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run_flow_local.py
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run_flow_local.py
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import sys
import json
import os
from pathlib import Path
from prefect.utilities.debug import raise_on_exception
from flows.data_pipeline import flow
# Parameters for test datasets
parameter_sets = [
# 0: For testing tiling data
dict(
model_id="geo-test-data",
run_id="test-run-1",
data_paths=[f"file://{Path(os.getcwd()).parent}/tests/data/geo-test-data.parquet"],
selected_output_tasks=[
"compute_global_timeseries",
"compute_regional_stats",
"compute_regional_timeseries",
"compute_regional_aggregation",
"compute_tiles",
],
),
# 1: Maxhop
dict(
model_id="maxhop-v0.2",
run_id="4675d89d-904c-466f-a588-354c047ecf72",
data_paths=[
"https://jataware-world-modelers.s3.amazonaws.com/dmc_results/4675d89d-904c-466f-a588-354c047ecf72/4675d89d-904c-466f-a588-354c047ecf72_maxhop-v0.2.parquet.gzip"
],
),
# 2: Test Qualifiers
dict(
is_indicator=True,
qualifier_map={
"fatalities": [
"event_type",
"sub_event_type",
"source_scale",
"country_non_primary",
"admin1_non_primary",
]
},
model_id="_qualifier-test",
run_id="indicator",
data_paths=["s3://test/_qualifier-test.bin"],
),
# 3: Test combining multiple parquet files with different columns
{
"data_paths": [
"https://jataware-world-modelers.s3.amazonaws.com/dmc_results_dev/9d7db850-0abe-486f-8979-b1e9ad2ef6ad/9d7db850-0abe-486f-8979-b1e9ad2ef6ad_7b1ceeb4-95a3-4bfd-b7cd-e2a89391742f.1.parquet.gzip",
"https://jataware-world-modelers.s3.amazonaws.com/dmc_results_dev/9d7db850-0abe-486f-8979-b1e9ad2ef6ad/9d7db850-0abe-486f-8979-b1e9ad2ef6ad_7b1ceeb4-95a3-4bfd-b7cd-e2a89391742f.2.parquet.gzip",
],
"is_indicator": False,
"model_id": "7b1ceeb4-95a3-4bfd-b7cd-e2a89391742f",
"qualifier_map": {
"yield_loss_risk": ["longitude", "latitude", "time"],
"harvested_area_at_risk": ["NameCrop", "NameIrrigation", "NameCategory"],
},
"qualifier_thresholds": {
"max_count": 10000,
"regional_timeseries_count": 100,
"regional_timeseries_max_level": 1,
},
"run_id": "9d7db850-0abe-486f-8979-b1e9ad2ef6ad",
},
# 4: Test combining multiple parquet files with different columns
{
"data_paths": [
"https://jataware-world-modelers.s3.amazonaws.com/dmc_results_dev/f2818712-09f7-49c6-b920-ea21c764d1c7/f2818712-09f7-49c6-b920-ea21c764d1c7_84fd427f-3a7d-473f-aa25-0c0a150ca216.3.parquet.gzip",
"https://jataware-world-modelers.s3.amazonaws.com/dmc_results_dev/f2818712-09f7-49c6-b920-ea21c764d1c7/f2818712-09f7-49c6-b920-ea21c764d1c7_84fd427f-3a7d-473f-aa25-0c0a150ca216.2.parquet.gzip",
"https://jataware-world-modelers.s3.amazonaws.com/dmc_results_dev/f2818712-09f7-49c6-b920-ea21c764d1c7/f2818712-09f7-49c6-b920-ea21c764d1c7_84fd427f-3a7d-473f-aa25-0c0a150ca216.1.parquet.gzip",
],
"is_indicator": False,
"model_id": "84fd427f-3a7d-473f-aa25-0c0a150ca216",
"qualifier_map": {
"export [kcal]": [],
"import [kcal]": [],
"supply [kcal]": [],
"Production [mt]": ["Year"],
"Consumption [mt]": ["Year"],
"Ending_stock [mt]": ["Year"],
"production [kcal]": [],
"World market_price [US$/mt]": ["Year"],
"export per capita [kcal pc]": [],
"import per capita [kcal pc]": [],
"supply per capita [kcal pc]": [],
"production change per capita [kcal pc]": [],
},
"qualifier_thresholds": {
"max_count": 10000,
"regional_timeseries_count": 100,
"regional_timeseries_max_level": 1,
},
"run_id": "f2818712-09f7-49c6-b920-ea21c764d1c7",
},
# 5: Invalid timestamps
dict( # Invalid timestamps
model_id="087c3e5a-cd3d-4ebc-bc5e-e13a4654005c",
run_id="9e1100d5-06e8-48b6-baea-56b3b820f82d",
data_paths=[
"https://jataware-world-modelers.s3.amazonaws.com/dmc_results_dev/9e1100d5-06e8-48b6-baea-56b3b820f82d/9e1100d5-06e8-48b6-baea-56b3b820f82d_087c3e5a-cd3d-4ebc-bc5e-e13a4654005c.1.parquet.gzip"
],
),
# 6: Testing weight column small
dict(
qualifier_map={"sam_rate": ["qual_1"], "gam_rate": ["qual_1"]},
weight_column="weights",
model_id="_weight-test-small",
run_id="test-run-1",
data_paths=["s3://test/weight-col.bin"],
),
# 7: Testing weight column 2
dict( # Weights
is_indicator=True,
qualifier_map={
"Surveyed Area": ["Locust Presence", "Control Pesticide Name"],
"Control Area Treated": ["Control Pesticide Name"],
"Estimated Control Kill (Mortality Rate)": ["Control Pesticide Name"],
},
weight_column="Locust Breeding",
model_id="_weight-test-1",
run_id="indicator",
data_paths=[
"https://jataware-world-modelers.s3.amazonaws.com/dev/indicators/39f7959d-a63e-4db4-a54d-24c66184cf82/39f7959d-a63e-4db4-a54d-24c66184cf82.parquet.gzip"
],
),
# 8: Testing weight column Big
dict( # Real weights
selected_output_tasks=[
"compute_global_timeseries",
"compute_regional_stats",
"compute_regional_timeseries",
"compute_regional_aggregation",
],
is_indicator=False,
qualifier_map={
"HWAM_AVE": ["year", "mgn", "season"],
"production": ["year", "mgn", "season"],
"crop_failure_area": ["year", "mgn", "season"],
"TOTAL_NITROGEN_APPLIED": ["year", "mgn", "season"],
},
weight_column="HAREA_TOT",
model_id="2af38a88-aa34-4f4a-94f6-a3e1e6630833",
run_id="test-run-1",
data_paths=[
"https://jataware-world-modelers.s3.amazonaws.com/dmc_results_dev/eba6ca6b-8c7f-44d1-b008-4349491cabf5/eba6ca6b-8c7f-44d1-b008-4349491cabf5_2af38a88-aa34-4f4a-94f6-a3e1e6630833.1.parquet.gzip"
],
),
# 9: DC Test 30K records
dict(
is_indicator=True,
model_id="3a013cd3-6064-4888-9cc6-0e9d637c690e",
run_id="indicator",
data_paths=[
"https://jataware-world-modelers.s3.amazonaws.com/dev/indicators/3a013cd3-6064-4888-9cc6-0e9d637c690e/3a013cd3-6064-4888-9cc6-0e9d637c690e.parquet.gzip",
"https://jataware-world-modelers.s3.amazonaws.com/dev/indicators/3a013cd3-6064-4888-9cc6-0e9d637c690e/3a013cd3-6064-4888-9cc6-0e9d637c690e_1.parquet.gzip",
"https://jataware-world-modelers.s3.amazonaws.com/dev/indicators/3a013cd3-6064-4888-9cc6-0e9d637c690e/3a013cd3-6064-4888-9cc6-0e9d637c690e_2.parquet.gzip",
],
fill_timestamp=0,
qualifier_map={
"data_id": ["event_date"],
"fatalities": ["event_date", "event_type", "sub_event_type", "actor1"],
},
),
# 10:
dict(
is_indicator=False,
model_id="2281e058-d521-4180-8216-54832700cedd",
run_id="22045d57-aa6a-4df6-a11d-793225878dab",
data_paths=[
"https://jataware-world-modelers.s3.amazonaws.com/dmc_results_dev/22045d57-aa6a-4df6-a11d-793225878dab/22045d57-aa6a-4df6-a11d-793225878dab_2281e058-d521-4180-8216-54832700cedd.1.parquet.gzip"
],
fill_timestamp=0,
qualifier_map={
"max": ["Date", "camp"],
"min": ["Date", "camp"],
"data": ["Date", "camp"],
"mean": ["Date", "camp"],
"error": ["Date", "camp"],
"median": ["Date", "camp"],
},
),
# 11: Related to bug logged in https://gitlab.uncharted.software/WM/slow-tortoise/-/issues/41
json.loads(
"""
{
"data_paths": ["https://jataware-world-modelers.s3.amazonaws.com/transition/datasets/76b6ec52-183e-49db-9b8f-01c0aaf0255c/76b6ec52-183e-49db-9b8f-01c0aaf0255c.parquet.gzip", "https://jataware-world-modelers.s3.amazonaws.com/transition/datasets/76b6ec52-183e-49db-9b8f-01c0aaf0255c/76b6ec52-183e-49db-9b8f-01c0aaf0255c_1.parquet.gzip"],
"fill_timestamp": 0,
"is_indicator": true,
"model_id": "76b6ec52-183e-49db-9b8f-01c0aaf0255c",
"raw_count_threshold": 10000,
"run_id": "indicator",
"selected_output_tasks": null,
"weight_column": ""
}
"""
),
# 12 Dataset with no available region columns (more details: https://gitlab.uncharted.software/WM/slow-tortoise/-/issues/45#note_404940)
json.loads(
"""
{
"data_paths": ["https://jataware-world-modelers.s3.amazonaws.com/transition/datasets/75a8ad46-a535-4557-9137-0033d8bd2531/75a8ad46-a535-4557-9137-0033d8bd2531.parquet.gzip"],
"fill_timestamp": 0,
"is_indicator": true,
"model_id": "test_indicator",
"raw_count_threshold": 10000,
"run_id": "indicator",
"selected_output_tasks": null,
"weight_column": ""
}
"""
),
]
if __name__ == "__main__":
with raise_on_exception():
parameters_set_index = 0 if len(sys.argv) < 2 else int(sys.argv[1])
flow.run(parameters=parameter_sets[parameters_set_index])