# python3
# Copyright 2020 The ChromiumOS Authors
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Proto-related helper functions."""

import importlib
import os

from typing import Any, Dict, List, Set, NamedTuple

from google.protobuf import message as pb_message
from google.protobuf import symbol_database
from google.protobuf.descriptor import FieldDescriptor

from chromiumos.config.public_replication import public_replication_pb2


def _build_type_map():
  """Build a map from the TYPE_* constants in protobuf to string names."""
  mapping = {}
  for field in dir(FieldDescriptor):
    if field.startswith("TYPE_"):
      mapping[getattr(FieldDescriptor, field)] = field[5:].lower()
  return mapping


type_strings = _build_type_map()


class FieldInfo(NamedTuple):
  """Named tuple to represent information about a proto field.

  Fields:
    name:     Name of the field in the message
    typeid:   FieldDescriptor type for the field
    typename: For compound fields, the name of the message type.
              For value fields, a string-ified type name
    repeated: True if the field is repeated
  """
  name: str
  typeid: int
  typename: str
  repeated: bool


def create_symbol_db() -> symbol_database.SymbolDatabase():
  """Load any generated messages from python/ and return symbol database.

  Messages auto-register when imported, so we just recursively import and
  generate protobuffer files and return the default instance of SymbolDatabase.

  Returns:
      symbol_database.Default()
  """

  def __import_modules(dirname: str, paths: [str]):
    """Recurse through a list of paths and automatically load protobufs.

      This starts with dirname and recursively descends looking for python files
      ending with _pb2.py and loads them into the current name space.

      Args:
        dirname: Directory name to process
        paths: list of parent paths names for current call
      """
    for path in os.listdir(dirname):
      full_path = os.path.join(dirname, path)

      if os.path.isdir(full_path) and not os.path.islink(full_path):
        __import_modules(full_path, paths + [path])
      elif os.path.isfile(full_path):
        if path.endswith("_pb2.py"):
          importlib.import_module('%s.%s' % ('.'.join(paths), path[:-3]))

  __import_modules(
      os.path.join(os.path.dirname(__file__), "../../python/chromiumos"),
      ["chromiumos"],
  )
  return symbol_database.Default()


def resolve_field_path(
    message: pb_message.Message,
    path: str,
) -> List[FieldInfo]:
  """Resolve a dotted field path into specific information about the fields.

  A field path is of the format foo.bar.baz where the dotted notation .field
  indicates a particular field of the preceding message type.

  We resolve this by iteratively looking up each field starting with a root
  message type, and populating information about it.

  The result is a list of FieldInfo instances, one per field.  If a field
  is not found, then None is returned for it and subsequent fields.

  Args:
    message: a protobuffer Message type to root the path in
    path: a dotted field path
  """

  fields = path.split('.')
  infos = [None] * len(fields)

  current = message.DESCRIPTOR
  for idx, field in enumerate(fields):
    descriptor = current.fields_by_name.get(field)
    if not descriptor:
      break

    typename = type_strings[descriptor.type]
    if descriptor.message_type:
      typename = descriptor.message_type.name

    infos[idx] = FieldInfo(
        name=field,
        typeid=descriptor.type,
        typename=typename,
        repeated=(descriptor.label == descriptor.LABEL_REPEATED),
    )

    # If field isn't a message type then we're done
    if descriptor.type != descriptor.TYPE_MESSAGE:
      break

    current = descriptor.message_type

  return infos


def get_all_fields(message: pb_message.Message) -> List[Any]:
  """Returns the value of each field in message.

  Note that the value, not the name, is returned. For example, given a Timestamp
  message:

  {
    "seconds": 1,
    "nanos": 2
  }

  the result is [1, 2].
  """
  fields = []
  for field_descriptor in message.DESCRIPTOR.fields:
    fields.append(getattr(message, field_descriptor.name))
  return fields


def get_dep_graph(message: pb_message.Message) -> Dict[str, List[str]]:
  """Compute the dep graph of a message.

  This is a sparse representation of a DAG as a dict where the key is the
  name of a message, and the value is the list of that message's
  dependencies.
  """

  def helper(dep_graph, descriptor):
    deps = set()
    for field in descriptor.fields:
      if field.type == field.TYPE_MESSAGE:
        deps.add(field.message_type.full_name)
        helper(dep_graph, field.message_type)
    dep_graph[descriptor.full_name] = sorted(deps)

  graph = {}
  helper(graph, message.DESCRIPTOR)
  return graph


def get_dep_order(message: pb_message.Message) -> List[str]:
  """Compute dependency order of protobuf type and its dependencies.

  This is a list from a preorder traversal of the dependency graph above.
  """

  def dfs(graph, callback, node, seen=None):
    if seen is None:
      seen = set()

    if node in graph:
      for child in graph[node]:
        dfs(graph, callback, child, seen)

    if not node in seen:
      callback(node)
    seen.add(node)

  deps = []
  dfs(get_dep_graph(message), deps.append, message.DESCRIPTOR.full_name)
  return deps


def apply_public_replication(src: pb_message.Message, dst: pb_message.Message):
  """Traverses src and merges fields to dst when a PublicReplication message is
  found.

  See the comment on the PublicReplication proto for a complete description of
  the semantics of PublicReplication.

  Args:
    src: Source message.
    dst: Destination message to be merged into.
  """
  __apply_public_replication_internal(src, dst, visited_messages=set())


def __apply_public_replication_internal(src: pb_message.Message,
                                        dst: pb_message.Message,
                                        visited_messages=Set[str]):
  """Private function to do most of the work of apply_public_replication.

  Allows bookkeeping information to be passed between recursive calls, along
  with the src and dst messages.

  Args:
    src: Source message.
    dst: Destination message to be merged into.
    visited_messages: Set of the full message names that have been visited
      higher in the call stack. Used to prevent infinite recursion if a message
      references itself.
  """
  if src.DESCRIPTOR.full_name != dst.DESCRIPTOR.full_name:
    raise ValueError(
        'src and dst must be the same message type. Got '
        f'{src.DESCRIPTOR.full_name} and {dst.DESCRIPTOR.full_name}')

  # If a message with the same type as src has been visited higher in the call
  # stack, stop here. Then, create a new set with src's name in it. Note that
  # it doesn't work to add src's name to visited_messages, because a message
  # with the same type as src might be visited after this function exists, e.g.
  # in a list of messages with the same type.
  if src.DESCRIPTOR.full_name in visited_messages:
    return

  visited_messages = visited_messages.union([src.DESCRIPTOR.full_name])

  # First, see if any of the fields on src are a PublicReplication message. If
  # one is found, apply the field mask within it.
  for field_descriptor in src.DESCRIPTOR.fields:
    message_descriptor = field_descriptor.message_type
    if (message_descriptor and message_descriptor.full_name
        == public_replication_pb2.PublicReplication.DESCRIPTOR.full_name):
      public_fields = getattr(src, field_descriptor.name).public_fields
      public_fields.MergeMessage(src, dst)

  # Iterate the fields of src and call __apply_public_replication_internal
  # recursively.
  for field_descriptor in src.DESCRIPTOR.fields:
    if field_descriptor.type != field_descriptor.TYPE_MESSAGE:
      continue

    if field_descriptor.label == field_descriptor.LABEL_REPEATED:
      # For repeated fields, for each message in src, create a new message in
      # dst and call __apply_public_replication_internal.
      for next_src in getattr(src, field_descriptor.name):
        # map fields are considered repeated messages, but do not have an 'add'
        # method. Skip this case. It wasn't clear if there was a better way to
        # detect a map field via the descriptor.
        dst_field = getattr(dst, field_descriptor.name)
        if hasattr(dst_field, 'add'):
          next_dst = dst_field.add()
          __apply_public_replication_internal(next_src, next_dst,
                                              visited_messages)
          # If the newly added field doesn't have any fields set, remove it to
          # avoid creating many empty messages on dst.
          if not dst_field[-1].ByteSize():
            dst_field.pop()
    else:
      # For non-repeated fields, get the field in src and dst and call
      # __apply_public_replication_internal.
      next_src = getattr(src, field_descriptor.name)
      next_dst = getattr(dst, field_descriptor.name)
      __apply_public_replication_internal(next_src, next_dst, visited_messages)
      # If the newly added field doesn't have any fields set, remove it to
      # avoid creating many empty messages on dst, unless it was also empty on
      # src, since the presence of message fields may be meaningful in some
      # cases. Additionally, this avoids clobbering fields nested within a
      # message in a oneof where the currently-set oneof is a different field.
      if not next_dst.ByteSize() and next_src.ByteSize():
        dst.ClearField(field_descriptor.name)