OpenNBT Tiny, liberally-licensed NBT library
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reader Python library Python NBT

OpenNBT Description

OpenNBT is a tiny NBT library written in Python that supports reading and writing compressed, uncompressed, big endian, little endian, or pocket edition (v2) NBT files transparently. It also includes helpers for region files and pocket detection.ScriptsThe OpenNBT package installs two scripts, debug-nbt and debug-region. These scripts can be used to pretty-print the NBT contents of plain NBT files and region files.Example:debug-nbt level.datTAG_Compound(''): 1 entries{ TAG_Compound('Data'): 18 entries { ... }}Using the LibraryUsing the library in your own programs is simple. By default, OpenNBT will try to save opened NBT files in the same format they were loaded from, however this behaviour is easily changed.WritingWhen writing NBT files with OpenNBT, every tag should be treated as if it was immutable. This is to simplify future changes to both the library and the format. Developer wise, building NBT files is less convienient, but very explicit. This is done because of the differences in basic types between NBT and python.from opennbt import NBTFile, TAG_Long, TAG_List, TAG_Stringstructure = { 'long_test': TAG_Long('long_test', 104005), 'list_test': TAG_List('list_test', TAG_String, )}nbt = NBTFile(root_name='', value=structure)nbt.save('out.nbt')ReadingReading is simple, and will accept any file-like object providing read() or a path to a file. If a path is provided, OpenNBT may open it multiple times to figure out the format. If you provide a file-like object, you need to specify the details yourself.Simply pretty-printing the file created from the example under writing:from opennbt import NBTFilenbt = NBTFile('out.nbt')print(nbt.pretty())This produces the output:TAG_Compound(''): 2 entries{ TAG_Long('long_test'): 104005 TAG_List('list_test'): 3 entries { TAG_String(None): 'Timmy' TAG_String(None): 'Billy' TAG_String(None): 'Sally' }}Every tag exposes a minimum of two fields, .name and .value. Every type's value maps to a plain Python type, such as a dict() for TAG_Compound and a list for TAG_List. Every tag also provides complete __repr__ methods for printing. This makes traversal very simple and familiar to existing Python developers.nbt = NBTFile('out.nbt')for name, tag in nbt.value.items(): print name, tagif 'list_test' in nbt.value: for tag in nbt.value.value: print tagProduct's homepage

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