Source code for libcst.codemod._cli

# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
"""
Provides helpers for CLI interaction.
"""

import difflib
import os.path
import re
import subprocess
import sys
import time
import traceback
from concurrent.futures import as_completed, Executor, ProcessPoolExecutor
from copy import deepcopy
from dataclasses import dataclass
from multiprocessing import cpu_count
from pathlib import Path
from typing import AnyStr, cast, Dict, List, Optional, Sequence, Type, Union
from warnings import warn

from libcst import parse_module, PartialParserConfig
from libcst.codemod._codemod import Codemod
from libcst.codemod._context import CodemodContext
from libcst.codemod._dummy_pool import DummyExecutor
from libcst.codemod._runner import (
    SkipFile,
    SkipReason,
    transform_module,
    TransformExit,
    TransformFailure,
    TransformResult,
    TransformSkip,
    TransformSuccess,
)
from libcst.helpers import calculate_module_and_package
from libcst.metadata import FullRepoManager

_DEFAULT_GENERATED_CODE_MARKER: str = f"@gen{''}erated"


def invoke_formatter(formatter_args: Sequence[str], code: AnyStr) -> AnyStr:
    """
    Given a code string, run an external formatter on the code and return new
    formatted code.
    """

    # Make sure there is something to run
    if len(formatter_args) == 0:
        raise Exception("No formatter configured but code formatting requested.")

    # Invoke the formatter, giving it the code as stdin and assuming the formatted
    # code comes from stdout.
    work_with_bytes = isinstance(code, bytes)
    return cast(
        AnyStr,
        subprocess.check_output(
            formatter_args,
            input=code,
            universal_newlines=not work_with_bytes,
            encoding=None if work_with_bytes else "utf-8",
        ),
    )


def print_execution_result(result: TransformResult) -> None:
    for warning in result.warning_messages:
        print(f"WARNING: {warning}", file=sys.stderr)

    if isinstance(result, TransformFailure):
        error = result.error
        if isinstance(error, subprocess.CalledProcessError):
            print(error.output.decode("utf-8"), file=sys.stderr)
        print(result.traceback_str, file=sys.stderr)


[docs] def gather_files( files_or_dirs: Sequence[str], *, include_stubs: bool = False ) -> List[str]: """ Given a list of files or directories (can be intermingled), return a list of all python files that exist at those locations. If ``include_stubs`` is ``True``, this will include ``.py`` and ``.pyi`` stub files. If it is ``False``, only ``.py`` files will be included in the returned list. """ ret: List[str] = [] for fd in files_or_dirs: if os.path.isfile(fd): ret.append(fd) elif os.path.isdir(fd): ret.extend( str(p) for p in Path(fd).rglob("*.py*") if Path.is_file(p) and ( str(p).endswith("py") or (include_stubs and str(p).endswith("pyi")) ) ) return sorted(ret)
[docs] def diff_code( oldcode: str, newcode: str, context: int, *, filename: Optional[str] = None ) -> str: """ Given two strings representing a module before and after a codemod, produce a unified diff of the changes with ``context`` lines of context. Optionally, assign the ``filename`` to the change, and if it is not available, assume that the change was performed on stdin/stdout. If no change is detected, return an empty string instead of returning an empty unified diff. This is comparable to revision control software which only shows differences for files that have changed. """ if oldcode == newcode: return "" if filename: difflines = difflib.unified_diff( oldcode.split("\n"), newcode.split("\n"), fromfile=filename, tofile=filename, lineterm="", n=context, ) else: difflines = difflib.unified_diff( oldcode.split("\n"), newcode.split("\n"), lineterm="", n=context ) return "\n".join(difflines)
[docs] def exec_transform_with_prettyprint( transform: Codemod, code: str, *, include_generated: bool = False, generated_code_marker: str = _DEFAULT_GENERATED_CODE_MARKER, format_code: bool = False, formatter_args: Sequence[str] = (), python_version: Optional[str] = None, ) -> Optional[str]: """ Given an instantiated codemod and a string representing a module, transform that code by executing the transform, optionally invoking the formatter and finally printing any generated warnings to stderr. If the code includes the generated marker at any spot and ``include_generated`` is not set to ``True``, the code will not be modified. If ``format_code`` is set to ``False`` or the instantiated codemod does not modify the code, the code will not be formatted. If a ``python_version`` is provided, then we will parse the module using this version. Otherwise, we will use the version of the currently executing python binary. In all cases a module will be returned. Whether it is changed depends on the input parameters as well as the codemod itself. """ if not include_generated and generated_code_marker in code: print( "WARNING: Code is generated and we are set to ignore generated code, " + "skipping!", file=sys.stderr, ) return code result = transform_module(transform, code, python_version=python_version) maybe_code: Optional[str] = ( None if isinstance(result, (TransformFailure, TransformExit, TransformSkip)) else result.code ) if maybe_code is not None and format_code: try: maybe_code = invoke_formatter(formatter_args, maybe_code) except Exception as ex: # Failed to format code, treat as a failure and make sure that # we print the exception for debugging. maybe_code = None result = TransformFailure( error=ex, traceback_str=traceback.format_exc(), warning_messages=result.warning_messages, ) # Finally, print the output, regardless of what happened print_execution_result(result) return maybe_code
@dataclass(frozen=True) class ExecutionResult: # File we have results for filename: str # Whether we actually changed the code for the file or not changed: bool # The actual result transform_result: TransformResult @dataclass(frozen=True) class ExecutionConfig: blacklist_patterns: Sequence[str] = () format_code: bool = False formatter_args: Sequence[str] = () generated_code_marker: str = _DEFAULT_GENERATED_CODE_MARKER include_generated: bool = False python_version: Optional[str] = None repo_root: Optional[str] = None unified_diff: Optional[int] = None def _prepare_context( repo_root: str, filename: str, scratch: Dict[str, object], repo_manager: Optional[FullRepoManager], ) -> CodemodContext: # determine the module and package name for this file try: module_name_and_package = calculate_module_and_package(repo_root, filename) mod_name = module_name_and_package.name pkg_name = module_name_and_package.package except ValueError as ex: print(f"Failed to determine module name for {filename}: {ex}", file=sys.stderr) mod_name = None pkg_name = None return CodemodContext( scratch=scratch, filename=filename, full_module_name=mod_name, full_package_name=pkg_name, metadata_manager=repo_manager, ) def _instantiate_transformer( transformer: Union[Codemod, Type[Codemod]], repo_root: str, filename: str, original_scratch: Dict[str, object], codemod_kwargs: Dict[str, object], repo_manager: Optional[FullRepoManager], ) -> Codemod: if isinstance(transformer, type): return transformer( # type: ignore context=_prepare_context(repo_root, filename, {}, repo_manager), **codemod_kwargs, ) transformer.context = _prepare_context( repo_root, filename, deepcopy(original_scratch), repo_manager ) return transformer def _check_for_skip( filename: str, config: ExecutionConfig ) -> Union[ExecutionResult, bytes]: for pattern in config.blacklist_patterns: if re.fullmatch(pattern, filename): return ExecutionResult( filename=filename, changed=False, transform_result=TransformSkip( skip_reason=SkipReason.BLACKLISTED, skip_description=f"Blacklisted by pattern {pattern}.", ), ) with open(filename, "rb") as fp: oldcode = fp.read() # Skip generated files if ( not config.include_generated and config.generated_code_marker.encode("utf-8") in oldcode ): return ExecutionResult( filename=filename, changed=False, transform_result=TransformSkip( skip_reason=SkipReason.GENERATED, skip_description="Generated file.", ), ) return oldcode def _execute_transform( transformer: Union[Codemod, Type[Codemod]], filename: str, config: ExecutionConfig, original_scratch: Dict[str, object], codemod_args: Optional[Dict[str, object]], repo_manager: Optional[FullRepoManager], ) -> ExecutionResult: warnings: list[str] = [] try: oldcode = _check_for_skip(filename, config) if isinstance(oldcode, ExecutionResult): return oldcode transformer_instance = _instantiate_transformer( transformer, config.repo_root or ".", filename, original_scratch, codemod_args or {}, repo_manager, ) # Run the transform, bail if we failed or if we aren't formatting code try: input_tree = parse_module( oldcode, config=( PartialParserConfig(python_version=str(config.python_version)) if config.python_version is not None else PartialParserConfig() ), ) output_tree = transformer_instance.transform_module(input_tree) newcode = output_tree.bytes encoding = output_tree.encoding warnings.extend(transformer_instance.context.warnings) except SkipFile as ex: warnings.extend(transformer_instance.context.warnings) return ExecutionResult( filename=filename, changed=False, transform_result=TransformSkip( skip_reason=SkipReason.OTHER, skip_description=str(ex), warning_messages=warnings, ), ) # Call formatter if needed, but only if we actually changed something in this # file if config.format_code and newcode != oldcode: newcode = invoke_formatter(config.formatter_args, newcode) # Format as unified diff if needed, otherwise save it back changed = oldcode != newcode if config.unified_diff: newcode = diff_code( oldcode.decode(encoding), newcode.decode(encoding), config.unified_diff, filename=filename, ) else: # Write back if we changed if changed: with open(filename, "wb") as fp: fp.write(newcode) # Not strictly necessary, but saves space in pickle since we won't use it newcode = "" # Inform success return ExecutionResult( filename=filename, changed=changed, transform_result=TransformSuccess(warning_messages=warnings, code=newcode), ) except KeyboardInterrupt: return ExecutionResult( filename=filename, changed=False, transform_result=TransformExit(warning_messages=warnings), ) except Exception as ex: return ExecutionResult( filename=filename, changed=False, transform_result=TransformFailure( error=ex, traceback_str=traceback.format_exc(), warning_messages=warnings, ), ) class Progress: ERASE_CURRENT_LINE: str = "\r\033[2K" def __init__(self, *, enabled: bool, total: int) -> None: self.enabled = enabled self.total = total # 1/100 = 0, len("0") = 1, precision = 0, more digits for more files self.pretty_precision: int = len(str(self.total // 100)) - 1 # Pretend we start processing immediately. This is not true, but it's # close enough to true. self.started_at: float = time.time() def print(self, finished: int) -> None: if not self.enabled: return left = self.total - finished percent = 100.0 * (float(finished) / float(self.total)) elapsed_time = max(time.time() - self.started_at, 0) print( f"{self.ERASE_CURRENT_LINE}{self._human_seconds(elapsed_time)} {percent:.{self.pretty_precision}f}% complete, {self.estimate_completion(elapsed_time, finished, left)} estimated for {left} files to go...", end="", file=sys.stderr, ) def _human_seconds(self, seconds: Union[int, float]) -> str: """ This returns a string which is a human-ish readable elapsed time such as 30.42s or 10m 31s """ minutes, seconds = divmod(seconds, 60) hours, minutes = divmod(minutes, 60) if hours > 0: return f"{hours:.0f}h {minutes:02.0f}m {seconds:02.0f}s" elif minutes > 0: return f"{minutes:02.0f}m {seconds:02.0f}s" else: return f"{seconds:02.2f}s" def estimate_completion( self, elapsed_seconds: float, files_finished: int, files_left: int ) -> str: """ Computes a really basic estimated completion given a number of operations still to do. """ if files_finished <= 0 or elapsed_seconds == 0: # Technically infinite but calculating sounds better. return "[calculating]" fps = files_finished / elapsed_seconds estimated_seconds_left = files_left / fps return self._human_seconds(estimated_seconds_left) def clear(self) -> None: if not self.enabled: return print(self.ERASE_CURRENT_LINE, end="", file=sys.stderr) def _print_parallel_result( exec_result: ExecutionResult, progress: Progress, *, unified_diff: bool, show_successes: bool, hide_generated: bool, hide_blacklisted: bool, ) -> None: filename = exec_result.filename result = exec_result.transform_result if isinstance(result, TransformSkip): # Skipped file, print message and don't write back since not changed. if not ( (result.skip_reason is SkipReason.BLACKLISTED and hide_blacklisted) or (result.skip_reason is SkipReason.GENERATED and hide_generated) ): progress.clear() print(f"Codemodding {filename}", file=sys.stderr) print_execution_result(result) print( f"Skipped codemodding {filename}: {result.skip_description}\n", file=sys.stderr, ) elif isinstance(result, TransformFailure): # Print any exception, don't write the file back. progress.clear() print(f"Codemodding {filename}", file=sys.stderr) print_execution_result(result) print(f"Failed to codemod {filename}\n", file=sys.stderr) elif isinstance(result, TransformSuccess): if show_successes or result.warning_messages: # Print any warnings, save the changes if there were any. progress.clear() print(f"Codemodding {filename}", file=sys.stderr) print_execution_result(result) print( f"Successfully codemodded {filename}" + (" with warnings\n" if result.warning_messages else "\n"), file=sys.stderr, ) # In unified diff mode, the code is a diff we must print. if unified_diff and result.code: print(result.code)
[docs] @dataclass(frozen=True) class ParallelTransformResult: """ The result of running :func:`~libcst.codemod.parallel_exec_transform_with_prettyprint` against a series of files. This is a simple summary, with counts for number of successfully codemodded files, number of files that we failed to codemod, number of warnings generated when running the codemod across the files, and the number of files that we skipped when running the codemod. """ #: Number of files that we successfully transformed. successes: int #: Number of files that we failed to transform. failures: int #: Number of warnings generated when running transform across files. warnings: int #: Number of files skipped because they were blacklisted, generated #: or the codemod requested to skip. skips: int
[docs] def parallel_exec_transform_with_prettyprint( # noqa: C901 transform: Union[Codemod, Type[Codemod]], files: Sequence[str], *, jobs: Optional[int] = None, unified_diff: Optional[int] = None, include_generated: bool = False, generated_code_marker: str = _DEFAULT_GENERATED_CODE_MARKER, format_code: bool = False, formatter_args: Sequence[str] = (), show_successes: bool = False, hide_generated: bool = False, hide_blacklisted: bool = False, hide_progress: bool = False, blacklist_patterns: Sequence[str] = (), python_version: Optional[str] = None, repo_root: Optional[str] = None, codemod_args: Optional[Dict[str, object]] = None, ) -> ParallelTransformResult: """ Given a list of files and a codemod we should apply to them, fork and apply the codemod in parallel to all of the files, including any configured formatter. The ``jobs`` parameter controls the maximum number of in-flight transforms, and needs to be at least 1. If not included, the number of jobs will automatically be set to the number of CPU cores. If ``unified_diff`` is set to a number, changes to files will be printed to stdout with ``unified_diff`` lines of context. If it is set to ``None`` or left out, files themselves will be updated with changes and formatting. If a ``python_version`` is provided, then we will parse each source file using this version. Otherwise, we will use the version of the currently executing python binary. A progress indicator as well as any generated warnings will be printed to stderr. To supress the interactive progress indicator, set ``hide_progress`` to ``True``. Files that include the generated code marker will be skipped unless the ``include_generated`` parameter is set to ``True``. Similarly, files that match a supplied blacklist of regex patterns will be skipped. Warnings for skipping both blacklisted and generated files will be printed to stderr along with warnings generated by the codemod unless ``hide_blacklisted`` and ``hide_generated`` are set to ``True``. Files that were successfully codemodded will not be printed to stderr unless ``show_successes`` is set to ``True``. We take a :class:`~libcst.codemod._codemod.Codemod` class, or an instantiated :class:`~libcst.codemod._codemod.Codemod`. In the former case, the codemod will be instantiated for each file, with ``codemod_args`` passed in to the constructor. Passing an already instantiated :class:`~libcst.codemod._codemod.Codemod` is deprecated, because it leads to sharing of the :class:`~libcst.codemod._codemod.Codemod` instance across files, which is a common source of hard-to-track-down bugs when the :class:`~libcst.codemod._codemod.Codemod` tracks its state on the instance. """ if isinstance(transform, Codemod): warn( "Passing transformer instances to `parallel_exec_transform_with_prettyprint` " "is deprecated and will break in a future version. " "Please pass the transformer class instead.", DeprecationWarning, stacklevel=2, ) # Ensure that we have no duplicates, otherwise we might get race conditions # on write. files = sorted({os.path.abspath(f) for f in files}) total = len(files) progress = Progress(enabled=not hide_progress, total=total) chunksize = 4 # Grab number of cores if we need to jobs = min( jobs if jobs is not None else cpu_count(), (len(files) + chunksize - 1) // chunksize, ) if jobs < 1: raise Exception("Must have at least one job to process!") if total == 0: return ParallelTransformResult(successes=0, failures=0, skips=0, warnings=0) metadata_manager: Optional[FullRepoManager] = None if repo_root is not None: # Make sure if there is a root that we have the absolute path to it. repo_root = os.path.abspath(repo_root) # Spin up a full repo metadata manager so that we can provide metadata # like type inference to individual forked processes. print("Calculating full-repo metadata...", file=sys.stderr) metadata_manager = FullRepoManager( repo_root, files, transform.get_inherited_dependencies(), ) metadata_manager.resolve_cache() print("Executing codemod...", file=sys.stderr) config = ExecutionConfig( repo_root=repo_root, unified_diff=unified_diff, include_generated=include_generated, generated_code_marker=generated_code_marker, format_code=format_code, formatter_args=formatter_args, blacklist_patterns=blacklist_patterns, python_version=python_version, ) pool_impl: type[Executor] if total == 1 or jobs == 1: # Simple case, we should not pay for process overhead. # Let's just use a dummy synchronous executor. jobs = 1 pool_impl = DummyExecutor else: pool_impl = ProcessPoolExecutor # Warm the parser, pre-fork. parse_module( "", config=( PartialParserConfig(python_version=python_version) if python_version is not None else PartialParserConfig() ), ) successes: int = 0 failures: int = 0 warnings: int = 0 skips: int = 0 original_scratch = ( deepcopy(transform.context.scratch) if isinstance(transform, Codemod) else {} ) with pool_impl(max_workers=jobs) as executor: # type: ignore try: futures = [ executor.submit( _execute_transform, transformer=transform, filename=filename, config=config, original_scratch=original_scratch, codemod_args=codemod_args, repo_manager=metadata_manager, ) for filename in files ] for future in as_completed(futures): result = future.result() # Print an execution result, keep track of failures _print_parallel_result( result, progress, unified_diff=bool(unified_diff), show_successes=show_successes, hide_generated=hide_generated, hide_blacklisted=hide_blacklisted, ) progress.print(successes + failures + skips) if isinstance(result.transform_result, TransformFailure): failures += 1 elif isinstance(result.transform_result, TransformSuccess): successes += 1 elif isinstance( result.transform_result, (TransformExit, TransformSkip) ): skips += 1 warnings += len(result.transform_result.warning_messages) finally: progress.clear() # Return whether there was one or more failure. return ParallelTransformResult( successes=successes, failures=failures, skips=skips, warnings=warnings )