def get_short_data(self):
"""
Returns a shortend version of the item data.
:returns: data of the item
:rtype: str
"""
data_dict = self.get_latest_data()
if data_dict["window_stop"] == Time(0):
return "No data yet"
elif (Time.now() - data_dict["window_stop"]) > Duration(MAXIMUM_OFFLINE_TIME):
# last entry was more than MAXIMUM_OFFLINE_TIME ago, it could be offline!
return "No data since " + str(round((Time.now() - data_dict["window_stop"]).to_sec(), ROUND_DIGITS)) \
+ " seconds"
content = ""
if data_dict["state"] is "error":
content += self.get_erroneous_entries_for_log()
else:
content += self.tr("node_cpu_usage_mean") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_mean"]) + " " + self.tr("node_cpu_usage_mean_unit") + " - "
content += self.tr("node_ramusage_mean") + ": " + prepare_number_for_representation(
data_dict["node_ramusage_mean"]) \
+ " " + self.tr("node_ramusage_mean_unit") + " - "
content += self.tr("node_message_frequency_mean") + ": " + prepare_number_for_representation(
data_dict["node_message_frequency_mean"]) \
+ " " + self.tr("node_message_frequency_mean_unit") + " - "
content += self.tr("node_bandwidth_mean") + ": " + prepare_number_for_representation(
data_dict["node_bandwidth_mean"]) \
+ " " + self.tr("node_bandwidth_mean_unit")
return content
def get_short_data(self):
"""
Returns a shortend version of the item data.
:returns: data of the item
:rtype: str
"""
data_dict = self.get_latest_data()
if data_dict["window_stop"] == Time(0):
return "No data yet"
elif (Time.now() - data_dict["window_stop"]) > Duration(MAXIMUM_OFFLINE_TIME):
# last entry was more than MAXIMUM_OFFLINE_TIME ago, it could be offline!
return "No data since " + prepare_number_for_representation(Time.now() - data_dict["window_stop"]) \
+ " seconds"
content = ""
if data_dict["state"] is "error":
content += self.get_erroneous_entries_for_log()
else:
content += self.tr("frequency") + ": " + prepare_number_for_representation(data_dict["frequency"]) \
+ " " + self.tr("frequency_unit") + " - "
content += self.tr("bandwidth") + ": " + prepare_number_for_representation(
data_dict["bandwidth"]) + " " \
+ self.tr("bandwidth_unit") + " - "
content += self.tr("dropped_msgs") + ": " + prepare_number_for_representation(data_dict["dropped_msgs"]) \
+ " " + self.tr("dropped_msgs_unit")
return content
def get_short_data(self):
"""
Returns a shortend version of the item data.
:returns: data of the item
:rtype: str
"""
data_dict = self.get_latest_data()
if data_dict["window_stop"] == Time(0):
return "No data yet"
elif (Time.now() -
data_dict["window_stop"]) > Duration(MAXIMUM_OFFLINE_TIME):
# last entry was more than MAXIMUM_OFFLINE_TIME ago, it could be offline!
return "No data since " + prepare_number_for_representation(Time.now() - data_dict["window_stop"]) \
+ " seconds"
content = ""
if data_dict["state"] is "error":
content += self.get_erroneous_entries_for_log()
else:
content += self.tr("frequency") + ": " + prepare_number_for_representation(data_dict["frequency"]) \
+ " " + self.tr("frequency_unit") + " - "
content += self.tr("bandwidth") + ": " + prepare_number_for_representation(
data_dict["bandwidth"]) + " " \
+ self.tr("bandwidth_unit") + " - "
content += self.tr("dropped_msgs") + ": " + prepare_number_for_representation(data_dict["dropped_msgs"]) \
+ " " + self.tr("dropped_msgs_unit")
return content
def get_detailed_data(self):
"""
Returns the detailed data of the RootItem.
:returns: detailed data
:rtype: str
"""
data_dict = self.get_latest_data()
content = "<p class=\"detailed_data_overview\">"
content += self.tr("total_traffic") + ": " + prepare_number_for_representation(data_dict["total_traffic"]) + " " + self.tr("bandwidth_mean_unit") + " <br>"
content += self.tr("connected_hosts") + ": " + str(data_dict["connected_hosts"]) + "<br>"
content += self.tr("connected_nodes") + ": " + str(data_dict["connected_nodes"]) + "<br>"
content += self.tr("topic_counter") + ": " + str(data_dict["topic_counter"]) + "<br>"
content += self.tr("connection_counter") + ": " + str(data_dict["connection_counter"]) + "<br>"
content += self.tr("cpu_usage_max") + ": " + prepare_number_for_representation(data_dict["cpu_usage_max"]) + " " + self.tr("cpu_usage_max_unit") + " <br>"
content += self.tr("cpu_temp_mean") + ": " + ("unknown" if prepare_number_for_representation(data_dict["cpu_temp_mean"]) is 0
else prepare_number_for_representation(data_dict["cpu_temp_mean"])) + " " + self.tr("cpu_temp_mean_unit") + " <br>"
content += self.tr("ram_usage_mean") + ": " + prepare_number_for_representation(data_dict["ram_usage_mean"]) + " " + self.tr("ram_usage_mean_unit") + " <br>"
content += self.tr("cpu_usage_mean") + ": " + prepare_number_for_representation(data_dict["cpu_usage_mean"]) + " " + self.tr("cpu_usage_mean_unit") + " <br>"
content += self.tr("cpu_temp_max") + ": " + ("unknown" if prepare_number_for_representation(data_dict["cpu_temp_max"]) is 0
else prepare_number_for_representation(data_dict["cpu_temp_max"])) + " " + self.tr("cpu_temp_max_unit") + " <br>"
content += self.tr("ram_usage_max") + ": " + prepare_number_for_representation(data_dict["ram_usage_max"]) + " " + self.tr("ram_usage_max_unit") + " <br>"
return content
def get_erroneous_entries(self):
"""
Returns the erroneous entries as a html string
:returns: an html string containing the erroneous entries yet preformatted
:rtype: str
"""
self._data_lock.acquire()
content = "<p class=\"get_erroneous_entries\">"
return_values = {}
if self.__state:
if self.get_state() is not "ok" and self.get_state(
) is not "unknown":
if self._rated_data["alive.state"]:
if self._rated_data["alive.state"][
-1] is "high" or self._rated_data["alive.state"][
-1] is "low":
content += self.tr("alive actual_value:") + \
" <span class=\"erroneous_entry\">" + prepare_number_for_representation(
self._rated_data["alive.actual_value"][-1][0]) + "</span>" + \
"<br>"
content += self.tr("alive expected_value:") + \
" <span class=\"erroneous_entry\">" + str(
self._rated_data["alive.expected_value"][-1][0]) + "</span>" + \
"<br>"
content += self.tr("alive state:") + \
" <span class=\"erroneous_entry\">" + str(
self._rated_data["alive.state"][-1]) + "</span>" + "<br>"
for entry in self._attributes:
if self._rated_data[entry + ".state"]:
if self._rated_data[
entry +
".state"][-1] is "high" or self._rated_data[
entry + ".state"][-1] is "low":
content += self.tr(entry) + \
self.tr(" actual_value:") + \
" <span class=\"erroneous_entry\">" + prepare_number_for_representation(
self._rated_data[entry + ".actual_value"][-1][0]) + "</span> " + \
self.tr(entry + "_unit") + "<br>"
content += self.tr(entry) + \
self.tr(" expected_value:") + \
" <span class=\"erroneous_entry\">" + str(
self._rated_data[entry + ".expected_value"][-1][0]) + "</span> " + \
self.tr(entry + "_unit") + "<br>"
content += self.tr(entry) + \
self.tr(" state:") + \
" <span class=\"erroneous_entry\">" + str(
self._rated_data[entry + ".state"][-1]) + "</span>" + "<br>"
content += "<br>"
content += "</p>"
self._data_lock.release()
return content
def get_erroneous_entries(self):
"""
Returns the erroneous entries as a html string
:returns: an html string containing the erroneous entries yet preformatted
:rtype: str
"""
self._data_lock.acquire()
content = "<p class=\"get_erroneous_entries\">"
return_values = {}
if self.__state:
if self.get_state() is not "ok" and self.get_state() is not "unknown":
if self._rated_data["alive.state"]:
if self._rated_data["alive.state"][-1] is "high" or self._rated_data["alive.state"][-1] is "low":
content += self.tr("alive actual_value:") + \
" <span class=\"erroneous_entry\">" + prepare_number_for_representation(
self._rated_data["alive.actual_value"][-1][0]) + "</span>" + \
"<br>"
content += self.tr("alive expected_value:") + \
" <span class=\"erroneous_entry\">" + str(
self._rated_data["alive.expected_value"][-1][0]) + "</span>" + \
"<br>"
content += self.tr("alive state:") + \
" <span class=\"erroneous_entry\">" + str(
self._rated_data["alive.state"][-1]) + "</span>" + "<br>"
for entry in self._attributes:
if self._rated_data[entry + ".state"]:
if self._rated_data[entry + ".state"][-1] is "high" or self._rated_data[entry + ".state"][
-1] is "low":
content += self.tr(entry) + \
self.tr(" actual_value:") + \
" <span class=\"erroneous_entry\">" + prepare_number_for_representation(
self._rated_data[entry + ".actual_value"][-1][0]) + "</span> " + \
self.tr(entry + "_unit") + "<br>"
content += self.tr(entry) + \
self.tr(" expected_value:") + \
" <span class=\"erroneous_entry\">" + str(
self._rated_data[entry + ".expected_value"][-1][0]) + "</span> " + \
self.tr(entry + "_unit") + "<br>"
content += self.tr(entry) + \
self.tr(" state:") + \
" <span class=\"erroneous_entry\">" + str(
self._rated_data[entry + ".state"][-1]) + "</span>" + "<br>"
content += "<br>"
content += "</p>"
self._data_lock.release()
return content
def get_detailed_data(self):
"""
Returns the detailed data of the HostItem.
:returns: detailed data
:rtype: str
"""
data_dict = self.get_latest_data()
for key in self.__calculated_data:
if self.__calculated_data[key]:
data_dict[key] = self.__calculated_data[key][-1]
else:
data_dict[key] = self.tr("Currently no value available")
data_dict["state"] = self.get_state()
content = "<p class=\"detailed_data\">"
content += self.get_erroneous_entries()
content += "Rounded to a second:<br>"
if "frequency" in self._attributes:
content += self.tr("frequency") + ": " + prepare_number_for_representation(data_dict["frequency"]) \
+ " " + self.tr("frequency_unit") + " <br>"
content += self.tr("bandwidth") + ": " + prepare_number_for_representation(bytes_to_kb(data_dict["bandwidth"])) \
+ " " + self.tr("bandwidth_unit") + " <br>"
content += self.tr("dropped_msgs") + ": " + prepare_number_for_representation(data_dict["dropped_msgs"]) \
+ " " + self.tr("dropped_msgs_unit") + " <br>"
content += self.tr("period_max") + ": " + prepare_number_for_representation(data_dict["period_max"]) \
+ " " + self.tr("period_max_unit") + " <br>"
content += self.tr("stamp_age_max") + ": " + prepare_number_for_representation(data_dict["stamp_age_max"]) \
+ " " + self.tr("stamp_age_max_unit") + " <br>"
## CARSON ADDED
if self.throttle is not None:
content += "<b>Active Throttle</b>"
content += "<ul>"
if isinstance(self.throttle, MessageThrottle):
content += "<li>" + "Type: Message Throttle" + "</li>"
content += "<li>" + "Rate: " + prepare_number_for_representation(
self.throttle.rate) + " Hz </li>"
else:
content += "<li>" + "Type: Bandwidth Throttle" + "</li>"
content += "<li>" + "Bandwidth: " + prepare_number_for_representation(
self.throttle.bandwidth) + " Bytes/s</li>"
content += "<li>" + "Window: " + prepare_number_for_representation(
self.throttle.window) + " s</li>"
content += "<li>" + "Publishing on: /%s" % (
self.throttle.outtopic) + "</li>"
content += "</ul>"
else:
content += "No Active Throttles <br>"
##
content += "</p>"
return content
def get_short_data(self):
"""
Returns a shortend version of the item data.
:returns: data of the item
:rtype: str
"""
data_dict = {}
for key in self.__calculated_data:
if self.__calculated_data[key]:
data_dict[key] = self.__calculated_data[key][-1]
else:
data_dict[key] = self.tr("Currently no value available")
data_dict["window_stop"] = Time(0)
data_dict["window_start"] = Time(0)
data_dict["state"] = self.get_state()
try:
if type(data_dict["window_stop"]) == type(1):
data_dict["window_stop"] = Time(data_dict["window_stop"])
if data_dict["window_stop"] == Time(0):
return "No data yet"
elif (Time.now() -
data_dict["window_stop"]) > Duration(MAXIMUM_OFFLINE_TIME):
# last entry was more than MAXIMUM_OFFLINE_TIME ago, it could be offline!
print("test 2")
return "No data since " + prepare_number_for_representation(Time.now() - data_dict["window_stop"]) \
+ " seconds"
except Exception as e:
print(data_dict["window_stop"])
print(e)
raise UserWarning
content = ""
if data_dict["state"] is "error":
content += self.get_erroneous_entries_for_log()
else:
content += self.tr("frequency") + ": " + prepare_number_for_representation(
data_dict["frequency"]) + " " \
+ self.tr("frequency_unit") + " - "
content += self.tr("bandwidth") + ": " + prepare_number_for_representation(bytes_to_kb(data_dict["bandwidth"])) \
+ " " + self.tr("bandwidth_unit") + " - "
content += self.tr("dropped_msgs") + ": " + prepare_number_for_representation(data_dict["dropped_msgs"]) \
+ " " + self.tr("dropped_msgs_unit")
return content
def get_short_data(self):
"""
Returns a shortend version of the item data.
:returns: data of the item
:rtype: str
"""
data_dict = self.get_latest_data()
if data_dict["window_stop"] == Time(0):
return "No data yet"
elif (Time.now() - data_dict["window_stop"]) > Duration(MAXIMUM_OFFLINE_TIME):
# last entry was more than MAXIMUM_OFFLINE_TIME ago, it could be offline!
return (
"No data since " + prepare_number_for_representation(Time.now() - data_dict["window_stop"]) + " seconds"
)
content = ""
if data_dict["state"] is "error":
content += self.get_erroneous_entries_for_log()
else:
content += (
self.tr("cpu_usage_mean")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_usage_mean"])
+ " "
+ self.tr("cpu_usage_mean_unit")
+ " - "
)
content += (
self.tr("ram_usage_mean")
+ ": "
+ prepare_number_for_representation(data_dict["ram_usage_mean"])
+ " "
+ self.tr("ram_usage_mean_unit")
+ " - "
)
content += (
self.tr("cpu_temp_mean")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_temp_mean"])
+ " "
+ self.tr("cpu_temp_mean_unit")
)
return content
def get_detailed_data(self):
"""
Returns the detailed data of the RootItem.
:returns: detailed data
:rtype: str
"""
data_dict = self.get_latest_data()
content = "<p class=\"detailed_data_overview\">"
content += self.tr(
"total_traffic") + ": " + prepare_number_for_representation(
data_dict["total_traffic"]) + " " + self.tr(
"bandwidth_mean_unit") + " <br>"
content += self.tr("connected_hosts") + ": " + str(
data_dict["connected_hosts"]) + "<br>"
content += self.tr("connected_nodes") + ": " + str(
data_dict["connected_nodes"]) + "<br>"
content += self.tr("topic_counter") + ": " + str(
data_dict["topic_counter"]) + "<br>"
content += self.tr("connection_counter") + ": " + str(
data_dict["connection_counter"]) + "<br>"
content += self.tr(
"cpu_usage_max") + ": " + prepare_number_for_representation(
data_dict["cpu_usage_max"]) + " " + self.tr(
"cpu_usage_max_unit") + " <br>"
content += self.tr("cpu_temp_mean") + ": " + (
"unknown" if
prepare_number_for_representation(data_dict["cpu_temp_mean"]) is 0
else prepare_number_for_representation(data_dict["cpu_temp_mean"])
) + " " + self.tr("cpu_temp_mean_unit") + " <br>"
content += self.tr(
"ram_usage_mean") + ": " + prepare_number_for_representation(
data_dict["ram_usage_mean"]) + " " + self.tr(
"ram_usage_mean_unit") + " <br>"
content += self.tr(
"cpu_usage_mean") + ": " + prepare_number_for_representation(
data_dict["cpu_usage_mean"]) + " " + self.tr(
"cpu_usage_mean_unit") + " <br>"
content += self.tr("cpu_temp_max") + ": " + (
"unknown" if
prepare_number_for_representation(data_dict["cpu_temp_max"]) is 0
else prepare_number_for_representation(data_dict["cpu_temp_max"])
) + " " + self.tr("cpu_temp_max_unit") + " <br>"
content += self.tr(
"ram_usage_max") + ": " + prepare_number_for_representation(
data_dict["ram_usage_max"]) + " " + self.tr(
"ram_usage_max_unit") + " <br>"
return content
def get_short_data(self):
"""
Returns a shortend version of the item data.
:returns: data of the item
:rtype: str
"""
data_dict = {}
for key in self.__calculated_data:
if self.__calculated_data[key]:
data_dict[key] = self.__calculated_data[key][-1]
else:
data_dict[key] = self.tr("Currently no value available")
data_dict["window_stop"] = Time(0)
data_dict["window_start"] = Time(0)
data_dict["state"] = self.get_state()
try:
if data_dict["window_stop"] == Time(0):
return "No data yet"
elif (Time.now() - data_dict["window_stop"]) > Duration(MAXIMUM_OFFLINE_TIME):
# last entry was more than MAXIMUM_OFFLINE_TIME ago, it could be offline!
return "No data since " + prepare_number_for_representation(Time.now() - data_dict["window_stop"]) \
+ " seconds"
except:
print(data_dict["window_stop"])
raise UserWarning
content = ""
if data_dict["state"] is "error":
content += self.get_erroneous_entries_for_log()
else:
content += self.tr("frequency") + ": " + prepare_number_for_representation(
data_dict["frequency"]) + " " \
+ self.tr("frequency_unit") + " - "
content += self.tr("bandwidth") + ": " + prepare_number_for_representation(data_dict["bandwidth"]) \
+ " " + self.tr("bandwidth_unit") + " - "
content += self.tr("dropped_msgs") + ": " + prepare_number_for_representation(data_dict["dropped_msgs"]) \
+ " " + self.tr("dropped_msgs_unit")
return content
def get_detailed_data(self):
"""
Returns the detailed data of the HostItem.
:returns: detailed data
:rtype: str
"""
data_dict = self.get_latest_data()
for key in self.__calculated_data:
if self.__calculated_data[key]:
data_dict[key] = self.__calculated_data[key][-1]
else:
data_dict[key] = self.tr("Currently no value available")
data_dict["state"] = self.get_state()
content = "<p class=\"detailed_data\">"
content += self.get_erroneous_entries()
content += "Rounded to a second:<br>"
if "frequency" in self._attributes:
content += self.tr("frequency") + ": " + prepare_number_for_representation(data_dict["frequency"]) \
+ " " + self.tr("frequency_unit") + " <br>"
content += self.tr("bandwidth") + ": " + prepare_number_for_representation(data_dict["bandwidth"]) \
+ " " + self.tr("bandwidth_unit") + " <br>"
content += self.tr("dropped_msgs") + ": " + prepare_number_for_representation(data_dict["dropped_msgs"]) \
+ " " + self.tr("dropped_msgs_unit") + " <br>"
content += self.tr("period_max") + ": " + prepare_number_for_representation(data_dict["period_max"]) \
+ " " + self.tr("period_max_unit") + " <br>"
content += self.tr("stamp_age_max") + ": " + prepare_number_for_representation(data_dict["stamp_age_max"]) \
+ " " + self.tr("stamp_age_max_unit") + " <br>"
content += "</p>"
return content
def get_detailed_data(self):
"""
Returns the detailed data of the HostItem.
:returns: detailed data
:rtype: str
"""
data_dict = self.get_latest_data()
for key in self.__calculated_data:
if self.__calculated_data[key]:
data_dict[key] = self.__calculated_data[key][-1]
else:
data_dict[key] = self.tr("Currently no value available")
data_dict["state"] = self.get_state()
content = "<p class=\"detailed_data\">"
content += self.get_erroneous_entries()
content += "Rounded to a second:<br>"
if "frequency" in self._attributes:
content += self.tr("frequency") + ": " + prepare_number_for_representation(data_dict["frequency"]) \
+ " " + self.tr("frequency_unit") + " <br>"
content += self.tr("bandwidth") + ": " + prepare_number_for_representation(data_dict["bandwidth"]) \
+ " " + self.tr("bandwidth_unit") + " <br>"
content += self.tr("dropped_msgs") + ": " + prepare_number_for_representation(data_dict["dropped_msgs"]) \
+ " " + self.tr("dropped_msgs_unit") + " <br>"
content += self.tr("period_max") + ": " + prepare_number_for_representation(data_dict["period_max"]) \
+ " " + self.tr("period_max_unit") + " <br>"
content += self.tr("stamp_age_max") + ": " + prepare_number_for_representation(data_dict["stamp_age_max"]) \
+ " " + self.tr("stamp_age_max_unit") + " <br>"
content += "</p>"
return content
def get_short_data(self):
"""
Returns a shortend version of the item data.
:returns: data of the item
:rtype: str
"""
data_dict = self.get_latest_data()
if data_dict["window_stop"] == Time(0):
return "No data yet"
elif (Time.now() -
data_dict["window_stop"]) > Duration(MAXIMUM_OFFLINE_TIME):
# last entry was more than MAXIMUM_OFFLINE_TIME ago, it could be offline!
return "No data since " + str(round((Time.now() - data_dict["window_stop"]).to_sec(), ROUND_DIGITS)) \
+ " seconds"
content = ""
if data_dict["state"] is "error":
content += self.get_erroneous_entries_for_log()
else:
content += self.tr(
"node_cpu_usage_mean"
) + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_mean"]) + " " + self.tr(
"node_cpu_usage_mean_unit") + " - "
content += self.tr("node_ramusage_mean") + ": " + prepare_number_for_representation(
data_dict["node_ramusage_mean"]) \
+ " " + self.tr("node_ramusage_mean_unit") + " - "
content += self.tr("node_message_frequency_mean") + ": " + prepare_number_for_representation(
data_dict["node_message_frequency_mean"]) \
+ " " + self.tr("node_message_frequency_mean_unit") + " - "
content += self.tr("node_bandwidth_mean") + ": " + prepare_number_for_representation(
data_dict["node_bandwidth_mean"]) \
+ " " + self.tr("node_bandwidth_mean_unit")
return content
def get_detailed_data(self):
"""
Returns the detailed data of the ConnectionItem.
:returns: str
"""
data_dict = self.get_latest_data()
if Time.now() - data_dict["window_stop"] > Duration(secs=5):
return "No recent data"
content = "<p class=\"detailed_data\">"
content += self.get_erroneous_entries()
if "frequency" in self._attributes:
content += self.tr("frequency") + ": " + prepare_number_for_representation(data_dict["frequency"]) \
+ " " + self.tr("frequency_unit") + " <br>"
content += self.tr("dropped_msgs") + ": " + prepare_number_for_representation(data_dict["dropped_msgs"]) + " " \
+ self.tr("dropped_msgs_unit") + " <br>"
content += self.tr("bandwidth") + ": " + prepare_number_for_representation(data_dict["bandwidth"]) + " " \
+ " " + self.tr("bandwidth_unit") + " <br>"
content += self.tr("period_mean") + ": " + prepare_number_for_representation(data_dict["period_mean"]) \
+ " " + self.tr("period_mean_unit") + " <br>"
content += self.tr("period_stddev") + ": " + prepare_number_for_representation(data_dict["period_stddev"]) \
+ " " + self.tr("period_stddev_unit") + " <br>"
content += self.tr("period_max") + ": " + prepare_number_for_representation(data_dict["period_max"]) + " " \
+ self.tr("period_max_unit") + " <br>"
content += self.tr("stamp_age_mean") + ": " + prepare_number_for_representation(data_dict["stamp_age_mean"]) \
+ " " + self.tr("stamp_age_mean_unit") + " <br>"
content += self.tr("stamp_age_stddev") + ": " + prepare_number_for_representation(data_dict["stamp_age_stddev"]) \
+ " " + self.tr("stamp_age_stddev_unit") + " <br>"
content += self.tr("stamp_age_max") + ": " + prepare_number_for_representation(data_dict["stamp_age_max"]) \
+ " " + self.tr("stamp_age_max_unit") + " <br>"
content += "</p>"
return content
def get_detailed_data(self):
"""
Returns the detailed data of the ConnectionItem.
:returns: str
"""
data_dict = self.get_latest_data()
if Time.now() - data_dict["window_stop"] > Duration(secs=5):
return "No recent data"
content = "<p class=\"detailed_data\">"
content += self.get_erroneous_entries()
if "frequency" in self._attributes:
content += self.tr("frequency") + ": " + prepare_number_for_representation(data_dict["frequency"]) \
+ " " + self.tr("frequency_unit") + " <br>"
content += self.tr("dropped_msgs") + ": " + prepare_number_for_representation(data_dict["dropped_msgs"]) + " " \
+ self.tr("dropped_msgs_unit") + " <br>"
content += self.tr("bandwidth") + ": " + prepare_number_for_representation(data_dict["bandwidth"]) + " " \
+ " " + self.tr("bandwidth_unit") + " <br>"
content += self.tr("period_mean") + ": " + prepare_number_for_representation(data_dict["period_mean"]) \
+ " " + self.tr("period_mean_unit") + " <br>"
content += self.tr("period_stddev") + ": " + prepare_number_for_representation(data_dict["period_stddev"]) \
+ " " + self.tr("period_stddev_unit") + " <br>"
content += self.tr("period_max") + ": " + prepare_number_for_representation(data_dict["period_max"]) + " " \
+ self.tr("period_max_unit") + " <br>"
content += self.tr("stamp_age_mean") + ": " + prepare_number_for_representation(data_dict["stamp_age_mean"]) \
+ " " + self.tr("stamp_age_mean_unit") + " <br>"
content += self.tr("stamp_age_stddev") + ": " + prepare_number_for_representation(data_dict["stamp_age_stddev"]) \
+ " " + self.tr("stamp_age_stddev_unit") + " <br>"
content += self.tr("stamp_age_max") + ": " + prepare_number_for_representation(data_dict["stamp_age_max"]) \
+ " " + self.tr("stamp_age_max_unit") + " <br>"
content += "</p>"
return content
def get_detailed_data(self):
"""
Returns the detailed data of the HostItem.
:returns: detailed data
:rtype: str
"""
data_dict = self.get_latest_data()
content = '<p class="detailed_data">'
content += self.get_erroneous_entries()
content += (
self.tr("cpu_usage_mean")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_usage_mean"])
+ " "
+ self.tr("cpu_usage_mean_unit")
+ " <br>"
)
content += (
self.tr("cpu_usage_stddev")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_usage_stddev"])
+ " "
+ self.tr("cpu_usage_stddev_unit")
+ " <br>"
)
content += (
self.tr("cpu_usage_max")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_usage_max"])
+ " "
+ self.tr("cpu_usage_max_unit")
+ " <br>"
)
content += (
self.tr("cpu_temp_mean")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_temp_mean"])
+ " "
+ self.tr("cpu_temp_mean_unit")
+ " <br>"
)
content += (
self.tr("cpu_temp_stddev")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_temp_stddev"])
+ " "
+ self.tr("cpu_temp_stddev_unit")
+ " <br>"
)
content += (
self.tr("cpu_temp_max")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_temp_max"])
+ " "
+ self.tr("cpu_temp_max_unit")
+ " <br>"
)
content += (
self.tr("ram_usage_mean")
+ ": "
+ prepare_number_for_representation(data_dict["ram_usage_mean"])
+ " "
+ self.tr("ram_usage_mean_unit")
+ " <br>"
)
content += (
self.tr("ram_usage_stddev")
+ ": "
+ prepare_number_for_representation(data_dict["ram_usage_stddev"])
+ " "
+ self.tr("ram_usage_stddev_unit")
+ " <br>"
)
content += (
self.tr("ram_usage_max")
+ ": "
+ prepare_number_for_representation(data_dict["ram_usage_max"])
+ " "
+ self.tr("ram_usage_max_unit")
+ " <br>"
)
for i in range(0, len(data_dict["cpu_usage_core_mean"])):
content += self.tr("core" + str(i + 1)) + "<br>"
content += (
self.tr("cpu_usage_core_mean")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_usage_core_mean"][i])
+ " "
+ self.tr("cpu_usage_core_mean_unit")
+ " <br>"
)
content += (
self.tr("cpu_usage_core_stddev")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_usage_core_stddev"][i])
+ " "
+ self.tr("cpu_usage_core_stddev_unit")
+ " <br>"
)
content += (
self.tr("cpu_usage_core_max")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_usage_core_max"][i])
+ " "
+ self.tr("cpu_usage_core_max_unit")
+ " <br>"
)
content += (
self.tr("cpu_temp_core_mean")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_temp_core_mean"][i])
+ " "
+ self.tr("cpu_temp_core_mean_unit")
+ " <br>"
)
content += (
self.tr("cpu_temp_core_stddev")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_temp_core_stddev"][i])
+ " "
+ self.tr("cpu_temp_core_stddev_unit")
+ " <br>"
)
content += (
self.tr("cpu_temp_core_max")
+ ": "
+ prepare_number_for_representation(data_dict["cpu_temp_core_max"][i])
+ " "
+ self.tr("cpu_temp_core_max_unit")
+ " <br>"
)
for i in range(0, len(data_dict["gpu_usage_mean"])):
content += (
self.tr("gpu_temp_mean")
+ ": "
+ prepare_number_for_representation(data_dict["gpu_temp_mean"][i])
+ " "
+ self.tr("gpu_temp_mean_unit")
+ " <br>"
)
content += (
self.tr("gpu_temp_stddev")
+ ": "
+ prepare_number_for_representation(data_dict["gpu_temp_stddev"][i])
+ " "
+ self.tr("gpu_temp_stddev_unit")
+ " <br>"
)
content += (
self.tr("gpu_temp_max")
+ ": "
+ prepare_number_for_representation(data_dict["gpu_temp_max"][i])
+ " "
+ self.tr("gpu_temp_max_unit")
+ " <br>"
)
content += (
self.tr("gpu_usage_mean")
+ ": "
+ prepare_number_for_representation(data_dict["gpu_usage_mean"][i])
+ " "
+ self.tr("gpu_usage_mean_unit")
+ " <br>"
)
content += (
self.tr("gpu_usage_stddev")
+ ": "
+ prepare_number_for_representation(data_dict["gpu_usage_stddev"][i])
+ " "
+ self.tr("gpu_usage_stddev_unit")
+ " <br>"
)
content += (
self.tr("gpu_usage_max")
+ ": "
+ prepare_number_for_representation(data_dict["gpu_usage_max"][i])
+ " "
+ self.tr("gpu_usage_max_unit")
+ " <br>"
)
for i in range(0, len(data_dict["interface_name"])):
content += str(data_dict["interface_name"][i]) + "<br>"
content += (
self.tr("message_frequency_mean")
+ ": "
+ prepare_number_for_representation(data_dict["message_frequency_mean"][i])
+ " "
+ self.tr("message_frequency_mean_unit")
+ " <br>"
)
content += (
self.tr("message_frequency_stddev")
+ ": "
+ prepare_number_for_representation(data_dict["message_frequency_stddev"][i])
+ " "
+ self.tr("message_frequency_stddev_unit")
+ " <br>"
)
content += (
self.tr("message_frequency_max")
+ ": "
+ prepare_number_for_representation(data_dict["message_frequency_max"][i])
+ " "
+ self.tr("message_frequency_max_unit")
+ " <br>"
)
content += (
self.tr("bandwidth_mean")
+ ": "
+ prepare_number_for_representation(data_dict["bandwidth_mean"][i])
+ " "
+ self.tr("bandwidth_mean_unit")
+ " <br>"
)
content += (
self.tr("bandwidth_stddev")
+ ": "
+ prepare_number_for_representation(data_dict["bandwidth_stddev"][i])
+ " "
+ self.tr("bandwidth_stddev_unit")
+ " <br>"
)
content += (
self.tr("bandwidth_max")
+ ": "
+ prepare_number_for_representation(data_dict["bandwidth_max"][i])
+ " "
+ self.tr("bandwidth_max_unit")
+ " <br>"
)
for i in range(0, len(data_dict["drive_name"])):
content += data_dict["drive_name"][i] + " <br>"
content += (
self.tr("drive_free_space")
+ ": "
+ prepare_number_for_representation(data_dict["drive_free_space"][i])
+ " "
+ self.tr("drive_free_space_unit")
+ " <br>"
)
content += (
self.tr("drive_read")
+ ": "
+ prepare_number_for_representation(data_dict["drive_read"][i])
+ " "
+ self.tr("drive_read_unit")
+ " <br>"
)
content += (
self.tr("drive_write")
+ ": "
+ prepare_number_for_representation(data_dict["drive_write"][i])
+ " "
+ self.tr("drive_write_unit")
+ " <br>"
)
content += "</p>"
return content
def get_detailed_data(self):
"""
Returns the detailed data of the NodeItem.
:returns: detailed data
:rtype: str
"""
data_dict = self.get_latest_data()
content = "<p class=\"detailed_data\">"
content += self.get_erroneous_entries()
content += self.tr("node_cpu_usage_mean") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_mean"]) + " " + self.tr("node_cpu_usage_mean_unit") + " <br>"
content += self.tr("node_cpu_usage_stddev") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_stddev"]) \
+ " " + self.tr("node_cpu_usage_stddev_unit") + " <br>"
content += self.tr("node_cpu_usage_max") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_max"]) \
+ " " + self.tr("node_cpu_usage_max_unit") + " <br>"
content += self.tr("node_ramusage_mean") + ": " + prepare_number_for_representation(
data_dict["node_ramusage_mean"]) \
+ " " + self.tr("node_ramusage_mean_unit") + " <br>"
content += self.tr("node_ramusage_stddev") + ": " + prepare_number_for_representation(
data_dict["node_ramusage_stddev"]) \
+ " " + self.tr("node_ramusage_stddev_unit") + " <br>"
content += self.tr("node_ramusage_max") + ": " + prepare_number_for_representation(
data_dict["node_ramusage_max"]) \
+ " " + self.tr("node_ramusage_max_unit") + " <br>"
for i in range(0, len(data_dict["node_cpu_usage_core_mean"])):
content += self.tr("core" + str(i + 1)) + "<br>"
content += self.tr("node_cpu_usage_core_mean") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_core_mean"][i]) \
+ " " + self.tr("node_cpu_usage_core_mean_unit") + " <br>"
content += self.tr("node_cpu_usage_core_stddev") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_core_stddev"][i]) \
+ " " + self.tr("node_cpu_usage_core_stddev_unit") + " <br>"
content += self.tr("node_cpu_usage_core_max") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_core_max"][i]) \
+ " " + self.tr("node_cpu_usage_core_max_unit") + " <br>"
for i in range(0, len(data_dict["node_gpu_usage_mean"])):
content += self.tr("node_gpu_usage_mean") + ": " + prepare_number_for_representation(
data_dict["node_gpu_usage_mean"][i]) \
+ " " + self.tr("node_gpu_usage_mean_unit") + " <br>"
content += self.tr("node_gpu_usage_stddev") + ": " + prepare_number_for_representation(
data_dict["node_gpu_usage_stddev"][i]) \
+ " " + self.tr("node_gpu_usage_stddev_unit") + " <br>"
content += self.tr("node_gpu_usage_max") + ": " + prepare_number_for_representation(
data_dict["node_gpu_usage_max"][i]) \
+ " " + self.tr("node_gpu_usage_max_unit") + " <br>"
content += self.tr("node_message_frequency_mean") + ": " + prepare_number_for_representation(
data_dict["node_message_frequency_mean"]) \
+ " " + self.tr("node_message_frequency_mean_unit") + " <br>"
content += self.tr("node_message_frequency_stddev") + ": " + prepare_number_for_representation(
data_dict["node_message_frequency_stddev"]) \
+ " " + self.tr("node_message_frequency_stddev_unit") + " <br>"
content += self.tr("node_message_frequency_max") + ": " + prepare_number_for_representation(
data_dict["node_message_frequency_max"]) \
+ " " + self.tr("node_message_frequency_max_unit") + " <br>"
content += self.tr("node_bandwidth_mean") + ": " + prepare_number_for_representation(
data_dict["node_bandwidth_mean"]) \
+ " " + self.tr("node_bandwidth_mean_unit") + " <br>"
content += self.tr("node_bandwidth_stddev") + ": " + prepare_number_for_representation(
data_dict["node_bandwidth_stddev"]) \
+ " " + self.tr("node_bandwidth_stddev_unit") + " <br>"
content += self.tr("node_bandwidth_max") + ": " + prepare_number_for_representation(
data_dict["node_bandwidth_max"]) \
+ " " + self.tr("node_bandwidth_max_unit") + " <br>"
content += self.tr("node_write_mean") + ": " + prepare_number_for_representation(data_dict["node_write_mean"]) \
+ " " + self.tr("node_write_mean_unit") + " <br>"
content += self.tr("node_write_stddev") + ": " + prepare_number_for_representation(
data_dict["node_write_stddev"]) \
+ " " + self.tr("node_write_stddev_unit") + " <br>"
content += self.tr("node_write_max") + ": " + prepare_number_for_representation(data_dict["node_write_max"]) \
+ " " + self.tr("node_write_max_unit") + " <br>"
content += self.tr("node_read_mean") + ": " + prepare_number_for_representation(data_dict["node_read_mean"]) \
+ " " + self.tr("node_read_mean_unit") + " <br>"
content += self.tr("node_read_stddev") + ": " + prepare_number_for_representation(data_dict["node_read_stddev"]) \
+ " " + self.tr("node_read_stddev_unit") + " <br>"
content += self.tr("node_read_max") + ": " + prepare_number_for_representation(data_dict["node_read_max"]) \
+ " " + self.tr("node_read_max_unit") + " <br>"
content += "</p>"
return content
def get_detailed_data(self):
"""
Returns the detailed data of the NodeItem.
:returns: detailed data
:rtype: str
"""
data_dict = self.get_latest_data()
content = "<p class=\"detailed_data\">"
content += self.get_erroneous_entries()
content += self.tr(
"node_cpu_usage_mean") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_mean"]) + " " + self.tr(
"node_cpu_usage_mean_unit") + " <br>"
content += self.tr("node_cpu_usage_stddev") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_stddev"]) \
+ " " + self.tr("node_cpu_usage_stddev_unit") + " <br>"
content += self.tr("node_cpu_usage_max") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_max"]) \
+ " " + self.tr("node_cpu_usage_max_unit") + " <br>"
content += self.tr("node_ramusage_mean") + ": " + prepare_number_for_representation(
data_dict["node_ramusage_mean"]) \
+ " " + self.tr("node_ramusage_mean_unit") + " <br>"
content += self.tr("node_ramusage_stddev") + ": " + prepare_number_for_representation(
data_dict["node_ramusage_stddev"]) \
+ " " + self.tr("node_ramusage_stddev_unit") + " <br>"
content += self.tr("node_ramusage_max") + ": " + prepare_number_for_representation(
data_dict["node_ramusage_max"]) \
+ " " + self.tr("node_ramusage_max_unit") + " <br>"
for i in range(0, len(data_dict["node_cpu_usage_core_mean"])):
content += self.tr("core" + str(i + 1)) + "<br>"
content += self.tr("node_cpu_usage_core_mean") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_core_mean"][i]) \
+ " " + self.tr("node_cpu_usage_core_mean_unit") + " <br>"
content += self.tr("node_cpu_usage_core_stddev") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_core_stddev"][i]) \
+ " " + self.tr("node_cpu_usage_core_stddev_unit") + " <br>"
content += self.tr("node_cpu_usage_core_max") + ": " + prepare_number_for_representation(
data_dict["node_cpu_usage_core_max"][i]) \
+ " " + self.tr("node_cpu_usage_core_max_unit") + " <br>"
for i in range(0, len(data_dict["node_gpu_usage_mean"])):
content += self.tr("node_gpu_usage_mean") + ": " + prepare_number_for_representation(
data_dict["node_gpu_usage_mean"][i]) \
+ " " + self.tr("node_gpu_usage_mean_unit") + " <br>"
content += self.tr("node_gpu_usage_stddev") + ": " + prepare_number_for_representation(
data_dict["node_gpu_usage_stddev"][i]) \
+ " " + self.tr("node_gpu_usage_stddev_unit") + " <br>"
content += self.tr("node_gpu_usage_max") + ": " + prepare_number_for_representation(
data_dict["node_gpu_usage_max"][i]) \
+ " " + self.tr("node_gpu_usage_max_unit") + " <br>"
content += self.tr("node_message_frequency_mean") + ": " + prepare_number_for_representation(
data_dict["node_message_frequency_mean"]) \
+ " " + self.tr("node_message_frequency_mean_unit") + " <br>"
content += self.tr("node_message_frequency_stddev") + ": " + prepare_number_for_representation(
data_dict["node_message_frequency_stddev"]) \
+ " " + self.tr("node_message_frequency_stddev_unit") + " <br>"
content += self.tr("node_message_frequency_max") + ": " + prepare_number_for_representation(
data_dict["node_message_frequency_max"]) \
+ " " + self.tr("node_message_frequency_max_unit") + " <br>"
content += self.tr("node_bandwidth_mean") + ": " + prepare_number_for_representation(
data_dict["node_bandwidth_mean"]) \
+ " " + self.tr("node_bandwidth_mean_unit") + " <br>"
content += self.tr("node_bandwidth_stddev") + ": " + prepare_number_for_representation(
data_dict["node_bandwidth_stddev"]) \
+ " " + self.tr("node_bandwidth_stddev_unit") + " <br>"
content += self.tr("node_bandwidth_max") + ": " + prepare_number_for_representation(
data_dict["node_bandwidth_max"]) \
+ " " + self.tr("node_bandwidth_max_unit") + " <br>"
content += self.tr("node_write_mean") + ": " + prepare_number_for_representation(data_dict["node_write_mean"]) \
+ " " + self.tr("node_write_mean_unit") + " <br>"
content += self.tr("node_write_stddev") + ": " + prepare_number_for_representation(
data_dict["node_write_stddev"]) \
+ " " + self.tr("node_write_stddev_unit") + " <br>"
content += self.tr("node_write_max") + ": " + prepare_number_for_representation(data_dict["node_write_max"]) \
+ " " + self.tr("node_write_max_unit") + " <br>"
content += self.tr("node_read_mean") + ": " + prepare_number_for_representation(data_dict["node_read_mean"]) \
+ " " + self.tr("node_read_mean_unit") + " <br>"
content += self.tr("node_read_stddev") + ": " + prepare_number_for_representation(data_dict["node_read_stddev"]) \
+ " " + self.tr("node_read_stddev_unit") + " <br>"
content += self.tr("node_read_max") + ": " + prepare_number_for_representation(data_dict["node_read_max"]) \
+ " " + self.tr("node_read_max_unit") + " <br>"
content += "</p>"
return content
def get_detailed_data(self):
"""
Returns the detailed data of the HostItem.
:returns: detailed data
:rtype: str
"""
data_dict = self.get_latest_data()
content = "<p class=\"detailed_data\">"
content += self.get_erroneous_entries()
content += self.tr("cpu_usage_mean") + ": " + prepare_number_for_representation(data_dict["cpu_usage_mean"]) \
+ " " + self.tr("cpu_usage_mean_unit") + " <br>"
content += self.tr("cpu_usage_stddev") + ": " + prepare_number_for_representation(data_dict["cpu_usage_stddev"]) \
+ " " + self.tr("cpu_usage_stddev_unit") + " <br>"
content += self.tr("cpu_usage_max") + ": " + prepare_number_for_representation(data_dict["cpu_usage_max"]) \
+ " " + self.tr("cpu_usage_max_unit") + " <br>"
content += self.tr("cpu_temp_mean") + ": " + prepare_number_for_representation(data_dict["cpu_temp_mean"]) \
+ " " + self.tr("cpu_temp_mean_unit") + " <br>"
content += self.tr("cpu_temp_stddev") + ": " + prepare_number_for_representation(data_dict["cpu_temp_stddev"]) \
+ " " + self.tr("cpu_temp_stddev_unit") + " <br>"
content += self.tr("cpu_temp_max") + ": " + prepare_number_for_representation(data_dict["cpu_temp_max"]) \
+ " " + self.tr("cpu_temp_max_unit") + " <br>"
content += self.tr("ram_usage_mean") + ": " + prepare_number_for_representation(data_dict["ram_usage_mean"]) \
+ " " + self.tr("ram_usage_mean_unit") + " <br>"
content += self.tr("ram_usage_stddev") + ": " + prepare_number_for_representation(data_dict["ram_usage_stddev"]) \
+ " " + self.tr("ram_usage_stddev_unit") + " <br>"
content += self.tr("ram_usage_max") + ": " + prepare_number_for_representation(data_dict["ram_usage_max"]) \
+ " " + self.tr("ram_usage_max_unit") + " <br>"
for i in range(0, len(data_dict["cpu_usage_core_mean"])):
content += self.tr("core" + str(i + 1)) + "<br>"
content += self.tr("cpu_usage_core_mean") + ": " + prepare_number_for_representation(
data_dict["cpu_usage_core_mean"][i]) \
+ " " + self.tr("cpu_usage_core_mean_unit") + " <br>"
content += self.tr("cpu_usage_core_stddev") + ": " + prepare_number_for_representation(
data_dict["cpu_usage_core_stddev"][i]) \
+ " " + self.tr("cpu_usage_core_stddev_unit") + " <br>"
content += self.tr("cpu_usage_core_max") + ": " + prepare_number_for_representation(
data_dict["cpu_usage_core_max"][i]) \
+ " " + self.tr("cpu_usage_core_max_unit") + " <br>"
content += self.tr("cpu_temp_core_mean") + ": " + prepare_number_for_representation(
data_dict["cpu_temp_core_mean"][i]) \
+ " " + self.tr("cpu_temp_core_mean_unit") + " <br>"
content += self.tr("cpu_temp_core_stddev") + ": " + prepare_number_for_representation(
data_dict["cpu_temp_core_stddev"][i]) \
+ " " + self.tr("cpu_temp_core_stddev_unit") + " <br>"
content += self.tr("cpu_temp_core_max") + ": " + prepare_number_for_representation(
data_dict["cpu_temp_core_max"][i]) \
+ " " + self.tr("cpu_temp_core_max_unit") + " <br>"
for i in range(0, len(data_dict["gpu_usage_mean"])):
content += self.tr("gpu_temp_mean") + ": " + prepare_number_for_representation(
data_dict["gpu_temp_mean"][i]) \
+ " " + self.tr("gpu_temp_mean_unit") + " <br>"
content += self.tr("gpu_temp_stddev") + ": " + prepare_number_for_representation(
data_dict["gpu_temp_stddev"][i]) \
+ " " + self.tr("gpu_temp_stddev_unit") + " <br>"
content += self.tr("gpu_temp_max") + ": " + prepare_number_for_representation(data_dict["gpu_temp_max"][i]) \
+ " " + self.tr("gpu_temp_max_unit") + " <br>"
content += self.tr("gpu_usage_mean") + ": " + prepare_number_for_representation(
data_dict["gpu_usage_mean"][i]) \
+ " " + self.tr("gpu_usage_mean_unit") + " <br>"
content += self.tr("gpu_usage_stddev") + ": " + prepare_number_for_representation(
data_dict["gpu_usage_stddev"][i]) \
+ " " + self.tr("gpu_usage_stddev_unit") + " <br>"
content += self.tr("gpu_usage_max") + ": " + prepare_number_for_representation(
data_dict["gpu_usage_max"][i]) \
+ " " + self.tr("gpu_usage_max_unit") + " <br>"
for i in range(0, len(data_dict["interface_name"])):
content += str(data_dict["interface_name"][i]) + "<br>"
content += self.tr("message_frequency_mean") + ": " + prepare_number_for_representation(
data_dict["message_frequency_mean"][i]) \
+ " " + self.tr("message_frequency_mean_unit") + " <br>"
content += self.tr("message_frequency_stddev") + ": " + prepare_number_for_representation(
data_dict["message_frequency_stddev"][i]) \
+ " " + self.tr("message_frequency_stddev_unit") + " <br>"
content += self.tr("message_frequency_max") + ": " + prepare_number_for_representation(
data_dict["message_frequency_max"][i]) \
+ " " + self.tr("message_frequency_max_unit") + " <br>"
content += self.tr("bandwidth_mean") + ": " + prepare_number_for_representation(
data_dict["bandwidth_mean"][i]) \
+ " " + self.tr("bandwidth_mean_unit") + " <br>"
content += self.tr("bandwidth_stddev") + ": " + prepare_number_for_representation(
data_dict["bandwidth_stddev"][i]) \
+ " " + self.tr("bandwidth_stddev_unit") + " <br>"
content += self.tr("bandwidth_max") + ": " + prepare_number_for_representation(
data_dict["bandwidth_max"][i]) \
+ " " + self.tr("bandwidth_max_unit") + " <br>"
for i in range(0, len(data_dict["drive_name"])):
content += data_dict["drive_name"][i] + " <br>"
content += self.tr("drive_free_space") + ": " + prepare_number_for_representation(
data_dict["drive_free_space"][i]) \
+ " " + self.tr("drive_free_space_unit") + " <br>"
content += self.tr("drive_read") + ": " + prepare_number_for_representation(data_dict["drive_read"][i]) \
+ " " + self.tr("drive_read_unit") + " <br>"
content += self.tr("drive_write") + ": " + prepare_number_for_representation(data_dict["drive_write"][i]) \
+ " " + self.tr("drive_write_unit") + " <br>"
content += "</p>"
return content
