updating the tools metrics script

error_by_markets.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:20ad9ae5cdd9e6c6ad36739926c79af4f6f16a6452e343b8d6db075daa414759
-size 10826
+oid sha256:1ab34475acc2a6d3cd664f68b80915dd7cb941c0d909a3f872b2bab087e1d6b7
+size 11148

errors_by_mech.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bc9b9f7263e4e0867611b1aa6e2dfe87bb4c4e112065d18f9600732799f70825
-size 6093
+oid sha256:f6a002ba1ea11c135eb14f8b046be29c01b266a3d269df8f5a1b26c818c8be2a
+size 6096

scripts/tools_metrics.py

@@ -3,12 +3,9 @@ from typing import List
 from utils import TMP_DIR, INC_TOOLS, ROOT_DIR
 
 
-def get_error_data_by_market(
-    tools_df: pd.DataFrame, inc_tools: List[str]
-) -> pd.DataFrame:
+def get_error_data_by_market(tools_df: pd.DataFrame) -> pd.DataFrame:
     """Gets the error data for the given tools and calculates the error percentage."""
-    tools_inc = tools_df[tools_df["tool"].isin(inc_tools)]
-    mech_tool_errors = tools_inc[tools_inc["error"] != -1]
+    mech_tool_errors = tools_df[tools_df["error"] != -1]
     error = (
         mech_tool_errors.groupby(
             ["tool", "request_month_year_week", "market_creator", "error"], sort=False
@@ -23,12 +20,9 @@ def get_error_data_by_market(
     return error
 
 
-def get_tool_winning_rate_by_market(
-    tools_df: pd.DataFrame, inc_tools: List[str]
-) -> pd.DataFrame:
+def get_tool_winning_rate_by_market(tools_df: pd.DataFrame) -> pd.DataFrame:
     """Gets the tool winning rate data for the given tools by market and calculates the winning percentage."""
-    tools_inc = tools_df[tools_df["tool"].isin(inc_tools)]
-    tools_non_error = tools_inc[tools_inc["error"] == 0]
+    tools_non_error = tools_df[tools_df["error"] == 0]
     tools_non_error.loc[:, "currentAnswer"] = tools_non_error["currentAnswer"].replace(
         {"no": "No", "yes": "Yes"}
     )
@@ -58,6 +52,8 @@ def get_tool_winning_rate_by_market(
 
 
 def prepare_tools(tools: pd.DataFrame) -> pd.DataFrame:
+    # remove non relevant tools
+    tools_df = tools[tools["tool"].isin(INC_TOOLS)]
     tools["request_time"] = pd.to_datetime(tools["request_time"], utc=True)
     tools = tools.sort_values(by="request_time", ascending=True)
     tools["request_date"] = tools["request_time"].dt.date
@@ -84,13 +80,11 @@ def get_error_category(error_value: int):
     return "request_error"
 
 
-def get_errors_by_mech_address(
-    tools_df: pd.DataFrame, inc_tools: List[str]
-) -> pd.DataFrame:
+def get_errors_by_mech_address(tools_df: pd.DataFrame) -> pd.DataFrame:
     """Gets the tool errors distribution by mech address in a weekly fashion"""
-    tools_inc = tools_df[tools_df["tool"].isin(inc_tools)]
+
     weekly_errors = (
-        tools_inc.groupby(
+        tools_df.groupby(
             ["request_month_year_week", "mech_address", "error"], sort=False
         )
         .size()
@@ -100,7 +94,7 @@ def get_errors_by_mech_address(
         lambda x: get_error_category(x)
     )
     total_requests_errors = (
-        tools_inc.groupby(["request_month_year_week", "mech_address"], sort=False)
+        tools_df.groupby(["request_month_year_week", "mech_address"], sort=False)
         .size()
         .reset_index(name="total_requests")
     )
@@ -122,19 +116,9 @@ def compute_tools_based_datasets():
         print(f"Error reading tools parquet file {e}")
         return None
 
-    # daily mech requests
-    daily_mech_req_per_tool = (
-        tools_df.groupby(["request_date", "tool", "market_creator"])["request_id"]
-        .count()
-        .reset_index(name="total_mech_requests")
-    )
-    daily_mech_req_per_tool.to_parquet(
-        ROOT_DIR / "daily_mech_requests.parquet", index=False
-    )
     # mech tool errors by markets
-    tool_error_by_markets = get_error_data_by_market(
-        tools_df=tools_df, inc_tools=INC_TOOLS
-    )
+    print("Computing mech tool errors by markets")
+    tool_error_by_markets = get_error_data_by_market(tools_df=tools_df)
     tool_error_by_markets.to_parquet(ROOT_DIR / "error_by_markets.parquet", index=False)
     try:
         tools_df = pd.read_parquet(TMP_DIR / "tools.parquet")
@@ -142,7 +126,7 @@ def compute_tools_based_datasets():
     except Exception as e:
         print(f"Error reading tools parquet file {e}")
         return None
-    winning_df = get_tool_winning_rate_by_market(tools_df, inc_tools=INC_TOOLS)
+    winning_df = get_tool_winning_rate_by_market(tools_df)
     winning_df.to_parquet(ROOT_DIR / "winning_df.parquet", index=False)
 
     # all errors by mech address
@@ -152,9 +136,31 @@ def compute_tools_based_datasets():
     except Exception as e:
         print(f"Error reading tools parquet file {e}")
         return None
-    errors_by_mech = get_errors_by_mech_address(tools_df=tools_df, inc_tools=INC_TOOLS)
+    errors_by_mech = get_errors_by_mech_address(tools_df=tools_df)
     errors_by_mech.to_parquet(ROOT_DIR / "errors_by_mech.parquet", index=False)
 
+    try:
+        tools_df = pd.read_parquet(TMP_DIR / "tools.parquet")
+        tools_df = prepare_tools(tools_df)
+    except Exception as e:
+        print(f"Error reading tools parquet file {e}")
+        return None
+    generate_daily_mech_requests_per_tool(tools_df=tools_df)
+
+
+def generate_daily_mech_requests_per_tool(tools_df: pd.DataFrame) -> pd.DataFrame:
+    """Generates the daily mech requests per tool."""
+
+    # daily mech requests in
+    daily_mech_req_per_tool = (
+        tools_df.groupby(["request_date", "tool", "market_creator"])["request_id"]
+        .count()
+        .reset_index(name="total_mech_requests")
+    )
+    daily_mech_req_per_tool.to_parquet(
+        ROOT_DIR / "daily_mech_requests.parquet", index=False
+    )
+
 
 if __name__ == "__main__":
     compute_tools_based_datasets()