Miroirs/slackbuilds_ponce
1
0
Fork 0
mirror of https://github.com/Ponce/slackbuilds synced 2024-11-04 20:29:09 +01:00
Code Issues Projects Releases Packages Wiki Activity Actions

python/construct: Wrap README at 72 columns.

Browse source 
Signed-off-by: B. Watson <yalhcru@gmail.com>
This commit is contained in:
B. Watson 2022-03-14 04:11:32 -04:00
parent 701cdb2b52
commit b952b6e8e5
1 changed files with 18 additions and 15 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

33
python/construct/README
View file

@ -1,21 +1,24 @@
Construct (python library)
Construct is a powerful declarative parser (and builder) for binary data.
Construct is a powerful declarative parser (and builder) for binary
data.
The library provides both simple, atomic constructs (such as integers of
various sizes), as well as composite ones which allow you form hierarchical
structures of increasing complexity. Construct features bit and byte
granularity, easy debugging and testing, an easy-to-extend subclass system,
and lots of primitive constructs to make your work easier:
The library provides both simple, atomic constructs (such as
integers of various sizes), as well as composite ones which allow
you form hierarchical structures of increasing complexity. Construct
features bit and byte granularity, easy debugging and testing, an
easy-to-extend subclass system, and lots of primitive constructs to
make your work easier:
-Fields: raw bytes or numerical types
-Structs and Sequences: combine simpler constructs into more complex ones
-Adapters: change how data is represented
-Arrays/Ranges: duplicate constructs
-Meta-constructs: use the context (history) to compute the size of data
-If/Switch: branch the computational path based on the context
-On-demand (lazy) parsing: read only what you require
-Pointers: jump from here to there in the data stream
-Tunneling: prefix data with a byte count or compress it
-Fields: raw bytes or numerical types
-Structs and Sequences: combine simpler constructs into more complex
ones
-Adapters: change how data is represented
-Arrays/Ranges: duplicate constructs
-Meta-constructs: use the context (history) to compute the size of data
-If/Switch: branch the computational path based on the context
-On-demand (lazy) parsing: read only what you require
-Pointers: jump from here to there in the data stream
-Tunneling: prefix data with a byte count or compress it
Optional dependancies include Enum34, Numpy, and Arrow.