(feat) update default configs in pages

frontend/pages/config/dman_maker_v2/app.py

@@ -52,7 +52,7 @@ st.plotly_chart(fig, use_container_width=True)
 
 # Combine inputs and dca_inputs into final config
 config = {**inputs, **dca_inputs}
-st.session_state["default_config"] = config
+st.session_state["default_config"].update(config)
 bt_results = backtesting_section(config, backend_api_client)
 if bt_results:
     fig = create_backtesting_figure(
@@ -68,4 +68,4 @@ if bt_results:
         st.write("---")
         render_close_types(bt_results["results"])
 st.write("---")
-render_save_config("dman_maker_v2", config)
+render_save_config(st.session_state["default_config"]["id"], st.session_state["default_config"])

frontend/pages/config/pmm_dynamic/app.py

@@ -55,12 +55,12 @@ with st.expander("Visualizing PMM Dynamic Indicators", expanded=True):
 st.write("### Executors Distribution")
 st.write("The order distributions are affected by the average NATR. This means that if the first order has a spread of "
          "1 and the NATR is 0.005, the first order will have a spread of 0.5% of the mid price.")
-buy_spread_distributions, sell_spread_distributions, buy_order_amounts_pct, sell_order_amounts_pct = get_executors_distribution_inputs()
+buy_spread_distributions, sell_spread_distributions, buy_order_amounts_pct, sell_order_amounts_pct = get_executors_distribution_inputs(use_custom_spread_units=True)
 inputs["buy_spreads"] = [spread * 100 for spread in buy_spread_distributions]
 inputs["sell_spreads"] = [spread * 100 for spread in sell_spread_distributions]
 inputs["buy_amounts_pct"] = buy_order_amounts_pct
 inputs["sell_amounts_pct"] = sell_order_amounts_pct
-st.session_state["default_config"] = inputs
+st.session_state["default_config"].update(inputs)
 with st.expander("Executor Distribution:", expanded=True):
     natr_avarage = spreads_multiplier.mean()
     buy_spreads = [spread * natr_avarage for spread in inputs["buy_spreads"]]
@@ -84,4 +84,4 @@ if bt_results:
         st.write("---")
         render_close_types(bt_results["results"])
 st.write("---")
-render_save_config("pmm_dynamic", inputs)
+render_save_config(st.session_state["default_config"]["id"], st.session_state["default_config"])

frontend/pages/config/pmm_simple/app.py

@@ -17,11 +17,14 @@ from frontend.visualization.backtesting_metrics import render_backtesting_metric
 initialize_st_page(title="PMM Simple", icon="👨‍🏫")
 backend_api_client = BackendAPIClient.get_instance(host=BACKEND_API_HOST, port=BACKEND_API_PORT)
 
+
 # Page content
 st.text("This tool will let you create a config for PMM Simple, backtest and upload it to the Backend API.")
 get_default_config_loader("pmm_simple")
+
 inputs = user_inputs()
 
+st.session_state["default_config"].update(inputs)
 with st.expander("Executor Distribution:", expanded=True):
     fig = create_executors_distribution_traces(inputs["buy_spreads"], inputs["sell_spreads"], inputs["buy_amounts_pct"], inputs["sell_amounts_pct"], inputs["total_amount_quote"])
     st.plotly_chart(fig, use_container_width=True)
@@ -41,4 +44,4 @@ if bt_results:
         st.write("---")
         render_close_types(bt_results["results"])
 st.write("---")
-render_save_config("pmm_simple", inputs)
+render_save_config(st.session_state["default_config"]["id"], st.session_state["default_config"])

frontend/pages/config/pmm_simple/user_inputs.py

@@ -35,5 +35,4 @@ def user_inputs():
             "trailing_delta": ts_delta
         }
     }
-    st.session_state["default_config"] = config
     return config