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jnywongjnywong
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Add fixtures for output data by hub and by component (#17)
1 parent 9d03611 commit eec4108

3 files changed

Lines changed: 558 additions & 10 deletions

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‎tests/generate_data.py‎

Lines changed: 34 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -50,29 +50,53 @@ def generate_test_data(
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json.dump(data, f, indent=4)
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def generate_test_output():
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def generate_test_output_hub():
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"""
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Generate test output based on the test usage and test cost data.
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Generate test output grouped by hub based on the test usage and test cost data.
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"""
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with open("test_data_usage.json") as f:
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data_usage = json.load(f)
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with open("test_data_cost.json") as f:
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data_cost = json.load(f)
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df_usage = pd.DataFrame(data_usage)
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df_cost = pd.DataFrame(data_cost)
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total_usage = df_usage.groupby(["date", "component", "hub"])["value"].transform(
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"sum"
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)
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df_usage["cost_factor"] = df_usage["value"] / total_usage
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merged = df_usage.merge(df_cost, on=["date", "component", "hub"], how="left")
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merged["cost"] = merged["cost_factor"] * merged["value_y"]
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df_usage["cost"] = merged["cost"]
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df_usage.to_json("test_output_hub.json", orient="records", indent=4)
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df_usage.to_json("test_output.json", orient="records", indent=4)
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def generate_test_output_component():
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"""
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Generate test output grouped by component based on the test usage and test cost data.
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"""
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with open("test_data_usage.json") as f:
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data_usage = json.load(f)
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with open("test_data_cost.json") as f:
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data_cost = json.load(f)
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df_usage = pd.DataFrame(data_usage)
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df_usage = df_usage.groupby(["date", "component", "user"], as_index=False).sum()
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df_cost = pd.DataFrame(data_cost)
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df_cost = (
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df_cost.groupby(["date", "component"], as_index=False)
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.sum()
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.drop(columns=["hub"])
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)
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total_usage = df_usage.groupby(["date", "component"], as_index=False)[
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"value"
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].transform("sum")
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df_usage["cost_factor"] = (
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df_usage.groupby(["date", "component", "user"], as_index=False)[
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"value"
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].transform("sum")
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/ total_usage
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)
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merged = df_usage.merge(df_cost, on=["date", "component"], how="left")
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merged["cost"] = merged["cost_factor"] * merged["value_y"]
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df_usage["cost"] = merged["cost"]
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df_usage = df_usage.drop(columns=["hub"])
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df_usage.to_json("test_output_component.json", orient="records", indent=4)

‎tests/test_output_component.json‎

Lines changed: 162 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,162 @@
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[
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{
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"date":"2025-01-01",
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"component":"compute",
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"user":"user_0",
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"value":8.0,
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"cost_factor":0.2,
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"cost":156.8
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},
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{
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"date":"2025-01-01",
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"component":"compute",
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"user":"user_1",
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"value":9.0,
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"cost_factor":0.225,
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"cost":176.4
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},
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{
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"date":"2025-01-01",
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"component":"compute",
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"user":"user_2",
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"value":12.0,
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"cost_factor":0.3,
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"cost":235.2
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},
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{
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"date":"2025-01-01",
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"component":"compute",
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"user":"user_3",
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"value":8.0,
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"cost_factor":0.2,
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"cost":156.8
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},
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{
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"date":"2025-01-01",
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"component":"compute",
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"user":"user_4",
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"value":3.0,
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"cost_factor":0.075,
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"cost":58.8
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},
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{
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"date":"2025-01-01",
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"component":"home-directory",
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"user":"user_0",
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"value":9.0,
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"cost_factor":0.18,
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"cost":16.92
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},
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{
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"date":"2025-01-01",
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"component":"home-directory",
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"user":"user_1",
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"value":9.0,
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"cost_factor":0.18,
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"cost":16.92
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},
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{
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"date":"2025-01-01",
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"component":"home-directory",
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"user":"user_2",
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"value":18.0,
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"cost_factor":0.36,
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"cost":33.84
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},
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{
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"date":"2025-01-01",
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"component":"home-directory",
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"user":"user_3",
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"value":7.0,
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"cost_factor":0.14,
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"cost":13.16
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},
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{
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"date":"2025-01-01",
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"component":"home-directory",
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"user":"user_4",
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"value":7.0,
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"cost_factor":0.14,
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"cost":13.16
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},
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{
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"date":"2025-01-02",
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"component":"compute",
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"user":"user_0",
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"value":16.0,
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"cost_factor":0.4,
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"cost":431.6
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},
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{
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"date":"2025-01-02",
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"component":"compute",
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"user":"user_1",
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"value":4.0,
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"cost_factor":0.1,
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"cost":107.9
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},
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{
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"date":"2025-01-02",
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"component":"compute",
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"user":"user_2",
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"value":11.0,
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"cost_factor":0.275,
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"cost":296.725
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},
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{
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"date":"2025-01-02",
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"component":"compute",
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"user":"user_3",
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"value":5.0,
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"cost_factor":0.125,
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"cost":134.875
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},
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{
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"date":"2025-01-02",
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"component":"compute",
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"user":"user_4",
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"value":4.0,
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"cost_factor":0.1,
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"cost":107.9
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},
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{
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"date":"2025-01-02",
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"component":"home-directory",
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"user":"user_0",
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"value":16.0,
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"cost_factor":0.3333333333,
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"cost":193.6666666667
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},
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{
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"date":"2025-01-02",
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"component":"home-directory",
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"user":"user_1",
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"value":12.0,
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"cost_factor":0.25,
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"cost":145.25
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},
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{
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"date":"2025-01-02",
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"component":"home-directory",
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"user":"user_2",
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"value":3.0,
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"cost_factor":0.0625,
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"cost":36.3125
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},
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{
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"date":"2025-01-02",
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"component":"home-directory",
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"user":"user_3",
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"value":11.0,
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"cost_factor":0.2291666667,
152+
"cost":133.1458333333
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},
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{
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"date":"2025-01-02",
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"component":"home-directory",
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"user":"user_4",
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"value":6.0,
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"cost_factor":0.125,
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"cost":72.625
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}
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]

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