How to use the resilient.SimpleClient function in resilient

To help you get started, we’ve selected a few resilient examples, based on popular ways it is used in public projects.

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github ibmresilient / resilient-community-apps / fn_machine_learning / fn_machine_learning / bin / res_ml.py View on Github external
requests.packages.urllib3.disable_warnings()
                verify = False
            elif os.path.isfile(cafile):
                #
                #   User specified a cafile for trusted certificate
                #
                verify = cafile
        except:
            verify = True

        args = {"base_url": url,
                "verify": verify,
                "org_name": org}

        resilient_client = resilient.SimpleClient(**args)
        session = resilient_client.connect(email, password)
        max_count = None
        if opt_parser.getopt(MACHINE_LEARNING_SECTION, "max_count"):
            max_count = int(opt_parser.getopt(MACHINE_LEARNING_SECTION, "max_count"))

        time_start = opt_parser.getopt(MACHINE_LEARNING_SECTION, "time_start")
        time_end = opt_parser.getopt(MACHINE_LEARNING_SECTION, "time_end")
        res_filter = IncidentTimeFilter(time_start=time_start,
                                        time_end=time_end,
                                        in_log=LOG)

        # get_incidents is going to download all the incidents using this resilient_client
        # The optional max_count controls how many samples to process. The conversion from
        # json to CSV will stop once reaches this limit.
        num_inc = resilient_utils.get_incidents(res_client=resilient_client,
                                                filename=csv_file,