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[FSTORE-1666] Import transformations functions from Hopsworks API in tutorials so that they are compatible with all project in APP #295

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merged 1 commit into from
Jan 22, 2025
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[FSTORE-1666] Import transformations functions from Hopsworks API in tutorials so that they are compatible with all project in APP #295

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167 changes: 27 additions & 140 deletions api_examples/feature_monitoring.ipynb
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Expand Up @@ -45,21 +45,10 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "78326a44",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Connected. Call `.close()` to terminate connection gracefully.\n",
"\n",
"Logged in to project, explore it here https://hopsworks0.logicalclocks.com/p/120\n",
"Connected. Call `.close()` to terminate connection gracefully.\n"
]
}
],
"outputs": [],
"source": [
"import hopsworks\n",
"import numpy as np\n",
Expand All @@ -82,7 +71,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "42e1c8b0",
"metadata": {},
"outputs": [],
Expand Down Expand Up @@ -120,42 +109,10 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"id": "a1ad04fa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Feature Group created successfully, explore it at \n",
"https://hopsworks0.logicalclocks.com/p/120/fs/68/fg/14\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "719e5cea6dca47bdbfd8e87f5b145c45",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Uploading Dataframe: 0.00% | | Rows 0/106020 | Elapsed Time: 00:00 | Remaining Time: ?"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Launching job: trans_fg_1_offline_fg_materialization\n",
"Job started successfully, you can follow the progress at \n",
"https://hopsworks0.logicalclocks.com/p/120/jobs/named/trans_fg_1_offline_fg_materialization/executions\n"
]
}
],
"outputs": [],
"source": [
"# Feature Group\n",
"trans_fg = fs.get_or_create_feature_group(\n",
Expand All @@ -174,32 +131,15 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "176ad761",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Feature view created successfully, explore it at \n",
"https://hopsworks0.logicalclocks.com/p/120/fs/68/fv/trans_fv/version/1\n",
"Training dataset job started successfully, you can follow the progress at \n",
"https://hopsworks0.logicalclocks.com/p/120/jobs/named/trans_fv_1_create_fv_td_16022024133852/executions\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"VersionWarning: Incremented version to `1`.\n"
]
}
],
"outputs": [],
"source": [
"query = trans_fg.select([\"fraud_label\", \"amount\", \"cc_num\"])\n",
"\n",
"min_max_scaler = fs.get_transformation_function(name=\"min_max_scaler\")\n",
"# Import transformation functions from Hopsworks.\n",
"from hopsworks.hsfs.builtin_transformations import min_max_scaler\n",
"\n",
"transformation_functions = [\n",
" min_max_scaler(\"amount\") \n",
Expand All @@ -224,26 +164,10 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"id": "29ae9922",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Training dataset job started successfully, you can follow the progress at \n",
"https://hopsworks0.logicalclocks.com/p/120/jobs/named/trans_fv_1_create_fv_td_16022024134233/executions\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"VersionWarning: Incremented version to `2`.\n"
]
}
],
"outputs": [],
"source": [
"_, _ = trans_fv.create_train_validation_test_split(\n",
" description = 'test extra filters',\n",
Expand Down Expand Up @@ -275,7 +199,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"id": "b82685fb",
"metadata": {},
"outputs": [],
Expand Down Expand Up @@ -303,7 +227,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": null,
"id": "703da6cc",
"metadata": {},
"outputs": [],
Expand All @@ -325,7 +249,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": null,
"id": "28a891bf",
"metadata": {},
"outputs": [],
Expand All @@ -347,7 +271,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"id": "fa5651be",
"metadata": {},
"outputs": [],
Expand Down Expand Up @@ -382,7 +306,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": null,
"id": "dce248fb",
"metadata": {},
"outputs": [],
Expand All @@ -408,21 +332,10 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": null,
"id": "7fcc0236",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"FeatureMonitoringConfig('fg_amount_monitoring_reference_value', STATISTICS_COMPARISON)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"fg_amount_monitoring_reference_value.with_reference_value(\n",
" value=100,\n",
Expand All @@ -444,7 +357,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": null,
"id": "b5ecd419",
"metadata": {},
"outputs": [],
Expand Down Expand Up @@ -477,7 +390,7 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": null,
"id": "2acd07e4",
"metadata": {},
"outputs": [],
Expand Down Expand Up @@ -530,7 +443,7 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": null,
"id": "07c863f2",
"metadata": {},
"outputs": [],
Expand All @@ -554,25 +467,10 @@
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": null,
"id": "58483800",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[FeatureMonitoringConfig('fg_full_monitoring_sliding', STATISTICS_COMPUTATION),\n",
" FeatureMonitoringConfig('fg_full_monitoring', STATISTICS_COMPUTATION),\n",
" FeatureMonitoringConfig('fg_amount_monitoring_reference_value', STATISTICS_COMPARISON),\n",
" FeatureMonitoringConfig('fg_amount_monitoring_reference_sliding', STATISTICS_COMPARISON),\n",
" FeatureMonitoringConfig('fg_amount_feature_monitoring', STATISTICS_COMPUTATION)]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"trans_fg.get_feature_monitoring_configs()"
]
Expand All @@ -587,21 +485,10 @@
},
{
"cell_type": "code",
"execution_count": 16,
"execution_count": null,
"id": "3372c2d8",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"FeatureMonitoringConfig('fg_full_monitoring', STATISTICS_COMPUTATION)"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"trans_fg.get_feature_monitoring_configs(name=\"fg_full_monitoring\")"
]
Expand All @@ -624,7 +511,7 @@
"hash": "e1ddeae6eefc765c17da80d38ea59b893ab18c0c0904077a035ef84cfe367f83"
},
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
Expand All @@ -638,7 +525,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.11"
"version": "3.12.5"
}
},
"nbformat": 4,
Expand Down
6 changes: 3 additions & 3 deletions batch-ai-systems/churn/2_churn_training_pipeline.ipynb
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Expand Up @@ -158,9 +158,9 @@
"metadata": {},
"outputs": [],
"source": [
"# Load transformation functions from the feature store\n",
"min_max_scaler = fs.get_transformation_function(name=\"min_max_scaler\")\n",
"label_encoder = fs.get_transformation_function(name=\"label_encoder\")\n",
"# Import transformation functions from Hopsworks.\n",
"from hopsworks.hsfs.builtin_transformations import label_encoder, min_max_scaler\n",
"\n",
"\n",
"# Define lists of numerical and categorical features\n",
"numerical_features = [\"tenure\", \"monthlycharges\", \"totalcharges\"]\n",
Expand Down
4 changes: 2 additions & 2 deletions batch-ai-systems/credit_scores/3_credit_scores_training_pipeline.ipynb
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Expand Up @@ -286,8 +286,8 @@
"# Extracting the names of categorical columns in the 'selected_features_show5query_show5' DataFrame\n",
"cat_cols = selected_features_show5.dtypes[selected_features_show5.dtypes == 'object'].index\n",
"\n",
"# Retrieving the Label Encoder transformation function from Featuretools\n",
"label_encoder = fs.get_transformation_function(name='label_encoder') \n",
"# Import transformation functions from Hopsworks.\n",
"from hopsworks.hsfs.builtin_transformations import label_encoder\n",
"\n",
"# Creating a dictionary of transformation functions, where each categorical column is associated with the Label Encoder\n",
"transformation_functions = [\n",
Expand Down
4 changes: 2 additions & 2 deletions batch-ai-systems/fraud_batch/2_fraud_batch_training_pipeline.ipynb
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Expand Up @@ -155,8 +155,8 @@
"metadata": {},
"outputs": [],
"source": [
"# Load transformation functions.\n",
"label_encoder = fs.get_transformation_function(name=\"label_encoder\")\n",
"# Import transformation functions from Hopsworks.\n",
"from hopsworks.hsfs.builtin_transformations import label_encoder\n",
"\n",
"# Map features to transformations.\n",
"transformation_functions = [\n",
Expand Down
5 changes: 2 additions & 3 deletions batch-ai-systems/hospital_wait_time/2_training_pipeline.ipynb
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Expand Up @@ -139,9 +139,8 @@
"metadata": {},
"outputs": [],
"source": [
"label_encoder = fs.get_transformation_function(name=\"label_encoder\")\n",
"\n",
"standard_scaler = fs.get_transformation_function(name=\"standard_scaler\")"
"# Import transformation functions from Hopsworks.\n",
"from hopsworks.hsfs.builtin_transformations import label_encoder, standard_scaler"
]
},
{
Expand Down
4 changes: 2 additions & 2 deletions integrations/mage_ai/mage_tutorial/custom/transactions_feature_view.py
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Expand Up @@ -39,8 +39,8 @@ def transform_custom(*args, **kwargs):
query = trans_fg.select(["fraud_label", "category", "amount", "age_at_transaction", "days_until_card_expires", "loc_delta"])\
.join(window_aggs_fg.select_except(["cc_num"]))

# Load transformation functions.
label_encoder = fs.get_transformation_function(name="label_encoder")
# Import transformation functions from Hopsworks.
from hopsworks.hsfs.builtin_transformations import label_encoder

# Map features to transformations.
transformation_functions = [
Expand Down
4 changes: 2 additions & 2 deletions integrations/mage_ai/mage_tutorial/data_exporters/transactions_feature_view.py
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Expand Up @@ -37,8 +37,8 @@ def create_feature_view(data, *args, **kwargs):
query = trans_fg.select(["fraud_label", "category", "amount", "age_at_transaction", "days_until_card_expires", "loc_delta"])\
.join(window_aggs_fg.select_except(["cc_num"]))

# Load transformation functions.
label_encoder = fs.get_transformation_function(name="label_encoder")
# Import transformation functions from Hopsworks.
from hopsworks.hsfs.builtin_transformations import label_encoder

# Map features to transformations.
transformation_functions = [
Expand Down
4 changes: 2 additions & 2 deletions integrations/neo4j/2_training_pipeline.ipynb
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Expand Up @@ -145,8 +145,8 @@
"metadata": {},
"outputs": [],
"source": [
"# Load built in transformation functions.\n",
"min_max_scaler = fs.get_transformation_function(name=\"min_max_scaler\")\n",
"# Import transformation functions from Hopsworks.\n",
"from hopsworks.hsfs.builtin_transformations import min_max_scaler\n",
"\n",
"# Map features to transformations.\n",
"transformation_functions = [\n",
Expand Down
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