Mercurial > hg > orthanc-stone
view Resources/CodeGeneration/stonegentool.py @ 876:580dd82e13f5 am-dev
added GetApproximateMemoryUsage
author | Alain Mazy <alain@mazy.be> |
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date | Wed, 03 Jul 2019 10:15:29 +0200 |
parents | 1b47f17863ba |
children |
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import json import yaml import re import os import sys from jinja2 import Template from io import StringIO import time import datetime import yamlloader """ 1 2 3 4 5 6 7 12345678901234567890123456789012345678901234567890123456789012345678901234567890 """ # see https://stackoverflow.com/a/2504457/2927708 def trim(docstring): if not docstring: return '' # Convert tabs to spaces (following the normal Python rules) # and split into a list of lines: lines = docstring.expandtabs().splitlines() # Determine minimum indentation (first line doesn't count): indent = sys.maxsize for line in lines[1:]: stripped = line.lstrip() if stripped: indent = min(indent, len(line) - len(stripped)) # Remove indentation (first line is special): trimmed = [lines[0].strip()] if indent < sys.maxsize: for line in lines[1:]: trimmed.append(line[indent:].rstrip()) # Strip off trailing and leading blank lines: while trimmed and not trimmed[-1]: trimmed.pop() while trimmed and not trimmed[0]: trimmed.pop(0) # Return a single string: return '\n'.join(trimmed) class JsonHelpers: """A set of utilities to perform JSON operations""" @staticmethod def removeCommentsFromJsonContent(string): """ Remove comments from a JSON file Comments are not allowed in JSON but, i.e., Orthanc configuration files contains C++ like comments that we need to remove before python can parse the file """ # remove all occurrence streamed comments (/*COMMENT */) from string string = re.sub(re.compile("/\*.*?\*/", re.DOTALL), "", string) # remove all occurrence singleline comments (//COMMENT\n ) from string string = re.sub(re.compile("//.*?\n"), "", string) return string @staticmethod def loadJsonWithComments(path): """ Reads a JSON file that may contain C++ like comments """ with open(path, "r") as fp: fileContent = fp.read() fileContent = JsonHelpers.removeCommentsFromJsonContent(fileContent) return json.loads(fileContent) class FieldDefinition: def __init__(self, name: str, type: str, defaultValue: str): self.name = name self.type = type self.defaultValue = defaultValue @staticmethod def fromKeyValue(key: str, value: str): if "=" in value: splitValue = value.split(sep="=") type = splitValue[0].strip(" ") defaultValue = splitValue[1].strip(" ") else: type = value defaultValue = None return FieldDefinition(name = key, type = type, defaultValue = defaultValue) def LoadSchemaFromJson(filePath): return JsonHelpers.loadJsonWithComments(filePath) def CanonToCpp(canonicalTypename): # C++: prefix map vector and string with std::map, std::vector and # std::string # replace int32... by int32_t... # replace float32 by float # replace float64 by double retVal = canonicalTypename retVal = retVal.replace("map", "std::map") retVal = retVal.replace("vector", "std::vector") retVal = retVal.replace("set", "std::set") retVal = retVal.replace("string", "std::string") #uint32 and uint64 are handled by int32 and uint32 (because search and replace are done as partial words) retVal = retVal.replace("int32", "int32_t") retVal = retVal.replace("int64", "int64_t") retVal = retVal.replace("float32", "float") retVal = retVal.replace("float64", "double") retVal = retVal.replace("json", "Json::Value") return retVal def CanonToTs(canonicalTypename): # TS: replace vector with Array and map with Map # string remains string # replace int32... by number # replace float32... by number retVal = canonicalTypename retVal = retVal.replace("map", "Map") retVal = retVal.replace("vector", "Array") retVal = retVal.replace("set", "Set") retVal = retVal.replace("uint32", "number") retVal = retVal.replace("uint64", "number") retVal = retVal.replace("int32", "number") retVal = retVal.replace("int64", "number") retVal = retVal.replace("float32", "number") retVal = retVal.replace("float64", "number") retVal = retVal.replace("bool", "boolean") retVal = retVal.replace("json", "Object") return retVal def NeedsTsConstruction(enums, tsType): if tsType == 'boolean': return False elif tsType == 'number': return False elif tsType == 'string': return False else: enumNames = [] for enum in enums: enumNames.append(enum['name']) if tsType in enumNames: return False return True def NeedsCppConstruction(canonTypename): return False def DefaultValueToTs(enums, field:FieldDefinition): tsType = CanonToTs(field.type) enumNames = [] for enum in enums: enumNames.append(enum['name']) if tsType in enumNames: return tsType + "." + field.defaultValue else: return field.defaultValue def DefaultValueToCpp(root, enums, field:FieldDefinition): cppType = CanonToCpp(field.type) enumNames = [] for enum in enums: enumNames.append(enum['name']) if cppType in enumNames: return root + "::" + cppType + "_" + field.defaultValue else: return field.defaultValue def RegisterTemplateFunction(template,func): """Makes a function callable by a jinja2 template""" template.globals[func.__name__] = func return func def MakeTemplate(templateStr): template = Template(templateStr) RegisterTemplateFunction(template,CanonToCpp) RegisterTemplateFunction(template,CanonToTs) RegisterTemplateFunction(template,NeedsTsConstruction) RegisterTemplateFunction(template,NeedsCppConstruction) RegisterTemplateFunction(template, DefaultValueToTs) RegisterTemplateFunction(template, DefaultValueToCpp) return template def MakeTemplateFromFile(templateFileName): with open(templateFileName, "r") as templateFile: templateFileContents = templateFile.read() return MakeTemplate(templateFileContents) def EatToken(sentence): """splits "A,B,C" into "A" and "B,C" where A, B and C are type names (including templates) like "int32", "TotoTutu", or "map<map<int32,vector<string>>,map<string,int32>>" """ if sentence.count("<") != sentence.count(">"): raise Exception( "Error in the partial template type list " + str(sentence) + "." + " The number of < and > do not match!" ) # the template level we're currently in templateLevel = 0 for i in range(len(sentence)): if (sentence[i] == ",") and (templateLevel == 0): return (sentence[0:i], sentence[i + 1 :]) elif sentence[i] == "<": templateLevel += 1 elif sentence[i] == ">": templateLevel -= 1 return (sentence, "") def SplitListOfTypes(typename): """Splits something like vector<string>,int32,map<string,map<string,int32>> in: - vector<string> - int32 map<string,map<string,int32>> This is not possible with a regex so """ stillStuffToEat = True tokenList = [] restOfString = typename while stillStuffToEat: firstToken, restOfString = EatToken(restOfString) tokenList.append(firstToken) if restOfString == "": stillStuffToEat = False return tokenList templateRegex = \ re.compile(r"([a-zA-Z0-9_]*[a-zA-Z0-9_]*)<([a-zA-Z0-9_,:<>]+)>") def ParseTemplateType(typename): """ If the type is a template like "SOMETHING<SOME<THING,EL<SE>>>", then it returns (true,"SOMETHING","SOME<THING,EL<SE>>") otherwise it returns (false,"","")""" # let's remove all whitespace from the type # split without argument uses any whitespace string as separator # (space, tab, newline, return or formfeed) typename = "".join(typename.split()) matches = templateRegex.match(typename) if matches == None: return (False, "", []) else: m = matches assert len(m.groups()) == 2 # we need to split with the commas that are outside of the # defined types. Simply splitting at commas won't work listOfDependentTypes = SplitListOfTypes(m.group(2)) return (True, m.group(1), listOfDependentTypes) def GetStructFields(struct): """This filters out the special metadata key from the struct fields""" return [k for k in struct.keys() if k != '__handler'] def ComputeOrderFromTypeTree( ancestors, genOrder, shortTypename, schema): if shortTypename in ancestors: raise Exception( "Cyclic dependency chain found: the last of " + str(ancestors) + + " depends on " + str(shortTypename) + " that is already in the list." ) if not (shortTypename in genOrder): (isTemplate, _, dependentTypenames) = ParseTemplateType(shortTypename) if isTemplate: # if it is a template, it HAS dependent types... They can be # anything (primitive, collection, enum, structs..). # Let's process them! for dependentTypename in dependentTypenames: # childAncestors = ancestors.copy() NO TEMPLATE ANCESTOR!!! # childAncestors.append(typename) ComputeOrderFromTypeTree( ancestors, genOrder, dependentTypename, schema ) else: # If it is not template, we are only interested if it is a # dependency that we must take into account in the dep graph, # i.e., a struct. if IsShortStructType(shortTypename, schema): struct = schema[GetLongTypename(shortTypename, schema)] # The keys in the struct dict are the member names # The values in the struct dict are the member types if struct: # we reach this if struct is not None AND not empty for field in GetStructFields(struct): # we fill the chain of dependent types (starting here) ancestors.append(shortTypename) ComputeOrderFromTypeTree( ancestors, genOrder, struct[field], schema) # don't forget to restore it! ancestors.pop() # now we're pretty sure our dependencies have been processed, # we can start marking our code for generation (it might # already have been done if someone referenced us earlier) if not shortTypename in genOrder: genOrder.append(shortTypename) # +-----------------------+ # | Utility functions | # +-----------------------+ def IsShortStructType(typename, schema): fullStructName = "struct " + typename return (fullStructName in schema) def GetLongTypename(shortTypename, schema): if shortTypename.startswith("enum "): raise RuntimeError('shortTypename.startswith("enum "):') enumName = "enum " + shortTypename isEnum = enumName in schema if shortTypename.startswith("struct "): raise RuntimeError('shortTypename.startswith("struct "):') structName = "struct " + shortTypename isStruct = ("struct " + shortTypename) in schema if isEnum and isStruct: raise RuntimeError('Enums and structs cannot have the same name') if isEnum: return enumName if isStruct: return structName def IsTypename(fullName): return (fullName.startswith("enum ") or fullName.startswith("struct ")) def IsEnumType(fullName): return fullName.startswith("enum ") def IsStructType(fullName): return fullName.startswith("struct ") def GetShortTypename(fullTypename): if fullTypename.startswith("struct "): return fullTypename[7:] elif fullTypename.startswith("enum"): return fullTypename[5:] else: raise RuntimeError \ ('fullTypename should start with either "struct " or "enum "') def CheckSchemaSchema(schema): if not "rootName" in schema: raise Exception("schema lacks the 'rootName' key") for name in schema.keys(): if (not IsEnumType(name)) and (not IsStructType(name)) and \ (name != 'rootName'): raise RuntimeError \ ('Type "' + str(name) + '" should start with "enum " or "struct "') # TODO: check enum fields are unique (in whole namespace) # TODO: check struct fields are unique (in each struct) # TODO: check that in the source schema, there are spaces after each colon nonTypeKeys = ['rootName'] def GetTypesInSchema(schema): """Returns the top schema keys that are actual type names""" typeList = [k for k in schema if k not in nonTypeKeys] return typeList # +-----------------------+ # | Main processing logic | # +-----------------------+ def ComputeRequiredDeclarationOrder(schema): # sanity check CheckSchemaSchema(schema) # we traverse the type dependency graph and we fill a queue with # the required struct types, in a bottom-up fashion, to compute # the declaration order # The genOrder list contains the struct full names in the order # where they must be defined. # We do not care about the enums here... They do not depend upon # anything and we'll handle them, in their original declaration # order, at the start genOrder = [] for fullName in GetTypesInSchema(schema): if IsStructType(fullName): realName = GetShortTypename(fullName) ancestors = [] ComputeOrderFromTypeTree(ancestors, genOrder, realName, schema) return genOrder def GetStructFields(fieldDict): """Returns the regular (non __handler) struct fields""" # the following happens for empty structs if fieldDict == None: return fieldDict ret = {} for k,v in fieldDict.items(): if k != "__handler": ret[k] = FieldDefinition.fromKeyValue(k, v) if k.startswith("__") and k != "__handler": raise RuntimeError("Fields starting with __ (double underscore) are reserved names!") return ret def GetStructMetadata(fieldDict): """Returns the __handler struct fields (there are default values that can be overridden by entries in the schema Not tested because it's a fail-safe: if something is broken in this, dependent projects will not build.""" metadataDict = {} metadataDict['handleInCpp'] = False metadataDict['handleInTypescript'] = False if fieldDict != None: for k,v in fieldDict.items(): if k.startswith("__") and k != "__handler": raise RuntimeError("Fields starting with __ (double underscore) are reserved names") if k == "__handler": if type(v) == list: for i in v: if i == "cpp": metadataDict['handleInCpp'] = True elif i == "ts": metadataDict['handleInTypescript'] = True else: raise RuntimeError("Error in schema. Allowed values for __handler are \"cpp\" or \"ts\"") elif type(v) == str: if v == "cpp": metadataDict['handleInCpp'] = True elif v == "ts": metadataDict['handleInTypescript'] = True else: raise RuntimeError("Error in schema. Allowed values for __handler are \"cpp\" or \"ts\" (or a list of both)") else: raise RuntimeError("Error in schema. Allowed values for __handler are \"cpp\" or \"ts\" (or a list of both)") return metadataDict def ProcessSchema(schema, genOrder): # sanity check CheckSchemaSchema(schema) # let's doctor the schema to clean it up a bit # order DOES NOT matter for enums, even though it's a list enums = [] for fullName in schema.keys(): if IsEnumType(fullName): # convert "enum Toto" to "Toto" typename = GetShortTypename(fullName) enum = {} enum['name'] = typename assert(type(schema[fullName]) == list) enum['fields'] = schema[fullName] # must be a list enums.append(enum) # now that the order has been established, we actually store\ # the structs in the correct order # the structs are like: # example = [ # { # "name": "Message1", # "fields": { # "someMember":"int32", # "someOtherMember":"vector<string>" # } # }, # { # "name": "Message2", # "fields": { # "someMember":"int32", # "someOtherMember22":"vector<Message1>" # } # } # ] structs = [] for i in range(len(genOrder)): # this is already the short name typename = genOrder[i] fieldDict = schema["struct " + typename] struct = {} struct['name'] = typename struct['fields'] = GetStructFields(fieldDict) struct['__meta__'] = GetStructMetadata(fieldDict) structs.append(struct) templatingDict = {} templatingDict['enums'] = enums templatingDict['structs'] = structs templatingDict['rootName'] = schema['rootName'] return templatingDict # +-----------------------+ # | Write to files | # +-----------------------+ # def WriteStreamsToFiles(rootName: str, genc: Dict[str, StringIO]) \ # -> None: # pass def LoadSchema(fn): # latin-1 is a trick, when we do NOT care about NON-ascii chars but # we wish to avoid using a decoding error handler # (see http://python-notes.curiousefficiency.org/en/latest/python3/text_file_processing.html#files-in-an-ascii-compatible-encoding-best-effort-is-acceptable) # TL;DR: all 256 values are mapped to characters in latin-1 so the file # contents never cause an error. with open(fn, 'r', encoding='latin-1') as f: schemaText = f.read() assert(type(schemaText) == str) return LoadSchemaFromString(schemaText = schemaText) def LoadSchemaFromString(schemaText:str): # ensure there is a space after each colon. Otherwise, dicts could be # erroneously recognized as an array of strings containing ':' for i in range(len(schemaText)-1): ch = schemaText[i] nextCh = schemaText[i+1] if ch == ':': if not (nextCh == ' ' or nextCh == '\n'): lineNumber = schemaText.count("\n",0,i) + 1 raise RuntimeError("Error at line " + str(lineNumber) + " in the schema: colons must be followed by a space or a newline!") schema = yaml.load(schemaText, Loader = yamlloader.ordereddict.SafeLoader) return schema def GetTemplatingDictFromSchemaFilename(fn): return GetTemplatingDictFromSchema(LoadSchema(fn)) def GetTemplatingDictFromSchema(schema): genOrder = ComputeRequiredDeclarationOrder(schema) templatingDict = ProcessSchema(schema, genOrder) currentDT = datetime.datetime.now() templatingDict['currentDatetime'] = str(currentDT) return templatingDict # +-----------------------+ # | ENTRY POINT | # +-----------------------+ def Process(schemaFile, outDir): tdico = GetTemplatingDictFromSchemaFilename(schemaFile) tsTemplateFile = \ os.path.join(os.path.dirname(__file__), 'template.in.ts.j2') template = MakeTemplateFromFile(tsTemplateFile) renderedTsCode = template.render(**tdico) outputTsFile = os.path.join( \ outDir,str(tdico['rootName']) + "_generated.ts") with open(outputTsFile,"wt",encoding='utf8') as outFile: outFile.write(renderedTsCode) cppTemplateFile = \ os.path.join(os.path.dirname(__file__), 'template.in.h.j2') template = MakeTemplateFromFile(cppTemplateFile) renderedCppCode = template.render(**tdico) outputCppFile = os.path.join( \ outDir, str(tdico['rootName']) + "_generated.hpp") with open(outputCppFile,"wt",encoding='utf8') as outFile: outFile.write(renderedCppCode) if __name__ == "__main__": import argparse parser = argparse.ArgumentParser( usage="""stonegentool.py [-h] [-o OUT_DIR] [-v] input_schema EXAMPLE: python stonegentool.py -o "generated_files/" """ + """ "mainSchema.yaml,App Specific Commands.json" """ ) parser.add_argument("input_schema", type=str, \ help="path to the schema file") parser.add_argument( "-o", "--out_dir", type=str, default=".", help="""path of the directory where the files will be generated. Default is current working folder""", ) parser.add_argument( "-v", "--verbosity", action="count", default=0, help="""increase output verbosity (0 == errors only, 1 == some verbosity, 2 == nerd mode""", ) args = parser.parse_args() schemaFile = args.input_schema outDir = args.out_dir Process(schemaFile, outDir)