comment
class CommentInCreate(RWSchema):
body: str
async def create_comment_for_article(
comment_create: CommentInCreate = Body(..., embed=True, alias="comment"),
article: Article = Depends(get_article_by_slug_from_path),
user: User = Depends(get_current_user_authorizer()),
comments_repo: CommentsRepository = Depends(get_repository(CommentsRepository)),
) -> CommentInResponse:
comment = await comments_repo.create_comment_for_article(
body=comment_create.body,
article=article,
user=user,
)
return CommentInResponse(comment=comment) | null |
167,837 | from typing import Optional
from fastapi import APIRouter, Body, Depends, Response
from starlette import status
from app.api.dependencies.articles import get_article_by_slug_from_path
from app.api.dependencies.authentication import get_current_user_authorizer
from app.api.dependencies.comments import (
check_comment_modification_permissions,
get_comment_by_id_from_path,
)
from app.api.dependencies.database import get_repository
from app.db.repositories.comments import CommentsRepository
from app.models.domain.articles import Article
from app.models.domain.comments import Comment
from app.models.domain.users import User
from app.models.schemas.comments import (
CommentInCreate,
CommentInResponse,
ListOfCommentsInResponse,
)
async def get_comment_by_id_from_path(
comment_id: int = Path(..., ge=1),
article: Article = Depends(articles.get_article_by_slug_from_path),
user: Optional[User] = Depends(
authentication.get_current_user_authorizer(required=False),
),
comments_repo: CommentsRepository = Depends(
database.get_repository(CommentsRepository),
),
) -> Comment:
try:
return await comments_repo.get_comment_by_id(
comment_id=comment_id,
article=article,
user=user,
)
except EntityDoesNotExist:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=strings.COMMENT_DOES_NOT_EXIST,
)
def get_repository(
repo_type: Type[BaseRepository],
) -> Callable[[Connection], BaseRepository]:
def _get_repo(
conn: Connection = Depends(_get_connection_from_pool),
) -> BaseRepository:
return repo_type(conn)
return _get_repo
class CommentsRepository(BaseRepository):
def __init__(self, conn: Connection) -> None:
super().__init__(conn)
self._profiles_repo = ProfilesRepository(conn)
async def get_comment_by_id(
self,
*,
comment_id: int,
article: Article,
user: Optional[User] = None,
) -> Comment:
comment_row = await queries.get_comment_by_id_and_slug(
self.connection,
comment_id=comment_id,
article_slug=article.slug,
)
if comment_row:
return await self._get_comment_from_db_record(
comment_row=comment_row,
author_username=comment_row["author_username"],
requested_user=user,
)
raise EntityDoesNotExist(
"comment with id {0} does not exist".format(comment_id),
)
async def get_comments_for_article(
self,
*,
article: Article,
user: Optional[User] = None,
) -> List[Comment]:
comments_rows = await queries.get_comments_for_article_by_slug(
self.connection,
slug=article.slug,
)
return [
await self._get_comment_from_db_record(
comment_row=comment_row,
author_username=comment_row["author_username"],
requested_user=user,
)
for comment_row in comments_rows
]
async def create_comment_for_article(
self,
*,
body: str,
article: Article,
user: User,
) -> Comment:
comment_row = await queries.create_new_comment(
self.connection,
body=body,
article_slug=article.slug,
author_username=user.username,
)
return await self._get_comment_from_db_record(
comment_row=comment_row,
author_username=comment_row["author_username"],
requested_user=user,
)
async def delete_comment(self, *, comment: Comment) -> None:
await queries.delete_comment_by_id(
self.connection,
comment_id=comment.id_,
author_username=comment.author.username,
)
async def _get_comment_from_db_record(
self,
*,
comment_row: Record,
author_username: str,
requested_user: Optional[User],
) -> Comment:
return Comment(
id_=comment_row["id"],
body=comment_row["body"],
author=await self._profiles_repo.get_profile_by_username(
username=author_username,
requested_user=requested_user,
),
created_at=comment_row["created_at"],
updated_at=comment_row["updated_at"],
)
class Comment(IDModelMixin, DateTimeModelMixin, RWModel):
body: str
author: Profile
async def delete_comment_from_article(
comment: Comment = Depends(get_comment_by_id_from_path),
comments_repo: CommentsRepository = Depends(get_repository(CommentsRepository)),
) -> None:
await comments_repo.delete_comment(comment=comment) | null |
167,838 | from fastapi import FastAPI
from fastapi.exceptions import RequestValidationError
from starlette.exceptions import HTTPException
from starlette.middleware.cors import CORSMiddleware
from app.api.errors.http_error import http_error_handler
from app.api.errors.validation_error import http422_error_handler
from app.api.routes.api import router as api_router
from app.core.config import get_app_settings
from app.core.events import create_start_app_handler, create_stop_app_handler
async def http_error_handler(_: Request, exc: HTTPException) -> JSONResponse:
return JSONResponse({"errors": [exc.detail]}, status_code=exc.status_code)
async def http422_error_handler(
_: Request,
exc: Union[RequestValidationError, ValidationError],
) -> JSONResponse:
return JSONResponse(
{"errors": exc.errors()},
status_code=HTTP_422_UNPROCESSABLE_ENTITY,
)
def get_app_settings() -> AppSettings:
app_env = BaseAppSettings().app_env
config = environments[app_env]
return config()
def create_start_app_handler(
app: FastAPI,
settings: AppSettings,
) -> Callable: # type: ignore
async def start_app() -> None:
await connect_to_db(app, settings)
return start_app
def create_stop_app_handler(app: FastAPI) -> Callable: # type: ignore
async def stop_app() -> None:
await close_db_connection(app)
return stop_app
def get_application() -> FastAPI:
settings = get_app_settings()
settings.configure_logging()
application = FastAPI(**settings.fastapi_kwargs)
application.add_middleware(
CORSMiddleware,
allow_origins=settings.allowed_hosts,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
application.add_event_handler(
"startup",
create_start_app_handler(application, settings),
)
application.add_event_handler(
"shutdown",
create_stop_app_handler(application),
)
application.add_exception_handler(HTTPException, http_error_handler)
application.add_exception_handler(RequestValidationError, http422_error_handler)
application.include_router(api_router, prefix=settings.api_prefix)
return application | null |
167,839 | import bcrypt
from passlib.context import CryptContext
def generate_salt() -> str:
return bcrypt.gensalt().decode() | null |
167,840 | import bcrypt
from passlib.context import CryptContext
pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
def verify_password(plain_password: str, hashed_password: str) -> bool:
return pwd_context.verify(plain_password, hashed_password) | null |
167,841 | import bcrypt
from passlib.context import CryptContext
pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
def get_password_hash(password: str) -> str:
return pwd_context.hash(password) | null |
167,842 | from typing import Tuple
import sqlalchemy as sa
from alembic import op
from sqlalchemy import func
def create_updated_at_trigger() -> None:
op.execute(
"""
CREATE FUNCTION update_updated_at_column()
RETURNS TRIGGER AS
$$
BEGIN
NEW.updated_at = now();
RETURN NEW;
END;
$$ language 'plpgsql';
"""
)
def create_users_table() -> None:
op.create_table(
"users",
sa.Column("id", sa.Integer, primary_key=True),
sa.Column("username", sa.Text, unique=True, nullable=False, index=True),
sa.Column("email", sa.Text, unique=True, nullable=False, index=True),
sa.Column("salt", sa.Text, nullable=False),
sa.Column("hashed_password", sa.Text),
sa.Column("bio", sa.Text, nullable=False, server_default=""),
sa.Column("image", sa.Text),
*timestamps(),
)
op.execute(
"""
CREATE TRIGGER update_user_modtime
BEFORE UPDATE
ON users
FOR EACH ROW
EXECUTE PROCEDURE update_updated_at_column();
"""
)
def create_followers_to_followings_table() -> None:
op.create_table(
"followers_to_followings",
sa.Column(
"follower_id",
sa.Integer,
sa.ForeignKey("users.id", ondelete="CASCADE"),
nullable=False,
),
sa.Column(
"following_id",
sa.Integer,
sa.ForeignKey("users.id", ondelete="CASCADE"),
nullable=False,
),
)
op.create_primary_key(
"pk_followers_to_followings",
"followers_to_followings",
["follower_id", "following_id"],
)
def create_articles_table() -> None:
op.create_table(
"articles",
sa.Column("id", sa.Integer, primary_key=True),
sa.Column("slug", sa.Text, unique=True, nullable=False, index=True),
sa.Column("title", sa.Text, nullable=False),
sa.Column("description", sa.Text, nullable=False),
sa.Column("body", sa.Text, nullable=False),
sa.Column(
"author_id", sa.Integer, sa.ForeignKey("users.id", ondelete="SET NULL")
),
*timestamps(),
)
op.execute(
"""
CREATE TRIGGER update_article_modtime
BEFORE UPDATE
ON articles
FOR EACH ROW
EXECUTE PROCEDURE update_updated_at_column();
"""
)
def create_tags_table() -> None:
op.create_table("tags", sa.Column("tag", sa.Text, primary_key=True))
def create_articles_to_tags_table() -> None:
op.create_table(
"articles_to_tags",
sa.Column(
"article_id",
sa.Integer,
sa.ForeignKey("articles.id", ondelete="CASCADE"),
nullable=False,
),
sa.Column(
"tag",
sa.Text,
sa.ForeignKey("tags.tag", ondelete="CASCADE"),
nullable=False,
),
)
op.create_primary_key(
"pk_articles_to_tags", "articles_to_tags", ["article_id", "tag"]
)
def create_favorites_table() -> None:
op.create_table(
"favorites",
sa.Column(
"user_id",
sa.Integer,
sa.ForeignKey("users.id", ondelete="CASCADE"),
nullable=False,
),
sa.Column(
"article_id",
sa.Integer,
sa.ForeignKey("articles.id", ondelete="CASCADE"),
nullable=False,
),
)
op.create_primary_key("pk_favorites", "favorites", ["user_id", "article_id"])
def create_commentaries_table() -> None:
op.create_table(
"commentaries",
sa.Column("id", sa.Integer, primary_key=True),
sa.Column("body", sa.Text, nullable=False),
sa.Column(
"author_id",
sa.Integer,
sa.ForeignKey("users.id", ondelete="CASCADE"),
nullable=False,
),
sa.Column(
"article_id",
sa.Integer,
sa.ForeignKey("articles.id", ondelete="CASCADE"),
nullable=False,
),
*timestamps(),
)
op.execute(
"""
CREATE TRIGGER update_comment_modtime
BEFORE UPDATE
ON commentaries
FOR EACH ROW
EXECUTE PROCEDURE update_updated_at_column();
"""
)
def upgrade() -> None:
create_updated_at_trigger()
create_users_table()
create_followers_to_followings_table()
create_articles_table()
create_tags_table()
create_articles_to_tags_table()
create_favorites_table()
create_commentaries_table() | null |
167,843 | from typing import Tuple
import sqlalchemy as sa
from alembic import op
from sqlalchemy import func
def downgrade() -> None:
op.drop_table("commentaries")
op.drop_table("favorites")
op.drop_table("articles_to_tags")
op.drop_table("tags")
op.drop_table("articles")
op.drop_table("followers_to_followings")
op.drop_table("users")
op.execute("DROP FUNCTION update_updated_at_column") | null |
167,844 | import pathlib
import sys
from logging.config import fileConfig
from alembic import context
from sqlalchemy import engine_from_config, pool
from app.core.config import get_app_settings
config = context.config
target_metadata = None
config.set_main_option("sqlalchemy.url", str(DATABASE_URL))
def run_migrations_online() -> None:
connectable = engine_from_config(
config.get_section(config.config_ini_section),
prefix="sqlalchemy.",
poolclass=pool.NullPool,
)
with connectable.connect() as connection:
context.configure(connection=connection, target_metadata=target_metadata)
with context.begin_transaction():
context.run_migrations() | null |
167,845 | import datetime
from pydantic import BaseConfig, BaseModel
def convert_datetime_to_realworld(dt: datetime.datetime) -> str:
return dt.replace(tzinfo=datetime.timezone.utc).isoformat().replace("+00:00", "Z") | null |
167,846 | import datetime
from pydantic import BaseConfig, BaseModel
def convert_field_to_camel_case(string: str) -> str:
return "".join(
word if index == 0 else word.capitalize()
for index, word in enumerate(string.split("_"))
) | null |
167,847 | import os, sys
os.environ["TOKENIZERS_PARALLELISM"] = "false"
import logging
import click
import numpy as np
from functools import partial
from pathlib import Path
from typing import Any, Dict, List, Tuple, Union
from datetime import datetime
from datasets import Dataset, load_dataset, load_from_disk
from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
DataCollatorForLanguageModeling,
PreTrainedTokenizer,
Trainer,
TrainingArguments,
set_seed,
)
from .consts import (
DEFAULT_INPUT_MODEL,
DEFAULT_SEED,
END_KEY,
INSTRUCTION_KEY,
RESPONSE_KEY,
INTRO_KEY,
INTRO
)
logger = logging.getLogger(__name__)
class DataCollatorForCompletionOnlyLM_Multi_Rounds(DataCollatorForLanguageModeling):
def torch_call(self, examples: List[Union[List[int], Any, Dict[str, Any]]]) -> Dict[str, Any]:
batch = super().torch_call(examples)
# The prompt ends with the response key plus a newline. We encode this and then try to find it in the
# sequence of tokens. This should just be a single token.
yayi_token_ids = self.tokenizer(RESPONSE_KEY)["input_ids"][0]
human_token_ids = self.tokenizer(INSTRUCTION_KEY)["input_ids"][0]
labels = batch["labels"].clone()
for i in range(len(examples)):
response_start, response_end = None, None
yayi_position = np.where(batch["labels"][i] == yayi_token_ids)[0].tolist()
human_position = np.where(batch["labels"][i] == human_token_ids)[0].tolist()
labels[i, :human_position[0]+3] = -100
for response_start,response_end in zip(human_position,yayi_position):
if response_start is None or response_end is None:
raise RuntimeError(
f'Could not find response key {yayi_token_ids}/{human_token_ids} in token IDs'
)
labels[i, response_start:response_end+3] = -100
batch["labels"] = labels
return batch
def get_model_tokenizer(
pretrained_model_name_or_path: str = DEFAULT_INPUT_MODEL, *, gradient_checkpointing: bool = False
) -> Tuple[AutoModelForCausalLM, PreTrainedTokenizer]:
tokenizer = load_tokenizer(pretrained_model_name_or_path)
model = load_model(pretrained_model_name_or_path, gradient_checkpointing=gradient_checkpointing)
model.resize_token_embeddings(len(tokenizer))
return model, tokenizer
def preprocess_dataset(tokenizer: AutoTokenizer, max_length: int, seed=DEFAULT_SEED, path_or_dataset=None) -> Dataset:
"""Loads the training dataset and tokenizes it so it is ready for training.
Args:
tokenizer (AutoTokenizer): Tokenizer tied to the model.
max_length (int): Maximum number of tokens to emit from tokenizer.
Returns:
Dataset: HuggingFace dataset
"""
dataset = load_training_dataset__multi_rounds(path_or_dataset=path_or_dataset)
logger.info("Preprocessing dataset")
_preprocessing_function = partial(preprocess_batch, max_length=max_length, tokenizer=tokenizer)
dataset = dataset.map(
_preprocessing_function,
batched=True,
remove_columns=["conversations", "system", "text"],
)
logger.info(f"datasets after processing: {dataset}")
# Make sure we don't have any truncated records, as this would mean the end keyword is missing.
logger.info("Processed dataset has %d rows", dataset.num_rows)
dataset = dataset.filter(lambda rec: len(rec["input_ids"]) < max_length)
logger.info("Processed dataset has %d rows after filtering for truncated records", dataset.num_rows)
logger.info("Shuffling dataset")
dataset = dataset.shuffle(seed=seed)
logger.info("Done preprocessing")
return dataset
def train(
*,
data_path: str,
input_model: str,
local_output_dir: str,
dbfs_output_dir: str,
epochs: int,
per_device_train_batch_size: int,
per_device_eval_batch_size: int,
lr: float,
seed: int,
deepspeed: str,
gradient_checkpointing: bool,
local_rank: str,
bf16: bool,
logging_steps: int,
save_steps: int,
eval_steps: int,
test_size: Union[float, int],
save_total_limit: int,
warmup_steps: int,
):
set_seed(seed)
# Create dir for saving logs and checkpoints
timestamp = datetime.now().strftime("%Y-%m-%dT%H:%M")
model_name = "YAYI_CHAT"
checkpoint_dir_name = f"{model_name}_{timestamp}"
local_output_dir = os.path.join(local_output_dir, checkpoint_dir_name)
os.makedirs(local_output_dir, exist_ok=True)
model, tokenizer = get_model_tokenizer(
pretrained_model_name_or_path=input_model, gradient_checkpointing=gradient_checkpointing
)
# Use the same max length that the model supports.
max_length = None
for length_setting in ["n_positions", "max_position_embeddings", "seq_length"]:
max_length = getattr(model.config, length_setting, None)
if max_length:
logger.info(f"Found max lenth: {max_length}")
break
if not max_length:
max_length = 1024
logger.info(f"Using default max length: {max_length}")
# Data processing
hf_data_dir = data_path.replace(".json","")
if os.path.exists(hf_data_dir):
logger.info("Load dataset from cache.")
split_dataset = load_from_disk(hf_data_dir)
else:
logger.info("Load dataset from disk.")
processed_dataset = preprocess_dataset(tokenizer=tokenizer, max_length=max_length, seed=seed, path_or_dataset=data_path)
split_dataset = processed_dataset.train_test_split(test_size=test_size, seed=seed)
logger.info("Train data size: %d", split_dataset["train"].num_rows)
logger.info("Test data size: %d", split_dataset["test"].num_rows)
data_collator = DataCollatorForCompletionOnlyLM_Multi_Rounds(
tokenizer=tokenizer, mlm=False, return_tensors="pt", pad_to_multiple_of=8
)
training_args = TrainingArguments(
output_dir=local_output_dir,
per_device_train_batch_size=per_device_train_batch_size,
per_device_eval_batch_size=per_device_eval_batch_size,
fp16=False,
bf16=bf16,
learning_rate=lr,
num_train_epochs=epochs,
deepspeed=deepspeed,
gradient_checkpointing=gradient_checkpointing,
logging_dir=f"{local_output_dir}/runs",
logging_strategy="steps",
logging_steps=logging_steps,
evaluation_strategy="steps",
eval_steps=eval_steps,
save_strategy="steps",
save_steps=save_steps,
save_total_limit=save_total_limit,
load_best_model_at_end=False,
report_to="tensorboard",
disable_tqdm=False,
remove_unused_columns=False,
local_rank=local_rank,
warmup_steps=warmup_steps,
lr_scheduler_type="cosine"
)
logger.info("Instantiating Trainer")
trainer = Trainer(
model=model,
tokenizer=tokenizer,
args=training_args,
train_dataset=split_dataset["train"],
eval_dataset=split_dataset["test"],
data_collator=data_collator,
)
logger.info("Training")
trainer.train()
logger.info(f"Saving Model to {local_output_dir}")
trainer.save_model(output_dir=local_output_dir)
if dbfs_output_dir:
logger.info(f"Saving Model to {dbfs_output_dir}")
trainer.save_model(output_dir=dbfs_output_dir)
logger.info("Done.") | null |
167,848 | import os
os.environ["TOKENIZERS_PARALLELISM"] = "false"
import logging, torch
import click
import numpy as np
from functools import partial
from pathlib import Path
from typing import Any, Dict, List, Tuple, Union
from datetime import datetime
from datasets import Dataset, load_dataset, load_from_disk
from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
DataCollatorForLanguageModeling,
PreTrainedTokenizer,
Trainer,
TrainingArguments,
set_seed,
)
from .consts import (
DEFAULT_INPUT_MODEL,
DEFAULT_SEED,
PROMPT_WITH_INPUT_FORMAT,
PROMPT_NO_INPUT_FORMAT,
END_KEY,
INSTRUCTION_KEY,
RESPONSE_KEY,
INTRO_KEY
)
logger = logging.getLogger(__name__)
class DataCollatorForCompletionOnlyLM(DataCollatorForLanguageModeling):
def torch_call(self, examples: List[Union[List[int], Any, Dict[str, Any]]]) -> Dict[str, Any]:
batch = super().torch_call(examples)
# The prompt ends with the response key plus a newline. We encode this and then try to find it in the
# sequence of tokens. This should just be a single token.
response_token_ids = self.tokenizer(RESPONSE_KEY)["input_ids"]
labels = batch["labels"].clone()
for i in range(len(examples)):
response_token_ids_start_idx = None
for idx in np.where(batch["labels"][i] == response_token_ids[0])[0]:
response_token_ids_start_idx = idx
break
if response_token_ids_start_idx is None:
raise RuntimeError(
f'Could not find response key {response_token_ids} in token IDs {batch["labels"][i]}'
)
response_token_ids_end_idx = response_token_ids_start_idx + 1
# Make pytorch loss function ignore all tokens up through the end of the response key
labels[i, :response_token_ids_end_idx] = -100
batch["labels"] = labels
return batch
def get_model_tokenizer(
pretrained_model_name_or_path: str = DEFAULT_INPUT_MODEL, *, gradient_checkpointing: bool = False
) -> Tuple[AutoModelForCausalLM, PreTrainedTokenizer]:
tokenizer = load_tokenizer(pretrained_model_name_or_path)
model = load_model(pretrained_model_name_or_path, gradient_checkpointing=gradient_checkpointing)
model.resize_token_embeddings(len(tokenizer))
return model, tokenizer
def preprocess_dataset(tokenizer: AutoTokenizer, max_length: int, seed=DEFAULT_SEED, path_or_dataset=None) -> Dataset:
"""Loads the training dataset and tokenizes it so it is ready for training.
Args:
tokenizer (AutoTokenizer): Tokenizer tied to the model.
max_length (int): Maximum number of tokens to emit from tokenizer.
Returns:
Dataset: HuggingFace dataset
"""
dataset = load_training_dataset(path_or_dataset=path_or_dataset)
logger.info("Preprocessing dataset")
_preprocessing_function = partial(preprocess_batch, max_length=max_length, tokenizer=tokenizer)
dataset = dataset.map(
_preprocessing_function,
batched=True,
remove_columns=["instruction", "input", "output", "text"],
)
logger.info(f"datasets after processing: {dataset}")
# Make sure we don't have any truncated records, as this would mean the end keyword is missing.
logger.info("Processed dataset has %d rows", dataset.num_rows)
dataset = dataset.filter(lambda rec: len(rec["input_ids"]) < max_length)
logger.info("Processed dataset has %d rows after filtering for truncated records", dataset.num_rows)
logger.info("Shuffling dataset")
dataset = dataset.shuffle(seed=seed)
logger.info("Done preprocessing")
return dataset
def train(
*,
data_path: str,
input_model: str,
local_output_dir: str,
dbfs_output_dir: str,
epochs: int,
per_device_train_batch_size: int,
per_device_eval_batch_size: int,
lr: float,
seed: int,
deepspeed: str,
gradient_checkpointing: bool,
local_rank: str,
bf16: bool,
logging_steps: int,
save_steps: int,
eval_steps: int,
test_size: Union[float, int],
save_total_limit: int,
warmup_steps: int,
):
set_seed(seed)
# Create dir for saving logs and checkpoints
timestamp = datetime.now().strftime("%Y-%m-%dT%H:%M")
model_name = "YAYI_INST"
checkpoint_dir_name = f"{model_name}_{timestamp}"
local_output_dir = os.path.join(local_output_dir, checkpoint_dir_name)
os.makedirs(local_output_dir, exist_ok=True)
model, tokenizer = get_model_tokenizer(
pretrained_model_name_or_path=input_model, gradient_checkpointing=gradient_checkpointing
)
# Use the same max length that the model supports.
max_length = None
for length_setting in ["n_positions", "max_position_embeddings", "seq_length"]:
max_length = getattr(model.config, length_setting, None)
if max_length:
logger.info(f"Found max lenth: {max_length}")
break
if not max_length:
max_length = 1024
logger.info(f"Using default max length: {max_length}")
# Data processing
hf_data_dir = data_path.replace(".json","")
if os.path.exists(hf_data_dir):
logger.info("Load dataset from cache.")
split_dataset = load_from_disk(hf_data_dir)
else:
logger.info("Load dataset from disk.")
processed_dataset = preprocess_dataset(tokenizer=tokenizer, max_length=max_length, seed=seed, path_or_dataset=data_path)
split_dataset = processed_dataset.train_test_split(test_size=test_size, seed=seed)
logger.info("Train data size: %d", split_dataset["train"].num_rows)
logger.info("Test data size: %d", split_dataset["test"].num_rows)
data_collator = DataCollatorForCompletionOnlyLM(
tokenizer=tokenizer, mlm=False, return_tensors="pt", pad_to_multiple_of=8
)
training_args = TrainingArguments(
output_dir=local_output_dir,
per_device_train_batch_size=per_device_train_batch_size,
per_device_eval_batch_size=per_device_eval_batch_size,
fp16=False,
bf16=bf16,
learning_rate=lr,
num_train_epochs=epochs,
deepspeed=deepspeed,
gradient_checkpointing=gradient_checkpointing,
logging_dir=f"{local_output_dir}/runs",
logging_strategy="steps",
logging_steps=logging_steps,
evaluation_strategy="steps",
eval_steps=eval_steps,
save_strategy="steps",
save_steps=save_steps,
save_total_limit=save_total_limit,
load_best_model_at_end=False,
report_to="tensorboard",
disable_tqdm=False,
remove_unused_columns=False,
local_rank=local_rank,
warmup_steps=warmup_steps,
)
logger.info("Instantiating Trainer")
trainer = Trainer(
model=model,
tokenizer=tokenizer,
args=training_args,
train_dataset=split_dataset["train"],
eval_dataset=split_dataset["test"],
data_collator=data_collator,
)
logger.info("Training")
trainer.train()
logger.info(f"Saving Model to {local_output_dir}")
trainer.save_model(output_dir=local_output_dir)
if dbfs_output_dir:
logger.info(f"Saving Model to {dbfs_output_dir}")
trainer.save_model(output_dir=dbfs_output_dir)
logger.info("Done.") | null |
167,849 | import os, sys
os.environ["TOKENIZERS_PARALLELISM"] = "false"
import logging
import click
import numpy as np
from functools import partial
from pathlib import Path
from typing import Any, Dict, List, Tuple, Union
from datetime import datetime
from datasets import Dataset, load_dataset, load_from_disk
from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
DataCollatorForLanguageModeling,
PreTrainedTokenizer,
Trainer,
TrainingArguments,
set_seed,
)
from .consts import (
DEFAULT_INPUT_MODEL,
DEFAULT_SEED,
PROMPT_WITH_INPUT_FORMAT,
PROMPT_NO_INPUT_FORMAT,
END_KEY,
INSTRUCTION_KEY,
RESPONSE_KEY,
INTRO_KEY
)
logger = logging.getLogger(__name__)
class DataCollatorForCompletionOnlyLM(DataCollatorForLanguageModeling):
def torch_call(self, examples: List[Union[List[int], Any, Dict[str, Any]]]) -> Dict[str, Any]:
def get_model_tokenizer(
pretrained_model_name_or_path: str = DEFAULT_INPUT_MODEL, *, gradient_checkpointing: bool = False, lora_dim: int = None, lora_module_name: str = None,
) -> Tuple[AutoModelForCausalLM, PreTrainedTokenizer]:
def preprocess_dataset(tokenizer: AutoTokenizer, max_length: int, seed=DEFAULT_SEED, path_or_dataset=None) -> Dataset:
def train(
*,
data_path: str,
input_model: str,
local_output_dir: str,
dbfs_output_dir: str,
epochs: int,
per_device_train_batch_size: int,
per_device_eval_batch_size: int,
lr: float,
seed: int,
deepspeed: str,
gradient_checkpointing: bool,
local_rank: str,
bf16: bool,
logging_steps: int,
save_steps: int,
eval_steps: int,
test_size: Union[float, int],
save_total_limit: int,
warmup_steps: int,
lora_dim: int,
lora_module_name: str,
):
set_seed(seed)
# Create dir for saving logs and checkpoints
timestamp = datetime.now().strftime("%Y-%m-%dT%H:%M")
model_name = "YAYI_LORA"
checkpoint_dir_name = f"{model_name}_{timestamp}"
local_output_dir = os.path.join(local_output_dir, checkpoint_dir_name)
os.makedirs(local_output_dir, exist_ok=True)
model, tokenizer = get_model_tokenizer(
pretrained_model_name_or_path=input_model, gradient_checkpointing=gradient_checkpointing, lora_dim=lora_dim, lora_module_name=lora_module_name,
)
# Use the same max length that the model supports.
max_length = None
for length_setting in ["n_positions", "max_position_embeddings", "seq_length"]:
max_length = getattr(model.config, length_setting, None)
if max_length:
logger.info(f"Found max lenth: {max_length}")
break
if not max_length:
max_length = 1024
logger.info(f"Using default max length: {max_length}")
# Data processing
hf_data_dir = data_path.replace(".json","")
if os.path.exists(hf_data_dir):
logger.info("Load dataset from cache.")
split_dataset = load_from_disk(hf_data_dir)
else:
logger.info("Load dataset from disk.")
processed_dataset = preprocess_dataset(tokenizer=tokenizer, max_length=max_length, seed=seed, path_or_dataset=data_path)
split_dataset = processed_dataset.train_test_split(test_size=test_size, seed=seed)
logger.info("Train data size: %d", split_dataset["train"].num_rows)
logger.info("Test data size: %d", split_dataset["test"].num_rows)
data_collator = DataCollatorForCompletionOnlyLM(
tokenizer=tokenizer, mlm=False, return_tensors="pt", pad_to_multiple_of=8
)
training_args = TrainingArguments(
output_dir=local_output_dir,
per_device_train_batch_size=per_device_train_batch_size,
per_device_eval_batch_size=per_device_eval_batch_size,
fp16=False,
bf16=bf16,
learning_rate=lr,
num_train_epochs=epochs,
deepspeed=deepspeed,
logging_dir=f"{local_output_dir}/runs",
logging_strategy="steps",
logging_steps=logging_steps,
evaluation_strategy="steps",
eval_steps=eval_steps,
save_strategy="steps",
save_steps=save_steps,
save_total_limit=save_total_limit,
load_best_model_at_end=False,
report_to="tensorboard",
disable_tqdm=False,
remove_unused_columns=False,
local_rank=local_rank,
warmup_steps=warmup_steps,
)
logger.info("Instantiating Trainer")
trainer = Trainer(
model=model,
tokenizer=tokenizer,
args=training_args,
train_dataset=split_dataset["train"],
eval_dataset=split_dataset["test"],
data_collator=data_collator,
)
logger.info("Training")
trainer.train()
logger.info(f"Saving Model to {local_output_dir}")
trainer.save_model(output_dir=local_output_dir)
if dbfs_output_dir:
logger.info(f"Saving Model to {dbfs_output_dir}")
trainer.save_model(output_dir=dbfs_output_dir)
logger.info("Done.") | null |
167,850 | import os, json
from argparse import ArgumentParser
from tqdm import tqdm
The provided code snippet includes necessary dependencies for implementing the `convert_inst_to_chat` function. Write a Python function `def convert_inst_to_chat(path)` to solve the following problem:
Usage: 将 `指令数据格式` 转换为 `对话数据格式`.
Here is the function:
def convert_inst_to_chat(path):
"""
Usage: 将 `指令数据格式` 转换为 `对话数据格式`.
"""
results = []
with open(path, 'r', encoding='utf-8') as f:
lines = f.readlines()
for line in tqdm(lines):
try:
inst_data = json.loads(line)
results.append({
"system": "",
"conversations": [
{"from": "human","value": str(inst_data['instruction'].strip()+"\n"+inst_data['input'].strip()).strip()},
{"from": "yayi","value": inst_data["output"].strip()}]})
except:
continue
print(f"Data num: {len(results)}")
print(f"Example:\n{json.dumps(results[0], ensure_ascii=False, indent=2) if results else 0}")
save_path = path.split('.')[0]+'_chat.json'
with open(save_path, 'w', encoding='utf-8') as f:
f.write(json.dumps(results, ensure_ascii=False, indent=2))
print(f"Save to {save_path}") | Usage: 将 `指令数据格式` 转换为 `对话数据格式`. |
167,851 | import os, json
from argparse import ArgumentParser
from tqdm import tqdm
The provided code snippet includes necessary dependencies for implementing the `convert_chat_to_inst` function. Write a Python function `def convert_chat_to_inst(path)` to solve the following problem:
Usage: 将 `对话数据格式` 转换为 `指令数据格式` 忽略多轮数据.
Here is the function:
def convert_chat_to_inst(path):
"""
Usage: 将 `对话数据格式` 转换为 `指令数据格式` 忽略多轮数据.
"""
results = []
with open(path, 'r', encoding='utf-8') as f:
lines = json.load(f)
for line in tqdm(lines):
try:
if len(line["conversations"])>2: continue
results.append({
"system": line.get("system", "").strip(),
"instruction": line["conversations"][0]["value"].strip(),
"input": "",
"output": line["conversations"][1]["value"].strip()
})
except:
continue
print(f"Data num: {len(results)}")
print(f"Example:\n{json.dumps(results[0], ensure_ascii=False, indent=2) if results else 0}")
save_path = path.split('.')[0]+'_inst.json'
with open(save_path, 'a+', encoding='utf-8') as f:
for each in results:
f.write(json.dumps(each, ensure_ascii=False)+"\n")
print(f"Save to {save_path}") | Usage: 将 `对话数据格式` 转换为 `指令数据格式` 忽略多轮数据. |
167,852 | import os, json
from argparse import ArgumentParser
from tqdm import tqdm
The provided code snippet includes necessary dependencies for implementing the `merge_multi_chat_files` function. Write a Python function `def merge_multi_chat_files(path)` to solve the following problem:
Usage: 合并多个 `对话数据格式` 文件.
Here is the function:
def merge_multi_chat_files(path):
"""
Usage: 合并多个 `对话数据格式` 文件.
"""
results = []
for filepath in path.split(","):
print(f"Loading {filepath}")
with open(filepath, 'r', encoding='utf-8') as f:
results.extend(json.load(f))
save_path = path.split('.')[0]+'_merged.json'
with open(save_path, 'w', encoding='utf-8') as f:
f.write(json.dumps(results, ensure_ascii=False, indent=2))
print(f"Save to {save_path}") | Usage: 合并多个 `对话数据格式` 文件. |
167,854 | from setuptools import find_packages, setup
import os
import subprocess
import time
version_file = 'pyiqa/version.py'
def get_hash():
def write_version_py():
content = """# GENERATED VERSION FILE
# TIME: {}
__version__ = '{}'
__gitsha__ = '{}'
version_info = ({})
"""
sha = get_hash()
with open('VERSION', 'r') as f:
SHORT_VERSION = f.read().strip()
VERSION_INFO = ', '.join([x if x.isdigit() else f'"{x}"' for x in SHORT_VERSION.split('.')])
version_file_str = content.format(time.asctime(), SHORT_VERSION, sha, VERSION_INFO)
with open(version_file, 'w') as f:
f.write(version_file_str) | null |
167,855 | from setuptools import find_packages, setup
import os
import subprocess
import time
version_file = 'pyiqa/version.py'
def get_version():
with open(version_file, 'r') as f:
exec(compile(f.read(), version_file, 'exec'))
return locals()['__version__'] | null |
167,858 | import math
import torch
from torch import autograd as autograd
from torch import nn as nn
from torch.nn import functional as F
from pyiqa.utils.registry import LOSS_REGISTRY
from .loss_util import weighted_loss
def l1_loss(pred, target):
return F.l1_loss(pred, target, reduction='none') | null |
167,859 | import math
import torch
from torch import autograd as autograd
from torch import nn as nn
from torch.nn import functional as F
from pyiqa.utils.registry import LOSS_REGISTRY
from .loss_util import weighted_loss
def mse_loss(pred, target):
return F.mse_loss(pred, target, reduction='none') | null |
167,860 | import math
import torch
from torch import autograd as autograd
from torch import nn as nn
from torch.nn import functional as F
from pyiqa.utils.registry import LOSS_REGISTRY
from .loss_util import weighted_loss
def cross_entropy(pred, target):
return F.cross_entropy(pred, target, reduction='none') | null |
167,861 | import math
import torch
from torch import autograd as autograd
from torch import nn as nn
from torch.nn import functional as F
from pyiqa.utils.registry import LOSS_REGISTRY
from .loss_util import weighted_loss
def nll_loss(pred, target):
return F.nll_loss(pred, target, reduction='none') | null |
167,862 | import math
import torch
from torch import autograd as autograd
from torch import nn as nn
from torch.nn import functional as F
from pyiqa.utils.registry import LOSS_REGISTRY
from .loss_util import weighted_loss
def charbonnier_loss(pred, target, eps=1e-12):
return torch.sqrt((pred - target)**2 + eps) | null |
167,863 | from cv2 import reduce
import torch
import numpy as np
from torch import nn as nn
from torch.nn import functional as F
from pyiqa.utils.registry import LOSS_REGISTRY
from .loss_util import weighted_loss
The provided code snippet includes necessary dependencies for implementing the `emd_loss` function. Write a Python function `def emd_loss(pred, target, r=2)` to solve the following problem:
Args: pred (Tensor): of shape (N, C). Predicted tensor. target (Tensor): of shape (N, C). Ground truth tensor. r (float): norm level, default l2 norm.
Here is the function:
def emd_loss(pred, target, r=2):
"""
Args:
pred (Tensor): of shape (N, C). Predicted tensor.
target (Tensor): of shape (N, C). Ground truth tensor.
r (float): norm level, default l2 norm.
"""
loss = torch.abs(torch.cumsum(pred, dim=-1) - torch.cumsum(target, dim=-1))**r
loss = loss.mean(dim=-1)**(1. / r)
return loss | Args: pred (Tensor): of shape (N, C). Predicted tensor. target (Tensor): of shape (N, C). Ground truth tensor. r (float): norm level, default l2 norm. |
167,864 | from cv2 import reduce
import torch
import numpy as np
from torch import nn as nn
from torch.nn import functional as F
from pyiqa.utils.registry import LOSS_REGISTRY
from .loss_util import weighted_loss
The provided code snippet includes necessary dependencies for implementing the `plcc_loss` function. Write a Python function `def plcc_loss(pred, target)` to solve the following problem:
Args: pred (Tensor): of shape (N, 1). Predicted tensor. target (Tensor): of shape (N, 1). Ground truth tensor.
Here is the function:
def plcc_loss(pred, target):
"""
Args:
pred (Tensor): of shape (N, 1). Predicted tensor.
target (Tensor): of shape (N, 1). Ground truth tensor.
"""
batch_size = pred.shape[0]
if batch_size > 1:
vx = pred - pred.mean()
vy = target - target.mean()
loss = F.normalize(vx, p=2, dim=0) * F.normalize(vy, p=2, dim=0)
loss = (1 - loss.sum()) / 2 # normalize to [0, 1]
else:
loss = F.l1_loss(pred, target)
return loss.mean() | Args: pred (Tensor): of shape (N, 1). Predicted tensor. target (Tensor): of shape (N, 1). Ground truth tensor. |
167,865 | from cv2 import reduce
import torch
import numpy as np
from torch import nn as nn
from torch.nn import functional as F
from pyiqa.utils.registry import LOSS_REGISTRY
from .loss_util import weighted_loss
The provided code snippet includes necessary dependencies for implementing the `norm_loss_with_normalization` function. Write a Python function `def norm_loss_with_normalization(pred, target, p, q)` to solve the following problem:
Args: pred (Tensor): of shape (N, 1). Predicted tensor. target (Tensor): of shape (N, 1). Ground truth tensor.
Here is the function:
def norm_loss_with_normalization(pred, target, p, q):
"""
Args:
pred (Tensor): of shape (N, 1). Predicted tensor.
target (Tensor): of shape (N, 1). Ground truth tensor.
"""
batch_size = pred.shape[0]
if batch_size > 1:
vx = pred - pred.mean()
vy = target - target.mean()
scale = np.power(2, p) * np.power(batch_size, max(0, 1 - p / q)) # p, q>0
norm_pred = F.normalize(vx, p=q, dim=0)
norm_target = F.normalize(vy, p=q, dim=0)
loss = torch.norm(norm_pred - norm_target, p=p) / scale
else:
loss = F.l1_loss(pred, target)
return loss.mean() | Args: pred (Tensor): of shape (N, 1). Predicted tensor. target (Tensor): of shape (N, 1). Ground truth tensor. |
167,866 | import math
import collections.abc
from itertools import repeat
import numpy as np
from typing import Tuple
import torch
from torch import nn as nn
from torch.nn import functional as F
from torch.nn import init as init
def _ntuple(n):
def parse(x):
if isinstance(x, collections.abc.Iterable):
return x
return tuple(repeat(x, n))
return parse | null |
167,867 | import math
import collections.abc
from itertools import repeat
import numpy as np
from typing import Tuple
import torch
from torch import nn as nn
from torch.nn import functional as F
from torch.nn import init as init
to_2tuple = _ntuple(2)
def symm_pad(im: torch.Tensor, padding: Tuple[int, int, int, int]):
"""Symmetric padding same as tensorflow.
Ref: https://discuss.pytorch.org/t/symmetric-padding/19866/3
"""
h, w = im.shape[-2:]
left, right, top, bottom = padding
x_idx = np.arange(-left, w + right)
y_idx = np.arange(-top, h + bottom)
def reflect(x, minx, maxx):
""" Reflects an array around two points making a triangular waveform that ramps up
and down, allowing for pad lengths greater than the input length """
rng = maxx - minx
double_rng = 2 * rng
mod = np.fmod(x - minx, double_rng)
normed_mod = np.where(mod < 0, mod + double_rng, mod)
out = np.where(normed_mod >= rng, double_rng - normed_mod, normed_mod) + minx
return np.array(out, dtype=x.dtype)
x_pad = reflect(x_idx, -0.5, w - 0.5)
y_pad = reflect(y_idx, -0.5, h - 0.5)
xx, yy = np.meshgrid(x_pad, y_pad)
return im[..., yy, xx]
def exact_padding_2d(x, kernel, stride=1, dilation=1, mode='same'):
assert len(x.shape) == 4, f'Only support 4D tensor input, but got {x.shape}'
kernel = to_2tuple(kernel)
stride = to_2tuple(stride)
dilation = to_2tuple(dilation)
b, c, h, w = x.shape
h2 = math.ceil(h / stride[0])
w2 = math.ceil(w / stride[1])
pad_row = (h2 - 1) * stride[0] + (kernel[0] - 1) * dilation[0] + 1 - h
pad_col = (w2 - 1) * stride[1] + (kernel[1] - 1) * dilation[1] + 1 - w
pad_l, pad_r, pad_t, pad_b = (pad_col // 2, pad_col - pad_col // 2, pad_row // 2, pad_row - pad_row // 2)
mode = mode if mode != 'same' else 'constant'
if mode != 'symmetric':
x = F.pad(x, (pad_l, pad_r, pad_t, pad_b), mode=mode)
elif mode == 'symmetric':
x = symm_pad(x, (pad_l, pad_r, pad_t, pad_b))
return x | null |
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