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Python interface to libexiv2

Project description

python-exiv2 is a low level interface (or binding) to the exiv2 C++ library. It is built using SWIG to automatically generate the interface code. The intention is to give direct access to all of the top-level classes in libexiv2, but with additional “Pythonic” helpers where necessary. Not everything in libexiv2 is available in the Python interface. If you need something that’s not there, please let me know.

Introduction

There are several other ways to access libexiv2 from within Python. The first one I used was pyexiv2 (old). After its development ceased I moved on to using gexiv2 and PyGObject. This works well, providing a Metadata object with high level functions such as set_tag_string and set_tag_multiple to get and set metadata values.

A more recent development is pyexiv2 (new). This new project is potentially very useful, providing a simple interface with functions to read and modify metadata using Python dict parameters.

For more complicated metadata operations I think a lower level interface is required, which is where this project comes in. Here is an example of its use:

Python 3.6.12 (default, Dec 02 2020, 09:44:23) [GCC] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import exiv2
>>> image = exiv2.ImageFactory.open('IMG_0211.JPG')
>>> image.readMetadata()
>>> data = image.exifData()
>>> data['Exif.Image.Artist']._print()
'Jim Easterbrook'
>>>

Documentation

The libexiv2 library is well documented for C++ users, in Doxygen format. Recent versions of SWIG can convert this documentation to pydoc format in the Python interface:

$ pydoc3 exiv2.Image.readMetadata
Help on method_descriptor in exiv2.Image:

exiv2.Image.readMetadata = readMetadata(...)
    Read all metadata supported by a specific image format from the
        image. Before this method is called, the image metadata will be
        cleared.

    This method returns success even if no metadata is found in the
    image. Callers must therefore check the size of individual metadata
    types before accessing the data.

    :raises: Error if opening or reading of the file fails or the image
            data is not valid (does not look like data of the specific image
            type).

Unfortunately some documentation gets lost in the manipulations needed to make a useful interface. The C++ documentation is still needed in these cases.

Assignment

libexiv2 stores metadata values in a generalised container whose type can be set by the type of a value assigned to it, for example:

// C or C++
exifData["Exif.Image.SamplesPerPixel"] = uint16_t(162);

This forces the Exif.Image.SamplesPerPixel value to be an unsigned short. Python doesn’t have such specific integer types, so if you need to set the type you can create an exiv2 value of the appropriate type and assign that:

# Python
exifData["Exif.Image.SamplesPerPixel"] = exiv2.UShortValue(162)

This allows you to set the value to any type, just like in C++, but the Python interface warns you if you set a type that isn’t the default for that tag. Alternatively you can use any Python object and let libexiv2 convert the string representation of that object to the appropriate type:

# Python
exifData["Exif.Image.SamplesPerPixel"] = 162

Iterators

The Exiv2::ExifData, Exiv2::IptcData, and Exiv2::XmpData classes use C++ iterators to expose private data, for example the ExifData class has a private member of std::list<Exifdatum> type. The classes have public begin(), end(), and findKey() methods that return std::list iterators. In C++ you can dereference one of these iterators to access the Exifdatum object, but Python doesn’t have a dereference operator.

This Python interface converts the std::list iterator to a Python object that has access to all the Exifdatum object’s methods without dereferencing. For example:

Python 3.6.12 (default, Dec 02 2020, 09:44:23) [GCC] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import exiv2
>>> image = exiv2.ImageFactory.open('IMG_0211.JPG')
>>> image.readMetadata()
>>> data = image.exifData()
>>> b = data.begin()
>>> b.key()
'Exif.Image.ProcessingSoftware'
>>>

Before using an iterator you must ensure that it is not equal to the end() value. Failure to do so may produce a segmentation fault, just like a C++ program would.

You can iterate over the data in a very C++ like style:

>>> data = image.exifData()
>>> b = data.begin()
>>> e = data.end()
>>> while b != e:
...     b.key()
...     next(b)
...
'Exif.Image.ProcessingSoftware'
<Swig Object of type 'Exiv2::Exifdatum *' at 0x7fd6053f9030>
'Exif.Image.ImageDescription'
<Swig Object of type 'Exiv2::Exifdatum *' at 0x7fd6053f9030>
[skip 227 line pairs]
'Exif.Thumbnail.JPEGInterchangeFormat'
<Swig Object of type 'Exiv2::Exifdatum *' at 0x7fd6053f9030>
'Exif.Thumbnail.JPEGInterchangeFormatLength'
<Swig Object of type 'Exiv2::Exifdatum *' at 0x7fd6053f9030>
>>>

The <Swig Object of type 'Exiv2::Exifdatum *' at 0x7fd6053f9030> lines are the Python interpreter showing the return value of next(b). You can also iterate in a more Pythonic style:

>>> data = image.exifData()
>>> for datum in data:
...     datum.key()
...
'Exif.Image.ProcessingSoftware'
'Exif.Image.ImageDescription'
[skip 227 lines]
'Exif.Thumbnail.JPEGInterchangeFormat'
'Exif.Thumbnail.JPEGInterchangeFormatLength'
>>>

The data container classes are like a cross between a Python list of Metadatum objects and a Python dict of (key, Value) pairs. (One way in which they are not like a dict is that you can have more than one member with the same key.) This allows them to be used in a very Pythonic style:

data = image.exifData()
print(data['Exif.Image.ImageDescription'].toString())
if 'Exif.Image.ProcessingSoftware' in data:
    del data['Exif.Image.ProcessingSoftware']
data = image.iptcData()
while 'Iptc.Application2.Keywords' in data:
    del data['Iptc.Application2.Keywords']

Warning: segmentation faults

Many of the libexiv2 objects point to data in other objects. For example, image.exifData() returns an object that points to data in image. The Python interface uses Python objects’ reference counting to prevent image being deleted while its data is being pointed at by another object. This avoids one possible cause of segfaults.

There may be other cases where the Python interface doesn’t prevent segfaults. Please let me know if you find any.

Error handling

libexiv2 has a multilevel warning system a bit like Python’s standard logger. The Python interface redirects all Exiv2 messages to Python logging with an appropriate log level. The exiv2.LogMsg.setLevel function can be used to control what severity of messages are logged.

Installation

Python “wheels” are available for Windows (Python 3.5 to 3.10) and Linux & MacOS (Python 3.6 to 3.10). These include the libexiv2 library and should not need any other software to be installed. They can be installed with Python’s pip package. For example, on Windows:

C:\Users\Jim>pip install python-exiv2

or on Linux or MacOS:

$ sudo pip3 install python-exiv2

You can install for a single user with the --user option:

$ pip3 install --user python-exiv2

If the available wheels are not compatible with your operating system then pip will download the python-exiv2 source and attempt to compile it. For more information, and details of how to compile python-exiv2 and libexiv2, see INSTALL.rst.

Problems?

Please email jim@jim-easterbrook.me.uk if you find any problems (or solutions!).

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