def _str(s):
# cloudant-python doesn't support unicode.
if isinstance(s, unicode):
log = LoggingMixin().log
log.debug(
'cloudant-python does not support unicode. Encoding %s as '
'ascii using "ignore".', s)
return s.encode('ascii', 'ignore')
return s
def handle_failure_retry(context):
ti = context['ti']
cmd_id = ti.xcom_pull(key='qbol_cmd_id', task_ids=ti.task_id)
if cmd_id is not None:
cmd = Command.find(cmd_id)
if cmd is not None:
if cmd.status == 'running':
log = LoggingMixin().log
log.info('Cancelling the Qubole Command Id: %s', cmd_id)
cmd.cancel()
def set(
cls,
key,
value,
execution_date,
task_id,
dag_id,
session=None):
"""保存中间结果
Store an XCom value.
TODO: "pickling" has been deprecated and JSON is preferred.
"pickling" will be removed in Airflow 2.0.
:return: None
"""
# 调用底层,清除所有session实例
session.expunge_all()
enable_pickling = configuration.getboolean('core', 'enable_xcom_pickling')
# 序列化中间结果
if enable_pickling:
value = pickle.dumps(value)
else:
try:
# 注意编码转换
value = json.dumps(value).encode('UTF-8')
except ValueError:
log = LoggingMixin().log
log.error("Could not serialize the XCOM value into JSON. "
"If you are using pickles instead of JSON "
"for XCOM, then you need to enable pickle "
"support for XCOM in your airflow config.")
raise
# remove any duplicate XComs
# 删除相同key的中间结果
session.query(cls).filter(
cls.key == key,
cls.execution_date == execution_date,
cls.task_id == task_id,
cls.dag_id == dag_id).delete()
session.commit()
# insert new XCom
session.add(XCom(
key=key,
value=value,
execution_date=execution_date,
task_id=task_id,
dag_id=dag_id))
session.commit()
def GetDefaultExecutor():
"""Creates a new instance of the configured executor if none exists and returns it"""
global DEFAULT_EXECUTOR
if DEFAULT_EXECUTOR is not None:
return DEFAULT_EXECUTOR
executor_name = configuration.conf.get('core', 'EXECUTOR')
DEFAULT_EXECUTOR = _get_executor(executor_name)
log = LoggingMixin().log
log.info("Using executor %s", executor_name)
return DEFAULT_EXECUTOR
def get_one(cls,
execution_date,
key=None,
task_id=None,
dag_id=None,
include_prior_dates=False,
session=None):
"""获取一条中间结果
Retrieve an XCom value, optionally meeting certain criteria.
TODO: "pickling" has been deprecated and JSON is preferred.
"pickling" will be removed in Airflow 2.0.
:return: XCom value
"""
# 构造搜索条件
filters = []
if key:
filters.append(cls.key == key)
if task_id:
filters.append(cls.task_id == task_id)
if dag_id:
filters.append(cls.dag_id == dag_id)
if include_prior_dates:
filters.append(cls.execution_date <= execution_date)
else:
filters.append(cls.execution_date == execution_date)
query = (
session.query(cls.value).filter(and_(*filters))
.order_by(cls.execution_date.desc(), cls.timestamp.desc()))
# 获得最近的一条记录
result = query.first()
if result:
enable_pickling = configuration.getboolean('core', 'enable_xcom_pickling')
if enable_pickling:
return pickle.loads(result.value)
else:
try:
# 注意编码转换
return json.loads(result.value.decode('UTF-8'))
except ValueError:
log = LoggingMixin().log
log.error("Could not deserialize the XCOM value from JSON. "
"If you are using pickles instead of JSON "
"for XCOM, then you need to enable pickle "
"support for XCOM in your airflow config.")
raise
def set_dirty(dag_id, session=None):
"""
:param dag_id: the dag_id to mark dirty
:param session: database session
:return:
"""
# 给dag的每一种状态都创建一条记录
# 将统计表中不存在的状态插入到db中
DagStat.create(dag_id=dag_id, session=session)
try:
# 给指定的dag所有的状态行加行锁
stats = session.query(DagStat).filter(
DagStat.dag_id == dag_id
).with_for_update().all()
# 修改设置dirty标记
for stat in stats:
stat.dirty = True
session.commit()
except Exception as e:
session.rollback()
log = LoggingMixin().log
log.warning("Could not update dag stats for %s", dag_id)
log.exception(e)
def send_MIME_email(e_from, e_to, mime_msg, dryrun=False):
"""发送邮件 ."""
log = LoggingMixin().log
SMTP_HOST = configuration.conf.get('smtp', 'SMTP_HOST')
SMTP_PORT = configuration.conf.getint('smtp', 'SMTP_PORT')
SMTP_STARTTLS = configuration.conf.getboolean('smtp', 'SMTP_STARTTLS')
SMTP_SSL = configuration.conf.getboolean('smtp', 'SMTP_SSL')
SMTP_USER = None
SMTP_PASSWORD = None
try:
SMTP_USER = configuration.conf.get('smtp', 'SMTP_USER')
SMTP_PASSWORD = configuration.conf.get('smtp', 'SMTP_PASSWORD')
except XToolConfigException:
log.debug(
"No user/password found for SMTP, so logging in with no authentication."
)
if not dryrun:
s = smtplib.SMTP_SSL(SMTP_HOST,
SMTP_PORT) if SMTP_SSL else smtplib.SMTP(
SMTP_HOST, SMTP_PORT)
if SMTP_STARTTLS:
s.starttls()
if SMTP_USER and SMTP_PASSWORD:
s.login(SMTP_USER, SMTP_PASSWORD)
log.info("Sent an alert email to %s", e_to)
s.sendmail(e_from, e_to, mime_msg.as_string())
s.quit()
def send_MIME_email(e_from,
e_to,
mime_msg,
host,
port,
ssl=False,
starttls=False,
user=None,
password=None,
dryrun=False):
"""发送邮件 ."""
log = LoggingMixin().log
if not user or not password:
log.debug(
"No user/password found for SMTP, so logging in with no authentication."
)
if not dryrun:
s = smtplib.SMTP_SSL(host, port) if ssl else smtplib.SMTP(host, port)
if starttls:
s.starttls()
s.login(user, password)
log.info("Sent an alert email to %s", e_to)
s.sendmail(e_from, e_to, mime_msg.as_string())
s.quit()
def load_login():
log = LoggingMixin().log
auth_backend = 'airflow.default_login'
try:
# 获得默认web认证
if conf.getboolean('webserver', 'AUTHENTICATE'):
auth_backend = conf.get('webserver', 'auth_backend')
except (AirflowConfigException, XToolConfigException):
if conf.getboolean('webserver', 'AUTHENTICATE'):
log.warning(
"auth_backend not found in webserver config reverting to "
"*deprecated* behavior of importing airflow_login")
auth_backend = "airflow_login"
# 导入认证模块
try:
global login
login = import_module(auth_backend)
except ImportError as err:
log.critical(
"Cannot import authentication module %s. "
"Please correct your authentication backend or disable authentication: %s",
auth_backend, err
)
if conf.getboolean('webserver', 'AUTHENTICATE'):
raise AirflowException("Failed to import authentication backend")
def execute_command(command):
"""airflow worker 执行shell命令 ."""
log = LoggingMixin().log
log.info("Executing command in Celery: %s", command)
env = os.environ.copy()
try:
# celery worker 收到消息后，执行消息中的shell命令
subprocess.check_call(command,
shell=True,
stderr=subprocess.STDOUT,
close_fds=True,
env=env)
except subprocess.CalledProcessError as e:
log.exception('execute_command encountered a CalledProcessError')
log.error(e.output)
raise AirflowException('Celery command failed')
def wrapper(*args, **kwargs):
metrics = {}
metrics['begin_datetime'] = datetime.now()
metrics['end_datetime'] = None
metrics['log'] = LoggingMixin().log
on_pre_execution(**metrics)
try:
return f(*args, **kwargs)
except Exception as e:
metrics['error'] = e
raise
finally:
metrics['end_datetime'] = datetime.now()
on_post_execution(**metrics)
def _to_timestamp(cls, col):
"""
Convert a column of a dataframe to UNIX timestamps if applicable
:param col: A Series object representing a column of a dataframe.
"""
# try and convert the column to datetimes
# the column MUST have a four digit year somewhere in the string
# there should be a better way to do this,
# but just letting pandas try and convert every column without a format
# caused it to convert floats as well
# For example, a column of integers
# between 0 and 10 are turned into timestamps
# if the column cannot be converted,
# just return the original column untouched
try:
col = pd.to_datetime(col)
except ValueError:
log = LoggingMixin().log
log.warning("Could not convert field to timestamps: %s", col.name)
return col
# now convert the newly created datetimes into timestamps
# we have to be careful here
# because NaT cannot be converted to a timestamp
# so we have to return NaN
converted = []
for i in col:
try:
converted.append(i.timestamp())
except ValueError:
converted.append(pd.np.NaN)
except AttributeError:
converted.append(pd.np.NaN)
# return a new series that maintains the same index as the original
return pd.Series(converted, index=col.index)
def _post_sendgrid_mail(mail_data):
log = LoggingMixin().log
sg = sendgrid.SendGridAPIClient(apikey=os.environ.get('SENDGRID_API_KEY'))
response = sg.client.mail.send.post(request_body=mail_data)
# 2xx status code.
if response.status_code >= 200 and response.status_code < 300:
log.info('Email with subject %s is successfully sent to recipients: %s' %
(mail_data['subject'], mail_data['personalizations']))
else:
log.warning('Failed to send out email with subject %s, status code: %s' %
(mail_data['subject'], response.status_code))
def update(dag_ids=None, dirty_only=True, session=None):
"""更新dag每个状态的dag_run的数量，并设置dirty为False
Updates the stats for dirty/out-of-sync dags
:param dag_ids: dag_ids to be updated
:type dag_ids: list
:param dirty_only: only updated for marked dirty, defaults to True
:type dirty_only: bool
:param session: db session to use
:type session: Session
"""
try:
qry = session.query(DagStat)
if dag_ids:
qry = qry.filter(DagStat.dag_id.in_(set(dag_ids)))
# 仅仅获得脏数据
if dirty_only:
qry = qry.filter(DagStat.dirty == True) # noqa
# 添加行级锁
qry = qry.with_for_update().all()
# 获得所有的dagId列表
dag_ids = set([dag_stat.dag_id for dag_stat in qry])
# avoid querying with an empty IN clause
if not dag_ids:
session.commit()
return
# 获得dag每个dagrun状态的记录数量
begin_time = datetime.now() - timedelta(days=configuration.getint('core', 'sql_query_history_days'))
dagstat_states = set(itertools.product(dag_ids, State.dag_states))
qry = (
session.query(DagRun.dag_id, DagRun.state, func.count('*'))
.filter(DagRun.dag_id.in_(dag_ids))
.filter(DagRun.execution_date > begin_time)
.group_by(DagRun.dag_id, DagRun.state)
)
counts = {(dag_id, state): count for dag_id, state, count in qry}
# 修改每个dag_id的每个状态的dagrund的数量
for dag_id, state in dagstat_states:
count = counts.get((dag_id, state), 0)
session.merge(
DagStat(dag_id=dag_id, state=state, count=count, dirty=False)
)
session.commit()
except Exception as e:
session.rollback()
log = LoggingMixin().log
log.warning("Could not update dag stat table")
log.exception(e)
def get_query_results(self):
log = LoggingMixin().log
if self.cmd is not None:
cmd_id = self.cmd.id
log.info("command id: " + str(cmd_id))
query_result_buffer = StringIO()
self.cmd.get_results(fp=query_result_buffer, inline=True, delim=COL_DELIM)
query_result = query_result_buffer.getvalue()
query_result_buffer.close()
return query_result
else:
log.info("Qubole command not found")
def handle_failure_retry(context):
ti = context['ti']
cmd_id = ti.xcom_pull(key='qbol_cmd_id', task_ids=ti.task_id)
if cmd_id is not None:
cmd = Command.find(cmd_id)
if cmd is not None:
log = LoggingMixin().log
if cmd.status == 'done':
log.info(
'Command ID: %s has been succeeded, hence marking this '
'TI as Success.', cmd_id)
ti.state = State.SUCCESS
elif cmd.status == 'running':
log.info('Cancelling the Qubole Command Id: %s', cmd_id)
cmd.cancel()
def filter_for_filesize(result, size=None):
"""
Will test the filepath result and test if its size is at least self.filesize
:param result: a list of dicts returned by Snakebite ls
:param size: the file size in MB a file should be at least to trigger True
:return: (bool) depending on the matching criteria
"""
if size:
log = LoggingMixin().log
log.debug('Filtering for file size >= %s in files: %s', size,
map(lambda x: x['path'], result))
size *= settings.MEGABYTE
result = [x for x in result if x['length'] >= size]
log.debug('HdfsSensor.poke: after size filter result is %s',
result)
return result
def get_val(self):
"""获得常量的值 ."""
log = LoggingMixin().log
if self._val and self.is_encrypted:
try:
# 解密常量值
fernet_key = configuration.conf.get('core', 'FERNET_KEY')
fernet = get_fernet(fernet_key)
return fernet.decrypt(bytes(self._val, 'utf-8')).decode()
except InvalidFernetToken:
# 解密失败返回None
log.error("Can't decrypt _val for key={}, invalid token "
"or value".format(self.key))
return None
except Exception:
log.error("Can't decrypt _val for key={}, FERNET_KEY "
"configuration missing".format(self.key))
return None
else:
return self._val
def _poll_with_exponential_delay(request, max_n, is_done_func, is_error_func):
log = LoggingMixin().log
for i in range(0, max_n):
try:
response = request.execute()
if is_error_func(response):
raise ValueError(
'The response contained an error: {}'.format(response)
)
elif is_done_func(response):
log.info('Operation is done: %s', response)
return response
else:
time.sleep((2**i) + (random.randint(0, 1000) / 1000))
except errors.HttpError as e:
if e.resp.status != 429:
log.info('Something went wrong. Not retrying: %s', format(e))
raise
else:
time.sleep((2**i) + (random.randint(0, 1000) / 1000))
def create(dag_id, session=None):
"""将统计表中不存在的状态插入到db中
Creates the missing states the stats table for the dag specified
:param dag_id: dag id of the dag to create stats for
:param session: database session
:return:
"""
# 获得DagStat中存在的状态
qry = session.query(DagStat).filter(DagStat.dag_id == dag_id).all()
states = {dag_stat.state for dag_stat in qry}
# 遍历所有状态， 找出不再数据库中的状态
states_not_found = set(State.dag_states) - states
for state in states_not_found:
try:
session.merge(DagStat(dag_id=dag_id, state=state))
session.commit()
except Exception as e:
session.rollback()
log = LoggingMixin().log
log.warning("Could not create stat record")
log.exception(e)
def filter_for_ignored_ext(result, ignored_ext, ignore_copying):
"""
Will filter if instructed to do so the result to remove matching criteria
:param result: (list) of dicts returned by Snakebite ls
:param ignored_ext: (list) of ignored extensions
:param ignore_copying: (bool) shall we ignore ?
:return: (list) of dicts which were not removed
"""
if ignore_copying:
log = LoggingMixin().log
regex_builder = "^.*\.(%s$)$" % '$|'.join(ignored_ext)
ignored_extentions_regex = re.compile(regex_builder)
log.debug(
'Filtering result for ignored extensions: %s in files %s',
ignored_extentions_regex.pattern,
map(lambda x: x['path'], result))
result = [
x for x in result
if not ignored_extentions_regex.match(x['path'])
]
log.debug('HdfsSensor.poke: after ext filter result is %s', result)
return result
# specific language governing permissions and limitations
# under the License.
import ssl
from airflow import configuration
from airflow.exceptions import AirflowConfigException, AirflowException
from xTool.exceptions import XToolConfigException
from xTool.utils.log.logging_mixin import LoggingMixin
def _broker_supports_visibility_timeout(url):
return url.startswith("redis://") or url.startswith("sqs://")
log = LoggingMixin().log
broker_url = configuration.conf.get('celery', 'BROKER_URL')
# 任务发出后，经过一段时间还未收到acknowledge , 就将任务重新交给其他worker执行
broker_transport_options = configuration.conf.getsection(
'celery_broker_transport_options')
if 'visibility_timeout' not in broker_transport_options:
if _broker_supports_visibility_timeout(broker_url):
broker_transport_options = {'visibility_timeout': 21600}
DEFAULT_CELERY_CONFIG = {
'accept_content': ['json', 'pickle'], # 指定接受的内容类型
'event_serializer':
'json', # 发送event message的格式
'worker_prefetch_multiplier':
1, # 每个worker每次只取一个消息
import six
from six import iteritems
import warnings
from zope.deprecation import deprecated as _deprecated
from xTool.crypto.fernet import generate_fernet_key
from xTool.exceptions import AirflowConfigException
from xTool.utils.helpers import expand_env_var
from xTool.utils.configuration import read_config_file
from xTool.utils.configuration import XToolConfigParser
from xTool.utils.file import mkdir_p
from xTool.utils.log.logging_mixin import LoggingMixin
standard_library.install_aliases()
log = LoggingMixin().log
# 控制警告错误的输出
# show Airflow's deprecation warnings
warnings.filterwarnings(action='default',
category=DeprecationWarning,
module='airflow')
warnings.filterwarnings(action='default',
category=PendingDeprecationWarning,
module='airflow')
def parameterized_config(template):
"""使用全局变量和局部变量渲染模版字符串
Generates a configuration from the provided template + variables defined in
current scope
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from xTool.utils.dates import days_ago
from xTool.utils.log.logging_mixin import LoggingMixin
from airflow.models import DAG
log = LoggingMixin().log
try:
# Kubernetes is optional, so not available in vanilla Airflow
# pip install apache-airflow[kubernetes]
from airflow.contrib.operators.kubernetes_pod_operator import KubernetesPodOperator
args = {'owner': 'airflow', 'start_date': days_ago(2)}
dag = DAG(dag_id='example_kubernetes_operator',
default_args=args,
schedule_interval=None)
k = KubernetesPodOperator(namespace='default',
image="ubuntu:16.04",
cmds=["bash", "-cx"],
def list_py_file_paths(directory,
followlinks=True,
ignore_filename='.ignore',
file_ext='.py',
safe_mode=False,
safe_filters=(b'xTool', b'XTool')):
"""递归遍历目录，返回匹配规则的文件列表
Traverse a directory and look for Python files.
:param directory: the directory to traverse
:type directory: unicode
:param safe_mode: whether to use a heuristic to determine whether a file
contains Airflow DAG definitions
:return: a list of paths to Python files in the specified directory
:rtype: list[unicode]
"""
file_paths = []
if directory is None:
return []
elif os.path.isfile(directory):
return [directory]
elif os.path.isdir(directory):
patterns = []
# 递归遍历目录，包含链接文件
for root, dirs, files in os.walk(directory, followlinks=followlinks):
# 获得需要忽略的文件
ignore_file = [f for f in files if f == ignore_filename]
if ignore_file:
f = open(os.path.join(root, ignore_file[0]), 'r')
patterns += [p.strip() for p in f.read().split('\n') if p]
f.close()
for f in files:
try:
# 获得文件的绝对路径
file_path = os.path.join(root, f)
if not os.path.isfile(file_path):
continue
# 验证文件后缀
mod_name, file_extension = os.path.splitext(
os.path.split(file_path)[-1])
if file_extension != file_ext and not zipfile.is_zipfile(
file_path):
continue
# 验证忽略规则
if any([re.findall(p, file_path) for p in patterns]):
continue
# 使用启发式方式猜测是否是一个DAG文件，DAG文件需要包含DAG 或 airflow
# Heuristic that guesses whether a Python file contains an
# Airflow DAG definition.
might_contain_dag = True
if safe_mode and not zipfile.is_zipfile(file_path):
with open(file_path, 'rb') as f:
content = f.read()
might_contain_dag = all(
[s in content for s in safe_filters])
if not might_contain_dag:
continue
file_paths.append(file_path)
except Exception:
log = LoggingMixin().log
log.exception("Error while examining %s", f)
return file_paths
# specific language governing permissions and limitations
# under the License.
#
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from airflow import configuration
from xTool.utils.log.logging_mixin import LoggingMixin
from xTool.utils.module_loading import prepare_classpath
from xTool.utils.module_loading import make_module
from xTool.plugins_manager import XToolPlugin
from xTool.plugins_manager import import_plugins
log = LoggingMixin().log
class AirflowPlugin(XToolPlugin):
pass
# 获得插件目录
plugins_folder = configuration.conf.get('core', 'plugins_folder')
if not plugins_folder:
plugins_folder = configuration.conf.get('core', 'airflow_home') + '/plugins'
# 将插件目录加入到系统路径中
prepare_classpath(plugins_folder)
# 导入插件
plugins = import_plugins(plugins_folder)
def list_py_file_paths(
directory,
followlinks=True,
ignore_filename='.ignore',
file_ext='.py',
safe_mode=False,
safe_filters=(b'xTool', b'XTool')):
"""递归遍历目录，返回匹配规则的文件列表
Traverse a directory and look for Python files.
:param directory: the directory to traverse
:type directory: unicode
:param safe_mode: whether to use a heuristic to determine whether a file
contains Airflow DAG definitions
:return: a list of paths to Python files in the specified directory
:rtype: list[unicode]
"""
file_paths = []
if directory is None:
return []
elif os.path.isfile(directory):
return [directory]
elif os.path.isdir(directory):
patterns_by_dir = {}
# 递归遍历目录，包含链接文件
for root, dirs, files in os.walk(directory, followlinks=followlinks):
patterns = patterns_by_dir.get(root, [])
# 获得需要忽略的文件
ignore_file = os.path.join(root, ignore_filename)
if os.path.isfile(ignore_file):
with open(ignore_file, 'r') as f:
# If we have new patterns create a copy so we don't change
# the previous list (which would affect other subdirs)
patterns = patterns + \
[p for p in f.read().split('\n') if p]
# If we can ignore any subdirs entirely we should - fewer paths
# to walk is better. We have to modify the ``dirs`` array in
# place for this to affect os.walk
dirs[:] = [
d
for d in dirs
if not any(re.search(p, os.path.join(root, d)) for p in patterns)
]
# We want patterns defined in a parent folder's .airflowignore to
# apply to subdirs too
for d in dirs:
patterns_by_dir[os.path.join(root, d)] = patterns
for f in files:
try:
# 获得文件的绝对路径
file_path = os.path.join(root, f)
if not os.path.isfile(file_path):
continue
# 验证文件后缀
mod_name, file_extension = os.path.splitext(
os.path.split(file_path)[-1])
if file_extension != file_ext and not zipfile.is_zipfile(
file_path):
continue
# 验证忽略规则
if any([re.findall(p, file_path) for p in patterns]):
continue
# 使用启发式方式猜测是否是一个DAG文件，DAG文件需要包含DAG 或 airflow
# Heuristic that guesses whether a Python file contains an
# Airflow DAG definition.
might_contain_dag = True
if safe_mode and not zipfile.is_zipfile(file_path):
with open(file_path, 'rb') as f:
content = f.read()
might_contain_dag = all(
[s in content for s in safe_filters])
if not might_contain_dag:
continue
file_paths.append(file_path)
except Exception:
log = LoggingMixin().log
log.exception("Error while examining %s", f)
return file_paths
# under the License.
from hdfs import InsecureClient, HdfsError
from airflow import configuration
from airflow.exceptions import AirflowException
from airflow.hooks.base_hook import BaseHook
from xTool.utils.log.logging_mixin import LoggingMixin
_kerberos_security_mode = configuration.conf.get("core",
"security") == "kerberos"
if _kerberos_security_mode:
try:
from hdfs.ext.kerberos import KerberosClient
except ImportError:
log = LoggingMixin().log
log.error("Could not load the Kerberos extension for the WebHDFSHook.")
raise
class AirflowWebHDFSHookException(AirflowException):
pass
class WebHDFSHook(BaseHook):
"""
Interact with HDFS. This class is a wrapper around the hdfscli library.
"""
def __init__(self, webhdfs_conn_id='webhdfs_default', proxy_user=None):
self.webhdfs_conn_id = webhdfs_conn_id
self.proxy_user = proxy_user
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from builtins import object
import imp
import inspect
import os
import re
import sys
from xTool import configuration
from xTool.utils.log.logging_mixin import LoggingMixin
log = LoggingMixin().log
class XToolPluginException(Exception):
pass
class XToolPlugin(object):
name = None
operators = []
sensors = []
hooks = []
executors = []
macros = []
admin_views = []
flask_blueprints = []
def get_connection(cls, conn_id):
conn = random.choice(cls.get_connections(conn_id))
if conn.host:
log = LoggingMixin().log
log.info("Using connection to: %s", conn.host)
return conn
