Metadata | |
---|---|
cEP | 22 |
Version | 1.0 |
Title | Integration of pyflakes-enhanced-AST into coala |
Authors | Ankit Joshi mailto:[email protected] |
Status | Proposed |
Type | Feature |
This document describes how to create a metabear to integrate pyflakes-enhanced-AST into coala and demonstrates its use by creating a simple dependent bear.
Flake8 is the most commonly used linter framework when it comes to static code analysis for python. It wraps around the tools pyflakes, pycodestyle and mccabe scripts. These tools are implemented on different interfaces and flake8 combines their potential.
It even provides with a plugin mechanism. Additional linters are supported using the flake8 plugin system, and may use CPython ast standard library or may be built using pycodestyle's internal logical-line-based checker API (checkout Hacking).
There has not been an option to use the pyflakes-enhanced-AST based checker API to create custom linters. Thus, the full potential of enhanced AST isn't utilized , a whole lot of rework is required to do the basic traversing and collection of important nodes. Pyflakes provides with a basic API that does the traversing. So, if a developer uses enhanced AST he just needs to work on the implementation of the new logic that his/her plugin provides and not about the fidelity of the basic node handlers.
The reason for choosing pyflakes over its equivalents like Astroid lies in its simplicity and provision of lots of re-usable analysis. Astroid is more detailed and powerful, thus making it complicated. Plus, there is a much larger ecosystem of flake8 plugins.
Here is a brief overview of the architecture:
- There will be a separate repository named as coala-pyflakes which will
be installable via
pip install pyflakes-bears
. - The repository will contain a new package
pyflakes-bears
which would house all bears which use pyflakes-enhanced-ast. - The
pyflakes-bears
would contain a metabearPyFlakesASTBear
which would be used by all other plugin bears. - The repository would even contain another package
pyflakes-generic-plugins
that would be independent of coala and could be run by flake8 or coala or any other similar tool.
The repository will use a similar mechanism of what is being
used in coala-bears
to test all its bears.
PyFlakesASTBear
will beLocalBear
returning result of the typeHiddenResult
since these results are not meant for the users but for the dependent bear. The result structure is described byPyFlakesResult
class.PyFlakesResult
consists of a snapshot of the module at class, function, module, generator and doctest level. Thus, providing the developer multiple views of a file allowing him to retrieve results as per his demand.- Apart from scope information, the metabear also returns a list of messages generated by pyflakes itself. These s can be used by the developer to add an additional filter layer that is required to be resolved by the user before executing the plugin. This is primarily done because pyflakes emits additional syntax errors which are not caught by python interpretor and may affect the working of a plugin. This check is optional and may or may not be incorparated by the developer.
- Helper function
get_nodes
provides with all the nodes of a particular type present in a scope.
Here is a prototype for the implementations of PyFlakesASTBear
:
# Imports not mentioned to maintain brevity
class PyFlakesResult(HiddenResult):
def __init__(self, origin, deadScopes, pyflakes_messages):
Result.__init__(self, origin, message='')
self.module_scope = self.get_scopes(ModuleScope, deadScopes)[0]
self.class_scopes = self.get_scopes(ClassScope, deadScopes)
self.function_scopes = self.get_scopes(FunctionScope, deadScopes)
self.generator_scopes = self.get_scopes(GeneratorScope, deadScopes)
self.doctest_scopes = self.get_scopes(DoctestScope, deadScopes)
self.pyflakes_messages = pyflakes_messages
def get_scopes(self, scope_type, scopes):
return list(filter(lambda scope: isinstance(scope, scope_type),
scopes))
def get_nodes(self, scope, node_type):
for _, node in scope.items():
if isinstance(node, node_type):
yield node
class PyFlakesASTBear(LocalBear):
AUTHORS = {'The coala developers'}
AUTHORS_EMAILS = {'[email protected]'}
LICENSE = 'AGPL-3.0'
def run(self, filename, file):
"""
Generates pyflakes-enhance-AST for the input file and returns
deadScopes as HiddenResult
:return:
One HiddenResult containing a dictionary with keys being
type of scope and values being a list of scopes generated
from the file.
"""
tree = ast.parse(''.join(file))
result = Checker(tree, filename=filename, withDoctest=True)
yield PyFlakesResult(self, result.deadScopes, result.messages)
A hassle free solution to the problem of finding all the future imports present in the source code.
Here is a prototype for the NoFutureImportBear
that uses PyFlakesASTBear
:
# Imports not mentioned to maintain brevity
class NoFutureImportBear(LocalBear):
"""
Uses pyflakes-enhance-AST to detect use of future imports
"""
BEAR_DEPS = {PyFlakesASTBear}
def run(self, filename, file,
dependency_results=dict()
):
for result in dependency_results.get(PyFlakesASTBear.name, []):
for node in result.get_nodes(result.module_scope,
FutureImportation):
corrected = self.remove_import(file, node.source.lineno, node.name)
yield Result.from_values(
origin=self,
message='Future import %s found' % node.name,
file=filename,
diffs={filename: corrected},
line=node.source.lineno)
This implementation doesn't requires coala to be installed and is
designed so that it can be used in other tools like flake8. coala
will also be able to use this plugin, but it is also usable by flake8.
This implementation will be housed in pyflakes-generic-plugins
.
Here is a prototype for the NoFutureImport
using pyflakes-enhanced-AST:
# Imports not mentioned to maintain brevity
__version__ = '0.1'
CODE = 'F482'
class NoFutureImport(object):
name = 'no_future'
version = __version__
def __init__(self, tree, filename):
self.tree = tree
self.filename = filename
self._checker = None
self._module_scope = None
@property
def checker(self):
if self._checker is None:
self._checker = Checker(self.tree, self.filename)
return self._checker
@checker.setter
def checker(self, checker):
self.checker = checker
@property
def module_scope(self):
if self._module_scope is None:
self._module_scope = list(filter(lambda scope: isinstance(scope,
ModuleScope),
self.checker.deadScopes))[0]
return self._module_scope
def run(self):
for _, node in self.module_scope.items():
if isinstance(node, FutureImportation):
message = '{code}: Future import {name} found'
.format(name=node.name,
code=CODE)
yield (node.source.lineno, node.source.col_offset,
message, NoFutureImport)
A hassle free solution to the problem of removing all the future imports present in the source code.
Here is a prototype for the NoFutureImportBear
that uses PyFlakesASTBear
:
# Imports not mentioned to maintain brevity
class NoFutureImportBear(LocalBear):
"""
Uses pyflakes-enhance-AST to remove future imports
"""
BEAR_DEPS = {PyFlakesASTBear}
# TODO: Adjust logic to support removal when `\` is used
def remove_future_imports(self, file, lineno,
max_col_offset, affected_lines):
"""
Removes all __future__ imports from the input line
"""
diff = Diff(file)
line = file[lineno - 1]
semicolon_indices = [i for i, a in enumerate(line) if a == ';']
if len(semicolon_indices) == 0:
diff.delete_line(lineno)
else:
for indice in semicolon_indices:
if indice > max_col_offset:
replacement = line[indice + 1:].lstrip()
diff.modify_line(lineno, replacement)
break
return diff
def run(self, filename, file,
dependency_results=dict()
):
"""
Uses PyFlakesASTBear to get only FutureImportation
"""
# Preprocess all the lines containing __future__ imports
affected_lines = set()
# Get the maximum column offset of FutureImportation for a line
max_column_for_a_line = dict()
for result in dependency_results.get(PyFlakesASTBear.name, []):
for node in result.get_nodes(result.module_scope,
FutureImportation):
lineno = node.source.lineno
col_offset = node.source.col_offset
if lineno in max_column_for_a_line:
max_column_for_a_line[lineno] = max(
max_column_for_a_line[lineno],
col_offset)
else:
max_column_for_a_line[lineno] = col_offset
affected_lines.add(lineno)
for line in affected_lines:
corrected = self.remove_future_imports(
file, line, max_column_for_a_line[lineno],
affected_lines
)
yield Result.from_values(
origin=self,
message='Future import(s) found',
file=filename,
diffs={filename: corrected},
line=line)