13. Create Feature List

Create a feature list¶

A feature list is an essential component in machine learning, comprising a collection of features that are used to train models. Let's compile a feature list using some of the features we've created.

In [1]:

import featurebyte as fb

# Set your profile to the tutorial environment
fb.use_profile("tutorial")

catalog_name = "Grocery Dataset SDK Tutorial"
catalog = fb.Catalog.activate(catalog_name)

import featurebyte as fb # Set your profile to the tutorial environment fb.use_profile("tutorial") catalog_name = "Grocery Dataset SDK Tutorial" catalog = fb.Catalog.activate(catalog_name)

11:15:26 | INFO     | SDK version: 3.2.0.dev66
INFO    :featurebyte:SDK version: 3.2.0.dev66
11:15:26 | INFO     | No catalog activated.
INFO    :featurebyte:No catalog activated.
11:15:26 | INFO     | Using profile: staging
INFO    :featurebyte:Using profile: staging
11:15:26 | INFO     | Using configuration file at: /Users/gxav/.featurebyte/config.yaml
INFO    :featurebyte:Using configuration file at: /Users/gxav/.featurebyte/config.yaml
11:15:26 | INFO     | Active profile: staging (https://staging.featurebyte.com/api/v1)
INFO    :featurebyte:Active profile: staging (https://staging.featurebyte.com/api/v1)
11:15:26 | INFO     | SDK version: 3.2.0.dev66
INFO    :featurebyte:SDK version: 3.2.0.dev66
11:15:26 | INFO     | No catalog activated.
INFO    :featurebyte:No catalog activated.
11:15:26 | INFO     | Catalog activated: Grocery Dataset SDK Tutorial
INFO    :featurebyte.api.catalog:Catalog activated: Grocery Dataset SDK Tutorial
16:11:44 | INFO     | Using configuration file at: /Users/gxav/.featurebyte/config.yaml
16:11:44 | INFO     | Active profile: tutorial (https://tutorials.featurebyte.com/api/v1)
16:11:44 | WARNING  | Remote SDK version (1.1.0.dev7) is different from local (1.1.0.dev1). Update local SDK to avoid unexpected behavior.
16:11:44 | INFO     | No catalog activated.
16:11:44 | INFO     | Catalog activated: Grocery Dataset Tutorial

List all features we created so far¶

In [2]:

catalog.list_features()

catalog.list_features()

Out[2]:

	id	name	dtype	readiness	online_enabled	tables	primary_tables	entities	primary_entities	created_at
0	68ef1190b71c16b74514b83d	CUSTOMER_vs_OVERALL_item_TotalCost_across_prod...	FLOAT	DRAFT	False	[GROCERYINVOICE, INVOICEITEMS, GROCERYPRODUCT]	[INVOICEITEMS]	[customer]	[customer]	2025-10-15T03:14:38.474000
1	68ef116a37e5b9ed2860624a	CUSTOMER_Latest_invoice_Amount_Z_Score_to_invo...	FLOAT	DRAFT	False	[GROCERYINVOICE]	[GROCERYINVOICE]	[customer]	[customer]	2025-10-15T03:13:51.207000
2	68ef112acbdce2fa954f3f85	CUSTOMER_Std_of_invoice_Amount_28d	FLOAT	DRAFT	False	[GROCERYINVOICE]	[GROCERYINVOICE]	[customer]	[customer]	2025-10-15T03:13:06.351000
3	68ef112acbdce2fa954f3f84	CUSTOMER_Std_of_invoice_Amount_14d	FLOAT	DRAFT	False	[GROCERYINVOICE]	[GROCERYINVOICE]	[customer]	[customer]	2025-10-15T03:13:05.888000
4	68ef112acbdce2fa954f3f83	CUSTOMER_Avg_of_invoice_Amount_28d	FLOAT	DRAFT	False	[GROCERYINVOICE]	[GROCERYINVOICE]	[customer]	[customer]	2025-10-15T03:13:05.462000
5	68ef112acbdce2fa954f3f82	CUSTOMER_Avg_of_invoice_Amount_14d	FLOAT	DRAFT	False	[GROCERYINVOICE]	[GROCERYINVOICE]	[customer]	[customer]	2025-10-15T03:13:05.011000
6	68ef112acbdce2fa954f3f81	CUSTOMER_Count_of_invoice_28d	INT	DRAFT	False	[GROCERYINVOICE]	[GROCERYINVOICE]	[customer]	[customer]	2025-10-15T03:13:04.596000
7	68ef112acbdce2fa954f3f80	CUSTOMER_Count_of_invoice_14d	INT	DRAFT	False	[GROCERYINVOICE]	[GROCERYINVOICE]	[customer]	[customer]	2025-10-15T03:13:04.233000
8	68ef112acbdce2fa954f3f7f	CUSTOMER_Latest_invoice_Amount	FLOAT	DRAFT	False	[GROCERYINVOICE]	[GROCERYINVOICE]	[customer]	[customer]	2025-10-15T03:13:03.880000
9	68ef112acbdce2fa954f3f7b	CUSTOMER_x_PRODUCTGROUP_Sum_of_item_TotalCost_28d	FLOAT	DRAFT	False	[GROCERYINVOICE, INVOICEITEMS, GROCERYPRODUCT]	[INVOICEITEMS]	[customer, productgroup]	[customer, productgroup]	2025-10-15T03:13:03.465000
10	68ef112acbdce2fa954f3f7a	CUSTOMER_x_PRODUCTGROUP_Sum_of_item_TotalCost_14d	FLOAT	DRAFT	False	[GROCERYINVOICE, INVOICEITEMS, GROCERYPRODUCT]	[INVOICEITEMS]	[customer, productgroup]	[customer, productgroup]	2025-10-15T03:13:02.976000
11	68ef112acbdce2fa954f3f7e	CUSTOMER_x_PRODUCTGROUP_Time_Since_Latest_Time...	FLOAT	DRAFT	False	[GROCERYINVOICE, INVOICEITEMS, GROCERYPRODUCT]	[INVOICEITEMS]	[customer, productgroup]	[customer, productgroup]	2025-10-15T03:13:02.464000
12	68ef110cd0ec86dc5121f2a2	CUSTOMER_Age_band	VARCHAR	DRAFT	False	[GROCERYCUSTOMER]	[GROCERYCUSTOMER]	[customer]	[customer]	2025-10-15T03:12:26.082000
13	68ef110cd0ec86dc5121f298	CUSTOMER_Age	INT	DRAFT	False	[GROCERYCUSTOMER]	[GROCERYCUSTOMER]	[customer]	[customer]	2025-10-15T03:12:19.677000

Get features from catalog¶

In [3]:

customer_age_band = catalog.get_feature("CUSTOMER_Age_band")
customer_latest_invoice_amount = catalog.get_feature("CUSTOMER_Latest_invoice_Amount")
customer_count_of_invoice_14d = catalog.get_feature("CUSTOMER_Count_of_invoice_14d")
customer_avg_of_invoice_amount_14d = catalog.get_feature("CUSTOMER_Avg_of_invoice_Amount_14d")
customer_std_of_invoice_amount_14d = catalog.get_feature("CUSTOMER_Std_of_invoice_Amount_14d")
customer_latest_invoice_amount_Z_score_to_invoice_amount_28d = catalog.get_feature(
    "CUSTOMER_Latest_invoice_Amount_Z_Score_to_invoice_Amount_28d"
)
customer_vs_overall_item_totalcost_across_product_productgroups_26w = catalog.get_feature(
    "CUSTOMER_vs_OVERALL_item_TotalCost_across_product_ProductGroups_26w"
)
customer_x_productgroup_sum_of_item_totalcost_14d = \
catalog.get_feature("CUSTOMER_x_PRODUCTGROUP_Sum_of_item_TotalCost_14d")
customer_x_productgroup_time_since_latest_timestamp = \
catalog.get_feature("CUSTOMER_x_PRODUCTGROUP_Time_Since_Latest_Timestamp")

customer_age_band = catalog.get_feature("CUSTOMER_Age_band") customer_latest_invoice_amount = catalog.get_feature("CUSTOMER_Latest_invoice_Amount") customer_count_of_invoice_14d = catalog.get_feature("CUSTOMER_Count_of_invoice_14d") customer_avg_of_invoice_amount_14d = catalog.get_feature("CUSTOMER_Avg_of_invoice_Amount_14d") customer_std_of_invoice_amount_14d = catalog.get_feature("CUSTOMER_Std_of_invoice_Amount_14d") customer_latest_invoice_amount_Z_score_to_invoice_amount_28d = catalog.get_feature( "CUSTOMER_Latest_invoice_Amount_Z_Score_to_invoice_Amount_28d" ) customer_vs_overall_item_totalcost_across_product_productgroups_26w = catalog.get_feature( "CUSTOMER_vs_OVERALL_item_TotalCost_across_product_ProductGroups_26w" ) customer_x_productgroup_sum_of_item_totalcost_14d = \ catalog.get_feature("CUSTOMER_x_PRODUCTGROUP_Sum_of_item_TotalCost_14d") customer_x_productgroup_time_since_latest_timestamp = \ catalog.get_feature("CUSTOMER_x_PRODUCTGROUP_Time_Since_Latest_Timestamp")

Create feature list¶

In [4]:

simple_feature_list = fb.FeatureList(
    [
        customer_age_band,
        customer_latest_invoice_amount,
        customer_count_of_invoice_14d,
        customer_avg_of_invoice_amount_14d,
        customer_std_of_invoice_amount_14d,
        customer_latest_invoice_amount_Z_score_to_invoice_amount_28d,
        customer_vs_overall_item_totalcost_across_product_productgroups_26w,
        customer_x_productgroup_sum_of_item_totalcost_14d,
        customer_x_productgroup_time_since_latest_timestamp,
    ],
    name="Customer x ProductGroup Simple FeatureList",
)

simple_feature_list = fb.FeatureList( [ customer_age_band, customer_latest_invoice_amount, customer_count_of_invoice_14d, customer_avg_of_invoice_amount_14d, customer_std_of_invoice_amount_14d, customer_latest_invoice_amount_Z_score_to_invoice_amount_28d, customer_vs_overall_item_totalcost_across_product_productgroups_26w, customer_x_productgroup_sum_of_item_totalcost_14d, customer_x_productgroup_time_since_latest_timestamp, ], name="Customer x ProductGroup Simple FeatureList", )

Preview feature list¶

In [5]:

# Check the primary entity of the feature list
simple_feature_list.primary_entity

# Check the primary entity of the feature list simple_feature_list.primary_entity

Out[5]:

[<featurebyte.api.entity.Entity at 0x31444eac0>
 {
   'name': 'customer',
   'created_at': '2025-10-15T03:06:58.482000',
   'updated_at': '2025-10-15T03:07:01.153000',
   'description': None,
   'serving_names': [
     'GROCERYCUSTOMERGUID'
   ],
   'catalog_name': 'Grocery Dataset SDK Tutorial'
 },
 <featurebyte.api.entity.Entity at 0x31442ba10>
 {
   'name': 'productgroup',
   'created_at': '2025-10-15T03:06:59.192000',
   'updated_at': '2025-10-15T03:07:02.278000',
   'description': None,
   'serving_names': [
     'PRODUCTGROUP'
   ],
   'catalog_name': 'Grocery Dataset SDK Tutorial'
 }]

In [6]:

# Get observation table: 'Preview Table with 10 items'
preview_table = catalog.get_observation_table("Preview Table with 10 items")

# Get observation table: 'Preview Table with 10 items' preview_table = catalog.get_observation_table("Preview Table with 10 items")

In [7]:

# Preview simple_feature_list
simple_feature_list.preview(preview_table)

# Preview simple_feature_list simple_feature_list.preview(preview_table)

Out[7]:

	POINT_IN_TIME	GROCERYINVOICEITEMGUID	CUSTOMER_Age_band	CUSTOMER_Latest_invoice_Amount	CUSTOMER_Count_of_invoice_14d	CUSTOMER_Avg_of_invoice_Amount_14d	CUSTOMER_Std_of_invoice_Amount_14d	CUSTOMER_Latest_invoice_Amount_Z_Score_to_invoice_Amount_28d	CUSTOMER_vs_OVERALL_item_TotalCost_across_product_ProductGroups_26w	CUSTOMER_x_PRODUCTGROUP_Sum_of_item_TotalCost_14d	CUSTOMER_x_PRODUCTGROUP_Time_Since_Latest_Timestamp
0	2023-04-07 13:41:35	f017e72e-1645-4fbe-988e-a9c09920c506	20-24	2.29	6	14.563333	9.129048	-1.230802	0.806031	4.57	261.460556
1	2023-01-08 15:40:02	879de04d-36ef-49a3-b1f7-a96495100dbe	40-44	1.47	4	7.605000	5.901197	-1.031903	0.629724	NaN	2974.097500
2	2022-07-14 18:12:49	a3245668-aeba-4259-87e1-1b99a1e7391c	45-49	3.28	1	3.280000	0.000000	NaN	0.828964	NaN	1400.391944
3	2022-12-01 13:28:57	600a7549-9f3e-42f9-8408-e3996d6c4750	50-54	8.00	1	8.000000	0.000000	-1.184455	0.733438	NaN	385.071944
4	2022-10-03 12:02:23	f25a7864-4e0d-43bb-8191-0ffdf56b5a21	60-64	16.21	3	15.686667	10.151717	-0.422419	0.751749	NaN	2017.952500
5	2022-12-12 10:27:30	9526bbd7-3b85-4bd5-99d7-2eecda85ada2	50-54	29.00	2	19.200000	9.800000	-0.342691	0.750365	5.99	73.632222
6	2022-09-12 16:29:49	f7de9fec-9e01-4478-8b2e-5a17427a53c1	30-34	63.04	7	20.120000	22.723340	1.963783	0.631107	6.79	217.573333
7	2023-03-18 09:43:40	7ec0da36-b85f-47cf-873e-461b5c2b1cbf	30-34	26.01	8	21.716250	18.080614	0.413984	0.816261	NaN	1458.053889
8	2023-05-14 15:41:46	e904b0bc-b342-4491-a7d9-216489b6ac01	50-54	67.87	1	67.870000	0.000000	1.000000	0.649150	NaN	768.540278
9	2022-10-30 09:08:11	5ee681b9-583c-4968-88bb-993704a6c54e	85-89	51.02	2	87.385000	36.365000	-1.000000	0.573548	7.47	113.858889

Save feature list¶

In [8]:

# Save feature list
simple_feature_list.save()
# Add description
simple_feature_list.update_description("Simple feature list for the customer x productgroup engagement")

# Save feature list simple_feature_list.save() # Add description simple_feature_list.update_description("Simple feature list for the customer x productgroup engagement")

Done! |████████████████████████████████████████| 100% in 3.1s (0.32%/s)         
Done! |████████████████████████████████████████| 100% in 6.1s (0.17%/s)         
Loading Feature(s) |████████████████████████████████████████| 9/9 [100%] in 0.4s
Done! |████████████████████████████████████████| 100% in 6.1s (0.17%/s)         
Done! |████████████████████████████████████████| 100% in 6.1s (0.17%/s)         
Loading Feature(s) |████████████████████████████████████████| 9/9 [100%] in 0.4s

Concepts in this tutorial¶

• More on feature lists

SDK Reference for¶

• Feature List
• FeatureList.save()