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[FSTORE-1081] GitHub Actions Fix #220

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Merged
merged 15 commits into from
Dec 14, 2023
Merged

[FSTORE-1081] GitHub Actions Fix #220

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17481be
Churn parse_dates
Maxxx-zh Nov 30, 2023
969c943
CreditScores parse_dates
Maxxx-zh Nov 30, 2023
5df21f2
LoanApproval wait_for_job
Maxxx-zh Nov 30, 2023
3cfcc2a
Update Quickstart FE
Maxxx-zh Nov 30, 2023
08724cc
FraudBatch wait_for_job
Maxxx-zh Nov 30, 2023
4c6fa59
Churn wait_for_job
Maxxx-zh Nov 30, 2023
2040a0f
Citibike wait_for_job
Maxxx-zh Nov 30, 2023
1cb70e3
Electricity wait_for_job
Maxxx-zh Dec 1, 2023
ec9a126
NycTaxi wait_for_job
Maxxx-zh Dec 1, 2023
514f489
TF Update
Maxxx-zh Dec 1, 2023
d887ff0
CreditScores Sampling
Maxxx-zh Dec 1, 2023
aa25357
Workflow Update
Maxxx-zh Dec 6, 2023
f4d683a
Loan Approval GE Fix
Maxxx-zh Dec 12, 2023
067a014
GE for FraudBatch
Maxxx-zh Dec 12, 2023
ba8759a
GE for FraudOnline
Maxxx-zh Dec 12, 2023
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6 changes: 3 additions & 3 deletions .github/workflows/test_tutorials.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,7 @@ jobs:
- name: Execute Python workflows from bash script
env:
HOPSWORKS_API_KEY: ${{ secrets.HOPSWORKS_API_KEY_38 }}
WEATHER_API_KEY: ${{ secrets.WEATHER_API_KEY }}
WEATHER_API_KEY: ${{ secrets.WEATHER_API_KEY38 }}
run: ./scripts/test-notebooks.sh

test_tutorials39:
Expand All @@ -49,7 +49,7 @@ jobs:
- name: Execute Python workflows from bash script
env:
HOPSWORKS_API_KEY: ${{ secrets.HOPSWORKS_API_KEY_39 }}
WEATHER_API_KEY: ${{ secrets.WEATHER_API_KEY }}
WEATHER_API_KEY: ${{ secrets.WEATHER_API_KEY39 }}
run: ./scripts/test-notebooks.sh

test_tutorials310:
Expand All @@ -72,5 +72,5 @@ jobs:
- name: execute python workflows from bash script
env:
HOPSWORKS_API_KEY: ${{ secrets.HOPSWORKS_API_KEY_310 }}
WEATHER_API_KEY: ${{ secrets.WEATHER_API_KEY }}
WEATHER_API_KEY: ${{ secrets.WEATHER_API_KEY310 }}
run: ./scripts/test-notebooks.sh
17 changes: 13 additions & 4 deletions advanced_tutorials/citibike/1_citibike_feature_backfill.ipynb
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Expand Up @@ -514,7 +514,10 @@
},
"outputs": [],
"source": [
"citibike_usage_fg.insert(df_enhanced)"
"citibike_usage_fg.insert(\n",
" df_enhanced,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -543,7 +546,10 @@
},
"outputs": [],
"source": [
"citibike_stations_info_fg.insert(df_stations_info)"
"citibike_stations_info_fg.insert(\n",
" df_stations_info,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand All @@ -569,7 +575,10 @@
"metadata": {},
"outputs": [],
"source": [
"us_holidays_fg.insert(df_holidays)"
"us_holidays_fg.insert(\n",
" df_holidays,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -634,7 +643,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
"version": "3.9.12"
}
},
"nbformat": 4,
Expand Down
36 changes: 27 additions & 9 deletions advanced_tutorials/credit_scores/1_credit_scores_feature_backfill.ipynb
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Collaborator

@manu-sj manu-sj Dec 11, 2023

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I see that you have performed an array slicing on the read dataframe. From my understanding this was done so that the query in the training pipeline will executed (When I tried with the entire dataframes that query never finished executing). But maybe we can modify and optimize the query so that it runs instead of slicing the dataframe.

Original file line number Diff line number Diff line change
Expand Up @@ -80,8 +80,11 @@
"metadata": {},
"outputs": [],
"source": [
"applications_df = pd.read_csv(\"https://repo.hops.works/dev/davit/credit_scores/applications.csv\")\n",
"applications_df.head()"
"applications_df = pd.read_csv(\n",
" \"https://repo.hops.works/dev/davit/credit_scores/applications.csv\",\n",
" parse_dates=['datetime'],\n",
")\n",
"applications_df.head(3)"
]
},
{
Expand Down Expand Up @@ -111,7 +114,9 @@
"metadata": {},
"outputs": [],
"source": [
"bureau_balances_df = pd.read_csv('https://repo.hops.works/dev/davit/credit_scores/bureau_balances.csv')\n",
"bureau_balances_df = pd.read_csv(\n",
" 'https://repo.hops.works/dev/davit/credit_scores/bureau_balances.csv',\n",
")[:5_000]\n",
"bureau_balances_df.head(3)"
]
},
Expand Down Expand Up @@ -142,7 +147,10 @@
"metadata": {},
"outputs": [],
"source": [
"bureaus_df = pd.read_csv('https://repo.hops.works/dev/davit/credit_scores/bureaus.csv')\n",
"bureaus_df = pd.read_csv(\n",
" 'https://repo.hops.works/dev/davit/credit_scores/bureaus.csv',\n",
" parse_dates=['datetime'],\n",
")[:5_000]\n",
"bureaus_df.head(3)"
]
},
Expand Down Expand Up @@ -173,7 +181,9 @@
"metadata": {},
"outputs": [],
"source": [
"credit_card_balances_df = pd.read_csv('https://repo.hops.works/dev/davit/credit_scores/credit_card_balances.csv')\n",
"credit_card_balances_df = pd.read_csv(\n",
" 'https://repo.hops.works/dev/davit/credit_scores/credit_card_balances.csv',\n",
")[:5_000]\n",
"credit_card_balances_df.head(3)"
]
},
Expand Down Expand Up @@ -204,7 +214,10 @@
"metadata": {},
"outputs": [],
"source": [
"installment_payments_df = pd.read_csv('https://repo.hops.works/dev/davit/credit_scores/installment_payments.csv')\n",
"installment_payments_df = pd.read_csv(\n",
" 'https://repo.hops.works/dev/davit/credit_scores/installment_payments.csv',\n",
" parse_dates=['datetime'],\n",
")[:5_000]\n",
"installment_payments_df.head(3)"
]
},
Expand Down Expand Up @@ -237,7 +250,9 @@
"metadata": {},
"outputs": [],
"source": [
"pos_cash_balances_df = pd.read_csv('https://repo.hops.works/dev/davit/credit_scores/pos_cash_balances.csv')\n",
"pos_cash_balances_df = pd.read_csv(\n",
" 'https://repo.hops.works/dev/davit/credit_scores/pos_cash_balances.csv'\n",
")[:5_000]\n",
"pos_cash_balances_df.head(3)"
]
},
Expand Down Expand Up @@ -270,7 +285,10 @@
"metadata": {},
"outputs": [],
"source": [
"previous_applications_df = pd.read_csv('https://repo.hops.works/dev/davit/credit_scores/previous_applications.csv')\n",
"previous_applications_df = pd.read_csv(\n",
" 'https://repo.hops.works/dev/davit/credit_scores/previous_applications.csv',\n",
" parse_dates=['datetime'],\n",
")[:5_000]\n",
"previous_applications_df.head(3)"
]
},
Expand Down Expand Up @@ -890,7 +908,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
"version": "3.9.12"
}
},
"nbformat": 4,
Expand Down
4 changes: 2 additions & 2 deletions advanced_tutorials/credit_scores/3_credit_scores_training_pipeline.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@
"metadata": {},
"outputs": [],
"source": [
"!pip install xgboost"
"!pip install xgboost --quiet"
]
},
{
Expand Down Expand Up @@ -619,7 +619,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
"version": "3.9.12"
}
},
"nbformat": 4,
Expand Down
12 changes: 9 additions & 3 deletions advanced_tutorials/electricity/1_electricity_feature_backfill.ipynb
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Expand Up @@ -275,7 +275,10 @@
},
"outputs": [],
"source": [
"meteorological_measurements_fg.insert(meteorological_measurements_df)"
"meteorological_measurements_fg.insert(\n",
" meteorological_measurements_df,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -306,7 +309,10 @@
},
"outputs": [],
"source": [
"electricity_prices_fg.insert(electricity_prices_df)"
"electricity_prices_fg.insert(\n",
" electricity_prices_df,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -376,7 +382,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
"version": "3.9.12"
}
},
"nbformat": 4,
Expand Down
7 changes: 5 additions & 2 deletions advanced_tutorials/nyc_taxi_fares/1_nyc_taxi_fares_feature_backfill.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -181,7 +181,10 @@
" statistics_config=True,\n",
")\n",
"\n",
"rides_fg.insert(df_rides)"
"rides_fg.insert(\n",
" df_rides,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -243,7 +246,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
"version": "3.9.12"
}
},
"nbformat": 4,
Expand Down
2 changes: 1 addition & 1 deletion advanced_tutorials/transformation_functions/custom/custom_transformation_functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -170,7 +170,7 @@
") \n",
"feature_group.insert(\n",
" df_original, \n",
" wait=True,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
Expand Down
10 changes: 8 additions & 2 deletions advanced_tutorials/transformation_functions/keras/keras_transformation_functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -172,7 +172,10 @@
" primary_key=['city_name', 'date'],\n",
" online_enabled=True,\n",
") \n",
"feature_group.insert(df_original)"
"feature_group.insert(\n",
" df_original,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -409,6 +412,9 @@
" # Create a new DataFrame with the encoded values\n",
" encoded_df = pd.DataFrame(city_encoded, columns=one_hot_encoder.categories_[0])\n",
"\n",
" # Reset the index of the original DataFrame\n",
" data = data.reset_index(drop=True)\n",
"\n",
" # Concatenate the encoded DataFrame with the original DataFrame\n",
" data = pd.concat([data.drop('city_name', axis=1), encoded_df], axis=1)\n",
" \n",
Expand Down Expand Up @@ -789,7 +795,7 @@
"outputs": [],
"source": [
"# Initialise feature view to retrieve batch data\n",
"feature_view.init_batch_scoring(training_dataset_version=td_version)\n",
"feature_view.init_batch_scoring(1)\n",
"\n",
"# Retrieve batch data\n",
"batch_data = feature_view.get_batch_data()\n",
Expand Down
10 changes: 8 additions & 2 deletions advanced_tutorials/transformation_functions/pytorch/pytorch_transformation_functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -174,7 +174,10 @@
" primary_key=['city_name', 'date'],\n",
" online_enabled=True,\n",
") \n",
"feature_group.insert(df_original)"
"feature_group.insert(\n",
" df_original,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -411,6 +414,9 @@
" # Create a new DataFrame with the encoded values\n",
" encoded_df = pd.DataFrame(city_encoded, columns=one_hot_encoder.categories_[0])\n",
"\n",
" # Reset the index of the original DataFrame\n",
" data = data.reset_index(drop=True)\n",
"\n",
" # Concatenate the encoded DataFrame with the original DataFrame\n",
" data = pd.concat([data.drop('city_name', axis=1), encoded_df], axis=1)\n",
" \n",
Expand Down Expand Up @@ -869,7 +875,7 @@
"outputs": [],
"source": [
"# Initialise feature view to retrieve batch data\n",
"feature_view.init_batch_scoring(training_dataset_version=td_version)\n",
"feature_view.init_batch_scoring(1)\n",
"\n",
"# Retrieve batch data\n",
"batch_data = feature_view.get_batch_data()\n",
Expand Down
7 changes: 5 additions & 2 deletions advanced_tutorials/transformation_functions/sklearn/sklearn_transformation_functions.ipynb
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Expand Up @@ -183,7 +183,10 @@
" primary_key=['city_name', 'date'],\n",
" online_enabled=True,\n",
") \n",
"feature_group.insert(df_original)"
"feature_group.insert(\n",
" df_original,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -619,7 +622,7 @@
"outputs": [],
"source": [
"# Initialise feature view to retrieve batch data\n",
"feature_view.init_batch_scoring(training_dataset_version=td_version)\n",
"feature_view.init_batch_scoring(1)\n",
"\n",
"# Retrieve batch data\n",
"batch_data = feature_view.get_batch_data()\n",
Expand Down
22 changes: 17 additions & 5 deletions churn/1_churn_feature_pipeline.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -86,8 +86,14 @@
"outputs": [],
"source": [
"demography_df = pd.read_csv(\"https://repo.hops.works/dev/davit/churn/demography.csv\")\n",
"customer_info_df = pd.read_csv(\"https://repo.hops.works/dev/davit/churn/customer_info.csv\")\n",
"subscriptions_df = pd.read_csv(\"https://repo.hops.works/dev/davit/churn/subscriptions.csv\")"
"customer_info_df = pd.read_csv(\n",
" \"https://repo.hops.works/dev/davit/churn/customer_info.csv\",\n",
" parse_dates=['datetime'],\n",
")\n",
"subscriptions_df = pd.read_csv(\n",
" \"https://repo.hops.works/dev/davit/churn/subscriptions.csv\",\n",
" parse_dates=['datetime'],\n",
")"
]
},
{
Expand Down Expand Up @@ -226,7 +232,10 @@
"outputs": [],
"source": [
"# Insert data into feature group\n",
"customer_info_fg.insert(customer_info_df)"
"customer_info_fg.insert(\n",
" customer_info_df,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -268,7 +277,10 @@
" primary_key=['customerID'],\n",
")\n",
"# Insert data into feature group\n",
"demography_fg.insert(demography_df)"
"demography_fg.insert(\n",
" demography_df,\n",
" write_options={\"wait_for_job\": True},\n",
")"
]
},
{
Expand Down Expand Up @@ -382,7 +394,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
"version": "3.9.12"
}
},
"nbformat": 4,
Expand Down
3 changes: 1 addition & 2 deletions churn/2_churn_training_pipeline.ipynb
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Expand Up @@ -436,7 +436,6 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"## <span style=\"color:#ff5f27;\">⏭️ **Next:** Part 03 </span>\n",
"\n",
"In the following notebook you will use your model for batch inference.\n",
Expand Down Expand Up @@ -464,7 +463,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
"version": "3.9.12"
}
},
"nbformat": 4,
Expand Down
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