def test_api_cors_headers_disallow_any_no_matched_allowed_origins(self):
get_config().set('cors', 'allow_any_origin', 'false')
get_config().set('cors', 'allowed_origins', '["foo", "bar"]')
response = self.fetch('/api/graph', headers={'Origin': 'foobar'})
headers = dict(response.headers)
self.assertIsNone(headers.get('Access-Control-Allow-Origin'))
def send_email(subject, message, sender, recipients, image_png=None):
config = configuration.get_config()
subject = _prefix(subject)
logger.debug("Emailing:\n"
"-------------\n"
"To: %s\n"
"From: %s\n"
"Subject: %s\n"
"Message:\n"
"%s\n"
"-------------", recipients, sender, subject, message)
if not recipients or recipients == (None,):
return
if (sys.stdout.isatty() or DEBUG) and (not config.getboolean('email', 'force-send', False)):
logger.info("Not sending email when running from a tty or in debug mode")
return
config = configuration.get_config()
# Clean the recipients lists to allow multiple error-email addresses, comma
# separated in client.cfg
recipients_tmp = []
for r in recipients:
recipients_tmp.extend(r.split(','))
# Replace original recipients with the clean list
recipients = recipients_tmp
if config.get('email', 'type', None) == "ses":
send_email_ses(config, sender, subject, message, recipients, image_png)
else:
send_email_smtp(config, sender, subject, message, recipients, image_png)
def parameters(self):
return {'CONN': configuration.get_config().get('mongodb', 'mongo_conn'),
'DB': configuration.get_config().get('mongodb', 'mongo_db'),
'II_COLLECTION': '%s_%s' % (self.mongodb_output_collection_name, 'II'),
'UI_COLLECTION': '%s_%s' % (self.mongodb_output_collection_name, 'UI'),
'OUTPUT_PATH': self.output_base_path
}
def test_api_cors_headers_disallow_any(self):
get_config().set('cors', 'allow_any_origin', 'false')
get_config().set('cors', 'allowed_origins', '["foo", "bar"]')
response = self.fetch('/api/graph', headers={'Origin': 'foo'})
headers = dict(response.headers)
self.assertEqual('foo', headers['Access-Control-Allow-Origin'])
def parameters(self):
return {'OUTPUT_PATH': self.output_base_path,
'USER_CONTRIB_TABLE': 'github_sqrt_contrib_recs_%s' % self.date_string,
'GRAVATAR_TABLE': 'github_sqrt_user_gravatar_ids_%s' % self.date_string,
'USER_INTEREST_TABLE': 'github_sqrt_user_interest_recs_%s' % self.date_string,
'ITEM_ITEM_TABLE': 'github_sqrt_repo_recs_%s' % self.date_string,
'AWS_ACCESS_KEY_ID': configuration.get_config().get('dynamodb', 'aws_access_key_id'),
'AWS_SECRET_ACCESS_KEY': configuration.get_config().get('dynamodb', 'aws_secret_access_key')}
def parameters(self):
"""
This method defines the parameters that will be passed to Mortar when starting
this pigscript.
"""
return {'CONN': configuration.get_config().get('mongodb', 'mongo_conn'),
'DB': configuration.get_config().get('mongodb', 'mongo_db'),
'COLLECTION': configuration.get_config().get('mongodb', 'mongo_input_collection'),
'OUTPUT_PATH': self.output_base_path}
def __init__(self, *args, **kwargs):
super(OptionalVerticaMixin, self).__init__(*args, **kwargs)
if not self.vertica_credentials:
self.vertica_credentials = get_config().get('vertica-export', 'credentials', None)
if not self.vertica_schema:
self.vertica_schema = get_config().get('vertica-export', 'schema', None)
self.vertica_enabled = self.vertica_credentials and self.vertica_schema
def parameters(self):
return {'DATABASE_DRIVER': 'org.postgresql.Driver',
'DATABASE_TYPE': 'postgresql',
'DATABASE_HOST': '%s:%s' % (configuration.get_config().get('postgres', 'host'), configuration.get_config().get('postgres', 'port')),
'DATABASE_NAME': configuration.get_config().get('postgres', 'dbname'),
'DATABASE_USER': configuration.get_config().get('postgres', 'user'),
'II_TABLE': '%s%s' % (self.table_name_prefix, 'ii'),
'UI_TABLE': '%s%s' % (self.table_name_prefix, 'ui'),
'OUTPUT_PATH': self.output_base_path
}
def run(self):
warnings.warn("The use of SparkJob is deprecated. Please use SparkSubmitTask or PySparkTask.", stacklevel=2)
original_output_path = self.output().path
path_no_slash = original_output_path[:-2] if original_output_path.endswith("/*") else original_output_path
path_no_slash = original_output_path[:-1] if original_output_path[-1] == "/" else path_no_slash
tmp_output = luigi.hdfs.HdfsTarget(path_no_slash + "-luigi-tmp-%09d" % random.randrange(0, 1e10))
args = ["org.apache.spark.deploy.yarn.Client"]
args += ["--jar", self.jar()]
args += ["--class", self.job_class()]
for a in self.job_args():
if a == self.output().path:
# pass temporary output path to job args
logger.info("Using temp path: %s for path %s", tmp_output.path, original_output_path)
args += ["--args", tmp_output.path]
else:
args += ["--args", str(a)]
if self.spark_workers is not None:
args += ["--num-workers", self.spark_workers]
if self.spark_master_memory is not None:
args += ["--master-memory", self.spark_master_memory]
if self.spark_worker_memory is not None:
args += ["--worker-memory", self.spark_worker_memory]
queue = self.queue
if queue is not None:
args += ["--queue", queue]
env = os.environ.copy()
env["SPARK_JAR"] = configuration.get_config().get("spark", "spark-jar")
env["HADOOP_CONF_DIR"] = configuration.get_config().get("spark", "hadoop-conf-dir")
env["MASTER"] = "yarn-client"
spark_class = configuration.get_config().get("spark", "spark-class")
temp_stderr = tempfile.TemporaryFile()
logger.info("Running: %s %s", spark_class, " ".join(args))
proc = subprocess.Popen(
[spark_class] + args, stdout=subprocess.PIPE, stderr=temp_stderr, env=env, close_fds=True
)
return_code, final_state, app_id = self.track_progress(proc)
if return_code == 0 and final_state != "FAILED":
tmp_output.move(path_no_slash)
elif final_state == "FAILED":
raise SparkJobError("Spark job failed: see yarn logs for %s" % app_id)
else:
temp_stderr.seek(0)
errors = "".join((x.decode("utf8") for x in temp_stderr.readlines()))
logger.error(errors)
raise SparkJobError("Spark job failed", err=errors)
def test_api_preflight_cors_headers_disabled(self):
get_config().set('cors', 'enabled', 'false')
response = self.fetch('/api/graph', method='OPTIONS', headers={'Origin': 'foo'})
headers = dict(response.headers)
self.assertNotIn('Access-Control-Allow-Headers', headers)
self.assertNotIn('Access-Control-Allow-Methods', headers)
self.assertNotIn('Access-Control-Allow-Origin', headers)
self.assertNotIn('Access-Control-Max-Age', headers)
self.assertNotIn('Access-Control-Allow-Credentials', headers)
self.assertNotIn('Access-Control-Expose-Headers', headers)
def test_api_preflight_cors_headers_disallow_any_no_matched_allowed_origins(self):
get_config().set('cors', 'allow_any_origin', 'false')
get_config().set('cors', 'allowed_origins', '["foo", "bar"]')
response = self.fetch('/api/graph', method='OPTIONS', headers={'Origin': 'foobar'})
headers = dict(response.headers)
self.assertNotIn('Access-Control-Allow-Headers', headers)
self.assertNotIn('Access-Control-Allow-Methods', headers)
self.assertNotIn('Access-Control-Allow-Origin', headers)
self.assertNotIn('Access-Control-Max-Age', headers)
self.assertNotIn('Access-Control-Allow-Credentials', headers)
self.assertNotIn('Access-Control-Expose-Headers', headers)
def run(self):
warnings.warn("The use of SparkJob is deprecated. Please use SparkSubmitTask or PySparkTask.", stacklevel=2)
original_output_path = self.output().path
path_no_slash = original_output_path[:-2] if original_output_path.endswith('/*') else original_output_path
path_no_slash = original_output_path[:-1] if original_output_path[-1] == '/' else path_no_slash
tmp_output = luigi.contrib.hdfs.HdfsTarget(path_no_slash + '-luigi-tmp-%09d' % random.randrange(0, 1e10))
args = ['org.apache.spark.deploy.yarn.Client']
args += ['--jar', self.jar()]
args += ['--class', self.job_class()]
for a in self.job_args():
if a == self.output().path:
# pass temporary output path to job args
logger.info('Using temp path: %s for path %s', tmp_output.path, original_output_path)
args += ['--args', tmp_output.path]
else:
args += ['--args', str(a)]
if self.spark_workers is not None:
args += ['--num-workers', self.spark_workers]
if self.spark_master_memory is not None:
args += ['--master-memory', self.spark_master_memory]
if self.spark_worker_memory is not None:
args += ['--worker-memory', self.spark_worker_memory]
queue = self.queue
if queue is not None:
args += ['--queue', queue]
env = os.environ.copy()
env['SPARK_JAR'] = configuration.get_config().get('spark', 'spark-jar')
env['HADOOP_CONF_DIR'] = configuration.get_config().get('spark', 'hadoop-conf-dir')
env['MASTER'] = 'yarn-client'
spark_class = configuration.get_config().get('spark', 'spark-class')
temp_stderr = tempfile.TemporaryFile()
logger.info('Running: %s %s', spark_class, subprocess.list2cmdline(args))
proc = subprocess.Popen([spark_class] + args, stdout=subprocess.PIPE,
stderr=temp_stderr, env=env, close_fds=True)
return_code, final_state, app_id = self.track_progress(proc)
if return_code == 0 and final_state != 'FAILED':
tmp_output.move(path_no_slash)
elif final_state == 'FAILED':
raise SparkJobError('Spark job failed: see yarn logs for %s' % app_id)
else:
temp_stderr.seek(0)
errors = "".join((x.decode('utf8') for x in temp_stderr.readlines()))
logger.error(errors)
raise SparkJobError('Spark job failed', err=errors)
def _set_tables(self):
headers = {'Accept': 'application/json',
'Accept-Encoding': 'gzip',
'Content-Type': 'application/json',
'User-Agent': 'mortar-luigi'}
url = self._client_update_endpoint()
body = {'ii_table': self.table_names()['ii_table'],
'ui_table': self.table_names()['ui_table']}
auth = HTTPBasicAuth(configuration.get_config().get('recsys', 'email'),
configuration.get_config().get('recsys', 'password'))
logger.info('Setting new tables to %s at %s' % (body, url))
response = requests.put(url, data=json.dumps(body), auth=auth, headers=headers)
response.raise_for_status()
def test_api_preflight_cors_headers_disallow_any(self):
get_config().set('cors', 'allow_any_origin', 'false')
get_config().set('cors', 'allowed_origins', '["foo", "bar"]')
response = self.fetch('/api/graph', method='OPTIONS', headers={'Origin': 'foo'})
headers = dict(response.headers)
self.assertEqual(self._default_cors.allowed_headers,
headers['Access-Control-Allow-Headers'])
self.assertEqual(self._default_cors.allowed_methods,
headers['Access-Control-Allow-Methods'])
self.assertEqual('foo', headers['Access-Control-Allow-Origin'])
self.assertEqual(str(self._default_cors.max_age), headers['Access-Control-Max-Age'])
self.assertIsNone(headers.get('Access-Control-Allow-Credentials'))
self.assertIsNone(headers.get('Access-Control-Expose-Headers'))
def test_api_preflight_cors_headers_all_response_headers(self):
get_config().set('cors', 'allow_credentials', 'true')
get_config().set('cors', 'exposed_headers', 'foo, bar')
response = self.fetch('/api/graph', method='OPTIONS', headers={'Origin': 'foo'})
headers = dict(response.headers)
self.assertEqual(self._default_cors.allowed_headers,
headers['Access-Control-Allow-Headers'])
self.assertEqual(self._default_cors.allowed_methods,
headers['Access-Control-Allow-Methods'])
self.assertEqual('*', headers['Access-Control-Allow-Origin'])
self.assertEqual(str(self._default_cors.max_age), headers['Access-Control-Max-Age'])
self.assertEqual('true', headers['Access-Control-Allow-Credentials'])
self.assertEqual('foo, bar', headers['Access-Control-Expose-Headers'])
def setUp(self):
super(ServerTest, self).setUp()
get_config().remove_section('cors')
self._default_cors = luigi.server.cors()
get_config().set('cors', 'enabled', 'true')
get_config().set('cors', 'allow_any_origin', 'true')
get_config().set('cors', 'allow_null_origin', 'true')
def _get_s3_config(self, key=None):
defaults = dict(configuration.get_config().defaults())
try:
config = dict(configuration.get_config().items('s3'))
except NoSectionError:
return {}
# So what ports etc can be read without us having to specify all dtypes
for k, v in six.iteritems(config):
try:
config[k] = int(v)
except ValueError:
pass
if key:
return config.get(key)
section_only = {k: v for k, v in config.items() if k not in defaults or v != defaults[k]}
return section_only
def _get_s3_config(self, key):
try:
return configuration.get_config().get('s3', key)
except NoSectionError:
return None
except NoOptionError:
return None
def __init__(self):
configuration = get_config()
self.partner = configuration.get('paypal', 'partner', 'PayPal')
self.vendor = configuration.get('paypal', 'vendor')
self.password = configuration.get('paypal', 'password')
self.user = configuration.get('paypal', 'user', None)
self.url = configuration.get('paypal', 'url')
def send_error_email(subject, message):
"""
Sends an email to the configured error-email.
If no error-email is configured, then a message is logged.
"""
config = configuration.get_config()
receiver = config.get('core', 'error-email', None)
sns_topic = config.get('core', 'error-sns-topic', None)
if receiver:
sender = config.get('core', 'email-sender', DEFAULT_CLIENT_EMAIL)
logger.info("Sending warning email to %r", receiver)
send_email(
subject=subject,
message=message,
sender=sender,
recipients=(receiver,)
)
elif sns_topic:
logger.info("Sending warning via %r", sns_topic)
send_sns_notification(
subject=subject,
message=message,
topic=sns_topic
)
else:
logger.info("Skipping error email. Set `error-email` in the `core` "
"section of the luigi config file to receive error "
"emails.")
def send_sns_notification(subject, message, topic):
import boto.sns
config = configuration.get_config()
con = boto.sns.connect_to_region(config.get('sns', 'region', 'us-east-1'),
aws_access_key_id=config.get('sns', 'AWS_ACCESS_KEY', None),
aws_secret_access_key=config.get('sns', 'AWS_SECRET_KEY', None))
con.publish(topic, message, subject[:100])
def run(self):
self.remove_output_on_overwrite()
ppr = PaypalReportRequest(
"SettlementReport",
processor="PayPal",
start_date=self.date.isoformat() + " 00:00:00",
end_date=self.date.isoformat() + " 23:59:59",
timezone="GMT",
)
report_response = ppr.execute()
report_id = report_response.report_id
is_running = report_response.is_running
timeout = get_config().getint("paypal", "timeout", 60 * 60 * 2)
start_time = time.time()
while is_running:
if timeout >= 0 and time.time() >= (start_time + timeout):
raise PaypalTimeoutError(start_time)
time.sleep(5)
results_response = PaypalReportResultsRequest(report_id=report_id).execute()
is_running = results_response.is_running
metadata_response = PaypalReportMetadataRequest(report_id=report_id).execute()
with self.output().open("w") as output_tsv_file:
for page_num in range(metadata_response.num_pages):
data_response = PaypalReportDataRequest(report_id=report_id, page_num=(page_num + 1)).execute()
for row in data_response.rows:
self.write_transaction_record(row, output_tsv_file)
def send_email(subject, message, sender, recipients, image_png=None):
"""
Decides whether to send notification. Notification is cancelled if there are
no recipients or if stdout is onto tty or if in debug mode.
Dispatches on config value email.type. Default is 'smtp'.
"""
config = configuration.get_config()
notifiers = {'ses': send_email_ses,
'sendgrid': send_email_sendgrid,
'smtp': send_email_smtp,
'sns': send_email_sns}
subject = _prefix(subject)
if not recipients or recipients == (None,):
return
if _email_disabled():
return
# Clean the recipients lists to allow multiple error-email addresses, comma
# separated in luigi.cfg
recipients_tmp = []
for r in recipients:
recipients_tmp.extend([a.strip() for a in r.split(',') if a.strip()])
# Replace original recipients with the clean list
recipients = recipients_tmp
# Get appropriate sender and call it to send the notification
email_sender_type = config.get('email', 'type', None)
email_sender = notifiers.get(email_sender_type, send_email_smtp)
email_sender(config, sender, subject, message, recipients, image_png)
def __init__(self):
config = configuration.get_config()
connection_string = config.get('task_history', 'db_connection')
self.engine = sqlalchemy.create_engine(connection_string)
self.session_factory = sqlalchemy.orm.sessionmaker(bind=self.engine, expire_on_commit=False)
Base.metadata.create_all(self.engine)
self.tasks = {} # task_id -> TaskRecord
def test_sends_smtp_email_exceptions(self):
"""
Call notificaions.send_email_smtp when it cannot connect to smtp server (socket.error)
starttls.
"""
smtp_kws = {"host": "my.smtp.local",
"port": 999,
"local_hostname": "ptms",
"timeout": 1200}
with mock.patch('smtplib.SMTP') as SMTP:
with mock.patch('luigi.notifications.generate_email') as generate_email:
SMTP.side_effect = socket.error()
generate_email.return_value \
.as_string.return_value = self.mocked_email_msg
try:
notifications.send_email_smtp(configuration.get_config(),
*self.notification_args)
except socket.error:
self.fail("send_email_smtp() raised expection unexpectedly")
SMTP.assert_called_once_with(**smtp_kws)
self.assertEqual(notifications.generate_email.called, False)
self.assertEqual(SMTP.sendemail.called, False)
def __init__(self):
configuration = get_config()
self.partner = configuration.get("paypal", "partner", "PayPal")
self.vendor = configuration.get("paypal", "vendor")
self.password = configuration.get("paypal", "password")
self.user = configuration.get("paypal", "user", None)
self.url = configuration.get("paypal", "url")
def __init__(self, config=None, resources=None, task_history_impl=None, **kwargs):
"""
Keyword Arguments:
:param config: an object of class "scheduler" or None (in which the global instance will be used)
:param resources: a dict of str->int constraints
:param task_history_override: ignore config and use this object as the task history
"""
self._config = config or scheduler(**kwargs)
self._state = SimpleTaskState(self._config.state_path)
if task_history_impl:
self._task_history = task_history_impl
elif self._config.record_task_history:
from luigi import db_task_history # Needs sqlalchemy, thus imported here
self._task_history = db_task_history.DbTaskHistory()
else:
self._task_history = history.NopHistory()
self._resources = resources or configuration.get_config().getintdict(
"resources"
) # TODO: Can we make this a Parameter?
self._make_task = functools.partial(
Task,
disable_failures=self._config.disable_failures,
disable_hard_timeout=self._config.disable_hard_timeout,
disable_window=self._config.disable_window,
)
def get_config(self, key):
config = configuration.get_config()
try:
return config.get('hdfs', key)
except:
raise RuntimeError("You must specify %s in the [hdfs] section of "
"the luigi client.cfg file" % key)
def run(self):
self.remove_output_on_overwrite()
ppr = PaypalReportRequest(
'SettlementReport',
processor='PayPal',
start_date=self.date.isoformat() + ' 00:00:00',
end_date=self.date.isoformat() + ' 23:59:59',
timezone='GMT'
)
report_response = ppr.execute()
report_id = report_response.report_id
is_running = report_response.is_running
timeout = get_config().getint('paypal', 'timeout', 60 * 60 * 2)
start_time = time.time()
while is_running:
if timeout >= 0 and time.time() >= (start_time + timeout):
raise PaypalTimeoutError(start_time)
time.sleep(5)
results_response = PaypalReportResultsRequest(report_id=report_id).execute()
is_running = results_response.is_running
metadata_response = PaypalReportMetadataRequest(report_id=report_id).execute()
if metadata_response.num_rows < 1 and not self.is_empty_transaction_allowed:
raise Exception('No transactions to process.')
with self.output().open('w') as output_tsv_file:
for page_num in range(metadata_response.num_pages):
data_response = PaypalReportDataRequest(report_id=report_id, page_num=(page_num + 1)).execute()
for row in data_response.rows:
self.write_transaction_record(row, output_tsv_file)
def run(self):
spark_submit = configuration.get_config().get('spark', 'spark-submit',
'spark-submit')
options = [
'--class', self.job_class(),
'--master', 'yarn-client',
]
if self.num_executors is not None:
options += ['--num-executors', self.num_executors]
if self.driver_memory is not None:
options += ['--driver-memory', self.driver_memory]
if self.executor_memory is not None:
options += ['--executor-memory', self.executor_memory]
if self.executor_cores is not None:
options += ['--executor-cores', self.executor_cores]
dependency_jars = self.dependency_jars()
if dependency_jars != []:
options += ['--jars', ','.join(dependency_jars)]
args = [spark_submit] + options + self.spark_options() + \
[self.jar()] + list(self.job_args())
args = map(str, args)
env = os.environ.copy()
temp_stderr = tempfile.TemporaryFile()
logger.info('Running: {0}'.format(repr(args)))
proc = subprocess.Popen(args, stdout=subprocess.PIPE,
stderr=temp_stderr, env=env, close_fds=True)
return_code, final_state, app_id = self.track_progress(proc)
if final_state == 'FAILED':
raise SparkJobError('Spark job failed: see yarn logs for {0}'
.format(app_id))
elif return_code != 0:
temp_stderr.seek(0)
errors = temp_stderr.readlines()
logger.error(errors)
raise SparkJobError('Spark job failed', err=errors)
def run(self):
spark_submit = configuration.get_config().get('spark', 'spark-submit',
'spark-submit')
options = [
'--class',
self.job_class(),
]
if self.num_executors is not None:
options += ['--num-executors', self.num_executors]
if self.driver_memory is not None:
options += ['--driver-memory', self.driver_memory]
if self.executor_memory is not None:
options += ['--executor-memory', self.executor_memory]
if self.executor_cores is not None:
options += ['--executor-cores', self.executor_cores]
if self.deploy_mode is not None:
options += ['--deploy-mode', self.deploy_mode]
if self.queue is not None:
options += ['--queue', self.queue]
if self.spark_master is not None:
options += ['--master', self.spark_master]
dependency_jars = self.dependency_jars()
if dependency_jars != []:
options += ['--jars', ','.join(dependency_jars)]
args = [spark_submit] + options + self.spark_options() + \
[self.jar()] + list(self.job_args())
args = map(str, args)
env = os.environ.copy()
temp_stderr = tempfile.TemporaryFile()
logger.info('Running: {0}'.format(repr(args)))
proc = subprocess.Popen(args,
stdout=subprocess.PIPE,
stderr=temp_stderr,
env=env,
close_fds=True)
return_code, final_state, app_id = self.track_progress(proc)
if final_state == 'FAILED':
raise SparkJobError(
'Spark job failed: see yarn logs for {0}'.format(app_id))
elif return_code != 0:
temp_stderr.seek(0)
errors = "".join(temp_stderr.readlines())
logger.error(errors)
raise SparkJobError('Spark job failed', err=errors)
class LDAParams(luigi.ExternalTask):
"""
Simulate parameters for an LDA model
This generates the beta and theta parameters that are the basis for the rest of the simulation.
Arguments:
D (int): How many samples are there in this experiment?
V (int): How many terms are there across samples?
K (int): How many topics are there?
alpha0 (float): What is the true theta parameter prior used in
generating data?
gamma0 (float): What is the true beta parameter prior used in generating
data?
"""
D = luigi.Parameter()
V = luigi.Parameter()
K = luigi.Parameter()
alpha0 = luigi.Parameter()
gamma0 = luigi.Parameter()
conf = configuration.get_config()
def run(self):
gen_id = hash_string("".join(
[self.D, self.V, self.K, self.alpha0, self.gamma0]))
run_cmd = [
"Rscript",
self.conf.get("expers", "param_script"),
self.conf.get("expers", "output_dir"), gen_id, self.D, self.V,
self.K, self.alpha0, self.gamma0
]
run_and_check(run_cmd)
def output(self):
gen_id = hash_string("".join(
[self.D, self.V, self.K, self.alpha0, self.gamma0]))
output_dir = self.conf.get("expers", "output_dir")
return [
luigi.LocalTarget(
os.path.join(output_dir, "beta-" + gen_id + ".feather")),
luigi.LocalTarget(
os.path.join(output_dir, "theta-" + gen_id + ".feather"))
]
def test_sns_subject_is_shortened(self):
"""
Call notificaions.send_email_sns with too long Subject (more than 100 chars)
and check that it is cut to lenght of 100 chars.
"""
long_subject = 'Luigi: SanityCheck(regexPattern=aligned-source\\|data-not-older\\|source-chunks-compl,'\
'mailFailure=False, mongodb=mongodb://localhost/stats) FAILED'
with mock.patch('boto3.resource') as res:
notifications.send_email_sns(configuration.get_config(),
self.sender, long_subject, self.message,
self.recipients, self.image_png)
SNS = res.return_value
SNS.Topic.assert_called_once_with(self.recipients[0])
called_subj = SNS.Topic.return_value.publish.call_args[1]['Subject']
self.assertTrue(len(called_subj) <= 100,
"Subject can be max 100 chars long! Found {}.".format(len(called_subj)))
def send_error_email(subject, message):
"""
Sends an email to the configured error-email.
If no error-email is configured, then a message is logged.
"""
config = configuration.get_config()
receiver = config.get('core', 'error-email', None)
if receiver:
sender = config.get('core', 'email-sender', DEFAULT_CLIENT_EMAIL)
logger.info("Sending warning email to %r", receiver)
send_email(subject=subject,
message=message,
sender=sender,
recipients=(receiver, ))
else:
logger.info("Skipping error email. Set `error-email` in the `core` "
"section of the luigi config file to receive error "
"emails.")
def test_sends_ses_email(self):
"""
Call notificaions.send_email_ses with fixture parameters
and check that boto is properly called.
"""
with mock.patch('boto3.client') as boto_client:
with mock.patch('luigi.notifications.generate_email') as generate_email:
generate_email.return_value\
.as_string.return_value = self.mocked_email_msg
notifications.send_email_ses(configuration.get_config(),
*self.notification_args)
SES = boto_client.return_value
SES.send_raw_email.assert_called_once_with(
Source=self.sender,
Destinations=self.recipients,
RawMessage={'Data': self.mocked_email_msg})
def create_spawner(turbsim_exe, fast_exe, turbsim_base_file, fast_base_file,
fast_version, runner_type, turbsim_working_dir,
fast_working_dir, outdir, prereq_outdir):
"""
:param turbsim_exe: Location of TurbSim executable
:param fast_exe: Location of FAST executable
:param turbsim_base_file: Baseline TurbSim input file (typically `TurbSim.inp`)
from which wind file generation tasks are spawned
:param fast_base_file: FAST input file (typically `.fst`) to which all parameter
editions are made and from which simulations are spawned
:param fast_version: Major version of FAST {'v7', 'v8'}
:param runner_type: default is `process`
:param turbsim_working_dir: Directory in which TurbSim wind generation tasks are executed
:param fast_working_dir: Directory in which FAST simulations are executed.
Note that the discon.dll must be in this directory
:param outdir: Root output directory for spawning and thus where simulation outputs are located
:param prereq_outdir: Root output directory for prerequisite tasks (i.e. wind file generation)
:returns: `FastSimulationSpawner` object
"""
validate_file(turbsim_exe, 'turbsim_exe')
validate_file(fast_exe, 'fast_exe')
validate_file(turbsim_base_file, 'turbsim_base_file')
validate_file(fast_base_file, 'fast_base_file')
validate_dir(turbsim_working_dir, 'turbsim_working_dir')
validate_dir(fast_working_dir, 'fast_working_dir')
luigi_config = configuration.get_config()
luigi_config.set(WindGenerationTask.__name__, '_exe_path', turbsim_exe)
luigi_config.set(WindGenerationTask.__name__, '_runner_type', runner_type)
luigi_config.set(WindGenerationTask.__name__, '_working_dir',
turbsim_working_dir)
luigi_config.set(FastSimulationTask.__name__, '_exe_path', fast_exe)
luigi_config.set(FastSimulationTask.__name__, '_runner_type', runner_type)
luigi_config.set(FastSimulationTask.__name__, '_working_dir',
fast_working_dir)
wind_spawner = TurbsimSpawner(TurbsimInput.from_file(turbsim_base_file))
fast_input_cls = {'v7': Fast7Input, 'v8': Fast8Input}
return FastSimulationSpawner(
fast_input_cls[fast_version].from_file(fast_base_file), wind_spawner,
path.join(outdir, prereq_outdir))
def __init__(self, url='http://localhost:8082/', connect_timeout=None):
assert not url.startswith('http+unix://') or HAS_UNIX_SOCKET, (
'You need to install requests-unixsocket for Unix socket support.')
self._url = url.rstrip('/')
config = configuration.get_config()
if connect_timeout is None:
connect_timeout = config.getfloat('core', 'rpc-connect-timeout',
10.0)
self._connect_timeout = connect_timeout
self._rpc_retry_attempts = config.getint('core', 'rpc-retry-attempts',
3)
self._rpc_retry_wait = config.getint('core', 'rpc-retry-wait', 30)
if HAS_REQUESTS:
self._fetcher = RequestsFetcher(requests.Session())
else:
self._fetcher = URLLibFetcher()
class Tweets_String(SparkSubmitTask):
sighting_date = luigi.DateParameter()
bucket = configuration.get_config().get('etl','bucket')
def requires(self):
return ReadContainer()
@property
def name(self):
return 'Tweets_String'
def app_options(self):
return [self.input().path, self.output().path]
@property
def app(self):
return 'tweets_string.py'
def output(self):
return luigi.file.LocalTarget('/home/dpa_worker/model_data/{}{}{}tweets.json'.format(self.sighting_date.year,self.sighting_date.month,self.sighting_date.day))
def __init__(self, config=None, resources=None, task_history_impl=None, **kwargs):
"""
Keyword Arguments:
:param config: an object of class "scheduler" or None (in which the global instance will be used)
:param resources: a dict of str->int constraints
:param task_history_impl: ignore config and use this object as the task history
"""
self._config = config or scheduler(**kwargs)
self._state = SimpleTaskState(self._config.state_path)
if task_history_impl:
self._task_history = task_history_impl
elif self._config.record_task_history:
from luigi import db_task_history # Needs sqlalchemy, thus imported here
self._task_history = db_task_history.DbTaskHistory()
else:
self._task_history = history.NopHistory()
self._resources = resources or configuration.get_config().getintdict('resources') # TODO: Can we make this a Parameter?
self._make_task = functools.partial(Task, retry_policy=self._config._get_retry_policy())
self._worker_requests = {}
def create_manifest_target(manifest_id, targets):
# If we are running locally, we need our manifest file to be a local file target, however, if we are running on
# a real Hadoop cluster, it has to be an HDFS file so that the input format can read it. Luigi makes it a little
# difficult for us to construct a target that can be one or the other of those types of targets at runtime since
# it relies on inheritance to signify the difference. We hack the inheritance here, by dynamically choosing the
# base class at runtime based on the URL of the manifest file.
# Construct the manifest file URL from the manifest_id and the configuration
base_url = configuration.get_config().get(CONFIG_SECTION, 'path')
manifest_file_path = url_path_join(base_url, manifest_id + '.manifest')
# Figure out the type of target that should be used to write/read the file.
manifest_file_target_class, init_args, init_kwargs = get_target_class_from_url(manifest_file_path)
# Ensure our constructed target inherits from the appropriate type of file target.
class ManifestInputTarget(ManifestInputTargetMixin, manifest_file_target_class):
pass
# This functionality is inherited from the Mixin which contains all of the substantial logic
return ManifestInputTarget.from_existing_targets(targets, *init_args, **init_kwargs)
def send_error_email(subject, message, additional_recipients=None):
"""
Sends an email to the configured error-email.
If no error-email is configured, then a message is logged.
"""
config = configuration.get_config()
recipients = _email_recipients(additional_recipients)
if recipients:
sender = config.get('core', 'email-sender', DEFAULT_CLIENT_EMAIL)
logger.info("Sending warning email to %r", recipients)
send_email(subject=subject,
message=message,
sender=sender,
recipients=recipients)
else:
logger.info(
"Skipping error email. Set `error-email` in the `core` "
"section of the luigi config file or override `owner_email`"
"in the task to receive error emails.")
def create_spawner(task_exe, working_dir, base_file, runner_type):
"""
Creates spawner that creates tasks taking a single JSON input file as command line argument
:param task_exe: Path of executable to run. If None, input files will be written but no tasks run
:param working_dir: Working directory of task execution
:param base_file: Baseline JSON file on which to make parameter editions and additions. If None, parameter additions
will be made onto an empty input
:return: :class:`SingleInputFileSpawner` object
"""
if task_exe is not None:
validate_file(task_exe, 'task_exe')
if working_dir is not None:
validate_dir(working_dir, 'working_dir')
if base_file is not None:
validate_file(base_file, 'base_file')
if task_exe is None:
task_exe = ''
if working_dir is None:
working_dir = '.'
logger = logging.getLogger(__name__)
logger.info("Creating Single input file spawner with JSON input")
logger.info("task_exe = %s", task_exe)
logger.info("working_dir = %s", working_dir)
logger.info("base_file = %s", base_file)
logger.info("runner_type = %s", runner_type)
luigi_config = configuration.get_config()
luigi_config.set(SimulationTask.__name__, '_exe_path', task_exe)
luigi_config.set(SimulationTask.__name__, '_working_dir', working_dir)
luigi_config.set(SimulationTask.__name__, '_runner_type', runner_type)
if base_file is not None:
with open(base_file, 'r') as fp:
params = json.load(fp)
else:
params = {}
sim_input = JsonSimulationInput(params, indent=2)
return SingleInputFileSpawner(sim_input, 'input.json')
class IngestPipeline(luigi.WrapperTask):
"""
Este wrapper ejecuta la ingesta de cada pipeline-task
Input Args (From luigi.cfg):
pipelines: lista con los pipeline-tasks especificados a correr.
"""
year_month = luigi.Parameter()
conf = configuration.get_config()
pipelines = parse_cfg_list(conf.get("IngestPipeline", "pipelines"))
#python_pipelines = parse_cfg_list(conf.get("IngestPipeline", "python_pipelines"))
def requires(self):
for pipeline_task in self.pipelines:
yield UpdateDB(pipeline_task=pipeline_task,
year_month=self.year_month)
def get_pgdict_from_cfg():
"""
loads postgres configuration from luigi config file
"""
try:
cfg = configuration.get_config()
pghost = cfg.get('postgres', 'host')
pgdb = cfg.get('postgres', 'database')
pguser = cfg.get('postgres', 'user')
pgpassword = cfg.get('postgres', 'password')
dbitems = {
'PGUSER': pguser,
'PGPASSWORD': pgpassword,
'PGHOST': pghost,
'PGDATABASE': pgdb
}
return dbitems
except:
return None
def should_include_answer(self, answer):
"""Determine if a problem "part" should be included in the distribution."""
response_type = answer.get('response_type')
# For problems which only have old responses, we don't
# have information about whether to include their answers.
if response_type is None:
return False
# read out valid types from client.cfg file. The 3rd argument below sets a default in case the
# config file is somehow misread. But to change the list, please update the client.cfg
valid_type_str = get_config().get(
'answer-distribution', 'valid_response_types',
'choiceresponse,optionresponse,multiplechoiceresponse,numericalresponse,stringresponse,formularesponse'
)
valid_types = set(valid_type_str.split(","))
if response_type in valid_types:
return True
return False
def convert_tasks_to_manifest_if_necessary(input_tasks): # pylint: disable=invalid-name
"""
Provide a manifest for the input paths if there are too many of them.
The configuration section "manifest" can contain a "threshold" option which, when exceeded, causes this function
to return a URLManifestTask instead of the original input_tasks.
"""
all_input_tasks = task.flatten(input_tasks)
targets = task.flatten(task.getpaths(all_input_tasks))
threshold = configuration.get_config().getint(CONFIG_SECTION, 'threshold',
-1)
if threshold > 0 and len(targets) >= threshold:
log.debug(
'Using manifest since %d inputs are greater than or equal to the threshold %d',
len(targets), threshold)
return [URLManifestTask(urls=[target.path for target in targets])]
else:
log.debug(
'Directly processing files since %d inputs are less than the threshold %d',
len(targets), threshold)
return all_input_tasks
def __init__(self,
auth_url=None,
client_id=None,
client_secret=None,
oauth_username=None,
oauth_password=None,
token_type=None):
self._expires_at = None
self._session = requests.Session()
self._session.hooks = {'response': log_response_hook}
config = configuration.get_config()
self.client_id = client_id or config.get('edx-rest-api', 'client_id')
self.client_secret = client_secret or config.get(
'edx-rest-api', 'client_secret')
self.auth_url = auth_url or config.get('edx-rest-api', 'auth_url')
self.token_type = token_type or 'jwt'
self.oauth_username = oauth_username or config.get(
'edx-rest-api', 'oauth_username', None)
self.oauth_password = oauth_password or config.get(
'edx-rest-api', 'oauth_password', None)
class CreateSchema(luigi.Task):
"""
Class to create a schema in the sedesol DB
This expects a parameter giving the name of the schema to create.
It has no dependencies.
"""
schema_name = luigi.Parameter()
conf = configuration.get_config()
output_param = (conf.get('etl', 'logging_path') + '%s_schema_created.log')
def requires(self):
query_string = "CREATE SCHEMA IF NOT EXISTS %s;" % self.schema_name
return pg_sed.QueryString(query_string)
def run(self):
output_path = self.output_param % self.schema_name
open(output_path, 'a').close() # touch the output file
def output(self):
output_path = self.output_param % self.schema_name
return luigi.LocalTarget(output_path)
class CreateIndices(luigi.Task):
"""
This executes the queries in the clean_table_indexer path
The queries have to be done in sequence, because we need to first drop any
queries before creating new ones. We also can't use the QueryString() class,
because that doesn't have a require statement (and will try making indices
indices before the clean tables are even created).
"""
pipeline_task = luigi.Parameter()
conf = configuration.get_config()
logging_path = conf.get('etl', 'logging_path')
def requires(self):
return RawToCleanSchema(self.pipeline_task)
def run(self):
query_filename = self.conf.get(self.pipeline_task,
'clean_table_indexer')
connection = pg_sed.db_connection()
connection.autocommit = True
cursor = connection.cursor()
all_queries = open(query_filename, 'r').read().split(';')
for query in all_queries:
if not query.isspace():
logger.info("Executing query: " + query)
cursor.execute(query)
connection.commit()
connection.close()
output_path = "%s%s_clean_indices_created.log" % (self.logging_path,
self.pipeline_task)
open(output_path, 'a').close()
def output(self):
output_path = "%s%s_clean_indices_created.log" % (self.logging_path,
self.pipeline_task)
return luigi.LocalTarget(output_path)
def send_email(subject, message, sender, recipients, image_png=None):
config = configuration.get_config()
subject = _prefix(subject)
logger.debug(
"Emailing:\n"
"-------------\n"
"To: %s\n"
"From: %s\n"
"Subject: %s\n"
"Message:\n"
"%s\n"
"-------------", recipients, sender, subject, message)
if not recipients or recipients == (None, ):
return
if (sys.stdout.isatty() or
DEBUG) and (not config.getboolean('email', 'force-send', False)):
logger.info(
"Not sending email when running from a tty or in debug mode")
return
# Clean the recipients lists to allow multiple error-email addresses, comma
# separated in client.cfg
recipients_tmp = []
for r in recipients:
recipients_tmp.extend(r.split(','))
# Replace original recipients with the clean list
recipients = recipients_tmp
email_sender_type = config.get('email', 'type', None)
if email_sender_type == "ses":
send_email_ses(config, sender, subject, message, recipients, image_png)
elif email_sender_type == "sendgrid":
send_email_sendgrid(config, sender, subject, message, recipients,
image_png)
else:
send_email_smtp(config, sender, subject, message, recipients,
image_png)
def requires(self):
config = get_config()
for merchant_id in self.cybersource_merchant_ids:
section_name = 'cybersource:' + merchant_id
interval_start = luigi.DateParameter().parse(
config.get(section_name, 'interval_start'))
interval_end = self.import_date
merchant_close_date = config.get(section_name,
'merchant_close_date', '')
if merchant_close_date:
parsed_date = luigi.DateParameter().parse(merchant_close_date)
interval_end = min(self.import_date, parsed_date)
cybersource_interval = date_interval.Custom(
interval_start, interval_end)
for date in cybersource_interval:
filename = "cybersource_{}.tsv".format(merchant_id)
url = url_path_join(self.warehouse_path, 'payments',
'dt=' + date.isoformat(), filename)
yield ExternalURL(url=url)
def job_runner(self):
config = configuration.get_config()
venv_path = self.venv_path
if not venv_path.lower().endswith(".zip"):
if venv_path.startswith('hdfs://'):
raise ValueError(
"Cannot automatically compress a venv located on HDFS"
)
venv_path = self._create_venv_archive(venv_path)
python_excutable = config.get('hadoop', 'python-executable', 'python')
self.old_python_executable = python_excutable
symbolic = venv_path.split('/')[-1].split('.')[0]
venv_archive = "{}#{}".format(venv_path, symbolic)
python_executable = "{}/bin/{}".format(symbolic, python_excutable)
config.set('hadoop', 'python-executable', python_executable)
return TYDefaultHadoopJobRunner(
archives=[venv_archive],
libjars=self.libjars,
)
class UnigramParams(luigi.ExternalTask):
"""
Simulate parameters for a Unigram model
This generates the parameters mu[t] for a particular instance of the
dynamic unigram model.
Arguments:
D (int): How many samples are there in this experiment?
V (int): How many terms are there across samples?
sigma0 (float): What is the true sigma random walk size parameter used in
generating the data?
"""
D = luigi.Parameter()
V = luigi.Parameter()
sigma0 = luigi.Parameter()
conf = configuration.get_config()
def run(self):
print("test")
gen_id = hash_string("".join([self.D, self.V, self.sigma0]))
print(gen_id)
run_cmd = [
"Rscript",
self.conf.get("expers", "param_script"),
self.conf.get("expers", "output_dir"), gen_id, self.D, self.V,
self.sigma0
]
run_and_check(run_cmd)
def output(self):
gen_id = hash_string("".join([self.D, self.V, self.sigma0]))
output_dir = self.conf.get("expers", "output_dir")
return [
luigi.LocalTarget(
os.path.join(output_dir, "mu-" + gen_id + ".feather"))
]
class MicrobiomePred(luigi.WrapperTask):
conf = configuration.get_config()
def requires(self):
ps_path = os.path.join(self.conf.get("paths", "project_dir"),
self.conf.get("paths", "phyloseq"))
ensemble = pf.values_from_conf(self.conf, "ensemble")
tasks = []
for i in ensemble.keys():
tasks.append(EnsembleEval(i))
exper = pf.values_from_conf(self.conf, "experiment")
for i in exper.keys():
for k in ["all", "all-cv"] + list(range(1, exper[i]["k_folds"])):
tasks.append(
CVEval(ps_path, exper[i]["preprocessing"],
str(exper[i]["validation_prop"]),
str(exper[i]["k_folds"]), exper[i]["features"],
exper[i]["model"], str(k), exper[i]["metrics"]))
return tasks
class LoadCVIndices(luigi.WrapperTask):
"""
Create CV indices for each current subset of the semantic table
"""
pipeline_task = luigi.Parameter()
conf = configuration.get_config()
def requires(self):
experiments_path = self.conf.get(self.pipeline_task, "experiments")
subsets = pg_sed.unique_experiment_subsets(
experiments_path,
self.conf,
self.pipeline_task
)
tasks = []
for subset in subsets:
tasks.append(
LoadCVIndex(self.pipeline_task, subset_table=subset[0])
)
return tasks
class RunModels(luigi.WrapperTask):
"""
Run, evaluate, and load many models
This runs models for different model / parameter / subset configurations,
as specified in the luigi.cfg file, and saves the resulting models to the
database.
"""
pipeline_task = luigi.Parameter()
conf = configuration.get_config()
k_folds = conf.get("shared", "k_folds")
def requires(self):
"""
Set off a task for all the model / parameter / fold combinations
This is heavily influenced by https://github.com/rayidghani/magicloops/
"""
experiments_path = self.conf.get(self.pipeline_task, "experiments")
with open(experiments_path) as experiments_file:
experiments_dict = json.load(experiments_file)
tasks = []
for exper_id, exper in experiments_dict.items():
params = {
param: ast.literal_eval(values)
for param, values in exper["model"]["params"].items()
}
parameter_combns = ParameterGrid(params)
for theta in parameter_combns:
for cur_fold in range(int(self.k_folds)):
cur_task = RunModel(exper_id, str(theta), str(cur_fold),
self.pipeline_task)
tasks.append(cur_task)
return tasks
class LoadNeo4j(luigi.WrapperTask):
"""
Clase que crea la infraestructura de Neo4j para poder correr queries y modelos
"""
conf = configuration.get_config()
logging_path = conf.get('etl', 'logging_path')
def requires(self):
return LoadNeo4jTalentos(), LoadNeo4jProyectos()
def run(self):
# Al final:
# Crear un archivo (vacío) para crear el log de carga de talentos a Neo4j
output_path = os.path.join(self.logging_path, "LoadedBothNeo4j")
open(output_path, "a").close()
def output(self):
"""
Output es un log file indicando que se cargaron correctamente ambas bases a Neo4j
"""
output_path = os.path.join(self.logging_path, "LoadedBothNeo4j")
return luigi.LocalTarget(output_path)
def run(self):
spark_submit = configuration.get_config().get('spark', 'spark-submit',
'spark-submit')
options = ['--master', 'yarn-client']
if self.num_executors is not None:
options += ['--num-executors', self.num_executors]
if self.driver_memory is not None:
options += ['--driver-memory', self.driver_memory]
if self.executor_memory is not None:
options += ['--executor-memory', self.executor_memory]
if self.executor_cores is not None:
options += ['--executor-cores', self.executor_cores]
py_files = self.py_files()
if py_files != []:
options += ['--py-files', ','.join(py_files)]
args = [spark_submit] + options + self.spark_options() + \
[self.program()] + list(self.job_args())
args = map(str, args)
env = os.environ.copy()
temp_stderr = tempfile.TemporaryFile()
logger.info('Running: %s', repr(args))
proc = subprocess.Popen(args,
stdout=subprocess.PIPE,
stderr=temp_stderr,
env=env,
close_fds=True)
return_code, final_state, app_id = self.track_progress(proc)
if final_state == 'FAILED':
raise SparkJobError('Spark job failed: see yarn logs for %s',
app_id)
elif return_code != 0:
temp_stderr.seek(0)
errors = "".join(
(x.decode('utf8') for x in temp_stderr.readlines()))
logger.error(errors)
raise SparkJobError('Spark job failed', err=errors)
class UnigramData(luigi.Task):
"""
Simulate data according to a Unigram model
Arguments:
D (int): How many samples are there in this experiment?
N (int): How many words are there in each sample?
V (int): How many terms are there across samples?
sigma0 (float): What is the true sigma random walk size parameter used in
generating the data?
"""
D = luigi.Parameter()
N = luigi.Parameter()
V = luigi.Parameter()
sigma0 = luigi.Parameter()
conf = configuration.get_config()
def requires(self):
return UnigramParams(self.D, self.V, self.sigma0)
def run(self):
mu_path = self.input()[0].open("r").name
gen_id = hash_string("".join([self.D, self.N, self.V, self.sigma0]))
run_cmd = [
"Rscript",
self.conf.get("expers", "sim_script"),
self.conf.get("expers", "output_dir"), gen_id, self.N, mu_path
]
run_and_check(run_cmd)
def output(self):
gen_id = hash_string("".join([self.D, self.N, self.V, self.sigma0]))
output_dir = self.conf.get("expers", "output_dir")
return luigi.LocalTarget(
os.path.join(output_dir, "x-" + gen_id + ".feather"))
def pig_home(self):
return configuration.get_config().get('pig', 'home', '/usr/share/pig')
