![]() Raises a LookupError in case the encoding cannot be found or the codecĭoesn’t support an incremental encoder. Look up the codec for the given encoding and return its incremental encoder Raises a LookupError in case the encoding cannot be found. Look up the codec for the given encoding and return its decoder function. Look up the codec for the given encoding and return its encoder function. These additional functions which use lookup() for the codec lookup: codecs. To simplify access to the various codec components, the module provides StreamWriter and StreamReader, respectively. Provide the interface defined by the base classes Stream writer and reader classes or factory functions. IncrementalEncoder and IncrementalDecoder, These have to provide the interface defined by the base classes Incremental encoder and decoder classes or factory functions. incrementalencoder ¶ incrementaldecoder ¶ The functions or methods are expected to work in a stateless mode. The encode() and decode() methods of Codec These must beįunctions or methods which have the same interface as The stateless encoding and decoding functions. The constructorĪrguments are stored in attributes of the same name: name ¶ CodecInfo ( encode, decode, streamreader = None, streamwriter = None, incrementalencoder = None, incrementaldecoder = None, name = None ) ¶Ĭodec details when looking up the codec registry. Is stored in the cache and returned to the caller. If no CodecInfo object isįound, a LookupError is raised. Looks up the codec info in the Python codec registry and returns aĮncodings are first looked up in the registry’s cache. The full details for each codec can also be looked up directly: codecs. decode ( obj, encoding = 'utf-8', errors = 'strict' ) ¶ĭecodes obj using the codec registered for encoding.ĭefault error handler is 'strict' meaning that decoding errors raise ValueError (or a more codec specific subclass, such as Theĭefault error handler is 'strict' meaning that encoding errors raise encode ( obj, encoding = 'utf-8', errors = 'strict' ) ¶Įncodes obj using the codec registered for encoding.Įrrors may be given to set the desired error handling scheme. The module defines the following functions for encoding and decoding withĪny codec: codecs. Text encodings or with codecs that encode to Types, but some module features are restricted to be used specifically with Custom codecs may encode and decode between arbitrary Most standard codecsĪre text encodings, which encode text to bytes (andĭecode bytes to text), but there are also codecs provided that encode text to Manages the codec and error handling lookup process. This module defines base classes for standard Python codecs (encoders andĭecoders) and provides access to the internal Python codec registry, which To get help with command line usage.Codecs - Codec registry and base classes ¶ The package can be run from the command line, in which case, it providesĪ routine for converting Matlab MAT-files to/from JSON files. The parameter data shall be a dict with the variables. Of simple data types, like dict, list, str, int and float.Įxample: Save a Python data structure to a MAT-file: savemat('datafile.mat', data) To be structured in the same way as for loadmat, i.e. Python data can be saved to a MAT-file, with the function savemat. The variable data is a dict with the variables and values contained in the MAT-file. The resulting data structure is composed of simple types that are compatibleĮxample: Load a MAT-file into a Python data structure: data = loadmat('datafile.mat') ![]() Arrays are squeezed to eliminate arrays with only one element. Numeric and cell arrays are converted to row-ordered nested lists. The function loadmat loads all variables stored in the MAT-file intoĪ simple Python data structure, using only Python’s dict and list ![]() The package can be run from the command line, in which case, it provides a routine for converting Matlab MAT-files to/from JSON files. Matlab structs and cells are represented using Python dicts. ![]() Matrices are stored row-major using lists of lists. Matlab data is loaded into basic Python data types. The package provides the mat4py module with the functions loadmat and
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