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update guide messages
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‎notebooks/feature_engineering.ipynb‎

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"id": "7bfd56a7",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[GUIDE] Successfully performed generate_entityset.\n",
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"\tYou can perform the next step by calling generate_label_times.\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"id": "e0ee16eb",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[GUIDE] Successfully performed generate_label_times.\n",
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"\tYou can perform the next step by calling generate_feature_matrix.\n"
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]
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},
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{
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"data": {
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"text/html": [
@@ -458,7 +474,9 @@
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"/Users/raymondpan/zephyr/Zephyr-repo/venv/lib/python3.8/site-packages/numpy/core/fromnumeric.py:3464: RuntimeWarning: Mean of empty slice.\n",
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" return _methods._mean(a, axis=axis, dtype=dtype,\n",
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"/Users/raymondpan/zephyr/Zephyr-repo/venv/lib/python3.8/site-packages/numpy/core/_methods.py:192: RuntimeWarning: invalid value encountered in scalar divide\n",
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" ret = ret.dtype.type(ret / rcount)\n"
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" ret = ret.dtype.type(ret / rcount)\n",
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"[GUIDE] Successfully performed generate_feature_matrix.\n",
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"\tYou can perform the next step by calling generate_train_test_split.\n"
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]
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}
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],
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" <Feature: MAX(pidata_processed.fft.mean.mean_value)>,\n",
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" <Feature: MIN(pidata_processed.fft.mean.mean_value)>,\n",
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" <Feature: SUM(pidata_processed.fft.mean.mean_value)>,\n",
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" <Feature: COUNT(alarms WHERE DES_NAME = Alarm2)>,\n",
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" <Feature: COUNT(alarms WHERE DES_NAME = Alarm1)>,\n",
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" <Feature: SUM(alarms.IND_DURATION WHERE DES_NAME = Alarm2)>,\n",
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" <Feature: COUNT(alarms WHERE DES_NAME = Alarm2)>,\n",
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" <Feature: SUM(alarms.IND_DURATION WHERE DES_NAME = Alarm1)>,\n",
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" <Feature: SUM(alarms.IND_DURATION WHERE DES_NAME = Alarm2)>,\n",
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" <Feature: MAX(stoppages.NUM_WORDS(DES_COMMENTS))>,\n",
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" <Feature: MAX(stoppages.NUM_WORDS(DES_DESCRIPTION))>,\n",
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" <Feature: MAX(stoppages.NUM_WORDS(DES_WO_NAME))>,\n",

‎notebooks/modeling.ipynb‎

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"text": [
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"/Users/raymondpan/zephyr/Zephyr-repo/venv/lib/python3.8/site-packages/sklearn/impute/_base.py:555: UserWarning: Skipping features without any observed values: [ 1 2 6 7 9 10 15 16 17 18]. At least one non-missing value is needed for imputation with strategy='mean'.\n",
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" warnings.warn(\n",
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"Performing set_feature_matrix. You are skipping the following steps:\n",
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"0. generate_entityset or set_entityset\n",
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"1. generate_label_times or set_label_times\n"
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"[GUIDE] STALE WARNING: \n",
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"\tPerforming step 2 from step -1 with set_feature_matrix.\n",
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"\tThis is a forward step via a set method.\n",
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"\tThe current step is -1.\n",
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"\tAll previous steps will be considered stale.\n",
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"[GUIDE] Successfully performed set_feature_matrix.\n",
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"\tYou can perform the next step by calling generate_train_test_split.\n",
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"[GUIDE] Successfully performed generate_train_test_split.\n",
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"\tYou can perform the next step by calling fit_pipeline.\n"
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]
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},
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{
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"execution_count": 3,
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"id": "edffee03",
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[GUIDE] Successfully performed fit_pipeline.\n",
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"\tYou can perform the next step by calling predict or evaluate.\n"
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]
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}
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],
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"source": [
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"hyperparameters = {\n",
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" \"xgboost.XGBClassifier#1\": {\n",
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"id": "78187756",
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"metadata": {},
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"outputs": [
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[GUIDE] Successfully performed predict.\n",
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"\tYou have reached the end of the predictive engineering workflow.\n",
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"\tYou can call predict or evaluate again or re-perform previous steps based on results.\n"
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]
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},
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"execution_count": 5,
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"id": "cd097853",
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"metadata": {},
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"outputs": [],
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"outputs": [
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[GUIDE] Successfully performed evaluate.\n",
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"\tYou have reached the end of the predictive engineering workflow.\n",
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"\tYou can call predict or evaluate again or re-perform previous steps based on results.\n"
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]
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}
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],
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"source": [
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"res = zephyr.evaluate()"
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]

‎notebooks/visualization.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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},
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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"text": [
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"/Users/raymondpan/zephyr/Zephyr-repo/venv/lib/python3.8/site-packages/sklearn/impute/_base.py:555: UserWarning: Skipping features without any observed values: [ 1 2 6 7 9 10 15 16 17 18]. At least one non-missing value is needed for imputation with strategy='mean'.\n",
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" warnings.warn(\n",
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"Performing set_feature_matrix. You are skipping the following steps:\n",
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"0. generate_entityset or set_entityset\n",
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"1. generate_label_times or set_label_times\n"
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"[GUIDE] STALE WARNING: \n",
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"\tPerforming step 2 from step -1 with set_feature_matrix.\n",
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"\tThis is a forward step via a set method.\n",
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"\tThe current step is -1.\n",
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"\tAll previous steps will be considered stale.\n",
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"[GUIDE] Successfully performed set_feature_matrix.\n",
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"\tYou can perform the next step by calling generate_train_test_split.\n",
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"[GUIDE] Successfully performed generate_train_test_split.\n",
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"\tYou can perform the next step by calling fit_pipeline.\n"
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]
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},
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{
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" Name: label, dtype: bool)"
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]
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"execution_count": 2,
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"output_type": "execute_result"
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},
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 3,
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"id": "683393df",
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"metadata": {},
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"outputs": [],
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"outputs": [
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[GUIDE] Successfully performed fit_pipeline.\n",
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"\tYou can perform the next step by calling predict or evaluate.\n"
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]
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}
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],
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"source": [
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"output = zephyr.fit_pipeline(pipeline = \"xgb_classifier\", visual=True)"
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]
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},
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": 4,
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"dict_keys(['threshold', 'scores'])"
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"execution_count": 4,
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‎tests/test_guide.py‎

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class DummyObject:
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def __init__(self):
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producers_and_getters = [
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([self.step0_key, self.step0_set], [self.step0_getter]),
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([self.step1_key, self.step1_set], [self.step1_getter]),
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([self.step2_key, self.step2_set], [self.step2_getter])
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([self.step0_key], [self.step0_set], [self.step0_getter]),
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([self.step1_key], [self.step1_set], [self.step1_getter]),
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([self.step2_key], [self.step2_set], [self.step2_getter])
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]
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set_methods = {
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self.step0_set.__name__,
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self.step1_set.__name__,
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self.step2_set.__name__
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}
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self._guide_handler = GuideHandler(producers_and_getters, set_methods)
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self._guide_handler = GuideHandler(producers_and_getters)
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@guide
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def step0_key(self):

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