mirror of
https://github.com/Telecominfraproject/wlan-lanforge-scripts.git
synced 2025-11-01 11:18:03 +00:00
Added monitor method, WIP
This commit is contained in:
Logan Lipke
@@ -1,10 +1,14 @@
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# !/usr/bin/env python3
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#!/usr/bin/env python3
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from LANforge.lfcli_base import LFCliBase
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import pprint
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from pprint import pprint
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from LANforge.lfcli_base import LFCliBase
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import csv
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import pandas as pd
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import time
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import datetime
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class GenCXProfile(LFCliBase):
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def __init__(self, lfclient_host, lfclient_port, local_realm, debug_=False):
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@@ -349,3 +353,152 @@ class GenCXProfile(LFCliBase):
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"cross_connect": data["alias"]
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})
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time.sleep(sleep_time)
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def monitor(self,
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duration_sec=60,
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monitor_interval_ms=1,
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sta_list=None,
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generic_cols=None,
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port_mgr_cols=None,
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created_cx=None,
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monitor=True,
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report_file=None,
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systeminfopath=None,
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output_format=None,
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script_name=None,
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arguments=None,
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compared_report=None,
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debug=False):
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try:
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duration_sec = self.parse_time(duration_sec).seconds
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except:
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if (duration_sec is None) or (duration_sec <= 1):
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raise ValueError("GenCXProfile::monitor wants duration_sec > 1 second")
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if (duration_sec <= monitor_interval_ms):
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raise ValueError("GenCXProfile::monitor wants duration_sec > monitor_interval")
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if report_file is None:
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raise ValueError("Monitor requires an output file to be defined")
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if systeminfopath is None:
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raise ValueError("Monitor requires a system info path to be defined")
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if created_cx is None:
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raise ValueError("Monitor needs a list of Layer 3 connections")
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if (monitor_interval_ms is None) or (monitor_interval_ms < 1):
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raise ValueError("GenCXProfile::monitor wants monitor_interval >= 1 second")
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if generic_cols is None:
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raise ValueError("GenCXProfile::monitor wants a list of column names to monitor")
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if output_format is not None:
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if output_format.lower() != report_file.split('.')[-1]:
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raise ValueError(
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'Filename %s has an extension that does not match output format %s .' % (report_file, output_format))
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else:
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output_format = report_file.split('.')[-1]
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# default save to csv first
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if report_file.split('.')[-1] != 'csv':
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report_file = report_file.replace(str(output_format), 'csv', 1)
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print("Saving rolling data into..." + str(report_file))
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# ================== Step 1, set column names and header row
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generic_cols = [self.replace_special_char(x) for x in generic_cols]
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generic_fields = ",".join(generic_cols)
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default_cols = ['Timestamp', 'Timestamp milliseconds epoch', 'Timestamp seconds epoch', 'Duration elapsed']
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default_cols.extend(generic_cols)
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if port_mgr_cols is not None:
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default_cols.extend(port_mgr_cols)
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header_row = default_cols
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# csvwriter.writerow([systeminfo['VersionInfo']['BuildVersion'], script_name, str(arguments)])
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if port_mgr_cols is not None:
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port_mgr_cols = [self.replace_special_char(x) for x in port_mgr_cols]
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port_mgr_cols_labelled = []
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for col_name in port_mgr_cols:
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port_mgr_cols_labelled.append("port mgr - " + col_name)
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port_mgr_fields = ",".join(port_mgr_cols)
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header_row.extend(port_mgr_cols_labelled)
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# create sys info file
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systeminfo = self.json_get('/')
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sysinfo = [str("LANforge GUI Build: " + systeminfo['VersionInfo']['BuildVersion']),
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str("Script Name: " + script_name), str("Argument input: " + str(arguments))]
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with open(systeminfopath, 'w') as filehandle:
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for listitem in sysinfo:
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filehandle.write('%s\n' % listitem)
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# ================== Step 2, monitor columns
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start_time = datetime.datetime.now()
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end_time = start_time + datetime.timedelta(seconds=duration_sec)
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passes = 0
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expected_passes = 0
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# instantiate csv file here, add specified column headers
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csvfile = open(str(report_file), 'w')
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csvwriter = csv.writer(csvfile, delimiter=",")
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csvwriter.writerow(header_row)
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# wait 10 seconds to get proper port data
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time.sleep(10)
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# for x in range(0,int(round(iterations,0))):
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initial_starttime = datetime.datetime.now()
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while datetime.datetime.now() < end_time:
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t = datetime.datetime.now()
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timestamp = t.strftime("%m/%d/%Y %I:%M:%S")
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t_to_millisec_epoch = int(self.get_milliseconds(t))
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t_to_sec_epoch = int(self.get_seconds(t))
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time_elapsed = int(self.get_seconds(t)) - int(self.get_seconds(initial_starttime))
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basecolumns = [timestamp, t_to_millisec_epoch, t_to_sec_epoch, time_elapsed]
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generic_response = self.json_get("/generic/%s?fields=%s" % (created_cx, generic_fields))
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if port_mgr_cols is not None:
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port_mgr_response = self.json_get("/port/1/1/%s?fields=%s" % (sta_list, port_mgr_fields))
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# get info from port manager with list of values from cx_a_side_list
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if "endpoints" not in generic_response or generic_response is None:
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print(generic_response)
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raise ValueError("Cannot find columns requested to be searched. Exiting script, please retry.")
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if debug:
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print("Json generic_response from LANforge... " + str(generic_response))
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if port_mgr_cols is not None:
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if "interfaces" not in port_mgr_response or port_mgr_response is None:
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print(port_mgr_response)
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raise ValueError("Cannot find columns requested to be searched. Exiting script, please retry.")
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if debug:
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print("Json port_mgr_response from LANforge... " + str(port_mgr_response))
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for endpoint in generic_response["endpoints"]: # each endpoint is a dictionary
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endp_values = list(endpoint.values())[0]
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temp_list = basecolumns
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for columnname in header_row[len(basecolumns):]:
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temp_list.append(endp_values[columnname])
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if port_mgr_cols is not None:
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for sta_name in sta_list_edit:
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if sta_name in current_sta:
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for interface in port_mgr_response["interfaces"]:
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if sta_name in list(interface.keys())[0]:
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merge = temp_endp_values.copy()
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# rename keys (separate port mgr 'rx bytes' from generic 'rx bytes')
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port_mgr_values_dict = list(interface.values())[0]
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renamed_port_cols = {}
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for key in port_mgr_values_dict.keys():
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renamed_port_cols['port mgr - ' + key] = port_mgr_values_dict[key]
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merge.update(renamed_port_cols)
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for name in port_mgr_cols:
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temp_list.append(merge[name])
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csvwriter.writerow(temp_list)
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time.sleep(monitor_interval_ms)
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csvfile.close()
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# comparison to last report / report inputted
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if compared_report is not None:
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compared_df = self.compare_two_df(dataframe_one=self.file_to_df(report_file),
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dataframe_two=self.file_to_df(compared_report))
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exit(1)
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# append compared df to created one
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if output_format.lower() != 'csv':
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self.df_to_file(dataframe=pd.read_csv(report_file), output_f=output_format, save_path=report_file)
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else:
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if output_format.lower() != 'csv':
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self.df_to_file(dataframe=pd.read_csv(report_file), output_f=output_format, save_path=report_file)
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