mirror of
https://github.com/Telecominfraproject/wlan-lanforge-scripts.git
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lf_webpage.py: updated for generating kpi.csv, single band 5G and 2.4G works, graphing temporarily disabled(WIP)
This commit is contained in:
Logan Lipke
@@ -26,6 +26,7 @@ Realm = realm.Realm
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PortUtils = realm.PortUtils
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lf_report = importlib.import_module("py-scripts.lf_report")
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lf_graph = importlib.import_module("py-scripts.lf_graph")
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lf_kpi_csv = importlib.import_module("py-scripts.lf_kpi_csv")
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class HttpDownload(Realm):
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@@ -473,59 +474,65 @@ class HttpDownload(Realm):
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return graph_png
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def generate_report(self, date, num_stations, duration, test_setup_info, dataset, lis, bands, threshold_2g,
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threshold_5g, threshold_both, dataset2, summary_table_value, result_data, test_input_infor):
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threshold_5g, threshold_both, dataset2, summary_table_value, result_data, test_rig,
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test_tag, dut_hw_version, dut_sw_version, dut_model_num, dut_serial_num, test_id,
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test_input_infor, csv_outfile):
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report = lf_report.lf_report(_results_dir_name="webpage_test", _output_html="Webpage.html", _output_pdf="Webpage.pdf")
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report.set_title("WEBPAGE DOWNLOAD TEST")
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report.set_date(date)
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report.build_banner()
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report.set_table_title("Test Setup Information")
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report.build_table_title()
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report.test_setup_table(value="Device under test", test_setup_data=test_setup_info)
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report.set_obj_html("Objective",
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"The Webpage Download Test is designed to test the performance of the Access Point.The goal is to check whether the webpage loading time of all the " + str(
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num_stations) + " clients which are downloading at the same time meets the expectation when clients connected on single radio as well as dual radio")
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report.build_objective()
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report.set_obj_html("Download Time Graph",
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"The below graph provides information about the download time taken by each client to download webpage for test duration of " + str(
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duration) + " min")
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report.build_objective()
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graph = self.generate_graph(dataset=dataset, lis=lis, bands=bands)
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report.set_graph_image(graph)
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report.set_csv_filename(graph)
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report.move_csv_file()
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report.move_graph_image()
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report.build_graph()
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report.set_obj_html("Download Rate Graph",
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"The below graph provides information about the download rate in Mbps of each client to download the webpage for test duration of " + str(
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duration) + " min")
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report.build_objective()
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graph2 = self.graph_2(dataset2, lis=lis, bands=bands)
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print("graph name {}".format(graph2))
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report.set_graph_image(graph2)
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report.set_csv_filename(graph2)
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report.move_csv_file()
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report.move_graph_image()
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report.build_graph()
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report.set_obj_html("Summary Table Description",
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"This Table shows you the summary result of Webpage Download Test as PASS or FAIL criteria. If the average time taken by " + str(
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num_stations) + " clients to access the webpage is less than " + str(
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threshold_2g) + "s it's a PASS criteria for 2.4 ghz clients, If the average time taken by " + "" + str(
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num_stations) + " clients to access the webpage is less than " + str(
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threshold_5g) + "s it's a PASS criteria for 5 ghz clients and If the average time taken by " + str(
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num_stations) + " clients to access the webpage is less than " + str(
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threshold_both) + "s it's a PASS criteria for 2.4 ghz and 5ghz clients")
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report.build_objective()
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test_setup1 = pd.DataFrame(summary_table_value)
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report.set_table_dataframe(test_setup1)
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report.build_table()
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report.set_obj_html("Download Time Table Description",
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"This Table will provide you information of the minimum, maximum and the average time taken by clients to download a webpage in seconds")
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report.build_objective()
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# Section commented because graphing breaks two band report generation
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# TODO: Fix graphing bug with multiple bands being recorded
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#
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# report.set_title("WEBPAGE DOWNLOAD TEST")
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# report.set_date(date)
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# report.build_banner()
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# report.set_table_title("Test Setup Information")
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# report.build_table_title()
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#
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# report.test_setup_table(value="Device under test", test_setup_data=test_setup_info)
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#
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# report.set_obj_html("Objective",
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# "The Webpage Download Test is designed to test the performance of the Access Point.The goal is to check whether the webpage loading time of all the " + str(
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# num_stations) + " clients which are downloading at the same time meets the expectation when clients connected on single radio as well as dual radio")
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# report.build_objective()
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# report.set_obj_html("Download Time Graph",
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# "The below graph provides information about the download time taken by each client to download webpage for test duration of " + str(
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# duration) + " min")
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# report.build_objective()
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# graph = self.generate_graph(dataset=dataset, lis=lis, bands=bands)
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# report.set_graph_image(graph)
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# report.set_csv_filename(graph)
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# report.move_csv_file()
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# report.move_graph_image()
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# report.build_graph()
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# report.set_obj_html("Download Rate Graph",
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# "The below graph provides information about the download rate in Mbps of each client to download the webpage for test duration of " + str(
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# duration) + " min")
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# report.build_objective()
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# graph2 = self.graph_2(dataset2, lis=lis, bands=bands)
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# print("graph name {}".format(graph2))
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# report.set_graph_image(graph2)
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# report.set_csv_filename(graph2)
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# report.move_csv_file()
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# report.move_graph_image()
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# report.build_graph()
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# report.set_obj_html("Summary Table Description",
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# "This Table shows you the summary result of Webpage Download Test as PASS or FAIL criteria. If the average time taken by " + str(
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# num_stations) + " clients to access the webpage is less than " + str(
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# threshold_2g) + "s it's a PASS criteria for 2.4 ghz clients, If the average time taken by " + "" + str(
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# num_stations) + " clients to access the webpage is less than " + str(
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# threshold_5g) + "s it's a PASS criteria for 5 ghz clients and If the average time taken by " + str(
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# num_stations) + " clients to access the webpage is less than " + str(
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# threshold_both) + "s it's a PASS criteria for 2.4 ghz and 5ghz clients")
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#
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# report.build_objective()
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# test_setup1 = pd.DataFrame(summary_table_value)
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# report.set_table_dataframe(test_setup1)
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# report.build_table()
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#
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# report.set_obj_html("Download Time Table Description",
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# "This Table will provide you information of the minimum, maximum and the average time taken by clients to download a webpage in seconds")
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#
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# report.build_objective()
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x = []
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for fcc in list(result_data.keys()):
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fcc_type = result_data[fcc]["min"]
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@@ -577,12 +584,52 @@ class HttpDownload(Realm):
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z2.append(i)
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download_table_value = {
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"": bands,
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"Band": bands,
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"Minimum": z,
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"Maximum": z1,
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"Average": z2
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}
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# Get the report path to create the kpi.csv path
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kpi_path = report.get_report_path()
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print("kpi_path :{kpi_path}".format(kpi_path=kpi_path))
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kpi_csv = lf_kpi_csv.lf_kpi_csv(
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_kpi_path=kpi_path,
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_kpi_test_rig=test_rig,
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_kpi_test_tag=test_tag,
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_kpi_dut_hw_version=dut_hw_version,
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_kpi_dut_sw_version=dut_sw_version,
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_kpi_dut_model_num=dut_model_num,
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_kpi_dut_serial_num=dut_serial_num,
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_kpi_test_id=test_id)
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kpi_csv.kpi_dict['Units'] = "Mbps"
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for band in range(len(download_table_value["Band"])):
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kpi_csv.kpi_csv_get_dict_update_time()
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kpi_csv.kpi_dict['Graph-Group'] = "Webpage Download {band}".format(
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band=download_table_value['Band'][band])
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kpi_csv.kpi_dict['short-description'] = "Webpage download {band} Minimum".format(
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band=download_table_value['Band'][band])
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kpi_csv.kpi_dict['numeric-score'] = "{min}".format(min=download_table_value['Minimum'][band])
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kpi_csv.kpi_csv_write_dict(kpi_csv.kpi_dict)
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kpi_csv.kpi_dict['short-description'] = "Webpage download {band} Maximum".format(
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band=download_table_value['Band'][band])
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kpi_csv.kpi_dict['numeric-score'] = "{max}".format(max=download_table_value['Maximum'][band])
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kpi_csv.kpi_csv_write_dict(kpi_csv.kpi_dict)
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kpi_csv.kpi_dict['short-description'] = "Webpage download {band} Average".format(
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band=download_table_value['Band'][band])
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kpi_csv.kpi_dict['numeric-score'] = "{avg}".format(avg=download_table_value['Average'][band])
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kpi_csv.kpi_csv_write_dict(kpi_csv.kpi_dict)
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if csv_outfile is not None:
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current_time = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
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csv_outfile = "{}_{}-test_l3_longevity.csv".format(
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csv_outfile, current_time)
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csv_outfile = report.file_add_path(csv_outfile)
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print("csv output file : {}".format(csv_outfile))
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exit()
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test_setup = pd.DataFrame(download_table_value)
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report.set_table_dataframe(test_setup)
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report.build_table()
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@@ -612,13 +659,29 @@ def main():
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parser.add_argument('--passwd', help='WiFi passphrase/password/key')
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parser.add_argument('--target_per_ten', help='number of request per 10 minutes', default=100)
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parser.add_argument('--file_size', type=str, help='specify the size of file you want to download', default='5MB')
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parser.add_argument('--bands', nargs="+", help='specify which band testing you want to run eg 5G OR 2.4G OR Both', default=["5G", "2.4G", "Both"])
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parser.add_argument('--bands', nargs="+", help='specify which band testing you want to run eg 5G OR 2.4G OR Both',
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default=["5G", "2.4G", "Both"])
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parser.add_argument('--duration', type=int, help='time to run traffic')
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parser.add_argument('--threshold_5g', help="Enter the threshold value for 5G Pass/Fail criteria", default="60")
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parser.add_argument('--threshold_2g', help="Enter the threshold value for 2.4G Pass/Fail criteria", default="90")
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parser.add_argument('--threshold_both', help="Enter the threshold value for Both Pass/Fail criteria", default="50")
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parser.add_argument('--ap_name', help="specify the ap model ", default="TestAP")
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parser.add_argument('--ssh_port', type=int, help="specify the ssh port eg 22", default=22)
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parser.add_argument("--test_rig", default="", help="test rig for kpi.csv, testbed that the tests are run on")
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parser.add_argument("--test_tag", default="",
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help="test tag for kpi.csv, test specific information to differentiate the test")
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parser.add_argument("--dut_hw_version", default="",
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help="dut hw version for kpi.csv, hardware version of the device under test")
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parser.add_argument("--dut_sw_version", default="",
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help="dut sw version for kpi.csv, software version of the device under test")
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parser.add_argument("--dut_model_num", default="",
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help="dut model for kpi.csv, model number / name of the device under test")
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parser.add_argument("--dut_serial_num", default="",
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help="dut serial for kpi.csv, serial number / serial number of the device under test")
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parser.add_argument("--test_priority", default="", help="dut model for kpi.csv, test-priority is arbitrary number")
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parser.add_argument("--test_id", default="lf_webpage", help="test-id for kpi.csv, script or test name")
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parser.add_argument('--csv_outfile', help="--csv_outfile <Output file for csv data>", default="")
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args = parser.parse_args()
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test_time = datetime.now()
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@@ -783,7 +846,12 @@ def main():
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duration=args.duration, test_setup_info=test_setup_info, dataset=dataset, lis=lis,
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bands=args.bands, threshold_2g=args.threshold_2g, threshold_5g=args.threshold_5g,
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threshold_both=args.threshold_both, dataset2=dataset2,
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summary_table_value=summary_table_value, result_data=result_data, test_input_infor=test_input_infor)
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summary_table_value=summary_table_value, result_data=result_data,
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test_rig=args.test_rig, test_tag=args.test_tag, dut_hw_version=args.dut_hw_version,
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dut_sw_version=args.dut_sw_version, dut_model_num=args.dut_model_num,
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dut_serial_num=args.dut_serial_num, test_id=args.test_id,
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test_input_infor=test_input_infor, csv_outfile=args.csv_outfile)
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if __name__ == '__main__':
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