Source code for

# Copyright (C) 2018-2022  The Software Heritage developers
# See the AUTHORS file at the top-level directory of this distribution
# License: GNU General Public License version 3, or any later version
# See top-level LICENSE file for more information

from collections import Counter, defaultdict
import itertools
import json
import math
import operator
import re
from typing import (

import attr

from swh.core.collections import SortedList
from swh.model.hashutil import hash_to_bytes, hash_to_hex
from swh.model.model import SHA1_SIZE
from import get_partition_bounds_bytes

from . import MAPPING_NAMES, check_id_duplicates
from .exc import IndexerStorageArgumentException
from .interface import PagedResult, Sha1
from .model import (
from .writer import JournalWriter


ToolId = int

def _transform_tool(tool):
    return {
        "id": tool["id"],
        "name": tool["tool_name"],
        "version": tool["tool_version"],
        "configuration": tool["tool_configuration"],

[docs] def check_id_types(data: List[Dict[str, Any]]): """Checks all elements of the list have an 'id' whose type is 'bytes'.""" if not all(isinstance(item.get("id"), bytes) for item in data): raise IndexerStorageArgumentException("identifiers must be bytes.")
def _key_from_dict(d): return tuple(sorted(d.items())) TValue = TypeVar("TValue", bound=BaseRow)
[docs] class SubStorage(Generic[TValue]): """Implements common missing/get/add logic for each indexer type.""" _data: Dict[Sha1, Dict[Tuple, Dict[str, Any]]] _tools_per_id: Dict[Sha1, Set[ToolId]] def __init__(self, row_class: Type[TValue], tools, journal_writer): self.row_class = row_class self._tools = tools self._sorted_ids = SortedList[bytes, Sha1]() self._data = defaultdict(dict) self._journal_writer = journal_writer self._tools_per_id = defaultdict(set) def _join_indexer_configuration(self, entries): """Replaces ``entry.indexer_configuration_id`` with a full tool dict in ``entry.tool``.""" joined_entries = [] for entry in entries: # get the tool used to generate this addition tool_id = entry.indexer_configuration_id assert tool_id tool = self._tools[tool_id] entry = attr.evolve( entry, tool={ "name": tool["tool_name"], "version": tool["tool_version"], "configuration": tool["tool_configuration"], }, indexer_configuration_id=None, ) joined_entries.append(entry) return joined_entries def _key_from_dict(self, d) -> Tuple: """Like the global _key_from_dict, but filters out dict keys that don't belong in the unique key.""" return _key_from_dict({k: d[k] for k in self.row_class.UNIQUE_KEY_FIELDS})
[docs] def missing(self, keys: Iterable[Dict]) -> List[Sha1]: """List data missing from storage. Args: data (iterable): dictionaries with keys: - **id** (bytes): sha1 identifier - **indexer_configuration_id** (int): tool used to compute the results Yields: missing sha1s """ results = [] for key in keys: tool_id = key["indexer_configuration_id"] id_ = key["id"] if tool_id not in self._tools_per_id.get(id_, set()): results.append(id_) return results
[docs] def get(self, ids: Iterable[Sha1]) -> List[TValue]: """Retrieve data per id. Args: ids (iterable): sha1 checksums Yields: dict: dictionaries with the following keys: - **id** (bytes) - **tool** (dict): tool used to compute metadata - arbitrary data (as provided to `add`) """ results = [] for id_ in ids: for entry in self._data[id_].values(): entry = entry.copy() tool_id = entry.pop("indexer_configuration_id") results.append( self.row_class( id=id_, tool=_transform_tool(self._tools[tool_id]), **entry, ) ) return results
[docs] def get_all(self) -> List[TValue]: return self.get(self._sorted_ids)
[docs] def get_partition( self, indexer_configuration_id: int, partition_id: int, nb_partitions: int, page_token: Optional[str] = None, limit: int = 1000, ) -> PagedResult[Sha1]: """Retrieve ids of content with `indexer_type` within partition partition_id bound by limit. Args: **indexer_type**: Type of data content to index (mimetype, etc...) **indexer_configuration_id**: The tool used to index data **partition_id**: index of the partition to fetch **nb_partitions**: total number of partitions to split into **page_token**: opaque token used for pagination **limit**: Limit result (default to 1000) **with_textual_data** (bool): Deal with only textual content (True) or all content (all contents by defaults, False) Raises: IndexerStorageArgumentException for; - limit to None - wrong indexer_type provided Returns: PagedResult of Sha1. If next_page_token is None, there is no more data to fetch """ if limit is None: raise IndexerStorageArgumentException("limit should not be None") (start, end) = get_partition_bounds_bytes( partition_id, nb_partitions, SHA1_SIZE ) if page_token: start = hash_to_bytes(page_token) if end is None: end = b"\xff" * SHA1_SIZE next_page_token: Optional[str] = None ids: List[Sha1] = [] sha1s = (sha1 for sha1 in self._sorted_ids.iter_from(start)) for counter, sha1 in enumerate(sha1s): if sha1 > end: break if counter >= limit: next_page_token = hash_to_hex(sha1) break ids.append(sha1) assert len(ids) <= limit return PagedResult(results=ids, next_page_token=next_page_token)
[docs] def add(self, data: Iterable[TValue]) -> int: """Add data not present in storage. Args: data (iterable): dictionaries with keys: - **id**: sha1 - **indexer_configuration_id**: tool used to compute the results - arbitrary data """ data = list(data) data_with_tools = self._join_indexer_configuration(data) check_id_duplicates(data_with_tools) object_type = self.row_class.object_type # type: ignore self._journal_writer.write_additions(object_type, data_with_tools) count = 0 for obj, obj_with_tool in zip(data, data_with_tools): item = obj.to_dict() id_ = item.pop("id") tool_id = item["indexer_configuration_id"] key = _key_from_dict(obj_with_tool.unique_key()) self._data[id_][key] = item self._tools_per_id[id_].add(tool_id) count += 1 if id_ not in self._sorted_ids: self._sorted_ids.add(id_) return count
[docs] class IndexerStorage: """In-memory SWH indexer storage.""" def __init__(self, journal_writer=None): self._tools = {} self.journal_writer = JournalWriter(journal_writer) args = (self._tools, self.journal_writer) self._mimetypes = SubStorage(ContentMimetypeRow, *args) self._licenses = SubStorage(ContentLicenseRow, *args) self._content_metadata = SubStorage(ContentMetadataRow, *args) self._directory_intrinsic_metadata = SubStorage( DirectoryIntrinsicMetadataRow, *args ) self._origin_intrinsic_metadata = SubStorage(OriginIntrinsicMetadataRow, *args) self._origin_extrinsic_metadata = SubStorage(OriginExtrinsicMetadataRow, *args)
[docs] def check_config(self, *, check_write): return True
[docs] def content_mimetype_missing( self, mimetypes: Iterable[Dict] ) -> List[Tuple[Sha1, int]]: return self._mimetypes.missing(mimetypes)
[docs] def content_mimetype_get_partition( self, indexer_configuration_id: int, partition_id: int, nb_partitions: int, page_token: Optional[str] = None, limit: int = 1000, ) -> PagedResult[Sha1]: return self._mimetypes.get_partition( indexer_configuration_id, partition_id, nb_partitions, page_token, limit )
[docs] def content_mimetype_add( self, mimetypes: List[ContentMimetypeRow] ) -> Dict[str, int]: added = self._mimetypes.add(mimetypes) return {"content_mimetype:add": added}
[docs] def content_mimetype_get(self, ids: Iterable[Sha1]) -> List[ContentMimetypeRow]: return self._mimetypes.get(ids)
[docs] def content_fossology_license_get( self, ids: Iterable[Sha1] ) -> List[ContentLicenseRow]: return self._licenses.get(ids)
[docs] def content_fossology_license_add( self, licenses: List[ContentLicenseRow] ) -> Dict[str, int]: added = self._licenses.add(licenses) return {"content_fossology_license:add": added}
[docs] def content_fossology_license_get_partition( self, indexer_configuration_id: int, partition_id: int, nb_partitions: int, page_token: Optional[str] = None, limit: int = 1000, ) -> PagedResult[Sha1]: return self._licenses.get_partition( indexer_configuration_id, partition_id, nb_partitions, page_token, limit )
[docs] def content_metadata_missing( self, metadata: Iterable[Dict] ) -> List[Tuple[Sha1, int]]: return self._content_metadata.missing(metadata)
[docs] def content_metadata_get(self, ids: Iterable[Sha1]) -> List[ContentMetadataRow]: return self._content_metadata.get(ids)
[docs] def content_metadata_add( self, metadata: List[ContentMetadataRow] ) -> Dict[str, int]: added = self._content_metadata.add(metadata) return {"content_metadata:add": added}
[docs] def directory_intrinsic_metadata_missing( self, metadata: Iterable[Dict] ) -> List[Tuple[Sha1, int]]: return self._directory_intrinsic_metadata.missing(metadata)
[docs] def directory_intrinsic_metadata_get( self, ids: Iterable[Sha1] ) -> List[DirectoryIntrinsicMetadataRow]: return self._directory_intrinsic_metadata.get(ids)
[docs] def directory_intrinsic_metadata_add( self, metadata: List[DirectoryIntrinsicMetadataRow] ) -> Dict[str, int]: added = self._directory_intrinsic_metadata.add(metadata) return {"directory_intrinsic_metadata:add": added}
[docs] def origin_intrinsic_metadata_get( self, urls: Iterable[str] ) -> List[OriginIntrinsicMetadataRow]: return self._origin_intrinsic_metadata.get(urls)
[docs] def origin_intrinsic_metadata_add( self, metadata: List[OriginIntrinsicMetadataRow] ) -> Dict[str, int]: added = self._origin_intrinsic_metadata.add(metadata) return {"origin_intrinsic_metadata:add": added}
[docs] def origin_intrinsic_metadata_search_fulltext( self, conjunction: List[str], limit: int = 100 ) -> List[OriginIntrinsicMetadataRow]: # A very crude fulltext search implementation, but that's enough # to work on English metadata tokens_re = re.compile("[a-zA-Z0-9]+") search_tokens = list(itertools.chain(*map(tokens_re.findall, conjunction))) def rank(data): # Tokenize the metadata text = json.dumps(data.metadata) text_tokens = tokens_re.findall(text) text_token_occurences = Counter(text_tokens) # Count the number of occurrences of search tokens in the text score = 0 for search_token in search_tokens: if text_token_occurences[search_token] == 0: # Search token is not in the text. return 0 score += text_token_occurences[search_token] # Normalize according to the text's length return score / math.log(len(text_tokens)) results = [ (rank(data), data) for data in self._origin_intrinsic_metadata.get_all() ] results = [(rank_, data) for (rank_, data) in results if rank_ > 0] results.sort( key=operator.itemgetter(0), reverse=True # Don't try to order 'data' ) return [result for (rank_, result) in results[:limit]]
[docs] def origin_intrinsic_metadata_search_by_producer( self, page_token: str = "", limit: int = 100, ids_only: bool = False, mappings: Optional[List[str]] = None, tool_ids: Optional[List[int]] = None, ) -> PagedResult[Union[str, OriginIntrinsicMetadataRow]]: assert isinstance(page_token, str) nb_results = 0 if mappings is not None: mapping_set = frozenset(mappings) if tool_ids is not None: tool_id_set = frozenset(tool_ids) rows = [] # we go to limit+1 to check whether we should add next_page_token in # the response for entry in self._origin_intrinsic_metadata.get_all(): if <= page_token: continue if nb_results >= (limit + 1): break if mappings and mapping_set.isdisjoint(entry.mappings): continue if tool_ids and entry.tool["id"] not in tool_id_set: continue rows.append(entry) nb_results += 1 if len(rows) > limit: rows = rows[:limit] next_page_token = rows[-1].id else: next_page_token = None if ids_only: rows = [ for row in rows] return PagedResult( results=rows, next_page_token=next_page_token, )
[docs] def origin_intrinsic_metadata_stats(self): mapping_count = {m: 0 for m in MAPPING_NAMES} total = non_empty = 0 for data in self._origin_intrinsic_metadata.get_all(): total += 1 if set(data.metadata) - {"@context"}: non_empty += 1 for mapping in data.mappings: mapping_count[mapping] += 1 return {"per_mapping": mapping_count, "total": total, "non_empty": non_empty}
[docs] def origin_extrinsic_metadata_get( self, urls: Iterable[str] ) -> List[OriginExtrinsicMetadataRow]: return self._origin_extrinsic_metadata.get(urls)
[docs] def origin_extrinsic_metadata_add( self, metadata: List[OriginExtrinsicMetadataRow] ) -> Dict[str, int]: added = self._origin_extrinsic_metadata.add(metadata) return {"origin_extrinsic_metadata:add": added}
[docs] def indexer_configuration_add(self, tools): inserted = [] for tool in tools: tool = tool.copy() id_ = self._tool_key(tool) tool["id"] = id_ self._tools[id_] = tool inserted.append(tool) return inserted
[docs] def indexer_configuration_get(self, tool): return self._tools.get(self._tool_key(tool))
def _tool_key(self, tool): return hash( ( tool["tool_name"], tool["tool_version"], json.dumps(tool["tool_configuration"], sort_keys=True), ) )