better refresh data
Browse files- app.py +119 -24
- data/all_trades_profitability.csv +2 -2
- data/delivers.csv +2 -2
- data/fpmmTrades.csv +2 -2
- data/fpmms.csv +2 -2
- data/requests.csv +2 -2
- data/summary_profitability.csv +2 -2
- data/t_map.pkl +2 -2
- data/tools.csv +2 -2
- test.py +92 -0
app.py
CHANGED
@@ -30,10 +30,82 @@ from tabs.error import (
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from tabs.about import about_olas_predict
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def refresh_data():
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try:
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global tools_df, trades_df, error_df, error_overall_df, winning_rate_df, winning_rate_overall_df, trades_count_df, trades_winning_rate_df
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logging.info("Refreshing data...")
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tools_df = pd.read_csv("./data/tools.csv", low_memory=False)
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trades_df = pd.read_csv("./data/all_trades_profitability.csv")
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trades_df = prepare_trades(trades_df)
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@@ -43,6 +115,7 @@ def refresh_data():
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winning_rate_overall_df = get_overall_winning_rate(wins_df=winning_rate_df)
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trades_count_df = get_overall_trades(trades_df=trades_df)
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trades_winning_rate_df = get_overall_winning_trades(trades_df=trades_df)
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logging.info("Data refreshed.")
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except Exception as e:
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logging.error("Failed to refresh data: %s", e)
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@@ -53,6 +126,7 @@ def pull_refresh_data():
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try:
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result = subprocess.run(["python", "./scripts/pull_data.py"], check=True)
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logging.info("Script executed successfully: %s", result)
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except subprocess.CalledProcessError as e:
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logging.error("Failed to run script: %s", e)
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return # Stop execution if the script fails
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@@ -113,13 +187,13 @@ with demo:
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with gr.Row():
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gr.Markdown("# Plot of number of trades by week")
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with gr.Row():
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-
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trades_df=trades_count_df
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)
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with gr.Row():
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gr.Markdown("# Plot of winning trades by week")
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with gr.Row():
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-
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trades_df=trades_winning_rate_df
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)
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with gr.Row():
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@@ -162,17 +236,15 @@ with demo:
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with gr.Row():
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with gr.Column():
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refresh_button = gr.Button("Refresh Data")
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-
with gr.Column():
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latest_data_label = gr.Label(
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value=f"Last data point: {trades_df['creation_timestamp'].max()}"
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)
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-
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-
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-
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-
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-
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-
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with gr.TabItem("🚀 Tool Winning Dashboard"):
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with gr.Row():
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@@ -219,7 +291,7 @@ with demo:
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)
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with gr.Row():
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-
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wins_df=winning_rate_df,
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tool=INC_TOOLS[0]
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)
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@@ -233,19 +305,30 @@ with demo:
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sel_tool.change(
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update_tool_winnings_by_tool_plot,
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inputs=sel_tool,
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-
outputs=
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)
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with gr.Row():
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sel_tool
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with gr.Row():
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-
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with gr.TabItem("🏥 Tool Error Dashboard"):
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with gr.Row():
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gr.Markdown("# Plot showing overall error")
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with gr.Row():
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-
plot_error_data(
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error_all_df=error_overall_df
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)
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with gr.Row():
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@@ -258,7 +341,7 @@ with demo:
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)
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with gr.Row():
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-
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error_df=error_df,
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tool=INC_TOOLS[0]
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)
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@@ -273,12 +356,12 @@ with demo:
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sel_tool.change(
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update_tool_error_plot,
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inputs=sel_tool,
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outputs=
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)
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with gr.Row():
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sel_tool
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with gr.Row():
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-
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with gr.Row():
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gr.Markdown("# Plot showing error by week")
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@@ -294,7 +377,7 @@ with demo:
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)
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with gr.Row():
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-
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error_df=error_df,
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week=choices[-1]
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)
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@@ -305,17 +388,29 @@ with demo:
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week=selected_week
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)
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sel_tool.change(update_tool_error_plot, inputs=sel_tool, outputs=
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sel_week.change(update_week_error_plot, inputs=sel_week, outputs=
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with gr.Row():
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sel_tool
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with gr.Row():
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-
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with gr.Row():
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sel_week
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with gr.Row():
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-
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with gr.TabItem("ℹ️ About"):
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with gr.Accordion("About Olas Predict"):
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from tabs.about import about_olas_predict
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+
def update_trades_plots():
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global tools_df, trades_df, error_df, error_overall_df, winning_rate_df, winning_rate_overall_df, trades_count_df, trades_winning_rate_df
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+
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refresh_data()
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+
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updated_trades_by_week_plot = plot_trades_by_week(
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trades_df=trades_count_df
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)
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updated_winning_trades_by_week_plot = plot_winning_trades_by_week(
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trades_df=trades_winning_rate_df
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)
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updated_trade_details_plot = plot_trade_details(
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trade_detail="mech calls",
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trades_df=trades_df
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)
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return (
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updated_trades_by_week_plot,
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updated_winning_trades_by_week_plot,
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updated_trade_details_plot
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)
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+
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def update_tool_winnings_plots():
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global tools_df, trades_df, error_df, error_overall_df, winning_rate_df, winning_rate_overall_df, trades_count_df, trades_winning_rate_df
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+
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refresh_data()
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updated_winning_plot = plot_tool_winnings_overall(
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wins_df=winning_rate_overall_df,
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winning_selector="win_perc"
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)
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updated_tool_winnings_by_tool_plot = plot_tool_winnings_by_tool(
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wins_df=winning_rate_df,
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tool=INC_TOOLS[0]
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)
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return (
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updated_winning_plot,
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updated_tool_winnings_by_tool_plot
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)
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+
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def update_error_plots():
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global tools_df, trades_df, error_df, error_overall_df, winning_rate_df, winning_rate_overall_df, trades_count_df, trades_winning_rate_df
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+
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refresh_data()
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+
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updated_error_overall_plot = plot_error_data(
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error_all_df=error_overall_df
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)
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updated_tool_error_plot = plot_tool_error_data(
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error_df=error_df,
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tool=INC_TOOLS[0]
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)
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+
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updated_week_error_plot = plot_week_error_data(
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error_df=error_df,
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week=choices[-1]
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)
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+
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return (
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updated_error_overall_plot,
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updated_tool_error_plot,
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updated_week_error_plot
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)
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+
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def refresh_data():
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try:
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global tools_df, trades_df, error_df, error_overall_df, winning_rate_df, winning_rate_overall_df, trades_count_df, trades_winning_rate_df
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+
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logging.info("Refreshing data...")
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+
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tools_df = pd.read_csv("./data/tools.csv", low_memory=False)
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trades_df = pd.read_csv("./data/all_trades_profitability.csv")
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trades_df = prepare_trades(trades_df)
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winning_rate_overall_df = get_overall_winning_rate(wins_df=winning_rate_df)
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trades_count_df = get_overall_trades(trades_df=trades_df)
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trades_winning_rate_df = get_overall_winning_trades(trades_df=trades_df)
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+
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logging.info("Data refreshed.")
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except Exception as e:
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logging.error("Failed to refresh data: %s", e)
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try:
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result = subprocess.run(["python", "./scripts/pull_data.py"], check=True)
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logging.info("Script executed successfully: %s", result)
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+
refresh_data()
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except subprocess.CalledProcessError as e:
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logging.error("Failed to run script: %s", e)
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return # Stop execution if the script fails
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with gr.Row():
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gr.Markdown("# Plot of number of trades by week")
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with gr.Row():
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trades_by_week_plot = plot_trades_by_week(
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trades_df=trades_count_df
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)
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with gr.Row():
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gr.Markdown("# Plot of winning trades by week")
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with gr.Row():
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+
winning_trades_by_week_plot = plot_winning_trades_by_week(
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trades_df=trades_winning_rate_df
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)
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with gr.Row():
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with gr.Row():
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with gr.Column():
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refresh_button = gr.Button("Refresh Data")
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refresh_button.click(
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update_trades_plots,
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+
outputs=[
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trades_by_week_plot,
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winning_trades_by_week_plot,
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trade_details_plot,
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]
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)
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with gr.TabItem("🚀 Tool Winning Dashboard"):
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with gr.Row():
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)
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with gr.Row():
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+
tool_winnings_by_tool_plot = plot_tool_winnings_by_tool(
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wins_df=winning_rate_df,
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tool=INC_TOOLS[0]
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)
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sel_tool.change(
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update_tool_winnings_by_tool_plot,
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inputs=sel_tool,
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+
outputs=tool_winnings_by_tool_plot
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)
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with gr.Row():
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sel_tool
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with gr.Row():
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tool_winnings_by_tool_plot
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with gr.Row():
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refresh_button = gr.Button("Refresh Data")
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+
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refresh_button.click(
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update_tool_winnings_plots,
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outputs=[
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winning_plot,
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tool_winnings_by_tool_plot
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]
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)
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+
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with gr.TabItem("🏥 Tool Error Dashboard"):
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with gr.Row():
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gr.Markdown("# Plot showing overall error")
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with gr.Row():
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+
error_overall_plot = plot_error_data(
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error_all_df=error_overall_df
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)
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with gr.Row():
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)
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with gr.Row():
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+
tool_error_plot = plot_tool_error_data(
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error_df=error_df,
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tool=INC_TOOLS[0]
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)
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sel_tool.change(
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update_tool_error_plot,
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inputs=sel_tool,
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+
outputs=tool_error_plot
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)
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with gr.Row():
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sel_tool
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with gr.Row():
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tool_error_plot
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with gr.Row():
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gr.Markdown("# Plot showing error by week")
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)
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with gr.Row():
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+
week_error_plot = plot_week_error_data(
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error_df=error_df,
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week=choices[-1]
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)
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week=selected_week
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)
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sel_tool.change(update_tool_error_plot, inputs=sel_tool, outputs=tool_error_plot)
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sel_week.change(update_week_error_plot, inputs=sel_week, outputs=week_error_plot)
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with gr.Row():
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sel_tool
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with gr.Row():
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+
tool_error_plot
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with gr.Row():
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sel_week
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with gr.Row():
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week_error_plot
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+
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with gr.Row():
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refresh_button = gr.Button("Refresh Data")
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refresh_button.click(
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update_error_plots,
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outputs=[
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error_overall_plot,
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tool_error_plot,
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week_error_plot
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]
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413 |
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)
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with gr.TabItem("ℹ️ About"):
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with gr.Accordion("About Olas Predict"):
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data/all_trades_profitability.csv
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
|
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+
oid sha256:0ed325e54d1901d69a27fbb18a19e3d7479bd2e89eac8fad22e5cbe01abfd335
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+
size 32001583
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data/delivers.csv
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
|
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+
oid sha256:0d7e07db2af936529c721932218be4832d7dbe113dbb50e534bb8bf060d609cc
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+
size 2014149364
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data/fpmmTrades.csv
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3e4abd630e8476e2d6cbfe684f14a843d7ae22e750133e4c4ee96e12ffabdb03
|
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+
size 69980018
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data/fpmms.csv
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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|
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version https://git-lfs.github.com/spec/v1
|
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+
oid sha256:04cb5e845138d2e7d69e699521fc3fa9adac5bc67438ad5afc0aab0dc9488568
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+
size 429913
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data/requests.csv
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:13b123c5b509f37032582888b51a9536c3c855a3954bbf6695e1ff23c1fc7f42
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+
size 148756035
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data/summary_profitability.csv
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:d2129ca0d2324e5c10fc2220913d0ef28067a788e69d3f84d2a261eed1f57588
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+
size 56460
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data/t_map.pkl
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
|
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:4ac7f44ec10ae465f40149c039181a427f82ff6e820a88f17207d33b8a7237fc
|
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+
size 6781847
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data/tools.csv
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:6657130c88b5e3f90d53725b5fb1646af030d45e33175cdb3cf6e5a81d5e740d
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size 2121884792
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test.py
ADDED
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import gradio as gr
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import pandas as pd
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demo = gr.Blocks()
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data1 = pd.DataFrame({
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"tool": ["tool1", "tool2", "tool3"],
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"error": [0.1, 0.2, 0.3]
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})
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data2 = pd.DataFrame({
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"tool": ["tool1", "tool2", "tool3", "tool4"],
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"error": [0.1, 0.2, 0.3, 0.4]
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})
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data3 = pd.DataFrame({
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"tool": ["tool1", "tool2", "tool3", "tool4", "tool5"],
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"error": [0.1, 0.2, 0.3, 0.4, 0.5]
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})
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def update_plot1():
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data = pd.DataFrame({
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"tool": ["tool1", "tool2", "tool3", "tool4"],
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"error": [0.1, 0.2, 0.3, 0.4]
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})
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return gr.BarPlot(
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data,
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x="tool",
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y="error"
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)
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def update_plot2():
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data = pd.DataFrame({
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"tool": ["tool1", "tool2", "tool3", "tool4", "tool5"],
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"error": [0.1, 0.2, 0.3, 0.4, 0.5]
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})
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return gr.BarPlot(
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data,
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x="tool",
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y="error"
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)
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def update_plot3():
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data = pd.DataFrame({
|
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"tool": ["tool1", "tool2", "tool3", "tool4", "tool5", "tool6"],
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"error": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6]
|
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})
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return gr.BarPlot(
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data,
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x="tool",
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y="error"
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)
|
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def update_plots():
|
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return update_plot1(), update_plot2(), update_plot3()
|
58 |
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|
59 |
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with demo:
|
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with gr.Row():
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plot1 = gr.BarPlot(
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data1,
|
63 |
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x="tool",
|
64 |
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y="error"
|
65 |
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)
|
66 |
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|
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with gr.Row():
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plot2 = gr.BarPlot(
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data2,
|
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x="tool",
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y="error"
|
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)
|
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|
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with gr.Row():
|
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plot3 = gr.BarPlot(
|
76 |
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data3,
|
77 |
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x="tool",
|
78 |
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y="error"
|
79 |
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)
|
80 |
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|
81 |
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with gr.Row():
|
82 |
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update_button = gr.Button("Update")
|
83 |
+
|
84 |
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update_button.click(
|
85 |
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update_plots,
|
86 |
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inputs=[],
|
87 |
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outputs=[plot1, plot2, plot3]
|
88 |
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)
|
89 |
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|
90 |
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demo.launch(
|
91 |
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debug=True
|
92 |
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)
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