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459 lines
15 KiB
Python
459 lines
15 KiB
Python
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# Copyright (c) 2006, 2008-2014 LOGILAB S.A. (Paris, FRANCE) <contact@logilab.fr>
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# Copyright (c) 2012 Ry4an Brase <ry4an-hg@ry4an.org>
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# Copyright (c) 2012 Google, Inc.
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# Copyright (c) 2012 Anthony VEREZ <anthony.verez.external@cassidian.com>
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# Copyright (c) 2014-2020 Claudiu Popa <pcmanticore@gmail.com>
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# Copyright (c) 2014 Brett Cannon <brett@python.org>
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# Copyright (c) 2014 Arun Persaud <arun@nubati.net>
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# Copyright (c) 2015 Ionel Cristian Maries <contact@ionelmc.ro>
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# Copyright (c) 2017, 2020 Anthony Sottile <asottile@umich.edu>
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# Copyright (c) 2017 Mikhail Fesenko <proggga@gmail.com>
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# Copyright (c) 2018 Scott Worley <scottworley@scottworley.com>
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# Copyright (c) 2018 ssolanki <sushobhitsolanki@gmail.com>
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# Copyright (c) 2019 Hugo van Kemenade <hugovk@users.noreply.github.com>
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# Copyright (c) 2019 Taewon D. Kim <kimt33@mcmaster.ca>
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# Copyright (c) 2019 Pierre Sassoulas <pierre.sassoulas@gmail.com>
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# Copyright (c) 2020 Shiv Venkatasubrahmanyam <shvenkat@users.noreply.github.com>
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# Licensed under the GPL: https://www.gnu.org/licenses/old-licenses/gpl-2.0.html
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# For details: https://github.com/PyCQA/pylint/blob/master/COPYING
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# pylint: disable=redefined-builtin
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"""a similarities / code duplication command line tool and pylint checker
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"""
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import sys
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from collections import defaultdict
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from getopt import getopt
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from itertools import groupby
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import astroid
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from pylint.checkers import BaseChecker, table_lines_from_stats
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from pylint.interfaces import IRawChecker
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from pylint.reporters.ureports.nodes import Table
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from pylint.utils import decoding_stream
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class Similar:
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"""finds copy-pasted lines of code in a project"""
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def __init__(
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self,
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min_lines=4,
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ignore_comments=False,
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ignore_docstrings=False,
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ignore_imports=False,
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):
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self.min_lines = min_lines
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self.ignore_comments = ignore_comments
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self.ignore_docstrings = ignore_docstrings
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self.ignore_imports = ignore_imports
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self.linesets = []
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def append_stream(self, streamid, stream, encoding=None):
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"""append a file to search for similarities"""
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if encoding is None:
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readlines = stream.readlines
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else:
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readlines = decoding_stream(stream, encoding).readlines
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try:
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self.linesets.append(
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LineSet(
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streamid,
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readlines(),
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self.ignore_comments,
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self.ignore_docstrings,
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self.ignore_imports,
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)
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)
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except UnicodeDecodeError:
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pass
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def run(self):
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"""start looking for similarities and display results on stdout"""
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self._display_sims(self._compute_sims())
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def _compute_sims(self):
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"""compute similarities in appended files"""
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no_duplicates = defaultdict(list)
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for num, lineset1, idx1, lineset2, idx2 in self._iter_sims():
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duplicate = no_duplicates[num]
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for couples in duplicate:
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if (lineset1, idx1) in couples or (lineset2, idx2) in couples:
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couples.add((lineset1, idx1))
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couples.add((lineset2, idx2))
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break
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else:
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duplicate.append({(lineset1, idx1), (lineset2, idx2)})
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sims = []
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for num, ensembles in no_duplicates.items():
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for couples in ensembles:
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sims.append((num, couples))
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sims.sort()
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sims.reverse()
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return sims
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def _display_sims(self, sims):
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"""display computed similarities on stdout"""
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nb_lignes_dupliquees = 0
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for num, couples in sims:
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print()
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print(num, "similar lines in", len(couples), "files")
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couples = sorted(couples)
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lineset = idx = None
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for lineset, idx in couples:
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print("==%s:%s" % (lineset.name, idx))
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if lineset:
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for line in lineset._real_lines[idx : idx + num]:
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print(" ", line.rstrip())
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nb_lignes_dupliquees += num * (len(couples) - 1)
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nb_total_lignes = sum([len(lineset) for lineset in self.linesets])
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print(
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"TOTAL lines=%s duplicates=%s percent=%.2f"
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% (
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nb_total_lignes,
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nb_lignes_dupliquees,
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nb_lignes_dupliquees * 100.0 / nb_total_lignes,
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)
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)
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def _find_common(self, lineset1, lineset2):
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"""find similarities in the two given linesets"""
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lines1 = lineset1.enumerate_stripped
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lines2 = lineset2.enumerate_stripped
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find = lineset2.find
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index1 = 0
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min_lines = self.min_lines
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while index1 < len(lineset1):
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skip = 1
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num = 0
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for index2 in find(lineset1[index1]):
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non_blank = 0
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for num, ((_, line1), (_, line2)) in enumerate(
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zip(lines1(index1), lines2(index2))
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):
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if line1 != line2:
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if non_blank > min_lines:
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yield num, lineset1, index1, lineset2, index2
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skip = max(skip, num)
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break
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if line1:
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non_blank += 1
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else:
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# we may have reach the end
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num += 1
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if non_blank > min_lines:
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yield num, lineset1, index1, lineset2, index2
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skip = max(skip, num)
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index1 += skip
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def _iter_sims(self):
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"""iterate on similarities among all files, by making a cartesian
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product
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"""
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for idx, lineset in enumerate(self.linesets[:-1]):
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for lineset2 in self.linesets[idx + 1 :]:
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yield from self._find_common(lineset, lineset2)
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def stripped_lines(lines, ignore_comments, ignore_docstrings, ignore_imports):
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"""return lines with leading/trailing whitespace and any ignored code
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features removed
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"""
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if ignore_imports:
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tree = astroid.parse("".join(lines))
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node_is_import_by_lineno = (
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(node.lineno, isinstance(node, (astroid.Import, astroid.ImportFrom)))
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for node in tree.body
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)
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line_begins_import = {
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lineno: all(is_import for _, is_import in node_is_import_group)
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for lineno, node_is_import_group in groupby(
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node_is_import_by_lineno, key=lambda x: x[0]
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)
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}
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current_line_is_import = False
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strippedlines = []
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docstring = None
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for lineno, line in enumerate(lines, start=1):
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line = line.strip()
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if ignore_docstrings:
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if not docstring:
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if line.startswith('"""') or line.startswith("'''"):
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docstring = line[:3]
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line = line[3:]
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elif line.startswith('r"""') or line.startswith("r'''"):
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docstring = line[1:4]
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line = line[4:]
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if docstring:
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if line.endswith(docstring):
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docstring = None
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line = ""
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if ignore_imports:
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current_line_is_import = line_begins_import.get(
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lineno, current_line_is_import
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)
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if current_line_is_import:
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line = ""
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if ignore_comments:
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line = line.split("#", 1)[0].strip()
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strippedlines.append(line)
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return strippedlines
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class LineSet:
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"""Holds and indexes all the lines of a single source file"""
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def __init__(
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self,
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name,
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lines,
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ignore_comments=False,
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ignore_docstrings=False,
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ignore_imports=False,
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):
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self.name = name
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self._real_lines = lines
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self._stripped_lines = stripped_lines(
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lines, ignore_comments, ignore_docstrings, ignore_imports
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)
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self._index = self._mk_index()
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def __str__(self):
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return "<Lineset for %s>" % self.name
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def __len__(self):
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return len(self._real_lines)
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def __getitem__(self, index):
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return self._stripped_lines[index]
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def __lt__(self, other):
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return self.name < other.name
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def __hash__(self):
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return id(self)
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def enumerate_stripped(self, start_at=0):
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"""return an iterator on stripped lines, starting from a given index
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if specified, else 0
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"""
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idx = start_at
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if start_at:
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lines = self._stripped_lines[start_at:]
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else:
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lines = self._stripped_lines
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for line in lines:
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# if line:
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yield idx, line
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idx += 1
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def find(self, stripped_line):
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"""return positions of the given stripped line in this set"""
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return self._index.get(stripped_line, ())
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def _mk_index(self):
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"""create the index for this set"""
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index = defaultdict(list)
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for line_no, line in enumerate(self._stripped_lines):
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if line:
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index[line].append(line_no)
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return index
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MSGS = {
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"R0801": (
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"Similar lines in %s files\n%s",
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"duplicate-code",
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"Indicates that a set of similar lines has been detected "
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"among multiple file. This usually means that the code should "
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"be refactored to avoid this duplication.",
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)
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}
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def report_similarities(sect, stats, old_stats):
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"""make a layout with some stats about duplication"""
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lines = ["", "now", "previous", "difference"]
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lines += table_lines_from_stats(
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stats, old_stats, ("nb_duplicated_lines", "percent_duplicated_lines")
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)
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sect.append(Table(children=lines, cols=4, rheaders=1, cheaders=1))
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# wrapper to get a pylint checker from the similar class
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class SimilarChecker(BaseChecker, Similar):
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"""checks for similarities and duplicated code. This computation may be
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memory / CPU intensive, so you should disable it if you experiment some
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problems.
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"""
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__implements__ = (IRawChecker,)
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# configuration section name
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name = "similarities"
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# messages
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msgs = MSGS
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# configuration options
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# for available dict keys/values see the optik parser 'add_option' method
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options = (
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(
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"min-similarity-lines", # type: ignore
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{
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"default": 4,
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"type": "int",
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"metavar": "<int>",
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"help": "Minimum lines number of a similarity.",
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},
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),
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(
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"ignore-comments",
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{
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"default": True,
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"type": "yn",
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"metavar": "<y or n>",
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"help": "Ignore comments when computing similarities.",
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},
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),
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(
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"ignore-docstrings",
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{
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"default": True,
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"type": "yn",
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"metavar": "<y or n>",
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"help": "Ignore docstrings when computing similarities.",
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},
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),
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(
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"ignore-imports",
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{
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"default": False,
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"type": "yn",
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"metavar": "<y or n>",
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"help": "Ignore imports when computing similarities.",
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},
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),
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)
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# reports
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reports = (("RP0801", "Duplication", report_similarities),) # type: ignore
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def __init__(self, linter=None):
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BaseChecker.__init__(self, linter)
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Similar.__init__(
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self, min_lines=4, ignore_comments=True, ignore_docstrings=True
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)
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self.stats = None
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def set_option(self, optname, value, action=None, optdict=None):
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"""method called to set an option (registered in the options list)
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overridden to report options setting to Similar
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"""
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BaseChecker.set_option(self, optname, value, action, optdict)
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if optname == "min-similarity-lines":
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self.min_lines = self.config.min_similarity_lines
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elif optname == "ignore-comments":
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self.ignore_comments = self.config.ignore_comments
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elif optname == "ignore-docstrings":
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self.ignore_docstrings = self.config.ignore_docstrings
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elif optname == "ignore-imports":
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self.ignore_imports = self.config.ignore_imports
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def open(self):
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"""init the checkers: reset linesets and statistics information"""
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self.linesets = []
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self.stats = self.linter.add_stats(
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nb_duplicated_lines=0, percent_duplicated_lines=0
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)
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def process_module(self, node):
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"""process a module
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the module's content is accessible via the stream object
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stream must implement the readlines method
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"""
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with node.stream() as stream:
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self.append_stream(self.linter.current_name, stream, node.file_encoding)
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def close(self):
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"""compute and display similarities on closing (i.e. end of parsing)"""
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total = sum(len(lineset) for lineset in self.linesets)
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duplicated = 0
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stats = self.stats
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for num, couples in self._compute_sims():
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msg = []
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lineset = idx = None
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for lineset, idx in couples:
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msg.append("==%s:%s" % (lineset.name, idx))
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msg.sort()
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if lineset:
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for line in lineset._real_lines[idx : idx + num]:
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msg.append(line.rstrip())
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self.add_message("R0801", args=(len(couples), "\n".join(msg)))
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duplicated += num * (len(couples) - 1)
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stats["nb_duplicated_lines"] = duplicated
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stats["percent_duplicated_lines"] = total and duplicated * 100.0 / total
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def register(linter):
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"""required method to auto register this checker """
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linter.register_checker(SimilarChecker(linter))
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def usage(status=0):
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"""display command line usage information"""
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print("finds copy pasted blocks in a set of files")
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print()
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print(
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"Usage: symilar [-d|--duplicates min_duplicated_lines] \
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[-i|--ignore-comments] [--ignore-docstrings] [--ignore-imports] file1..."
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)
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sys.exit(status)
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def Run(argv=None):
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"""standalone command line access point"""
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if argv is None:
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argv = sys.argv[1:]
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s_opts = "hdi"
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l_opts = (
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"help",
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"duplicates=",
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"ignore-comments",
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"ignore-imports",
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"ignore-docstrings",
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)
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min_lines = 4
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ignore_comments = False
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ignore_docstrings = False
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ignore_imports = False
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opts, args = getopt(argv, s_opts, l_opts)
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for opt, val in opts:
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if opt in ("-d", "--duplicates"):
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|
min_lines = int(val)
|
||
|
elif opt in ("-h", "--help"):
|
||
|
usage()
|
||
|
elif opt in ("-i", "--ignore-comments"):
|
||
|
ignore_comments = True
|
||
|
elif opt in ("--ignore-docstrings",):
|
||
|
ignore_docstrings = True
|
||
|
elif opt in ("--ignore-imports",):
|
||
|
ignore_imports = True
|
||
|
if not args:
|
||
|
usage(1)
|
||
|
sim = Similar(min_lines, ignore_comments, ignore_docstrings, ignore_imports)
|
||
|
for filename in args:
|
||
|
with open(filename) as stream:
|
||
|
sim.append_stream(filename, stream)
|
||
|
sim.run()
|
||
|
sys.exit(0)
|
||
|
|
||
|
|
||
|
if __name__ == "__main__":
|
||
|
Run()
|