🎉 successful parsing grammar for jobshop data

- now using arpeggio as a parsing lib

requirements.txt

@@ -1,2 +1,3 @@
 mypy
 parsimonious
+Arpeggio

src/JobShopParser/jobshop2_parser.py

@@ -0,0 +1,21 @@
+from arpeggio.cleanpeg import ParserPEG
+
+grammar = """
+problem_data    = trim_ws num_jobs ' ' num_machines eol job_data+ EOF
+trim_ws         = r'[ \t]*'
+eol             = "\n" / "\r\n"
+nonneg_num     = r'\d+'
+num_jobs        = nonneg_num
+num_machines    = nonneg_num
+machine         = nonneg_num
+duration        = nonneg_num
+job_data        = ' '* machine ' '+ duration (' '+ machine ' '+ duration)* trim_ws eol 
+"""
+
+parser = ParserPEG(grammar, "problem_data", skipws=False)
+
+with open('./inputdata/jobshop2/ta13') as jobdatafile:
+    jobdata : str = jobdatafile.read()
+    print("zu parsender String:\n\v\v", jobdata)
+    parse_tree = parser.parse(jobdata)
+    print(parse_tree)