parsing tree from excel sheet

[alb]

Hi Peter,

Peter Otten <__peter__ at web.de> wrote:
[]
> You can save the excel sheet as csv so that you an use the csv module which 
> may be easier to use than xlrd. The rest should be doable by hand. Here's 
> what I hacked together:
> 
> $ cat parse_column_tree.py
> import csv
> 
> def column_index(row):
>    for result, cell in enumerate(row, 0):
>        if cell:
>            return result
>    raise ValueError
> 
> 
> class Node:
>    def __init__(self, name, level):
>        self.name = name
>        self.level = level
>        self.children = []
> 
>    def append(self, child):
>        self.children.append(child)
> 
>    def __str__(self):
>        return "\%s{%s}" % (self.level, self.name)
> 
>    def show(self):
>        yield [self.name]
>        for i, child in enumerate(self.children):
>            lastchild = i == len(self.children)-1
>            first = True
>            for c in child.show():
>                if first:
>                    yield ["\---> " if lastchild else "+---> "] + c
>                    first = False
>                else:
>                    yield ["      " if lastchild else "|     "] + c
>    def show2(self):
>        yield str(self)
>        for child in self.children:
>            yield from child.show2()
> 
> def show(root):
>    for row in root.show():
>        print("".join(row))
> 
> def show2(root):
>    for line in root.show2():
>        print(line)
> 
> def read_tree(rows, levelnames):
>    root = Node("#ROOT", "#ROOT")
>    old_level = 0
>    stack = [root]
>    for i, row in enumerate(rows, 1):
> 
>        new_level = column_index(row)
>        node = Node(row[new_level], levelnames[new_level])
> 
>        if new_level == old_level:
>            stack[-1].append(node)
>        elif new_level > old_level:
>            if new_level - old_level != 1:
>                raise ValueError
> 
>            stack.append(stack[-1].children[-1])
>            stack[-1].append(node)
>            old_level = new_level
>        else:
>            while new_level < old_level:
>                stack.pop(-1)
>                old_level -= 1
>            stack[-1].append(node)
>    return root
> 
> def main():
>    import argparse
>    parser = argparse.ArgumentParser()
>    parser.add_argument("infile")
>    parser.add_argument("--latex", action="store_true")
> 
>    args = parser.parse_args()
> 
>    with open(args.infile) as f:
>        rows = csv.reader(f)
>        levelnames = next(rows) # skip header
>        tree = read_tree(rows, levelnames)
> 
>        show_tree = show2 if args.latex else show
>        for node in tree.children:
>            show_tree(node)
>            print("")
> 
> if __name__ == "__main__":
>    main()
> $ cat data.csv
> subsystem,chapter,section,subsection,subsubsec,
> A,,,,,
> ,func0,,,,
> ,,interface,,,
> ,,latency,,,
> ,,priority,,,
> ,func1,,,,
> ,,interface,,,
> ,,latency,,,
> ,,priority,,,
> ,,depend,,,
> ,,,variables,,
> ,,,,static,
> ,,,,global,
> ,,,functions,,
> ,,,,internal,
> ,,,,external,
> $ python3 parse_column_tree.py data.csv
> A
> +---> func0
> |     +---> interface
> |     +---> latency
> |     \---> priority
> \---> func1
>      +---> interface
>      +---> latency
>      +---> priority
>      \---> depend
>            +---> variables
>            |     +---> static
>            |     \---> global
>            \---> functions
>                  +---> internal
>                  \---> external
> 
> $ python3 parse_column_tree.py data.csv --latex
> \subsystem{A}
> \chapter{func0}
> \section{interface}
> \section{latency}
> \section{priority}
> \chapter{func1}
> \section{interface}
> \section{latency}
> \section{priority}
> \section{depend}
> \subsection{variables}
> \subsubsec{static}
> \subsubsec{global}
> \subsection{functions}
> \subsubsec{internal}
> \subsubsec{external}

WOW! I didn't really want someone else to write what I needed but thanks 
a lot! That's a lot of food to digest in a single byte, so I'll first 
play a bit with it (hopefully understanding what is doing) and then come 
back with comments.

I really appreciated your time and effort.

Al