def group_name_usage(report_columns_usage_dct, device_rename_df, max_title,
force_group_name_usage_update_flag):
"""
Function to determine if device alias Group_Name column required in report tables.
Value (True or False) written to the dictonary so no need to return value.
"""
info = f'Device Group Name usage'
# if all devices were renamed and force flag is off column is dropped from report tables
if device_rename_df['Device_Host_Name_rename'].notna().all(
) and not force_group_name_usage_update_flag:
report_columns_usage_dct['group_name_usage'] = False
print(info, end=" ")
status_info('off', max_title, len(info))
# if no information in report_columns_usage_dct or force flag is on or any device keep old name
# ask user input
elif report_columns_usage_dct.get('group_name_usage') is None or \
force_group_name_usage_update_flag or \
device_rename_df['Device_Host_Name_rename'].isna().any():
print('\n')
reply = reply_request(
'Do you want to use Alias Group Device names? (y)es/(n)o: ')
print('\n')
if reply == 'y':
report_columns_usage_dct['group_name_usage'] = True
print(info, end=" ")
status_info('on', max_title, len(info))
else:
report_columns_usage_dct['group_name_usage'] = False
print(info, end=" ")
status_info('off', max_title, len(info))
def download_summary(ns_3par_df, report_data_lst):
"""Function to print configurations download from STATs summary and
save summary to file if user agreed"""
if not 'STATs_status' in ns_3par_df.columns and \
not 'Local_status' in ns_3par_df.columns:
ns_3par_df['Status'] = 'skip'
print('\n')
print('3PAR Storage Systems configuaration download summary')
print(ns_3par_df)
print('\n')
# if 'STATs_status' in ns_3par_df.columns and \
# ns_3par_df['STATs_status'].isin(['skip', 'fail']).any():
# print('Some configurations are missing.')
query = 'Do you want to SAVE download SUMMARY? (y)es/(n)o: '
reply = reply_request(query)
if reply == 'y':
save_xlsx_file(ns_3par_df,
'stats_summary',
report_data_lst,
force_flag=True)
def define_device_to_rename(portshow_aggregated_df, device_rename_df,
max_title, force_form_update_flag,
force_change_data_lst, report_data_lst):
"""
Function to define (create new, return previously saved or return empty)
device_rename_df DataFrame to apply device rename schema
"""
# if device_rename_df DataFrame doesn't exist (1st iteration)
# or force flag to change device_rename_df DataFrame is on
# or some related DataFrames was forcibly changed
if device_rename_df is None or force_form_update_flag:
print('\n')
if force_change_data_lst:
print(
f"Request to force change of {', '.join(force_change_data_lst)} data was received."
)
reply = reply_request(
'Do you want to change auto assigned device names? (y)es/(n)o: ')
if reply == 'y':
# if device_rename_df DataFrame doesn't exist (1st iteration)
if device_rename_df is None:
# create new device rename DataFrame
manual_device_rename_df = create_device_rename_form(
portshow_aggregated_df)
else:
# if any related DataFrames was forcibly changed ask if device rename form reset required
if force_change_data_lst:
reply = reply_request(
'Do you want to apply previously saved device rename schema? (y)es/(n)o: '
)
if reply == 'y':
print('\n')
return device_rename_df
else:
print('\n')
reply = reply_request(
'Do you want to reset device rename form? (y)es/(n)o: '
)
if reply == 'y':
# create new device rename DataFrame
manual_device_rename_df = create_device_rename_form(
portshow_aggregated_df)
else:
# use saved device rename DataFrame
manual_device_rename_df = device_rename_df.copy()
else:
# if no force change in related DataFrames but device_rename_df DataFrame
# change initiated use saved device rename DataFrame
manual_device_rename_df = device_rename_df.copy()
# save manual_device_rename_df DataFrame to excel file to use at as form to fill
sheet_title = 'device_rename_form'
file_path = save_xlsx_file(manual_device_rename_df,
sheet_title,
report_data_lst,
force_flag=True)
file_name = os.path.basename(file_path)
file_directory = os.path.dirname(file_path)
print(
f"\nTo rename devices put new names into the '{file_name}' file, '{sheet_title}' sheet in\n'{file_directory}' directory"
)
print('ATTN! CLOSE file after changes were made\n')
# complete the manual_device_rename_df form and import it
reply = reply_request("When finish enter 'yes': ", ['yes'])
if reply == 'y':
print('\n')
device_rename_df = dataframe_import(sheet_title,
max_title,
init_file=file_path,
header=2)
else:
# if don't change auto assigned names save empty device_rename_df DataFrame
device_rename_columns = [
'Fabric_name', 'Device_Host_Name', 'Group_Name', 'deviceType',
'deviceSubtype', 'Device_Host_Name_rename'
]
device_rename_df = pd.DataFrame(columns=device_rename_columns)
else:
# check loaded device_rename_df DataFrame (if it's empty)
device_rename_df = verify_data(report_data_lst, ['device_rename'],
device_rename_df,
show_status=False)
return device_rename_df
def fabriclabels_main(switchshow_ports_df, switch_params_df, fabricshow_df,
ag_principal_df, report_data_lst):
"""Function to set Fabric labels"""
# report_data_lst contains information:
# customer_name, dir_report, dir to save obtained data, max_title, report_steps_dct
customer_name, report_path, _, max_title, report_steps_dct = report_data_lst
# names to save data obtained after current module execution
data_names = ['fabric_labels']
# service step information
print(f'\n\n{report_steps_dct[data_names[0]][3]}\n')
# load data if they were saved on previos program execution iteration
data_lst = load_data(report_data_lst, *data_names)
# unpacking DataFrames from the loaded list with data
# pylint: disable=unbalanced-tuple-unpacking
fabricshow_ag_labels_df, = data_lst
# list of data to analyze from report_info table
analyzed_data_names = []
# force run when any data from data_lst was not saved (file not found) or
# procedure execution explicitly requested for output data or data used during fn execution
force_run = verify_force_run(data_names, data_lst, report_steps_dct,
max_title, analyzed_data_names)
if force_run:
print('\nSETTING UP FABRICS NAMES AND LABELS ...\n')
fabricshow_summary_df = auto_fabrics_labeling(switchshow_ports_df,
switch_params_df,
fabricshow_df,
report_data_lst)
# display automatic fabric labeling
info_labels = [
'Fabric_name', 'Fabric_label', 'chassis_name',
'Principal_switch_name', 'Fabric_ID', 'FC_Route', 'Total_switch',
'Domain_IDs', 'Switch_names', 'Device_ports', 'Online_ports',
'LS_type', 'Fabric_Name'
]
# service file name for detailed information
current_date = str(date.today())
file_name = customer_name + '_' + report_steps_dct[
'fabricshow_summary'][2] + '_' + current_date + '.xlsx'
# file_name = customer_name + '_analysis_report_' + current_date + '.xlsx'
print('\nAutomatic fabrics labeling\n')
# set option to show all columns
with pd.option_context('display.max_columns', None,
'display.expand_frame_repr', False):
# pd.set_option('max_columns', None)
# pd.set_option('expand_frame_repr', False)
print(fabricshow_summary_df.loc[:, info_labels])
print(
f"\nFor detailed switch port types and numbers statistic in each fabric check '{file_name}' file 'fabricshow_statistics' sheet in"
)
print(f'{report_path} directory')
print('ATTN! CLOSE file after check\n')
# ask user if Automatic Fabric labeling need to be corrected
query = 'Do you want to change Fabrics Names or Labels? (y)es/(n)o: '
reply = reply_request(query)
if reply == 'y':
# saving DataFrame to Excel to check during manual labeling if required
save_xlsx_file(fabricshow_summary_df,
'fabricshow_summary',
report_data_lst,
force_flag=True)
fabricshow_summary_df = manual_fabrics_labeling(
fabricshow_summary_df, info_labels)
# takes all switches working in Native and AG switches
# merge the in one DataFrame and identify which Fabrics they belong too with fabricshow_summary DataFrame
fabricshow_ag_labels_df = native_ag_labeling(fabricshow_df,
ag_principal_df,
fabricshow_summary_df)
# # disable option to show all columns
# pd.reset_option('max_columns')
# pd.reset_option('expand_frame_repr')
# create list with partitioned DataFrames
data_lst = [fabricshow_ag_labels_df]
# saving data to json or csv file
save_data(report_data_lst, data_names, *data_lst)
# verify if loaded data is empty and replace information string with empty DataFrame
else:
fabricshow_ag_labels_df = verify_data(report_data_lst, data_names,
*data_lst)
data_lst = [fabricshow_ag_labels_df]
# save data to excel file if it's required
for data_name, data_frame in zip(data_names, data_lst):
save_xlsx_file(data_frame, data_name, report_data_lst)
return fabricshow_ag_labels_df
def manual_fabrics_labeling(fabricshow_summary_df, info_labels):
"""Function to manual change Fabric Name and Fabric Label."""
# copy of initial fabricshow_summary DataFrame
# to be able to reset all changes
fabricshow_summary_default_df = fabricshow_summary_df.copy()
# convert DataFrame indexes to string versions
fabric_indexes_str_lst = [str(i) for i in fabricshow_summary_df.index]
# DataFrame operation options (save, reset, exit)
opeartion_options_lst = ['s', 'r', 'v', 'x']
# aggregated list of available operations
full_options_lst = fabric_indexes_str_lst + opeartion_options_lst
# parameters to change
rename_options_dct = {'NAME': 'Fabric_name', 'LABEL': 'Fabric_label'}
# user input from full_options_lst
# initial value is None to enter while
input_option = None
# work with DataFrame until it is saved or exit without saving
while not input_option in ['s', 'x']:
fabricshow_summary_df.sort_values(by=[
'Fabric_name', 'Fabric_label', 'Principal_switch_name',
'Domain_IDs'
],
inplace=True,
ignore_index=True)
# no need to print fabric info after verification
if input_option != 'v':
# printing actual fabricshow_summary DataFrame
print('\nCurrent fabric labeling\n')
print(fabricshow_summary_df.loc[:, info_labels])
# printing menu options to choose to work with DataFrame
# save, reset, exit or fabric index number to change
print(
'\nS/s - Save changes in labeling\nR/r - Reset to default labeling\nV/v - Veriify labeling\nX/x - Exit without saving'
)
print(
f"{', '.join(fabric_indexes_str_lst)} - Choose fabric index to change labeling\n"
)
# reset input_option value after each iteration to enter while loop
input_option = reply_request("Choose option: ",
reply_options=full_options_lst,
show_reply=True)
# user input is fabric index to change labeling
if input_option in fabric_indexes_str_lst:
print('\n')
# make copy of actual fabricshow_summary DataFrame
# to be able to reset current iteration changes
fabricshow_summary_before_df = fabricshow_summary_df.copy()
# convert user input fabric number to integer
fabric_num = int(input_option)
# printing information for current fabric
print(fabricshow_summary_df.iloc[fabric_num])
print('\n')
# list to save user input
reply_lst = []
# initial user input to check if nan is entered
value = 'empty'
# ask user to change labels and names by looping over rename_options_dct
for option_name, option_column in rename_options_dct.items():
if value:
reply = reply_request(
f'Do you want to change Fabric {option_name}? (y)es/(n)o: '
)
# save user input to the list
reply_lst.append(reply)
# if user want to change name or label ask to enter new value
if reply == 'y':
current_value = fabricshow_summary_df.loc[
fabric_num, rename_options_dct[option_name]]
value = input(
f'\nEnter new Fabric {option_name}. 0 or None will remove fabric from assessment. Current value is {current_value}: '
)
value = value.strip()
# 0 or None means no labeling
if value.lower() in ['0', 'none']:
value = None
fabricshow_summary_df.loc[
fabric_num,
['Fabric_name', 'Fabric_label']] = [
np.nan, np.nan
]
elif len(value) == 0:
value = current_value
print(f'Fabric {option_name} was not changed')
else:
# change values in fabricshow_summary DataFrame
fabricshow_summary_df.loc[fabric_num,
option_column] = value
# if user didn't reply "no" two times
if reply_lst != ['n'] * 2:
print('\n')
# print current fabric information after change
print(fabricshow_summary_df.iloc[fabric_num])
print('\n')
# verify if Fabric names or label is NaN and ask input
label_name_uniformity = fabricshow_summary_df.loc[
fabric_num,
rename_options_dct.values()].isna().nunique() == 1
if not label_name_uniformity:
print(
'Fabric NAME and Fabric LABEL fields BOTH must have values'
)
# verify which label have Nan value
nan_option_name, = [
key for key, value in rename_options_dct.items()
if pd.isna(fabricshow_summary_df.loc[fabric_num,
value])
]
while True:
current_value = fabricshow_summary_df.loc[
fabric_num, rename_options_dct[nan_option_name]]
value = input(
f'\nEnter new Fabric {nan_option_name}. Current value is {current_value}: '
)
value = value.strip()
# 0, None or '' means no labeling
if value in ['0', 'None', '', 'none']:
print(f"Fabric {nan_option_name} must have value.")
continue
else:
fabricshow_summary_df.loc[
fabric_num,
rename_options_dct[nan_option_name]] = value
print('\n')
# print current fabric information after change
print(fabricshow_summary_df.iloc[fabric_num])
print('\n')
break
reply = reply_request(
'Do you want to keep changes? (y)es/(n)o: ')
# when user doesn't want to keep data fabricshow_summary DataFrame
# returns to the state saved bedore current iteration
if reply == 'n':
fabricshow_summary_df = fabricshow_summary_before_df.copy()
# user input is verify fabric labeling
elif input_option == 'v':
count_labels_df = verify_fabric_labels(fabricshow_summary_df)
print('\n', count_labels_df, '\n')
# user input is save current labeling configuration and exit
elif input_option == 's':
count_labels_df = verify_fabric_labels(fabricshow_summary_df)
print('\n', count_labels_df, '\n')
# check for errors in fabric labeling
if (count_labels_df['Verification'] == 'ERROR').any():
print(
'There is an error in fabric labeling. Please re-label fabrics.'
)
input_option = None
else:
# if fabric labeling is ok request to save
reply = reply_request(
'Do you want to save changes and exit? (y)es/(n)o: ')
# for save option do nothing and while loop stops on next condition check
if reply == 'y':
print('\nSaved fabric labeling\n')
else:
input_option = None
# user input is reset current labeling configuration and start labeling from scratch
elif input_option == 'r':
reply = reply_request(
'Do you want to reset fabric labeling to original values? (y)es/(n)o: '
)
# for reset option actual fabricshow_summary DataFrame returns back
# to initial DataFrame version and while loop don't stop
if reply == 'y':
fabricshow_summary_df = fabricshow_summary_default_df.copy()
print('\nFabric labeling has been reset to original version\n')
# user input is exit without saving
elif input_option == 'x':
reply = reply_request(
'Do you want to leave without saving? (y)es/(n)o: ')
# for exit option DataFrame returns back to initial version
# and while loop stops
if reply == 'y':
fabricshow_summary_df = fabricshow_summary_default_df.copy()
print('\nKeeping original labeling version\n')
else:
input_option = None
else:
# show actual version of DataFrame after user inputs save or exit
print(fabricshow_summary_df.loc[:, info_labels])
print('\n')
return fabricshow_summary_df
def err_sfp_cfg_analysis_main(portshow_aggregated_df, sfpshow_df,
portcfgshow_df, report_columns_usage_dct,
report_data_lst):
"""Main function to add porterr, transceiver and portcfg information to portshow DataFrame"""
# report_data_lst contains information:
# customer_name, dir_report, dir to save obtained data, max_title, report_steps_dct
*_, max_title, report_steps_dct = report_data_lst
portshow_sfp_force_flag = False
portshow_sfp_export_flag, *_ = report_steps_dct['portshow_sfp_aggregated']
# names to save data obtained after current module execution
data_names = [
'portshow_sfp_aggregated', 'Ошибки', 'Параметры_SFP',
'Параметры_портов'
]
# service step information
print(f'\n\n{report_steps_dct[data_names[0]][3]}\n')
# load data if they were saved on previos program execution iteration
data_lst = load_data(report_data_lst, *data_names)
# unpacking DataFrames from the loaded list with data
# pylint: disable=unbalanced-tuple-unpacking
portshow_sfp_aggregated_df, error_report_df, sfp_report_df, portcfg_report_df = data_lst
# list of data to analyze from report_info table
analyzed_data_names = [
'portshow_aggregated', 'sfpshow', 'portcfgshow', 'portcmd',
'switchshow_ports', 'switch_params_aggregated', 'fdmi',
'device_rename', 'report_columns_usage_upd', 'nscamshow', 'nsshow',
'alias', 'blade_servers', 'fabric_labels'
]
# force run when any data from data_lst was not saved (file not found) or
# procedure execution explicitly requested for output data or data used during fn execution
force_run = verify_force_run(data_names, data_lst, report_steps_dct,
max_title, analyzed_data_names)
if force_run:
# import transeivers information from file
sfp_model_df = dataframe_import('sfp_models', max_title)
# current operation information string
info = f'Updating connected devices table'
print(info, end=" ")
# add sfpshow, transceiver information and portcfg to aggregated portcmd DataFrame
portshow_sfp_aggregated_df = port_complete(portshow_aggregated_df,
sfpshow_df, sfp_model_df,
portcfgshow_df)
# after finish display status
status_info('ok', max_title, len(info))
# warning if UKNOWN SFP present
if (portshow_sfp_aggregated_df['Transceiver_Supported'] ==
'Unknown SFP').any():
info_columns = [
'Fabric_name', 'Fabric_label', 'configname', 'chassis_name',
'chassis_wwn', 'slot', 'port', 'Transceiver_Supported'
]
portshow_sfp_info_df = portshow_sfp_aggregated_df.drop_duplicates(
subset=info_columns).copy()
unknown_count = len(portshow_sfp_info_df[
portshow_sfp_info_df['Transceiver_Supported'] ==
'Unknown SFP'])
info = f'{unknown_count} {"port" if unknown_count == 1 else "ports"} with UNKNOWN supported SFP tag found'
print(info, end=" ")
status_info('warning', max_title, len(info))
# ask if save portshow_aggregated_df
if not portshow_sfp_export_flag:
reply = reply_request(
"Do you want to save 'portshow_sfp_aggregated'? (y)es/(n)o: "
)
if reply == 'y':
portshow_sfp_force_flag = True
# create reaport tables from port_complete_df DataFrtame
error_report_df, sfp_report_df, portcfg_report_df = \
create_report_tables(portshow_sfp_aggregated_df, data_names[1:], report_columns_usage_dct, max_title)
# saving data to json or csv file
data_lst = [
portshow_sfp_aggregated_df, error_report_df, sfp_report_df,
portcfg_report_df
]
save_data(report_data_lst, data_names, *data_lst)
# verify if loaded data is empty and reset DataFrame if yes
else:
portshow_sfp_aggregated_df, error_report_df, sfp_report_df, portcfg_report_df \
= verify_data(report_data_lst, data_names, *data_lst)
data_lst = [
portshow_sfp_aggregated_df, error_report_df, sfp_report_df,
portcfg_report_df
]
# save data to excel file if it's required
for data_name, data_frame in zip(data_names, data_lst):
force_flag = False
if data_name == 'portshow_sfp_aggregated':
force_flag = portshow_sfp_force_flag
save_xlsx_file(data_frame,
data_name,
report_data_lst,
force_flag=force_flag)
return portshow_sfp_aggregated_df
def warning_notification(portshow_aggregated_df, switch_params_aggregated_df,
nsshow_unsplit_df, expected_ag_links_df,
report_data_lst):
"""Function to show WARNING notification if any deviceType is UNKNOWN,
if any PortSymb or NodeSymb was not parsed or if new switch founded which was
not previously discovered"""
*_, max_title, report_steps_dct = report_data_lst
portshow_force_flag = False
nsshow_unsplit_force_flag = False
expected_ag_links_force_flag = False
portshow_export_flag, *_ = report_steps_dct['portshow_aggregated']
nsshow_unsplit_export_flag, *_ = report_steps_dct['nsshow_unsplit']
expected_ag_links_export_flag, *_ = report_steps_dct['expected_ag_links']
# warning if UKNOWN device class present
if (portshow_aggregated_df['deviceType'] == 'UNKNOWN').any():
unknown_count = len(portshow_aggregated_df[
portshow_aggregated_df['deviceType'] == 'UNKNOWN'])
info = f'{unknown_count} {"port" if unknown_count == 1 else "ports"} with UNKNOWN device Class found'
print(info, end=" ")
status_info('warning', max_title, len(info))
# ask if save portshow_aggregated_df
if not portshow_export_flag:
reply = reply_request(
"Do you want to save 'portshow_aggregated'? (y)es/(n)o: ")
if reply == 'y':
portshow_force_flag = True
# warning if any values in PortSymb or NodeSymb were not parsed
if not nsshow_unsplit_df.empty:
portsymb_unsplit_count = nsshow_unsplit_df['PortSymb'].notna().sum()
nodesymb_unsplit_count = nsshow_unsplit_df['NodeSymb'].notna().sum()
unsplit_lst = [[portsymb_unsplit_count, 'PortSymb'],
[nodesymb_unsplit_count, 'NodeSymb']]
unsplit_str = ' and '.join(
[str(num) + " " + name for num, name in unsplit_lst if num])
info = f'{unsplit_str} {"is" if portsymb_unsplit_count + nodesymb_unsplit_count == 1 else "are"} UNPARSED'
print(info, end=" ")
status_info('warning', max_title, len(info))
# ask if save nsshow_unsplit
if not nsshow_unsplit_export_flag:
reply = reply_request(
"Do you want to save 'nsshow_unsplit'? (y)es/(n)o: ")
if reply == 'y':
nsshow_unsplit_force_flag = True
# warning if unknown switches was found
switch_name_set = set(switch_params_aggregated_df['switchName'])
# all founded switches in portshow_aggregated_df
mask_switch = portshow_aggregated_df['deviceType'] == 'SWITCH'
portshow_switch_name_set = set(
portshow_aggregated_df.loc[mask_switch, 'Device_Host_Name'])
# if unknown switches found
if not portshow_switch_name_set.issubset(switch_name_set):
unknown_count = len(
portshow_switch_name_set.difference(switch_name_set))
info = f'{unknown_count} NEW {"switch" if unknown_count == 1 else "switches"} detected'
print(info, end=" ")
status_info('warning', max_title, len(info))
# ask if save portshow_aggregated_df
if not portshow_export_flag and not portshow_force_flag:
reply = reply_request(
"Do you want to save 'portshow_aggregated'? (y)es/(n)o: ")
if reply == 'y':
portshow_force_flag = True
# if any unconfirmed AG links found
if not expected_ag_links_df.empty:
unknown_count = expected_ag_links_df['chassis_name'].notna().sum()
info = f'{unknown_count} AG {"link" if unknown_count == 1 else "links"} detected'
print(info, end=" ")
status_info('warning', max_title, len(info))
# ask if save expected_ag_links_df
if not expected_ag_links_export_flag:
reply = reply_request(
"Do you want to save 'expected_ag_link'? (y)es/(n)o: ")
if reply == 'y':
expected_ag_links_force_flag = True
return portshow_force_flag, nsshow_unsplit_force_flag, expected_ag_links_force_flag
def configs_download(ns_3par_df, project_folder, local_3par_folder, comp_keys,
match_keys, comp_dct, report_data_lst):
"""Function to prepare 3PAR configuration files for parsing.
Download in from STATs and local (defined in report.xlsx file) folders"""
*_, max_title, _ = report_data_lst
# folder for 3par config files download is in project folder
download_folder = os.path.join(project_folder, '3par_configs')
# verify if download folder exist (created on previous iterations)
download_folder_exist = verify_download_folder(download_folder,
create=False)
# if download folder exist and there are 3par config files
# ask if user wants to use them or download new files after removing existing
if download_folder_exist:
configs_downloaded_lst = find_files(
download_folder,
max_title,
filename_contains=comp_dct['configname_3par'])
if configs_downloaded_lst:
print(
f'{len(configs_downloaded_lst)} 3PAR configuration files found in download folder.'
)
print(
'Do you want to USE EXISTING FILES to extract port and host information?'
)
print(
"If you want to update configuarion files and reply 'no' then existing files are removed."
)
query = "Please select '(y)es' (use existing) or '(n)o' (update): "
reply = reply_request(query)
if reply == 'n':
# delete 3par config files
remove_files(configs_downloaded_lst, max_title)
else:
return configs_downloaded_lst
# download from STATs
query = 'Do you want DOWNLOAD configuration files from STATs? (y)es/(n)o: '
reply = reply_request(query)
if reply == 'y':
query = 'Are you connected to HPE network?: '
reply = reply_request(query)
if reply == 'y':
# download configs from STATs
ns_3par_df = stats_download(ns_3par_df, download_folder, max_title)
else:
print('STATs is only available within HPE network.')
# find configuration files in local 3PAR folder
if local_3par_folder:
configs_local_lst = find_files(
local_3par_folder,
max_title,
filename_contains=comp_dct['configname_3par'])
if configs_local_lst:
print('\n')
print(
f'{len(configs_local_lst)} 3PAR configuration files found in local folder.'
)
query = 'Do you want COPY configuration files from LOCAL to download folder? (y)es/(n)o: '
reply = reply_request(query)
if reply == 'y':
# download configs from loacl folder
ns_3par_df = local_download(ns_3par_df, configs_local_lst,
download_folder, comp_keys,
match_keys, comp_dct, max_title)
download_summary(ns_3par_df, report_data_lst)
# create configs list in download folder if it exist (if user reject download config files
# from both sources download folder is not created)
download_folder_exist = verify_download_folder(download_folder,
create=False)
if download_folder_exist:
configs_3par_lst = find_files(
download_folder,
max_title,
filename_contains=comp_dct['configname_3par'])
return configs_3par_lst
else:
return []