Parse a .py file, read the AST, modify it, then write back the modified source code

Pythoscope does this to the test cases it automatically generates as does the 2to3 tool for python 2.6 (it converts python 2.x source into python 3.x source).

Both these tools uses the lib2to3 library which is an implementation of the python parser/compiler machinery that can preserve comments in source when it's round tripped from source -> AST -> source.

The rope project may meet your needs if you want to do more refactoring like transforms.

The ast module is your other option, and there's an older example of how to "unparse" syntax trees back into code (using the parser module). But the ast module is more useful when doing an AST transform on code that is then transformed into a code object.

The redbaron project also may be a good fit (ht Xavier Combelle)

The builtin ast module doesn't seem to have a method to convert back to source. However, the codegen module here provides a pretty printer for the ast that would enable you do do so. eg.

import ast
import codegen

expr="""
def foo():
   print("hello world")
"""
p=ast.parse(expr)

p.body[0].body = [ ast.parse("return 42").body[0] ] # Replace function body with "return 42"

print(codegen.to_source(p))

This will print:

def foo():
    return 42

Note that you may lose the exact formatting and comments, as these are not preserved.

However, you may not need to. If all you require is to execute the replaced AST, you can do so simply by calling compile() on the ast, and execing the resulting code object.

Took a while, but Python 3.9 has this: https://docs.python.org/3.9/whatsnew/3.9.html#ast https://docs.python.org/3.9/library/ast.html#ast.unparse

ast.unparse(ast_obj)

Unparse an ast.AST object and generate a string with code that would produce an equivalent ast.AST object if parsed back with ast.parse().

You might not need to re-generate source code. That's a bit dangerous for me to say, of course, since you have not actually explained why you think you need to generate a .py file full of code; but:

• If you want to generate a .py file that people will actually use, maybe so that they can fill out a form and get a useful .py file to insert into their project, then you don't want to change it into an AST and back because you'll lose all formatting (think of the blank lines that make Python so readable by grouping related sets of lines together) (ast nodes have lineno and col_offset attributes) comments. Instead, you'll probably want to use a templating engine (the Django template language, for example, is designed to make templating even text files easy) to customize the .py file, or else use Rick Copeland's MetaPython extension.

• If you are trying to make a change during compilation of a module, note that you don't have to go all the way back to text; you can just compile the AST directly instead of turning it back into a .py file.

• But in almost any and every case, you are probably trying to do something dynamic that a language like Python actually makes very easy, without writing new .py files! If you expand your question to let us know what you actually want to accomplish, new .py files will probably not be involved in the answer at all; I have seen hundreds of Python projects doing hundreds of real-world things, and not a single one of them needed to ever writer a .py file. So, I must admit, I'm a bit of a skeptic that you've found the first good use-case. :-)

Update: now that you've explained what you're trying to do, I'd be tempted to just operate on the AST anyway. You will want to mutate by removing, not lines of a file (which could result in half-statements that simply die with a SyntaxError), but whole statements — and what better place to do that than in the AST?

If you are looking at this in 2019, then you can use this libcst package. It has syntax similar to ast. This works like a charm, and preserve the code structure. It's basically helpful for the project where you have to preserve comments, whitespace, newline etc.

If you don't need to care about the preserving comments, whitespace and others, then the combination of ast and astor works well.

Unfortunately none of the answers above actually met both of these conditions

• Preserve the syntactical integrity for the surrounding source code (e.g keeping comments, other sorts of formatting for the rest of the code)
• Actually use AST (not CST).

I've recently written a small toolkit to do pure AST based refactorings, called refactor. For example if you want to replace all placeholders with 42, you can simply write a rule like this;

class Replace(Rule):
    
    def match(self, node):
        assert isinstance(node, ast.Name)
        assert node.id == 'placeholder'
        
        replacement = ast.Constant(42)
        return ReplacementAction(node, replacement)

And it will find all acceptable nodes, replace them with the new nodes and generate the final form;

--- test_file.py
+++ test_file.py

@@ -1,11 +1,11 @@

 def main():
-    print(placeholder * 3 + 2)
-    print(2 +               placeholder      + 3)
+    print(42 * 3 + 2)
+    print(2 +               42      + 3)
     # some commments
-    placeholder # maybe other comments
+    42 # maybe other comments
     if something:
         other_thing
-    print(placeholder)
+    print(42)
 
 if __name__ == "__main__":
     main()

A Program Transformation System is a tool that parses source text, builds ASTs, allows you to modify them using source-to-source transformations ("if you see this pattern, replace it by that pattern"). Such tools are ideal for doing mutation of existing source codes, which are just "if you see this pattern, replace by a pattern variant".

Of course, you need a program transformation engine that can parse the language of interest to you, and still do the pattern-directed transformations. Our DMS Software Reengineering Toolkit is a system that can do that, and handles Python, and a variety of other languages.

See this SO answer for an example of a DMS-parsed AST for Python capturing comments accurately. DMS can make changes to the AST, and regenerate valid text, including the comments. You can ask it to prettyprint the AST, using its own formatting conventions (you can changes these), or do "fidelity printing", which uses the original line and column information to maximally preserve the original layout (some change in layout where new code is inserted is unavoidable).

To implement a "mutation" rule for Python with DMS, you could write the following:

rule mutate_addition(s:sum, p:product):sum->sum =
  " \s + \p " -> " \s - \p"
 if mutate_this_place(s);

This rule replace "+" with "-" in a syntactically correct way; it operates on the AST and thus won't touch strings or comments that happen to look right. The extra condition on "mutate_this_place" is to let you control how often this occurs; you don't want to mutate every place in the program.

You'd obviously want a bunch more rules like this that detect various code structures, and replace them by the mutated versions. DMS is happy to apply a set of rules. The mutated AST is then prettyprinted.

I used to use baron for this, but have now switched to parso because it's up to date with modern python. It works great.

I also needed this for a mutation tester. It's really quite simple to make one with parso, check out my code at https://github.com/boxed/mutmut