def exclude_data_files(self, package, src_dir, files):
        globs = (self.exclude_package_data.get('', [])
                 + self.exclude_package_data.get(package, []))
        bad = []
        for pattern in globs:
            bad.extend(
                fnmatch.filter(
                    files, os.path.join(src_dir, convert_path(pattern))
                )
            )
        bad = dict.fromkeys(bad)
        seen = {}
        return [
            f for f in files if f not in bad
                and f not in seen and seen.setdefault(f,1)  # ditch dupes
        ]
Create a learning curve that uses more training cases with
dataset/ETHPy150Open AppScale/appscale/AppServer/lib/setuptools-0.6c11/setuptools/command/build_py.py/build_py.exclude_data_files--crossover with--dataset/ETHPy150Open dnouri/nolearn/nolearn/metrics.py/LearningCurve.__call__