def xml_to_py(trees, fortran_file):
translator = XML_to_JSON_translator()
output_dict = translator.analyze(trees)
comments = get_comments(fortran_file)
output_dict["comments"] = comments
# print_unhandled_tags() was originally intended to alert us to program
# constructs we were not handling. It isn't clear we actually use this
# so I'm commenting out this call for now. Eventually this code (and all
# the code that keeps track of unhandled tags) should go away.
# --SKD 06/2019
#translator.print_unhandled_tags()
return output_dict
def generate_outputdict(rectified_tree, preprocessed_fortran_file) -> Dict:
"""This function generates a dictionary of ast and generates a dict
with XML generated by translate.py and comments obtained with
get_comments.py.
Args:
rectified_tree (:obj: 'ET'): An object of rectified XML.
preprocessed_fortran_file (str): Path to preprocessed fortran file
Returns:
dict: A dictionary of XML generated by translate.py
"""
output_dictionary = translate.xml_to_py([rectified_tree])
output_dictionary["comments"] = get_comments.get_comments(
preprocessed_fortran_file)
return output_dictionary
def get_python_source(
original_fortran_file) -> Tuple[str, str, str, str, Dict]:
stem = original_fortran_file.stem
preprocessed_fortran_file = stem + "_preprocessed.f"
lambdas_filename = stem + "_lambdas.py"
json_filename = stem + ".json"
python_filename = stem + ".py"
with open(original_fortran_file, "r") as f:
inputLines = f.readlines()
with open(preprocessed_fortran_file, "w") as f:
f.write(preprocessor.process(inputLines))
xml_string = sp.run(
[
"java",
"fortran.ofp.FrontEnd",
"--class",
"fortran.ofp.XMLPrinter",
"--verbosity",
"0",
preprocessed_fortran_file,
],
stdout=sp.PIPE,
).stdout
trees = [ET.fromstring(xml_string)]
comments = get_comments.get_comments(preprocessed_fortran_file)
os.remove(preprocessed_fortran_file)
xml_to_json_translator = translate.XMLToJSONTranslator()
mode_mapper_tree = ET.fromstring(xml_string)
generator = mod_index_generator.moduleGenerator()
mode_mapper_dict = generator.analyze(mode_mapper_tree)
outputDict = xml_to_json_translator.analyze(trees, comments)
pySrc = pyTranslate.create_python_source_list(outputDict)[0][0]
return pySrc, lambdas_filename, json_filename, python_filename, mode_mapper_dict
def from_fortran_file(cls, fortran_file: str, tmpdir: str = "."):
"""Builds GrFN object from a Fortran program."""
stem = Path(fortran_file).stem
if tmpdir == "." and "/" in fortran_file:
tmpdir = Path(fortran_file).parent
preprocessed_fortran_file = f"{tmpdir}/{stem}_preprocessed.f"
lambdas_path = f"{tmpdir}/{stem}_lambdas.py"
json_filename = stem + ".json"
with open(fortran_file, "r") as f:
inputLines = f.readlines()
with open(preprocessed_fortran_file, "w") as f:
f.write(preprocessor.process(inputLines))
xml_string = sp.run(
[
"java",
"fortran.ofp.FrontEnd",
"--class",
"fortran.ofp.XMLPrinter",
"--verbosity",
"0",
preprocessed_fortran_file,
],
stdout=sp.PIPE,
).stdout
trees = [ET.fromstring(xml_string)]
comments = get_comments.get_comments(preprocessed_fortran_file)
os.remove(preprocessed_fortran_file)
xml_to_json_translator = translate.XMLToJSONTranslator()
outputDict = xml_to_json_translator.analyze(trees, comments)
pySrc = pyTranslate.create_python_source_list(outputDict)[0][0]
G = cls.from_python_src(pySrc, lambdas_path, json_filename, stem)
return G
def processCode():
form = MyForm()
code = form.source_code.data
app.code = code
if code == "":
return render_template("index.html", form=form)
lines = [
line.replace("\r", "") + "\n"
for line in [line for line in code.split("\n")] if line != ""
]
filename = f"input_code_{str(uuid4())}"
input_code_tmpfile = f"/tmp/automates/{filename}.f"
with open(input_code_tmpfile, "w") as f:
f.write(preprocessor.process(lines))
xml_string = sp.run(
[
"java",
"fortran.ofp.FrontEnd",
"--class",
"fortran.ofp.XMLPrinter",
"--verbosity",
"0",
input_code_tmpfile,
],
stdout=sp.PIPE,
).stdout
trees = [ET.fromstring(xml_string)]
comments = get_comments.get_comments(input_code_tmpfile)
outputDict = translate.XMLToJSONTranslator().analyze(trees, comments)
pySrc = pyTranslate.create_python_source_list(outputDict)[0][0]
lambdas = f"{filename}_lambdas"
lambdas_path = f"/tmp/automates/{lambdas}.py"
G = GroundedFunctionNetwork.from_python_src(pySrc,
lambdas_path,
f"{filename}.json",
filename,
save_file=False)
graphJSON, layout = get_grfn_surface_plot(G)
scopeTree_elementsJSON = to_cyjs_grfn(G)
CAG = G.to_CAG()
program_analysis_graph_elementsJSON = to_cyjs_cag(CAG)
os.remove(input_code_tmpfile)
os.remove(f"/tmp/automates/{lambdas}.py")
return render_template(
"index.html",
form=form,
code=app.code,
python_code=highlight(pySrc, PYTHON_LEXER, PYTHON_FORMATTER),
scopeTree_elementsJSON=scopeTree_elementsJSON,
graphJSON=graphJSON,
layout=layout,
program_analysis_graph_elementsJSON=program_analysis_graph_elementsJSON,
)
"-g",
"--gen",
nargs="*",
help=
"Pickled version of routines for which dependency graphs should be generated",
)
parser.add_argument(
"-f",
"--files",
nargs="+",
required=True,
help="A list of AST files in XML format to analyze",
)
parser.add_argument("-i",
"--input",
nargs="*",
help="Original Fortran Source code file.")
args = parser.parse_args(sys.argv[1:])
fortranFile = args.input[0]
pickleFile = args.gen[0]
trees = get_trees(args.files)
comments = get_comments(fortranFile)
translator = XMLToJSONTranslator()
outputDict = translator.analyze(trees, comments)
translator.print_unhandled_tags()
with open(pickleFile, "wb") as f:
pickle.dump(outputDict, f)