def execute(self, arguments):
"""Task code.
:param arguments: dictionary with task arguments
:return: {}, results
"""
self._strict_assert(arguments.get('name'))
self._strict_assert(arguments.get('ecosystem'))
# get rid of version if scheduled from the core analyses
arguments.pop('version', None)
arguments.pop('document_id', None)
db = self.storage.session
try:
ecosystem = Ecosystem.by_name(db, arguments['ecosystem'])
except NoResultFound:
raise FatalTaskError('Unknown ecosystem: %r' %
arguments['ecosystem'])
package = Package.get_or_create(db,
ecosystem_id=ecosystem.id,
name=arguments['name'])
url = self.get_upstream_url(arguments)
upstream = self.get_upstream_entry(package, url)
if upstream is None:
upstream = self.add_or_update_upstream(package, url)
arguments['url'] = upstream.url
if not arguments.get('force'):
# can potentially schedule two flows of a same type at the same
# time as there is no lock, but let's say it's OK
if upstream.updated_at is not None \
and datetime.datetime.utcnow() - upstream.updated_at < self._UPDATE_INTERVAL:
self.log.info(
'Skipping upstream package check as data are considered as recent - '
'last update %s.', upstream.updated_at)
# keep track of start, but do not schedule nothing more
# discard changes like updates
db.rollback()
return arguments
# if this fails, it's actually OK, as there could be concurrency
package_analysis = PackageAnalysis(
package_id=package.id,
started_at=datetime.datetime.utcnow(),
finished_at=None)
db.add(package_analysis)
# keep track of updates
upstream.updated_at = datetime.datetime.utcnow()
db.commit()
arguments['document_id'] = package_analysis.id
return arguments
def execute(self, arguments):
self._strict_assert(arguments.get('name'))
self._strict_assert(arguments.get('ecosystem'))
# get rid of version if scheduled from the core analyses
arguments.pop('version', None)
db = self.storage.session
ecosystem = Ecosystem.by_name(db, arguments['ecosystem'])
package = Package.get_or_create(db,
ecosystem_id=ecosystem.id,
name=arguments['name'])
upstream = self.get_upstream_entry(db, package,
self.get_upstream_url(arguments))
arguments['url'] = upstream.url
if not arguments.get('force'):
# can potentially schedule two flows of a same type at the same
# time as there is no lock, but let's say it's OK
if upstream.updated_at is not None \
and upstream.updated_at - datetime.datetime.now() < self._UPDATE_INTERVAL:
self.log.info(
'Skipping upstream package check as data are considered as recent - '
'last update %s.', upstream.updated_at)
# keep track of start, but do not schedule nothing more
# discard changes like updates
db.rollback()
return arguments
# if this fails, it's actually OK, as there could be concurrency
package_analysis = PackageAnalysis(package_id=package.id,
started_at=datetime.datetime.now(),
finished_at=None)
db.add(package_analysis)
# keep track of updates
upstream.updated_at = datetime.datetime.now()
db.commit()
arguments['document_id'] = package_analysis.id
return arguments
def execute(self, arguments):
"""Task code.
:param arguments: dictionary with task arguments
:return: {}, results
"""
self.log.debug("Input Arguments: {}".format(arguments))
self._strict_assert(arguments.get('name'))
self._strict_assert(arguments.get('version'))
self._strict_assert(arguments.get('ecosystem'))
# make sure we store package name based on ecosystem package naming case sensitivity
arguments['name'] = normalize_package_name(arguments['ecosystem'], arguments['name'])
db = self.storage.session
try:
ecosystem = Ecosystem.by_name(db, arguments['ecosystem'])
except NoResultFound:
raise FatalTaskError('Unknown ecosystem: %r' % arguments['ecosystem'])
p = Package.get_or_create(db, ecosystem_id=ecosystem.id, name=arguments['name'])
v = Version.get_or_create(db, package_id=p.id, identifier=arguments['version'])
if not arguments.get('force'):
# TODO: this is OK for now, but if we will scale and there will be
# 2+ workers running this task they can potentially schedule two
# flows of a same type at the same time
if db.query(Analysis).filter(Analysis.version_id == v.id).count() > 0:
# we need to propagate flags that were passed to flow, but not
# E/P/V - this way we are sure that for example graph import is
# scheduled (arguments['force_graph_sync'] == True)
arguments.pop('name')
arguments.pop('version')
arguments.pop('ecosystem')
self.log.debug("Arguments returned by initAnalysisFlow without force: {}"
.format(arguments))
return arguments
cache_path = mkdtemp(dir=self.configuration.WORKER_DATA_DIR)
epv_cache = ObjectCache.get_from_dict(arguments)
try:
if not epv_cache.\
has_source_tarball():
_, source_tarball_path = IndianaJones.fetch_artifact(
ecosystem=ecosystem,
artifact=arguments['name'],
version=arguments['version'],
target_dir=cache_path
)
epv_cache.put_source_tarball(source_tarball_path)
if ecosystem.is_backed_by(EcosystemBackend.maven):
if not epv_cache.has_source_jar():
try:
source_jar_path = self._download_source_jar(cache_path, ecosystem,
arguments)
epv_cache.put_source_jar(source_jar_path)
except Exception as e:
self.log.info(
'Failed to fetch source jar for maven artifact "{n}/{v}": {err}'.
format(n=arguments.get('name'),
v=arguments.get('version'),
err=str(e))
)
if not epv_cache.has_pom_xml():
pom_xml_path = self._download_pom_xml(cache_path, ecosystem, arguments)
epv_cache.put_pom_xml(pom_xml_path)
finally:
# always clean up cache
shutil.rmtree(cache_path)
a = Analysis(version=v, access_count=1, started_at=datetime.datetime.utcnow())
db.add(a)
db.commit()
arguments['document_id'] = a.id
# export ecosystem backend so we can use it to easily control flow later
arguments['ecosystem_backend'] = ecosystem.backend.name
self.log.debug("Arguments returned by InitAnalysisFlow are: {}".format(arguments))
return arguments
def execute(self, arguments):
"""Task code.
:param arguments: dictionary with task arguments
:return: {}, results
"""
self.log.debug("Input Arguments: {}".format(arguments))
self._strict_assert(isinstance(arguments.get('ecosystem'), str))
self._strict_assert(isinstance(arguments.get('name'), str))
self._strict_assert(isinstance(arguments.get('version'), str))
db = self.storage.session
try:
ecosystem = Ecosystem.by_name(db, arguments['ecosystem'])
except NoResultFound:
raise FatalTaskError('Unknown ecosystem: %r' %
arguments['ecosystem'])
# make sure we store package name in its normalized form
arguments['name'] = normalize_package_name(ecosystem.backend.name,
arguments['name'])
if len(pattern_ignore.findall(arguments['version'])) > 0:
self.log.info("Incorrect version alert {} {}".format(
arguments['name'], arguments['version']))
raise NotABugFatalTaskError("Incorrect version alert {} {}".format(
arguments['name'], arguments['version']))
# Dont try ingestion for private packages
if is_pkg_public(arguments['ecosystem'], arguments['name']):
self.log.info("Ingestion flow for {} {}".format(
arguments['ecosystem'], arguments['name']))
else:
self.log.info("Private package ingestion ignored {} {}".format(
arguments['ecosystem'], arguments['name']))
raise NotABugFatalTaskError("Private package alert {} {}".format(
arguments['ecosystem'], arguments['name']))
p = Package.get_or_create(db,
ecosystem_id=ecosystem.id,
name=arguments['name'])
v = Version.get_or_create(db,
package_id=p.id,
identifier=arguments['version'])
if not arguments.get('force'):
if db.query(Analysis).filter(
Analysis.version_id == v.id).count() > 0:
arguments['analysis_already_exists'] = True
self.log.debug(
"Arguments returned by initAnalysisFlow without force: {}".
format(arguments))
return arguments
cache_path = mkdtemp(dir=self.configuration.WORKER_DATA_DIR)
epv_cache = ObjectCache.get_from_dict(arguments)
npm_dir = self.configuration.NPM_DATA_DIR
try:
if not epv_cache.\
has_source_tarball():
_, source_tarball_path = IndianaJones.fetch_artifact(
ecosystem=ecosystem,
artifact=arguments['name'],
version=arguments['version'],
target_dir=cache_path)
epv_cache.put_source_tarball(source_tarball_path)
if ecosystem.is_backed_by(EcosystemBackend.maven):
if not epv_cache.has_source_jar():
try:
source_jar_path = self._download_source_jar(
cache_path, ecosystem, arguments)
epv_cache.put_source_jar(source_jar_path)
except Exception as e:
self.log.info(
'Failed to fetch source jar for maven artifact "{n}/{v}": {err}'
.format(n=arguments.get('name'),
v=arguments.get('version'),
err=str(e)))
if not epv_cache.has_pom_xml():
pom_xml_path = self._download_pom_xml(
cache_path, ecosystem, arguments)
epv_cache.put_pom_xml(pom_xml_path)
finally:
# always clean up cache
shutil.rmtree(cache_path)
if arguments['ecosystem'] == "npm":
shutil.rmtree(npm_dir, True)
a = Analysis(version=v,
access_count=1,
started_at=datetime.datetime.utcnow())
db.add(a)
db.commit()
arguments['document_id'] = a.id
# export ecosystem backend so we can use it to easily control flow later
arguments['ecosystem_backend'] = ecosystem.backend.name
self.log.debug(
"Arguments returned by InitAnalysisFlow are: {}".format(arguments))
return arguments
