class ApiWeekday(data_model.DataObject):
"""
This represents the Weekday object used by the API when an ApiSchedule
is setup for a Days Of Week frequency. It should not be used by users of
this SDK. The ScheduleAdaptor will convert between ApiWeekday and
Weekday during calls. Refer to documentation about Schedule, ScheduleInfo,
and Weekday for more information.
:param day: [required]
:type day: int
:param offset: [required]
:type offset: int
"""
day = data_model.property("day",
int,
array=False,
optional=False,
documentation=None)
offset = data_model.property("offset",
int,
array=False,
optional=False,
documentation=None)
def __init__(self, **kwargs):
data_model.DataObject.__init__(self, **kwargs)
class DaysOfMonthFrequency(Frequency):
"""
Use this class when setting the frequency of a Schedule to Days Of Month.
Days of month schedules trigger on the monthdays and time specified.
:param minutes: The minutes within the hour the snapshot will be created
on the set weekdays.
Valid values are: 0 - 59. Default is 0.
:type minutes: int
:param The hour of the day the next snapshot will be created on the set
weekdays.
Valid values are: 0 - 24. Default is 0
:type hours: int
:param monthdays: An array of the days of the month a snapshot will be
created on.
Valid values are: 1 - 31
:type monthdays: int
"""
minutes = data_model.property(
"minutes",
int,
array=False,
optional=True,
documentation="Minute of hour the snapshot is to be created. "
"Valid values are: 0 - 59")
hours = data_model.property(
"hours",
int,
array=False,
optional=True,
documentation="Hour of day the snapshot is to be created. "
"Valid values are: 0 - 24")
monthdays = data_model.property(
"monthdays",
int,
array=True,
optional=False,
documentation="Days of the month the snapshot is to be created. "
"Valid values are: 1 - 31")
class DaysOfWeekFrequency(Frequency):
"""
Use this class when setting the frequency of a Schedule to Days Of Week.
Days of week schedules trigger on the weekdays and time specified.
:param minutes: The minutes within the hour the snapshot will be created
on the set weekdays.
Valid values are: 0 - 59. Default is 0.
:type minutes: int
:param The hour of the day the next snapshot will be created on the set
weekdays.
Valid values are: 0 - 24. Default is 0
:type hours: int
:param weekdays: The days of the week a snapshot will be created on.
:type weekdays: int
"""
minutes = data_model.property(
"minutes",
int,
array=False,
optional=True,
documentation="Minute of hour the snapshot is to be created. "
"Valid values are: 0 - 59")
hours = data_model.property(
"hours",
int,
array=False,
optional=True,
documentation="Hour of day the snapshot is to be created. "
"Valid values are: 0 - 24")
weekdays = data_model.property(
"weekdays",
Weekday,
array=True,
optional=False,
documentation="Days of the week the snapshot is to be created. "
"Valid values are: "
"Weekday - 1 - 7 (Sunday - Saturday).")
class TimeIntervalFrequency(Frequency):
"""
Use this class when setting the frequency of a Schedule to Time Interval.
Time Interval schedules trigger after the specified interval of time has
passed.
:param minutes: The minutes that will elapse before the next snapshot is
created.
Valid values are: 0 - 59. Default is 0.
:type minutes: int
:param hours: The hours that will elapse before the next snapshot is
created.
Valid values 0 - 24. Default is 0.
:type hours: int
:param days: The days that will elapse before the next snapshot is created.
Default is 0.
:type days: int
"""
minutes = data_model.property(
"minutes",
int,
array=False,
optional=True,
documentation="Number of minutes between snapshots. "
"Valid values are: 0 - 59")
hours = data_model.property(
"hours",
int,
array=False,
optional=True,
documentation="Number of hours between snapshots. "
"Valid values are: 0 - 24")
days = data_model.property(
"days",
int,
array=False,
optional=False,
documentation="Number of days between snapshots.")
class CHAPSecret(data_model.DataObject):
"""
A representation of the CHAP Secret
:param secret: [required] A 12 - 16 character string.
:type start: str
"""
secret = data_model.property("secret",
str,
array=False,
optional=False,
documentation="A 12 - 16 character string.")
def __init__(self, **kwargs): #changed parameters number @subansu
secretInput = kwargs.pop('secretInput', None) #@subansu
data_model.DataObject.__init__(self, **kwargs)
if (secretInput != None):
self.secret = secretInput
@staticmethod
def auto_generate():
"""
Used in 'AddAccount' and 'ModifyAccount' to cause a CHAP Secret to be
auto generated by the cluster.
"""
chap = CHAPSecret()
chap.secret = AUTO_GENERATE_SECRET
return chap
@classmethod
def custom_extract(cls, data):
"""
Deserialize the property from json.
:param data: the data to be converted.
:return: the extracted data.
"""
chap = CHAPSecret()
chap.secret = data
return chap
def custom_to_json(self):
"""
Custom json serialize logic
:return:
"""
if self.secret == AUTO_GENERATE_SECRET:
return None
else:
return self.secret
class ApiModifyScheduleResult(data_model.DataObject):
"""
The object returned by the \"modify_schedule\" API Service call.
"""
schedule = data_model.property(
"schedule", ApiSchedule,
array=False, optional=False,
documentation="\
Schedule attributes with modifications.\
"
)
def __init__(self, **kwargs):
data_model.DataObject.__init__(self, **kwargs)
class ApiGetScheduleResult(data_model.DataObject):
"""
The object returned by the \"get_schedule\" API Service call.
:param schedule: [required] The schedule attributes.
:type schedule: Schedule
"""
schedule = data_model.property("schedule",
ApiSchedule,
array=False,
optional=False,
documentation="\
The schedule attributes.\
")
def __init__(self, **kwargs):
data_model.DataObject.__init__(self, **kwargs)
class ApiListSchedulesResult(data_model.DataObject):
"""
The object returned by the \"list_schedules\" API Service call.
:param schedules: [required] The list of schedules currently on the
cluster.
:type schedules: Schedule
"""
schedules = data_model.property("schedules",
ApiSchedule,
array=True,
optional=False,
documentation="\
The list of schedules currently on the cluster.\
")
def __init__(self, **kwargs):
data_model.DataObject.__init__(self, **kwargs)
class ApiScheduleInfo(data_model.DataObject):
"""
This represents the ScheduleInfo object in the ApiSchedule class. It
should not be used by users of this SDK. The ScheduleAdaptor will
convert between ApiScheduleInfo and ScheduleInfo during calls. Refer to
documentation about Schedule, ScheduleInfo, and Weekday for more
information.
:param volume_id: (optional) The ID of the volume to be included in the
snapshot.
:type volume_id: int
:param volumes: (required) A list of volume *ids* to be included in the
group snapshot.
:type volumes: int
:param name: (optional) The snapshot name to be used.
:type name: str
:param enable_remote_replication: (optional) Indicates if the snapshot
should be included in remote replication.
:type enable_remote_replication: bool
:param retention: (optional) The amount of time the snapshot will be
retained in HH:mm:ss.
:type retention: str
"""
volume_id = data_model.property("volumeID",
int,
array=False,
optional=True,
documentation="\
The ID of the volume to be included in the snapshot.\
")
volumes = data_model.property("volumes",
int,
array=True,
optional=False,
documentation="\
A list of volume *ids* to be included in the group snapshot.\
")
name = data_model.property("name",
str,
array=False,
optional=True,
documentation="\
The snapshot name to be used.\
")
enable_remote_replication = data_model.property("enableRemoteReplication",
bool,
array=False,
optional=True,
documentation="\
Indicates if the snapshot should be included in remote replication.\
")
retention = data_model.property("retention",
str,
array=False,
optional=True,
documentation="\
The amount of time the snapshot will be retained in HH:mm:ss.\
")
def __init__(self, **kwargs):
data_model.DataObject.__init__(self, **kwargs)
class ApiSchedule(data_model.DataObject):
"""
Schedule is an object containing information about each schedule created to
autonomously make a snapshot of a volume. The return object includes
information for all schedules. If *schedule_id* is used to identify a
specific schedule then only information for that *schedule_id* is returned.
Schedules information is returned with the API method, see *list_schedules*
on the SolidFire API guide page 245.
:param attributes: [required] Indicates the frequency of the schedule
occurrence.
Valid values are:
Day of Week
Day of Month
Time Interval
:type attributes: dict
:param has_error: Indicates whether or not the schedule has
errors.
:type has_error: bool
:param hours: [required] Shows the hours that will elapse before the next
snapshot is created.
Valid values are: 0 - 24
:type hours: int
:param last_run_status: Indicates the status of the last
scheduled snapshot.
Valid values are:
Success
Failed
:type last_run_status: str
:param last_run_time_started: Indicates the last time the schedule
started n ISO 8601 date string. Valid values are:
Success
Failed
:type last_run_time_started: str
:param minutes: [required] Shows the minutes that will elapse before the
next snapshot is created. Valid values are: 0 - 59
:type minutes: int
:param monthdays: Shows the days of the month that the next
snapshot will be created on. Valid values are: 0 - 31
:type monthdays: int
:param paused: Indicates whether or not the schedule is paused.
:type paused: bool
:param recurring: Indicates whether or not the schedule is
recurring.
:type recurring: bool
:param run_next_interval: Indicates whether or not the schedule
will run the next time the scheduler is active. When set to \"true\",
the schedule will run the next time the scheduler is active and then
reset back to \"false\".
:type run_next_interval: bool
:param schedule_id: Unique ID of the schedule
:type schedule_id: int
:param schedule_info: [required] Includes the unique name given to the
schedule, the retention period for the snapshot that was created, and
the volume ID of the volume from which the snapshot was created.
:type schedule_info: ScheduleInfo
:param schedule_name: Unique name assigned to the schedule.
:type schedule_name: str
:param schedule_type: [required] Only \"snapshot\" is supported at this
time.
:type schedule_type: str
:param starting_date: Indicates the date the first time the
schedule began of will begin. Formatted in UTC time.
:type starting_date: str
:param to_be_deleted: Indicates if the schedule is marked for
deletion.
:type to_be_deleted: bool
:param weekdays: Indicates the days of the week that a snapshot
will be made.
:type weekdays: Weekday
"""
attributes = data_model.property("attributes",
dict,
array=False,
optional=True,
documentation="\
Indicates the frequency of the schedule occurrence.\
Valid values are:\
Day of Week\
Day of Month\
Time Interval\
")
has_error = data_model.property("hasError",
bool,
array=False,
optional=True,
documentation="\
Indicates whether or not the schedule has errors.\
")
hours = data_model.property("hours",
int,
array=False,
optional=False,
documentation="\
Shows the hours that will elapse before the next snapshot is created.\
Valid values are: 0 - 24\
")
last_run_status = data_model.property("lastRunStatus",
str,
array=False,
optional=True,
documentation="\
Indicates the status of the last scheduled snapshot.\
Valid values are:\
Success\
Failed\
")
last_run_time_started = data_model.property("lastRunTimeStarted",
str,
array=False,
optional=True,
documentation="\
Indicates the last time the schedule started n ISO 8601 date string.\
Valid values are:\
Success\
Failed\
")
minutes = data_model.property("minutes",
int,
array=False,
optional=False,
documentation="\
Shows the minutes that will elapse before the next snapshot is\
created.\
Valid values are: 0 - 59\
")
monthdays = data_model.property("monthdays",
int,
array=True,
optional=False,
documentation="\
Shows the days of the month that the next snapshot will be created on.\
Valid values are: 0 - 31\
")
paused = data_model.property("paused",
bool,
array=False,
optional=True,
documentation="\
Indicates whether or not the schedule is paused.\
")
recurring = data_model.property("recurring",
bool,
array=False,
optional=True,
documentation="\
Indicates whether or not the schedule is recurring.\
")
run_next_interval = data_model.property("runNextInterval",
bool,
array=False,
optional=True,
documentation="\
Indicates whether or not the schedule will run the next time the\
scheduler is active. When set to \"true\", the schedule will run the\
next time the scheduler is active and then reset back to \"false\".\
")
schedule_id = data_model.property("scheduleID",
int,
array=False,
optional=True,
documentation="\
Unique ID of the schedule\
")
schedule_info = data_model.property("scheduleInfo",
ApiScheduleInfo,
array=False,
optional=False,
documentation="\
Includes the unique name given to the schedule, the retention period\
for the snapshot that was created, and the volume ID of the volume\
from which the snapshot was created.\
")
schedule_name = data_model.property("scheduleName",
str,
array=False,
optional=True,
documentation="\
Unique name assigned to the schedule.\
")
schedule_type = data_model.property("scheduleType",
str,
array=False,
optional=False,
documentation="\
Only \"snapshot\" is supported at this time.\
")
starting_date = data_model.property("startingDate",
str,
array=False,
optional=True,
documentation="\
Indicates the date the first time the schedule began of will begin.\
Formatted in UTC time.\
")
to_be_deleted = data_model.property("toBeDeleted",
bool,
array=False,
optional=True,
documentation="\
Indicates if the schedule is marked for deletion.\
")
weekdays = data_model.property("weekdays",
ApiWeekday,
array=True,
optional=False,
documentation="\
Indicates the days of the week that a snapshot will be made.\
")
def __init__(self, **kwargs):
data_model.DataObject.__init__(self, **kwargs)
