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Property list files are often used to store a user's settings. They are also used to store information about bundles and applications, a task served by the resource fork in the old Mac OS. Property lists are also used for localization strings for development. These files use the .strings or .stringsdict extensions.
RDFLib is a Python library for working with RDF, [2] a simple yet powerful language for representing information. This library contains parsers/serializers for almost all of the known RDF serializations, such as RDF/XML, Turtle, N-Triples, & JSON-LD, many of which are now supported in their updated form (e.g. Turtle 1.1).
It can convert a wide range of complex data structures, including dict, array, numpy ndarray, into JData representations and export the data as JSON or UBJSON files. The BJData Python module, pybj, [4] enabling reading/writing BJData/UBJSON files, is also available on PyPI, Debian/Ubuntu and GitHub.
Byte Strings are encoded as <length>:<contents>. The length is the number of bytes in the string, encoded in base 10. A colon (:) separates the length and the contents. The contents are the exact number of bytes specified by the length. Examples: An empty string is encoded as 0:. The string "bencode" is encoded as 7:bencode.
The standard dictd [7] server made by the DICT Development Group [1] uses a special dict file format. It comprises two files, a .index file and a .dict file (or .dict.dz if compressed). These files are usually generated by a program called dictfmt. For example, the Unix command:
reStructuredText (RST, ReST, or reST) is a file format for textual data used primarily in the Python programming language community for technical documentation.. It is part of the Docutils project of the Python Doc-SIG (Documentation Special Interest Group), aimed at creating a set of tools for Python similar to Javadoc for Java or Plain Old Documentation (POD) for Perl.
A dictionary coder, also sometimes known as a substitution coder, is a class of lossless data compression algorithms which operate by searching for matches between the text to be compressed and a set of strings contained in a data structure (called the 'dictionary') maintained by the encoder. When the encoder finds such a match, it substitutes ...
For example, one could define a dictionary having a string "toast" mapped to the integer 42 or vice versa. The keys in a dictionary must be of an immutable Python type, such as an integer or a string, because under the hood they are implemented via a hash function. This makes for much faster lookup times, but requires keys not change.