Merge branch 'master' into fork/Runtee/sql-dump

.github/workflows/ci.yml

@@ -1,6 +1,6 @@
 name: CI Workflow
 
-on: [push]
+on: [push, pull_request]
 
 
 jobs:

.github/workflows/dashboard_app_ci.yml

@@ -1,6 +1,6 @@
 name: DashBoard App CI Workflow
 
-on: [push]
+on: [push, pull_request]
 
 jobs:
   run_tests:

.github/workflows/dashboard_app_pylint.yml

@@ -1,6 +1,6 @@
 name: Dashboard App
 
-on: [push]
+on: [push, pull_request]
 
 jobs:
   lint:

.github/workflows/sdk_app_ci.yml

@@ -1,6 +1,6 @@
 name: SDK testing workflow
 
-on: [push]
+on: [push, pull_request]
 
 jobs:
   run_tests:

.github/workflows/wep_app_ci.yml

@@ -1,6 +1,6 @@
 name: Web App CI Workflow
 
-on: [push]
+on: [push, pull_request]
 
 jobs:
   run_tests:

.gitignore

@@ -2,6 +2,14 @@ __pycache__
 .ipynb_checkpoints
 .vscode
 .env
+.venv
+shell.nix
 storage_credentials.json
 env/
-.venv
+.venv
+
+.env.dev
+
+.idea/
+.DS_Store
+

apps/dashboard_app/Dockerfile

@@ -11,5 +11,5 @@ COPY legacy_app/src legacy_app/src
 COPY legacy_app/app.py .
 COPY legacy_app/update_data.py .
 
-CMD ["streamlit", "run", "app.py"]
+CMD ["streamlit", "run", "dashboard.py"]
 

apps/dashboard_app/README.md

@@ -12,11 +12,17 @@ Interactive dashboard application for visualizing and analyzing DeRisk data.
 ### Docker Setup
 
 1. Build the image:
-
-
+```
+docker-compose -f devops/dev/docker-compose.dashboard-app.yaml build
+```
 2. Run the container:
-
+```
+docker-compose -f devops/dev/docker-compose.dashboard-app.yaml up
+```
 3. stop container:
+```
+docker-compose -f devops/dev/docker-compose.dashboard-app.yaml down
+```
 
 ## Key Features
 

apps/dashboard_app/charts/main.py

@@ -1,6 +1,7 @@
 """
 This module defines the Dashboard class for rendering a DeRisk dashboard using Streamlit.
 """
+
 import numpy as np
 import pandas as pd
 import plotly
@@ -25,6 +26,7 @@
     get_bar_chart_figures,
     get_main_chart_figure,
     get_specific_loan_usd_amounts,
+    get_user_history
 )
 from .utils import (
     get_protocol_data_mappings,
@@ -33,6 +35,7 @@
     transform_loans_data,
     transform_main_chart_data,
 )
+
 
 
 class Dashboard:
@@ -385,7 +388,61 @@ def load_comparison_lending_protocols_chart(self):
                     figure = self._plot_chart(token, "supply")
                     st.plotly_chart(figure, True)
 
+    def get_user_history(self, wallet_id):  
+        """  
+        Fetch and return the transaction history for a specific user.  
+        """  
+        user_data = get_user_history(wallet_id)  
+        if user_data is None or user_data.empty:  
+            st.error("No data found for this user.")  
+            return None  
+
+        user_data.columns = [CommonValues.protocol.value, CommonValues.total_usd.value]  
+        user_data = user_data.sort_values(CommonValues.total_usd.value, ascending=False)  
+        user_data.reset_index(drop=True, inplace=True)  
+
+        st.dataframe(user_data)  
+        return user_data  
+
         # TODO: add last update functionality
+
+    def load_leaderboard(self):
+        """
+        Display a leaderboard of the top 5 biggest collateral and debt per token.
+        """
+        st.header("Leaderboard: Top 5 Collateral & Debt per Token")
+
+        if self.collateral_stats.empty or self.debt_stats.empty:
+            st.warning("No data available for leaderboard.")
+            return
+
+        top_collateral = (
+            self.collateral_stats.groupby("token")["amount_usd"]
+            .sum()
+            .nlargest(5)
+            .reset_index()
+        )
+        top_collateral["type"] = "Collateral"
+
+        top_debt = (
+            self.debt_stats.groupby("token")["amount_usd"]
+            .sum()
+            .nlargest(5)
+            .reset_index()
+        )
+        top_debt["type"] = "Debt"
+
+        leaderboard_df = pd.concat([top_collateral, top_debt])
+
+        def highlight_values(row):
+            color = "green" if row["type"] == "Collateral" else "red"
+            return [f'background-color: {color}; color: white' for _ in row]
+
+        st.dataframe(
+            leaderboard_df.style.apply(highlight_values, axis=1),
+            hide_index=True,
+            use_container_width=True,
+        )
 
     def _plot_chart(self, token: str, stats_type: str) -> plotly.express.data:
         """
@@ -427,3 +484,5 @@ def run(self):
         self.load_top_loans_chart()
         self.load_detail_loan_chart()
         self.load_comparison_lending_protocols_chart()
+        self.get_user_history()
+        self.load_leaderboard()

apps/dashboard_app/charts/main_chart_figure.py

@@ -4,8 +4,8 @@
 
 import math
 from decimal import Decimal
-
 import pandas as pd
+import streamlit as st  
 import plotly.express
 import plotly.graph_objs
 from shared.amms import SwapAmm
@@ -385,4 +385,28 @@ def get_user_history(user_id: str, df: pd.DataFrame) -> pd.DataFrame:
         print(f"User ID {user_id} not found in the DataFrame.")
         return pd.DataFrame()
 
+def display_user_history_chart(df: pd.DataFrame):  
+    """  
+    Displays a chart based on the user's wallet ID input to show their transaction history.  
+
+    Args:  
+        df (pd.DataFrame): The DataFrame containing all transactions.  
+    """  
+    st.subheader("Input Wallet ID to View History")  
+
+    wallet_id = st.text_input("Enter Wallet ID:")  
+
+    if wallet_id:  
+        user_history_data = get_user_history(wallet_id, df)   
+
+        if not user_history_data.empty:  
+            st.dataframe(user_history_data)  
+
+            st.subheader(f"Collateral and Debt History for Wallet ID: {wallet_id}")  
+            chart_data = user_history_data.set_index("Transaction")[["Collateral", "Debt"]]  
+            st.line_chart(chart_data)  
+        else:  
+            st.error("No data found for this wallet ID.") 
+
+
 

apps/dashboard_app/charts/utils.py

@@ -14,16 +14,16 @@
 from shared.amms import SwapAmm
 from shared.constants import PAIRS
 
-from helpers.ekubo import EkuboLiquidity
-from helpers.loans_table import get_loans_table_data
-from helpers.settings import (
+from dashboard_app.helpers.ekubo import EkuboLiquidity
+from dashboard_app.helpers.loans_table import get_loans_table_data
+from dashboard_app.helpers.settings import (
     COLLATERAL_TOKENS,
     DEBT_TOKENS,
     STABLECOIN_BUNDLE_NAME,
     TOKEN_SETTINGS,
     UNDERLYING_SYMBOLS_TO_UNDERLYING_ADDRESSES,
 )
-from helpers.tools import get_main_chart_data, get_prices
+from dashboard_app.helpers.tools import get_main_chart_data, get_prices
 
 logger = logging.getLogger(__name__)
 
@@ -306,7 +306,6 @@ def transform_main_chart_data(
 
     return main_chart_data
 
-
 def infer_protocol_name(input_protocol: str, valid_protocols: list[str]) -> str:
     """Find the closest matching protocol name from a list of valid protocols using fuzzy matching.