KLL Compiler
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KLL Compiler Re-Write This was many months of efforts in re-designing how the KLL compiler should work. The major problem with the original compiler was how difficult it was to extend language wise. This lead to many delays in KLL 0.4 and 0.5 being implemented. The new design is a multi-staged compiler, where even tokenization occurs over multiple stages. This allows individual parsing and token regexes to be expressed more simply without affect other expressions. Another area of change is the concept of Contexts. In the original KLL compiler the idea of a cache assigned was "hacked" on when I realized the language was "broken" (after nearly finishing the compiler). Since assignment order is generally considered not to matter for keymappings, I created a "cached" assignment where the whole file is read into a sub-datastructure, then apply to the master datastructure. Unfortunately, this wasn't really all that clear, so it was annoying to work with. To remedy this, I created KLL Contexts, which contain information about a group of expressions. Not only can these groups can be merged with other Contexts, they have historical data about how they were generated allowing for errors very late in processing to be pin-pointed back to the offending kll file. Backends work nearly the same as they did before. However, all call-backs for capability evaluations have been removed. This makes the interface much cleaner as Contexts can only be symbolically merged now. (Previously datastructures did evaluation merges where the ScanCode or Capability was looked up right before passing to the backend, but this required additional information from the backend). Many of the old parsing and tokenization rules have been reused, along with the hid_dict.py code. The new design takes advantage of processor pools to handle multithreading where it makes sense. For example, all specified files are loaded into ram simulatenously rather than sparingly reading from. The reason for this is so that each Context always has all the information it requires at all times. kll - Program entry point (previously kll.py) - Very small now, does some setting up of command-line args - Most command-line args are specified by the corresponding processing stage common/channel.py - Pixel Channel container classes common/context.py - Context container classes - As is usual with other files, blank classes inherit a base class - These blank classes are identified by the class name itself to handle special behaviour - And if/when necessary functions are re-implemented - MergeConext class facilitates merging of contexts while maintaining lineage common/expression.py - Expression container classes * Expression base class * AssignmentExpression * NameAssociationExpression * DataAssociationExpression * MapExpression - These classes are used to store expressions after they have finished parsing and tokenization common/file.py - Container class for files being read by the KLL compiler common/emitter.py - Base class for all KLL emitters - TextEmitter for dealing with text file templates common/hid_dict.py - Slightly modified version of kll_lib/hid_dict.py common/id.py - Identification container classes - Used to indentify different types of elements used within the KLL language common/modifier.py - Container classes for animation and pixel change functions common/organization.py - Data structure merging container classes - Contains all the sub-datastructure classes as well - The Organization class handles the merge orchestration and expression insertion common/parse.py - Parsing rules for funcparserlib - Much of this file was taken from the original kll.py - Many changes to support the multi-stage processing and support KLL 0.5 common/position.py - Container class dealing with physical positions common/schedule.py - Container class dealing with scheduling and timing events common/stage.py - Contains ControlStage and main Stage classes * CompilerConfigurationStage * FileImportStage * PreprocessorStage * OperationClassificationStage * OperationSpecificsStage * OperationOrganizationStage * DataOrganziationStage * DataFinalizationStage * DataAnalysisStage * CodeGenerationStage * ReportGenerationStage - Each of these classes controls the life-cycle of each stage - If multi-threading is desired, it must be handled within the class * The next stage will not start until the current stage is finished - Errors are handled such that as many errors as possible are recorded before forcing an exit * The exit is handled at the end of each stage if necessary - Command-line arguments for each stage can be defined if necessary (they are given their own grouping) - Each stage can pull variables and functions from other stages if necessary using a name lookup * This means you don't have to worry about over-arching datastructures emitters/emitters.py - Container class for KLL emitters - Handles emitter setup and selection emitters/kiibohd/kiibohd.py - kiibohd .h file KLL emitter - Re-uses some backend code from the original KLL compiler funcparserlib/parser.py - Added debug mode control examples/assignment.kll examples/defaultMapExample.kll examples/example.kll examples/hhkbpro2.kll examples/leds.kll examples/mapping.kll examples/simple1.kll examples/simple2.kll examples/simpleExample.kll examples/state_scheduling.kll - Updating/Adding rules for new compiler and KLL 0.4 + KLL 0.5 support
7 년 전
KLL Compiler Re-Write This was many months of efforts in re-designing how the KLL compiler should work. The major problem with the original compiler was how difficult it was to extend language wise. This lead to many delays in KLL 0.4 and 0.5 being implemented. The new design is a multi-staged compiler, where even tokenization occurs over multiple stages. This allows individual parsing and token regexes to be expressed more simply without affect other expressions. Another area of change is the concept of Contexts. In the original KLL compiler the idea of a cache assigned was "hacked" on when I realized the language was "broken" (after nearly finishing the compiler). Since assignment order is generally considered not to matter for keymappings, I created a "cached" assignment where the whole file is read into a sub-datastructure, then apply to the master datastructure. Unfortunately, this wasn't really all that clear, so it was annoying to work with. To remedy this, I created KLL Contexts, which contain information about a group of expressions. Not only can these groups can be merged with other Contexts, they have historical data about how they were generated allowing for errors very late in processing to be pin-pointed back to the offending kll file. Backends work nearly the same as they did before. However, all call-backs for capability evaluations have been removed. This makes the interface much cleaner as Contexts can only be symbolically merged now. (Previously datastructures did evaluation merges where the ScanCode or Capability was looked up right before passing to the backend, but this required additional information from the backend). Many of the old parsing and tokenization rules have been reused, along with the hid_dict.py code. The new design takes advantage of processor pools to handle multithreading where it makes sense. For example, all specified files are loaded into ram simulatenously rather than sparingly reading from. The reason for this is so that each Context always has all the information it requires at all times. kll - Program entry point (previously kll.py) - Very small now, does some setting up of command-line args - Most command-line args are specified by the corresponding processing stage common/channel.py - Pixel Channel container classes common/context.py - Context container classes - As is usual with other files, blank classes inherit a base class - These blank classes are identified by the class name itself to handle special behaviour - And if/when necessary functions are re-implemented - MergeConext class facilitates merging of contexts while maintaining lineage common/expression.py - Expression container classes * Expression base class * AssignmentExpression * NameAssociationExpression * DataAssociationExpression * MapExpression - These classes are used to store expressions after they have finished parsing and tokenization common/file.py - Container class for files being read by the KLL compiler common/emitter.py - Base class for all KLL emitters - TextEmitter for dealing with text file templates common/hid_dict.py - Slightly modified version of kll_lib/hid_dict.py common/id.py - Identification container classes - Used to indentify different types of elements used within the KLL language common/modifier.py - Container classes for animation and pixel change functions common/organization.py - Data structure merging container classes - Contains all the sub-datastructure classes as well - The Organization class handles the merge orchestration and expression insertion common/parse.py - Parsing rules for funcparserlib - Much of this file was taken from the original kll.py - Many changes to support the multi-stage processing and support KLL 0.5 common/position.py - Container class dealing with physical positions common/schedule.py - Container class dealing with scheduling and timing events common/stage.py - Contains ControlStage and main Stage classes * CompilerConfigurationStage * FileImportStage * PreprocessorStage * OperationClassificationStage * OperationSpecificsStage * OperationOrganizationStage * DataOrganziationStage * DataFinalizationStage * DataAnalysisStage * CodeGenerationStage * ReportGenerationStage - Each of these classes controls the life-cycle of each stage - If multi-threading is desired, it must be handled within the class * The next stage will not start until the current stage is finished - Errors are handled such that as many errors as possible are recorded before forcing an exit * The exit is handled at the end of each stage if necessary - Command-line arguments for each stage can be defined if necessary (they are given their own grouping) - Each stage can pull variables and functions from other stages if necessary using a name lookup * This means you don't have to worry about over-arching datastructures emitters/emitters.py - Container class for KLL emitters - Handles emitter setup and selection emitters/kiibohd/kiibohd.py - kiibohd .h file KLL emitter - Re-uses some backend code from the original KLL compiler funcparserlib/parser.py - Added debug mode control examples/assignment.kll examples/defaultMapExample.kll examples/example.kll examples/hhkbpro2.kll examples/leds.kll examples/mapping.kll examples/simple1.kll examples/simple2.kll examples/simpleExample.kll examples/state_scheduling.kll - Updating/Adding rules for new compiler and KLL 0.4 + KLL 0.5 support
7 년 전
KLL Compiler Re-Write This was many months of efforts in re-designing how the KLL compiler should work. The major problem with the original compiler was how difficult it was to extend language wise. This lead to many delays in KLL 0.4 and 0.5 being implemented. The new design is a multi-staged compiler, where even tokenization occurs over multiple stages. This allows individual parsing and token regexes to be expressed more simply without affect other expressions. Another area of change is the concept of Contexts. In the original KLL compiler the idea of a cache assigned was "hacked" on when I realized the language was "broken" (after nearly finishing the compiler). Since assignment order is generally considered not to matter for keymappings, I created a "cached" assignment where the whole file is read into a sub-datastructure, then apply to the master datastructure. Unfortunately, this wasn't really all that clear, so it was annoying to work with. To remedy this, I created KLL Contexts, which contain information about a group of expressions. Not only can these groups can be merged with other Contexts, they have historical data about how they were generated allowing for errors very late in processing to be pin-pointed back to the offending kll file. Backends work nearly the same as they did before. However, all call-backs for capability evaluations have been removed. This makes the interface much cleaner as Contexts can only be symbolically merged now. (Previously datastructures did evaluation merges where the ScanCode or Capability was looked up right before passing to the backend, but this required additional information from the backend). Many of the old parsing and tokenization rules have been reused, along with the hid_dict.py code. The new design takes advantage of processor pools to handle multithreading where it makes sense. For example, all specified files are loaded into ram simulatenously rather than sparingly reading from. The reason for this is so that each Context always has all the information it requires at all times. kll - Program entry point (previously kll.py) - Very small now, does some setting up of command-line args - Most command-line args are specified by the corresponding processing stage common/channel.py - Pixel Channel container classes common/context.py - Context container classes - As is usual with other files, blank classes inherit a base class - These blank classes are identified by the class name itself to handle special behaviour - And if/when necessary functions are re-implemented - MergeConext class facilitates merging of contexts while maintaining lineage common/expression.py - Expression container classes * Expression base class * AssignmentExpression * NameAssociationExpression * DataAssociationExpression * MapExpression - These classes are used to store expressions after they have finished parsing and tokenization common/file.py - Container class for files being read by the KLL compiler common/emitter.py - Base class for all KLL emitters - TextEmitter for dealing with text file templates common/hid_dict.py - Slightly modified version of kll_lib/hid_dict.py common/id.py - Identification container classes - Used to indentify different types of elements used within the KLL language common/modifier.py - Container classes for animation and pixel change functions common/organization.py - Data structure merging container classes - Contains all the sub-datastructure classes as well - The Organization class handles the merge orchestration and expression insertion common/parse.py - Parsing rules for funcparserlib - Much of this file was taken from the original kll.py - Many changes to support the multi-stage processing and support KLL 0.5 common/position.py - Container class dealing with physical positions common/schedule.py - Container class dealing with scheduling and timing events common/stage.py - Contains ControlStage and main Stage classes * CompilerConfigurationStage * FileImportStage * PreprocessorStage * OperationClassificationStage * OperationSpecificsStage * OperationOrganizationStage * DataOrganziationStage * DataFinalizationStage * DataAnalysisStage * CodeGenerationStage * ReportGenerationStage - Each of these classes controls the life-cycle of each stage - If multi-threading is desired, it must be handled within the class * The next stage will not start until the current stage is finished - Errors are handled such that as many errors as possible are recorded before forcing an exit * The exit is handled at the end of each stage if necessary - Command-line arguments for each stage can be defined if necessary (they are given their own grouping) - Each stage can pull variables and functions from other stages if necessary using a name lookup * This means you don't have to worry about over-arching datastructures emitters/emitters.py - Container class for KLL emitters - Handles emitter setup and selection emitters/kiibohd/kiibohd.py - kiibohd .h file KLL emitter - Re-uses some backend code from the original KLL compiler funcparserlib/parser.py - Added debug mode control examples/assignment.kll examples/defaultMapExample.kll examples/example.kll examples/hhkbpro2.kll examples/leds.kll examples/mapping.kll examples/simple1.kll examples/simple2.kll examples/simpleExample.kll examples/state_scheduling.kll - Updating/Adding rules for new compiler and KLL 0.4 + KLL 0.5 support
7 년 전
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  1. #!/usr/bin/env python3
  2. '''
  3. KLL Data Organization
  4. '''
  5. # Copyright (C) 2016 by Jacob Alexander
  6. #
  7. # This file is free software: you can redistribute it and/or modify
  8. # it under the terms of the GNU General Public License as published by
  9. # the Free Software Foundation, either version 3 of the License, or
  10. # (at your option) any later version.
  11. #
  12. # This file is distributed in the hope that it will be useful,
  13. # but WITHOUT ANY WARRANTY; without even the implied warranty of
  14. # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15. # GNU General Public License for more details.
  16. #
  17. # You should have received a copy of the GNU General Public License
  18. # along with this file. If not, see <http://www.gnu.org/licenses/>.
  19. ### Imports ###
  20. import copy
  21. import re
  22. ### Decorators ###
  23. ## Print Decorator Variables
  24. ERROR = '\033[5;1;31mERROR\033[0m:'
  25. WARNING = '\033[5;1;33mWARNING\033[0m:'
  26. ansi_escape = re.compile(r'\x1b[^m]*m')
  27. ### Classes ###
  28. class Data:
  29. '''
  30. Base class for KLL datastructures
  31. '''
  32. # Debug output formatters
  33. debug_output = {
  34. 'add' : "\t\033[1;42;37m++\033[0m\033[1mADD KEY\033[1;42;37m++\033[0m \033[1m<==\033[0m {0}",
  35. 'app' : "\t\033[1;45;37m**\033[0m\033[1mAPP KEY\033[1;45;37m**\033[0m \033[1m<==\033[0m {0}",
  36. 'mod' : "\t\033[1;44;37m##\033[0m\033[1mMOD KEY\033[1;44;37m##\033[0m \033[1m<==\033[0m {0}",
  37. 'rem' : "\t\033[1;41;37m--\033[0m\033[1mREM KEY\033[1;41;37m--\033[0m \033[1m<==\033[0m {0}",
  38. 'drp' : "\t\033[1;43;37m@@\033[0m\033[1mDRP KEY\033[1;43;37m@@\033[0m \033[1m<==\033[0m {0}",
  39. 'dup' : "\t\033[1;46;37m!!\033[0m\033[1mDUP KEY\033[1;46;37m!!\033[0m \033[1m<==\033[0m {0}",
  40. }
  41. def __init__( self, parent ):
  42. '''
  43. Initialize datastructure
  44. @param parent: Parent organization, used to query data from other datastructures
  45. '''
  46. self.data = {}
  47. self.parent = parent
  48. def add_expression( self, expression, debug ):
  49. '''
  50. Add expression to data structure
  51. May have multiple keys to add for a given expression
  52. @param expression: KLL Expression (fully tokenized and parsed)
  53. @param debug: Enable debug output
  54. '''
  55. # Lookup unique keys for expression
  56. keys = expression.unique_keys()
  57. # Add/Modify expressions in datastructure
  58. for key, uniq_expr in keys:
  59. # Check which operation we are trying to do, add or modify
  60. if debug[0]:
  61. if key in self.data.keys():
  62. output = self.debug_output['mod'].format( key )
  63. else:
  64. output = self.debug_output['add'].format( key )
  65. print( debug[1] and output or ansi_escape.sub( '', output ) )
  66. self.data[ key ] = uniq_expr
  67. def merge( self, merge_in, debug ):
  68. '''
  69. Merge in the given datastructure to this datastructure
  70. This datastructure serves as the base.
  71. @param merge_in: Data structure from another organization to merge into this one
  72. @param debug: Enable debug out
  73. '''
  74. # The default case is just to add the expression in directly
  75. for key, kll_expression in merge_in.data.items():
  76. # Display key:expression being merged in
  77. if debug[0]:
  78. output = merge_in.elem_str( key, True )
  79. print( debug[1] and output or ansi_escape.sub( '', output ), end="" )
  80. self.add_expression( kll_expression, debug )
  81. def reduction( self ):
  82. '''
  83. Simplifies datastructure
  84. Most of the datastructures don't have a reduction. Just do nothing in this case.
  85. '''
  86. pass
  87. def elem_str( self, key, single=False ):
  88. '''
  89. Debug output for a single element
  90. @param key: Index to datastructure
  91. @param single: Setting to True will bold the key
  92. '''
  93. if single:
  94. return "\033[1;33m{0: <20}\033[0m \033[1;36;41m>\033[0m {1}\n".format( key, self.data[ key ] )
  95. else:
  96. return "{0: <20} \033[1;36;41m>\033[0m {1}\n".format( key, self.data[ key ] )
  97. def __repr__( self ):
  98. output = ""
  99. # Display sorted list of keys, along with the internal value
  100. for key in sorted( self.data ):
  101. output += self.elem_str( key )
  102. return output
  103. class MappingData( Data ):
  104. '''
  105. KLL datastructure for data mapping
  106. ScanCode trigger -> result
  107. USBCode trigger -> result
  108. Animation trigger -> result
  109. '''
  110. def add_expression( self, expression, debug ):
  111. '''
  112. Add expression to data structure
  113. May have multiple keys to add for a given expression
  114. Map expressions insert into the datastructure according to their operator.
  115. +Operators+
  116. : Add/Modify
  117. :+ Append
  118. :- Remove
  119. :: Lazy Add/Modify
  120. i: Add/Modify
  121. i:+ Append
  122. i:- Remove
  123. i:: Lazy Add/Modify
  124. The i or isolation operators are stored separately from the main ones.
  125. Each key is pre-pended with an i
  126. The :: or lazy operators act just like : operators, except that they will be ignore if the evaluation
  127. merge cannot resolve a ScanCode.
  128. @param expression: KLL Expression (fully tokenized and parsed)
  129. @param debug: Enable debug output
  130. '''
  131. # Lookup unique keys for expression
  132. keys = expression.unique_keys()
  133. # Add/Modify expressions in datastructure
  134. for key, uniq_expr in keys:
  135. # Determine which the expression operator
  136. operator = expression.operator
  137. # Except for the : operator, all others have delayed action
  138. # Meaning, they change behaviour depending on how Contexts are merged
  139. # This means we can't simplify yet
  140. # In addition, :+ and :- are stackable, which means each key has a list of expressions
  141. # We append the operator to differentiate between the different types of delayed operations
  142. key = "{0}{1}".format( operator, key )
  143. # Determine if key exists already
  144. exists = key in self.data.keys()
  145. # Add/Modify
  146. if operator in [':', '::', 'i:', 'i::']:
  147. debug_tag = exists and 'mod' or 'add'
  148. # Append/Remove
  149. else:
  150. # Check to make sure we haven't already appended expression
  151. # Use the string representation to do the comparison (general purpose)
  152. if exists and "{0}".format( uniq_expr ) in [ "{0}".format( elem ) for elem in self.data[ key ] ]:
  153. debug_tag = 'dup'
  154. # Append
  155. elif operator in [':+', 'i:+']:
  156. debug_tag = 'app'
  157. # Remove
  158. else:
  159. debug_tag = 'rem'
  160. # Debug output
  161. if debug[0]:
  162. output = self.debug_output[ debug_tag ].format( key )
  163. print( debug[1] and output or ansi_escape.sub( '', output ) )
  164. # Don't append if a duplicate
  165. if debug_tag == 'dup':
  166. continue
  167. # Append, rather than replace
  168. if operator in [':+', ':-', 'i:+', 'i:-']:
  169. if exists:
  170. self.data[ key ].append( uniq_expr )
  171. # Create initial list
  172. else:
  173. self.data[ key ] = [ uniq_expr ]
  174. else:
  175. self.data[ key ] = [ uniq_expr ]
  176. def set_interconnect_id( self, interconnect_id, triggers ):
  177. '''
  178. Traverses the sequence of combo of identifiers to set the interconnect_id
  179. '''
  180. for sequence in triggers:
  181. for combo in sequence:
  182. for identifier in combo:
  183. identifier.interconnect_id = interconnect_id
  184. def merge( self, merge_in, debug ):
  185. '''
  186. Merge in the given datastructure to this datastructure
  187. This datastructure serves as the base.
  188. Map expressions merge differently than insertions.
  189. +Operators+
  190. : Add/Modify - Replace
  191. :+ Append - Add
  192. :- Remove - Remove
  193. :: Lazy Add/Modify - Replace if found, otherwise drop
  194. i: Add/Modify - Replace
  195. i:+ Append - Add
  196. i:- Remove - Remove
  197. i:: Lazy Add/Modify - Replace if found, otherwise drop
  198. @param merge_in: Data structure from another organization to merge into this one
  199. @param debug: Enable debug out
  200. '''
  201. # Check what the current interconnectId is
  202. # If not set, we set to 0 (default)
  203. # We use this to calculate the scancode during the DataAnalysisStage
  204. interconnect_id = 0
  205. if 'interconnectId' in self.parent.variable_data.data.keys():
  206. interconnect_id = self.parent.variable_data.data['interconnectId']
  207. # Sort different types of keys
  208. cur_keys = merge_in.data.keys()
  209. # Lazy Set ::
  210. lazy_keys = [ key for key in cur_keys if key[0:2] == '::' or key[0:3] == 'i::' ]
  211. cur_keys = list( set( cur_keys ) - set( lazy_keys ) )
  212. # Append :+
  213. append_keys = [ key for key in cur_keys if key[0:2] == ':+' or key[0:3] == 'i:+' ]
  214. cur_keys = list( set( cur_keys ) - set( append_keys ) )
  215. # Remove :-
  216. remove_keys = [ key for key in cur_keys if key[0:2] == ':-' or key[0:3] == 'i:-' ]
  217. cur_keys = list( set( cur_keys ) - set( remove_keys ) )
  218. # Set :
  219. # Everything left is just a set
  220. set_keys = cur_keys
  221. # First process the :: (or lazy) operators
  222. # We need to read into this datastructure and apply those first
  223. # Otherwise we may get undesired behaviour
  224. for key in lazy_keys:
  225. # Display key:expression being merged in
  226. if debug[0]:
  227. output = merge_in.elem_str( key, True )
  228. print( debug[1] and output or ansi_escape.sub( '', output ), end="" )
  229. # Construct target key
  230. target_key = key[0] == 'i' and "i{0}".format( key[2:] ) or key[1:]
  231. # If target key exists, replace
  232. if target_key in self.data.keys():
  233. debug_tag = 'mod'
  234. else:
  235. debug_tag = 'drp'
  236. # Debug output
  237. if debug[0]:
  238. output = self.debug_output[ debug_tag ].format( key )
  239. print( debug[1] and output or ansi_escape.sub( '', output ) )
  240. # Only replace
  241. if debug_tag == 'mod':
  242. self.data[ target_key ] = merge_in.data[ key ]
  243. # Then apply : assignment operators
  244. for key in set_keys:
  245. # Display key:expression being merged in
  246. if debug[0]:
  247. output = merge_in.elem_str( key, True )
  248. print( debug[1] and output or ansi_escape.sub( '', output ), end="" )
  249. # Construct target key
  250. target_key = key
  251. # Indicate if add or modify
  252. if target_key in self.data.keys():
  253. debug_tag = 'mod'
  254. else:
  255. debug_tag = 'add'
  256. # Debug output
  257. if debug[0]:
  258. output = self.debug_output[ debug_tag ].format( key )
  259. print( debug[1] and output or ansi_escape.sub( '', output ) )
  260. # Set into new datastructure regardless
  261. self.data[ target_key ] = merge_in.data[ key ]
  262. # Only the : is used to set ScanCodes
  263. # We need to set the interconnect_id just in case the base context has it set
  264. # and in turn influence the new context as well
  265. # This must be done during the merge
  266. for elem in self.data[ target_key ]:
  267. if elem.type == 'ScanCode':
  268. self.set_interconnect_id( interconnect_id, elem.triggers )
  269. # Now apply append operations
  270. for key in append_keys:
  271. # Display key:expression being merged in
  272. if debug[0]:
  273. output = merge_in.elem_str( key, True )
  274. print( debug[1] and output or ansi_escape.sub( '', output ), end="" )
  275. # Construct target key
  276. target_key = key[0] == 'i' and "i:{0}".format( key[3:] ) or ":{0}".format( key[2:] )
  277. # Alwyays appending
  278. debug_tag = 'app'
  279. # Debug output
  280. if debug[0]:
  281. output = self.debug_output[ debug_tag ].format( key )
  282. print( debug[1] and output or ansi_escape.sub( '', output ) )
  283. # Extend list if it exists
  284. if target_key in self.data.keys():
  285. self.data[ target_key ].extend( merge_in.data[ key ] )
  286. else:
  287. self.data[ target_key ] = merge_in.data[ key ]
  288. # Finally apply removal operations to this datastructure
  289. # If the target removal doesn't exist, ignore silently (show debug message)
  290. for key in remove_keys:
  291. # Display key:expression being merged in
  292. if debug[0]:
  293. output = merge_in.elem_str( key, True )
  294. print( debug[1] and output or ansi_escape.sub( '', output ), end="" )
  295. # Construct target key
  296. target_key = key[0] == 'i' and "i:{0}".format( key[3:] ) or ":{0}".format( key[2:] )
  297. # Drop right away if target datastructure doesn't have target key
  298. if target_key not in self.data.keys():
  299. debug_tag = 'drp'
  300. # Debug output
  301. if debug[0]:
  302. output = self.debug_output[ debug_tag ].format( key )
  303. print( debug[1] and output or ansi_escape.sub( '', output ) )
  304. continue
  305. # Compare expressions to be removed with the current set
  306. # Use strings to compare
  307. remove_expressions = [ "{0}".format( expr ) for expr in merge_in.data[ key ] ]
  308. current_expressions = [ ( "{0}".format( expr ), expr ) for expr in self.data[ target_key ] ]
  309. for string, expr in current_expressions:
  310. debug_tag = 'drp'
  311. # Check if an expression matches
  312. if string in remove_expressions:
  313. debug_tag = 'rem'
  314. # Debug output
  315. if debug[0]:
  316. output = self.debug_output[ debug_tag ].format( key )
  317. print( debug[1] and output or ansi_escape.sub( '', output ) )
  318. # Remove if found
  319. if debug_tag == 'rem':
  320. self.data[ target_key ] = [ value for value in self.data.values() if value != expr ]
  321. def reduction( self ):
  322. '''
  323. Simplifies datastructure
  324. Used to replace all trigger HIDCode(USBCode)s with ScanCodes
  325. NOTE: Make sure to create a new MergeContext before calling this as you lose data and prior context
  326. '''
  327. scan_code_lookup = {}
  328. # Build dictionary of single ScanCodes first
  329. for key, expr in self.data.items():
  330. if expr[0].elems()[0] == 1 and expr[0].triggers[0][0][0].type == 'ScanCode':
  331. scan_code_lookup[ key ] = expr
  332. # Using this dictionary, replace all the trigger USB codes
  333. new_data = copy.copy( scan_code_lookup )
  334. # 1) Single USB Codes trigger results will replace the original ScanCode result
  335. # 2)
  336. #TODO
  337. #print("YAY")
  338. #print( scan_code_lookup )
  339. class AnimationData( Data ):
  340. '''
  341. KLL datastructure for Animation configuration
  342. Animation -> modifiers
  343. '''
  344. class AnimationFrameData( Data ):
  345. '''
  346. KLL datastructure for Animation Frame configuration
  347. Animation -> Pixel Settings
  348. '''
  349. class CapabilityData( Data ):
  350. '''
  351. KLL datastructure for Capability mapping
  352. Capability -> C Function/Identifier
  353. '''
  354. class DefineData( Data ):
  355. '''
  356. KLL datastructure for Define mapping
  357. Variable -> C Define/Identifier
  358. '''
  359. class PixelChannelData( Data ):
  360. '''
  361. KLL datastructure for Pixel Channel mapping
  362. Pixel -> Channels
  363. '''
  364. class PixelPositionData( Data ):
  365. '''
  366. KLL datastructure for Pixel Position mapping
  367. Pixel -> Physical Location
  368. '''
  369. class ScanCodePositionData( Data ):
  370. '''
  371. KLL datastructure for ScanCode Position mapping
  372. ScanCode -> Physical Location
  373. '''
  374. class VariableData( Data ):
  375. '''
  376. KLL datastructure for Variables and Arrays
  377. Variable -> Data
  378. Array -> Data
  379. '''
  380. class Organization:
  381. '''
  382. Container class for KLL datastructures
  383. The purpose of these datastructures is to symbolically store at first, and slowly solve/deduplicate expressions.
  384. Since the order in which the merges occurs matters, this involves a number of intermediate steps.
  385. '''
  386. def __init__( self ):
  387. '''
  388. Intialize data structure
  389. '''
  390. # Setup each of the internal sub-datastructures
  391. self.animation_data = AnimationData( self )
  392. self.animation_frame_data = AnimationFrameData( self )
  393. self.capability_data = CapabilityData( self )
  394. self.define_data = DefineData( self )
  395. self.mapping_data = MappingData( self )
  396. self.pixel_channel_data = PixelChannelData( self )
  397. self.pixel_position_data = PixelPositionData( self )
  398. self.scan_code_position_data = ScanCodePositionData( self )
  399. self.variable_data = VariableData( self )
  400. # Expression to Datastructure mapping
  401. self.data_mapping = {
  402. 'AssignmentExpression' : {
  403. 'Array' : self.variable_data,
  404. 'Variable' : self.variable_data,
  405. },
  406. 'DataAssociationExpression' : {
  407. 'Animation' : self.animation_data,
  408. 'AnimationFrame' : self.animation_frame_data,
  409. 'PixelPosition' : self.pixel_position_data,
  410. 'ScanCodePosition' : self.scan_code_position_data,
  411. },
  412. 'MapExpression' : {
  413. 'ScanCode' : self.mapping_data,
  414. 'USBCode' : self.mapping_data,
  415. 'Animation' : self.mapping_data,
  416. 'PixelChannel' : self.pixel_channel_data,
  417. },
  418. 'NameAssociationExpression' : {
  419. 'Capability' : self.capability_data,
  420. 'Define' : self.define_data,
  421. },
  422. }
  423. def stores( self ):
  424. '''
  425. Returns list of sub-datastructures
  426. '''
  427. return [
  428. self.animation_data,
  429. self.animation_frame_data,
  430. self.capability_data,
  431. self.define_data,
  432. self.mapping_data,
  433. self.pixel_channel_data,
  434. self.pixel_position_data,
  435. self.scan_code_position_data,
  436. self.variable_data,
  437. ]
  438. def add_expression( self, expression, debug ):
  439. '''
  440. Add expression to datastructure
  441. Will automatically determine which type of expression and place in the relevant store
  442. @param expression: KLL Expression (fully tokenized and parsed)
  443. @param debug: Enable debug output
  444. '''
  445. # Determine type of of Expression
  446. expression_type = expression.__class__.__name__
  447. # Determine Expression Subtype
  448. expression_subtype = expression.type
  449. # Locate datastructure
  450. data = self.data_mapping[ expression_type ][ expression_subtype ]
  451. # Debug output
  452. if debug[0]:
  453. output = "\t\033[4m{0}\033[0m".format( data.__class__.__name__ )
  454. print( debug[1] and output or ansi_escape.sub( '', output ) )
  455. # Add expression to determined datastructure
  456. data.add_expression( expression, debug )
  457. def merge( self, merge_in, debug ):
  458. '''
  459. Merge in the given organization to this organization
  460. This organization serves as the base.
  461. @param merge_in: Organization to merge into this one
  462. @param debug: Enable debug out
  463. '''
  464. # Merge each of the sub-datastructures
  465. for this, that in zip( self.stores(), merge_in.stores() ):
  466. this.merge( that, debug )
  467. def reduction( self ):
  468. '''
  469. Simplifies datastructure
  470. NOTE: This will remove data, therefore, context is lost
  471. '''
  472. for store in self.stores():
  473. store.reduction()
  474. def __repr__( self ):
  475. return "{0}".format( self.stores() )