AntiNex Consts¶
Here are the environment variables and constants used by the AntiNex client.
LOGIN_SUCCESS = 0
LOGIN_NOT_ATTEMPTED = 1
LOGIN_FAILED = 2
SUCCESS = 0
FAILED = 1
ERROR = 2
NOT_SET = 3
DISABLED = 4
Client Environment Variables¶
These are the environment variables used by the AntiNex client.
Note
Please make sure these match up with your local, running stack:
AntiNex REST API flags, endpoint and credentials https://github.com/jay-johnson/train-ai-with-django-swagger-jwt
AntiNex is running using compose.yml file: https://github.com/jay-johnson/train-ai-with-django-swagger-jwt/blob/master/compose.yml
ANTINEX_PUBLISH_ENABLED = bool(ev(
"ANTINEX_PUBLISH_ENABLED",
"1") == "1")
ANTINEX_URL = ev(
"ANTINEX_URL",
"http://localhost:8010")
ANTINEX_CA_FILE = os.getenv(
"ANTINEX_CA_FILE",
None)
ANTINEX_CERT_FILE = os.getenv(
"ANTINEX_CERT_FILE",
None)
ANTINEX_KEY_FILE = os.getenv(
"ANTINEX_KEY_FILE",
None)
ANTINEX_USER = ev(
"ANTINEX_USER",
"root")
ANTINEX_EMAIL = ev(
"ANTINEX_EMAIL",
"notreal@test.com")
ANTINEX_PASSWORD = ev(
"ANTINEX_PASSWORD",
"123321")
# provide a template request publish file like:
# https://github.com/jay-johnson/antinex-client/blob/master/examples/predict-rows-scaler-full-django.json
ANTINEX_PUBLISH_REQUEST_FILE = ev(
"ANTINEX_PUBLISH_REQUEST_FILE",
("/opt/antinex/client/examples/"
"predict-rows-scaler-full-django.json"))
# comma-separated list
ANTINEX_FEATURES_TO_PROCESS_STR = os.getenv(
"ANTINEX_FEATURES_TO_PROCESS",
None)
# comma-separated list
ANTINEX_IGNORE_FEATURES_STR = os.getenv(
"ANTINEX_IGNORE_FEATURES",
None)
# comma-separated list
ANTINEX_SORT_VALUES_STR = os.getenv(
"ANTINEX_SORT_VALUES",
None)
# comma-separated list
ANTINEX_METRICS_STR = os.getenv(
"ANTINEX_METRICS",
None)
# comma-separated list
ANTINEX_HISTORIES_STR = os.getenv(
"ANTINEX_HISTORIES",
None)
ANTINEX_ML_TYPE = ev(
"ANTINEX_ML_TYPE",
"classification")
ANTINEX_USE_MODEL_NAME = ev(
"ANTINEX_USE_MODEL_NAME",
"Full-Django-AntiNex-Simple-Scaler-DNN")
ANTINEX_PREDICT_FEATURE = ev(
"ANTINEX_PREDICT_FEATURE",
"label_value")
ANTINEX_SEED = int(ev(
"ANTINEX_SEED",
"42"))
ANTINEX_TEST_SIZE = float(ev(
"ANTINEX_TEST_SIZE",
"0.2"))
ANTINEX_BATCH_SIZE = int(ev(
"ANTINEX_BATCH_SIZE",
"32"))
ANTINEX_EPOCHS = int(ev(
"ANTINEX_EPOCHS",
"15"))
ANTINEX_NUM_SPLITS = int(ev(
"ANTINEX_NUM_SPLITS",
"3"))
ANTINEX_LOSS = ev(
"ANTINEX_LOSS",
"binary_crossentropy")
ANTINEX_OPTIMIZER = ev(
"ANTINEX_OPTIMIZER",
"adam")
ANTINEX_VERSION = ev(
"ANTINEX_VERSION",
"1")
ANTINEX_CONVERT_DATA = bool(ev(
"ANTINEX_CONVERT_DATA",
"1") == "1")
ANTINEX_CONVERT_DATA_TYPE = ev(
"ANTINEX_CONVERT_DATA_TYPE",
"float")
ANTINEX_INCLUDE_FAILED_CONVERSIONS = bool(ev(
"ANTINEX_INCLUDE_FAILED_CONVERSIONS",
"0") == "1")
ANTINEX_MISSING_VALUE = ev(
"ANTINEX_MISSING_VALUE",
"-1.0")
ANTINEX_PUBLISH_TO_CORE = bool(ev(
"ANTINEX_PUBLISH_TO_CORE",
"1") == "1")
ANTINEX_CHECK_MISSING_PREDICT = bool(ev(
"ANTINEX_CHECK_MISSING_PREDICT",
"1") == "1")
ANTINEX_CLIENT_VERBOSE = bool(ev(
"ANTINEX_CLIENT_VERBOSE",
"1") == "1")
ANTINEX_CLIENT_DEBUG = bool(ev(
"ANTINEX_CLIENT_DEBUG",
"0") == "1")
# set empty defaults
ANTINEX_FEATURES_TO_PROCESS = []
ANTINEX_IGNORE_FEATURES = []
ANTINEX_SORT_VALUES = []
ANTINEX_METRICS = []
ANTINEX_HISTORIES = []
These environment variables are set as lists based of commas:
if ANTINEX_FEATURES_TO_PROCESS_STR:
ANTINEX_FEATURES_TO_PROCESS = \
ANTINEX_FEATURES_TO_PROCESS_STR.split(",")
if ANTINEX_IGNORE_FEATURES_STR:
ANTINEX_IGNORE_FEATURES = \
ANTINEX_IGNORE_FEATURES_STR.split(",")
if ANTINEX_SORT_VALUES_STR:
ANTINEX_SORT_VALUES = \
ANTINEX_SORT_VALUES_STR.split(",")
if ANTINEX_METRICS_STR:
ANTINEX_METRICS = \
ANTINEX_METRICS_STR.split(",")
if ANTINEX_HISTORIES_STR:
ANTINEX_HISTORIES = \
ANTINEX_HISTORIES_STR.split(",")
Environment variables that are set to dictionaries for faster lookups:
FILTER_FEATURES_DICT = {}
FILTER_FEATURES = []
for idx, f in enumerate(ANTINEX_FEATURES_TO_PROCESS):
include_feature = True
if f == ANTINEX_PREDICT_FEATURE:
include_feature = False
for i in ANTINEX_IGNORE_FEATURES:
if f == i:
include_feature = False
break
if include_feature:
FILTER_FEATURES.append(f)
FILTER_FEATURES_DICT[f] = idx
# end of for all features not being ignored