# Copyright (C) 2016-2018 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 import abc import ast import os import logging import shutil import tempfile import datetime from copy import deepcopy from contextlib import contextmanager from swh.scheduler import get_scheduler from swh.storage import get_storage from swh.core.config import SWHConfig from swh.objstorage import get_objstorage from swh.objstorage.exc import ObjNotFoundError from swh.indexer.storage import get_indexer_storage, INDEXER_CFG_KEY from swh.model import hashutil from swh.core import utils @contextmanager def write_to_temp(filename, data, working_directory): """Write the sha1's content in a temporary file. Args: filename (str): one of sha1's many filenames data (bytes): the sha1's content to write in temporary file Returns: The path to the temporary file created. That file is filled in with the raw content's data. """ os.makedirs(working_directory, exist_ok=True) temp_dir = tempfile.mkdtemp(dir=working_directory) content_path = os.path.join(temp_dir, filename) with open(content_path, 'wb') as f: f.write(data) yield content_path shutil.rmtree(temp_dir) class BaseIndexer(SWHConfig, metaclass=abc.ABCMeta): """Base class for indexers to inherit from. The main entry point is the :func:`run` function which is in charge of triggering the computations on the batch dict/ids received. Indexers can: - filter out ids whose data has already been indexed. - retrieve ids data from storage or objstorage - index this data depending on the object and store the result in storage. To implement a new object type indexer, inherit from the BaseIndexer and implement indexing: :meth:`~BaseIndexer.run`: object_ids are different depending on object. For example: sha1 for content, sha1_git for revision, directory, release, and id for origin To implement a new concrete indexer, inherit from the object level classes: :class:`ContentIndexer`, :class:`RevisionIndexer`, :class:`OriginIndexer`. Then you need to implement the following functions: :meth:`~BaseIndexer.filter`: filter out data already indexed (in storage). :meth:`~BaseIndexer.index_object`: compute index on id with data (retrieved from the storage or the objstorage by the id key) and return the resulting index computation. :meth:`~BaseIndexer.persist_index_computations`: persist the results of multiple index computations in the storage. The new indexer implementation can also override the following functions: :meth:`~BaseIndexer.prepare`: Configuration preparation for the indexer. When overriding, this must call the `super().prepare()` instruction. :meth:`~BaseIndexer.check`: Configuration check for the indexer. When overriding, this must call the `super().check()` instruction. :meth:`~BaseIndexer.register_tools`: This should return a dict of the tool(s) to use when indexing or filtering. """ CONFIG = 'indexer/base' DEFAULT_CONFIG = { INDEXER_CFG_KEY: ('dict', { 'cls': 'remote', 'args': { 'url': 'http://localhost:5007/' } }), 'storage': ('dict', { 'cls': 'remote', 'args': { 'url': 'http://localhost:5002/', } }), 'objstorage': ('dict', { 'cls': 'remote', 'args': { 'url': 'http://localhost:5003/', } }) } ADDITIONAL_CONFIG = {} USE_TOOLS = True def __init__(self, config=None, **kw): """Prepare and check that the indexer is ready to run. """ super().__init__() if config is not None: self.config = config else: config_keys = ('base_filename', 'config_filename', 'additional_configs', 'global_config') config_args = {k: v for k, v in kw.items() if k in config_keys} if self.ADDITIONAL_CONFIG: config_args.setdefault('additional_configs', []).append( self.ADDITIONAL_CONFIG) self.config = self.parse_config_file(**config_args) self.prepare() self.check() self.log.debug('%s: config=%s', self, self.config) def prepare(self): """Prepare the indexer's needed runtime configuration. Without this step, the indexer cannot possibly run. """ config_storage = self.config.get('storage') if config_storage: self.storage = get_storage(**config_storage) objstorage = self.config['objstorage'] self.objstorage = get_objstorage(objstorage['cls'], objstorage['args']) idx_storage = self.config[INDEXER_CFG_KEY] self.idx_storage = get_indexer_storage(**idx_storage) _log = logging.getLogger('requests.packages.urllib3.connectionpool') _log.setLevel(logging.WARN) self.log = logging.getLogger('swh.indexer') if self.USE_TOOLS: self.tools = list(self.register_tools( self.config.get('tools', []))) self.results = [] @property def tool(self): return self.tools[0] def check(self): """Check the indexer's configuration is ok before proceeding. If ok, does nothing. If not raise error. """ if self.USE_TOOLS and not self.tools: raise ValueError('Tools %s is unknown, cannot continue' % self.tools) def _prepare_tool(self, tool): """Prepare the tool dict to be compliant with the storage api. """ return {'tool_%s' % key: value for key, value in tool.items()} def register_tools(self, tools): """Permit to register tools to the storage. Add a sensible default which can be overridden if not sufficient. (For now, all indexers use only one tool) Expects the self.config['tools'] property to be set with one or more tools. Args: tools (dict/[dict]): Either a dict or a list of dict. Returns: list: List of dicts with additional id key. Raises: ValueError: if not a list nor a dict. """ if isinstance(tools, list): tools = list(map(self._prepare_tool, tools)) elif isinstance(tools, dict): tools = [self._prepare_tool(tools)] else: raise ValueError('Configuration tool(s) must be a dict or list!') if tools: return self.idx_storage.indexer_configuration_add(tools) else: return [] def index(self, id, data): """Index computation for the id and associated raw data. Args: id (bytes): identifier data (bytes): id's data from storage or objstorage depending on object type Returns: dict: a dict that makes sense for the :meth:`.persist_index_computations` method. """ raise NotImplementedError() def filter(self, ids): """Filter missing ids for that particular indexer. Args: ids ([bytes]): list of ids Yields: iterator of missing ids """ yield from ids @abc.abstractmethod def persist_index_computations(self, results, policy_update): """Persist the computation resulting from the index. Args: results ([result]): List of results. One result is the result of the index function. policy_update ([str]): either 'update-dups' or 'ignore-dups' to respectively update duplicates or ignore them Returns: None """ pass def next_step(self, results, task): """Do something else with computations results (e.g. send to another queue, ...). (This is not an abstractmethod since it is optional). Args: results ([result]): List of results (dict) as returned by index function. task (dict): a dict in the form expected by `scheduler.backend.SchedulerBackend.create_tasks` without `next_run`, plus an optional `result_name` key. Returns: None """ if task: if getattr(self, 'scheduler', None): scheduler = self.scheduler else: scheduler = get_scheduler(**self.config['scheduler']) task = deepcopy(task) result_name = task.pop('result_name', None) task['next_run'] = datetime.datetime.now() if result_name: task['arguments']['kwargs'][result_name] = self.results scheduler.create_tasks([task]) @abc.abstractmethod def run(self, ids, policy_update, next_step=None, **kwargs): """Given a list of ids: - retrieves the data from the storage - executes the indexing computations - stores the results (according to policy_update) Args: ids ([bytes]): id's identifier list policy_update (str): either 'update-dups' or 'ignore-dups' to respectively update duplicates or ignore them next_step (dict): a dict in the form expected by `scheduler.backend.SchedulerBackend.create_tasks` without `next_run`, plus a `result_name` key. **kwargs: passed to the `index` method """ pass class ContentIndexer(BaseIndexer): """A content indexer working on a list of ids directly. To work on indexer range, use the :class:`ContentRangeIndexer` instead. Note: :class:`ContentIndexer` is not an instantiable object. To use it, one should inherit from this class and override the methods mentioned in the :class:`BaseIndexer` class. """ def run(self, ids, policy_update, next_step=None, **kwargs): """Given a list of ids: - retrieve the content from the storage - execute the indexing computations - store the results (according to policy_update) Args: ids (Iterable[Union[bytes, str]]): sha1's identifier list policy_update (str): either 'update-dups' or 'ignore-dups' to respectively update duplicates or ignore them next_step (dict): a dict in the form expected by `scheduler.backend.SchedulerBackend.create_tasks` without `next_run`, plus an optional `result_name` key. **kwargs: passed to the `index` method """ ids = [hashutil.hash_to_bytes(id_) if isinstance(id_, str) else id_ for id_ in ids] results = [] try: for sha1 in ids: try: raw_content = self.objstorage.get(sha1) except ObjNotFoundError: self.log.warning('Content %s not found in objstorage' % hashutil.hash_to_hex(sha1)) continue res = self.index(sha1, raw_content, **kwargs) if res: # If no results, skip it results.append(res) self.persist_index_computations(results, policy_update) self.results = results return self.next_step(results, task=next_step) except Exception: self.log.exception( 'Problem when reading contents metadata.') class ContentRangeIndexer(BaseIndexer): """A content range indexer. This expects as input a range of ids to index. To work on a list of ids, use the :class:`ContentIndexer` instead. Note: :class:`ContentRangeIndexer` is not an instantiable object. To use it, one should inherit from this class and override the methods mentioned in the :class:`BaseIndexer` class. """ @abc.abstractmethod def indexed_contents_in_range(self, start, end): """Retrieve indexed contents within range [start, end]. Args: start (bytes): Starting bound from range identifier end (bytes): End range identifier Yields: bytes: Content identifier present in the range ``[start, end]`` """ pass def _list_contents_to_index(self, start, end, indexed): """Compute from storage the new contents to index in the range [start, end]. The already indexed contents are skipped. Args: start (bytes): Starting bound from range identifier end (bytes): End range identifier indexed (Set[bytes]): Set of content already indexed. Yields: bytes: Identifier of contents to index. """ if not isinstance(start, bytes) or not isinstance(end, bytes): raise TypeError('identifiers must be bytes, not %r and %r.' % (start, end)) while start: result = self.storage.content_get_range(start, end) contents = result['contents'] for c in contents: _id = hashutil.hash_to_bytes(c['sha1']) if _id in indexed: continue yield _id start = result['next'] def _index_contents(self, start, end, indexed, **kwargs): """Index the contents from within range [start, end] Args: start (bytes): Starting bound from range identifier end (bytes): End range identifier indexed (Set[bytes]): Set of content already indexed. Yields: dict: Data indexed to persist using the indexer storage """ for sha1 in self._list_contents_to_index(start, end, indexed): try: raw_content = self.objstorage.get(sha1) except ObjNotFoundError: self.log.warning('Content %s not found in objstorage' % hashutil.hash_to_hex(sha1)) continue res = self.index(sha1, raw_content, **kwargs) if res: if not isinstance(res['id'], bytes): raise TypeError( '%r.index should return ids as bytes, not %r' % (self.__class__.__name__, res['id'])) yield res def _index_with_skipping_already_done(self, start, end): """Index not already indexed contents in range [start, end]. Args: start** (Union[bytes, str]): Starting range identifier end (Union[bytes, str]): Ending range identifier Yields: bytes: Content identifier present in the range ``[start, end]`` which are not already indexed. """ while start: indexed_page = self.indexed_contents_in_range(start, end) contents = indexed_page['ids'] _end = contents[-1] if contents else end yield from self._index_contents( start, _end, contents) start = indexed_page['next'] def run(self, start, end, skip_existing=True, **kwargs): """Given a range of content ids, compute the indexing computations on the contents within. Either the indexer is incremental (filter out existing computed data) or not (compute everything from scratch). Args: start (Union[bytes, str]): Starting range identifier end (Union[bytes, str]): Ending range identifier skip_existing (bool): Skip existing indexed data (default) or not **kwargs: passed to the `index` method Returns: bool: True if data was indexed, False otherwise. """ with_indexed_data = False try: if isinstance(start, str): start = hashutil.hash_to_bytes(start) if isinstance(end, str): end = hashutil.hash_to_bytes(end) if skip_existing: gen = self._index_with_skipping_already_done(start, end) else: gen = self._index_contents(start, end, indexed=[]) for results in utils.grouper(gen, n=self.config['write_batch_size']): self.persist_index_computations( results, policy_update='update-dups') with_indexed_data = True except Exception: self.log.exception( 'Problem when computing metadata.') finally: return with_indexed_data def origin_get_params(id_): """From any of the two types of origin identifiers (int or type+url), returns a dict that can be passed to Storage.origin_get. Also accepts JSON-encoded forms of these (used via the task scheduler). >>> from pprint import pprint >>> origin_get_params(123) {'id': 123} >>> pprint(origin_get_params(['git', 'https://example.com/foo.git'])) {'type': 'git', 'url': 'https://example.com/foo.git'} >>> origin_get_params("123") {'id': 123} >>> pprint(origin_get_params('["git", "https://example.com/foo.git"]')) {'type': 'git', 'url': 'https://example.com/foo.git'} """ if isinstance(id_, str): # Data coming from JSON, which requires string keys, so # one extra level of deserialization is needed id_ = ast.literal_eval(id_) if isinstance(id_, (tuple, list)): if len(id_) != 2: raise TypeError('Expected a (type, url) tuple.') (type_, url) = id_ params = {'type': type_, 'url': url} elif isinstance(id_, int): params = {'id': id_} else: raise TypeError('Invalid value in "ids": %r' % id_) return params class OriginIndexer(BaseIndexer): """An object type indexer, inherits from the :class:`BaseIndexer` and implements Origin indexing using the run method Note: the :class:`OriginIndexer` is not an instantiable object. To use it in another context one should inherit from this class and override the methods mentioned in the :class:`BaseIndexer` class. """ def run(self, ids, policy_update='update-dups', parse_ids=True, next_step=None, **kwargs): """Given a list of origin ids: - retrieve origins from storage - execute the indexing computations - store the results (according to policy_update) Args: ids ([Union[int, Tuple[str, bytes]]]): list of origin ids or (type, url) tuples. policy_update (str): either 'update-dups' or 'ignore-dups' to respectively update duplicates (default) or ignore them next_step (dict): a dict in the form expected by `scheduler.backend.SchedulerBackend.create_tasks` without `next_run`, plus an optional `result_name` key. parse_ids (bool): Do we need to parse id or not (default) **kwargs: passed to the `index` method """ if parse_ids: ids = [o.split('+', 1) if ':' in o else int(o) # type+url or id for o in ids] origins_filtered = [] origins = self.storage.origin_get( [origin_get_params(id_) for id_ in ids]) for (id_, origin) in zip(ids, origins): if not origin: self.log.warning('Origin %s not found in storage' % id_) continue origins_filtered.append(origin) results = self.index_list(origins_filtered, **kwargs) self.persist_index_computations(results, policy_update) self.results = results return self.next_step(results, task=next_step) def index_list(self, origins, **kwargs): results = [] for origin in origins: try: res = self.index(origin, **kwargs) if res: # If no results, skip it results.append(res) except Exception: self.log.exception( 'Problem when processing origin %s', origin['id']) return results class RevisionIndexer(BaseIndexer): """An object type indexer, inherits from the :class:`BaseIndexer` and implements Revision indexing using the run method Note: the :class:`RevisionIndexer` is not an instantiable object. To use it in another context one should inherit from this class and override the methods mentioned in the :class:`BaseIndexer` class. """ def run(self, ids, policy_update, next_step=None): """Given a list of sha1_gits: - retrieve revisions from storage - execute the indexing computations - store the results (according to policy_update) Args: ids ([bytes or str]): sha1_git's identifier list policy_update (str): either 'update-dups' or 'ignore-dups' to respectively update duplicates or ignore them """ results = [] ids = [hashutil.hash_to_bytes(id_) if isinstance(id_, str) else id_ for id_ in ids] revs = self.storage.revision_get(ids) for rev in revs: if not rev: self.log.warning('Revisions %s not found in storage' % list(map(hashutil.hash_to_hex, ids))) continue try: res = self.index(rev) if res: # If no results, skip it results.append(res) except Exception: self.log.exception( 'Problem when processing revision') self.persist_index_computations(results, policy_update) self.results = results return self.next_step(results, task=next_step)