Merge pull request #347 from Joewizy/feat/pipeline-dashboard

Feat/pipeline dashboard

.github/workflows/dashboard_app_pylint.yml

@@ -0,0 +1,44 @@
+name: Dashboard App
+
+on: [push]
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: Set up Python 3.11
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.11'
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install pylint
+
+    - name: Debug Information
+      run: |
+        echo "Current directory:"
+        pwd
+        echo "\nDirectory structure:"
+        ls -R
+        echo "\nGit root directory:"
+        git rev-parse --show-toplevel
+        echo "\nSearching for Python files:"
+        find . -name "*.py"
+        echo "\nGit ls-files output:"
+        git ls-files
+        echo "\nSpecific path search:"
+        git ls-files 'dashboard_app/*.py'
+        git ls-files './dashboard_app/*.py'
+        git ls-files 'apps/dashboard_app/*.py'
+        git ls-files './apps/dashboard_app/*.py'
+
+    - name: Run Pylint
+      run: |
+        files=$(git ls-files 'dashboard_app/*.py')
+        if [ -n "$files" ]; then
+          pylint $files --disable=all --enable=C0114,C0115,C0116,C0301
+        fi

apps/dashboard_app/charts/__init__.py

@@ -1 +1,5 @@
+"""
+Imports the Dashboard class from the main module in the dashboard_app.charts package.
+"""
+
 from dashboard_app.charts.main import Dashboard

apps/dashboard_app/charts/main.py

@@ -1,3 +1,7 @@
+"""
+This module defines the Dashboard class for rendering a DeRisk dashboard using Streamlit.
+"""
+
 import streamlit as st
 
 from dashboard_app.charts.main_chart_figure import get_main_chart_figure
@@ -16,6 +20,9 @@
 
 
 class Dashboard:
+    """
+    A class representing a dashboard for managing protocol names.
+    """
     PROTOCOL_NAMES = [
         "zkLend",
         # "Nostra Alpha",
@@ -44,6 +51,9 @@ def __init__(self, zklend_state):
         self.collateral_token_price = 0
 
     def load_sidebar(self):
+        """
+        Creates an interactive sidebar for selecting multiple protocols, debt and collateral token.
+        """
         col1, _ = st.columns([1, 3])
         with col1:
             self.protocols = st.multiselect(
@@ -73,6 +83,9 @@ def load_sidebar(self):
                 )
 
     def load_main_chart(self):
+        """
+        Generates a chart that visualizes liquidable debt against available supply.
+        """
         (
             protocol_main_chart_data_mapping,
             protocol_loans_data_mapping,
@@ -116,6 +129,9 @@ def load_main_chart(self):
         st.plotly_chart(figure_or_data=figure, use_container_width=True)
 
     def run(self):
+        """
+        This function executes/runs the load_sidebar() and load_main_chart() function.
+        """
         # Load sidebar with protocol settings
         self.load_sidebar()
         self.load_main_chart()

apps/dashboard_app/charts/main_chart_figure.py

@@ -1,19 +1,24 @@
+"""
+This module includes functions to generate financial charts using token price and liquidity data.
+"""
+
 import math
 
 import pandas as pd
 import plotly.express
 import plotly.graph_objs
 
+from shared.amms import SwapAmm
+from shared.state import State
+from shared.types import Prices
+
 from dashboard_app.helpers.settings import TOKEN_SETTINGS
 from dashboard_app.helpers.tools import (
     get_collateral_token_range,
     get_custom_data,
     get_prices,
     get_underlying_address,
 )
-from shared.amms import SwapAmm
-from shared.state import State
-from shared.types import Prices
 
 AMMS = ("10kSwap", "MySwap", "SithSwap", "JediSwap")
 
@@ -25,6 +30,11 @@ def get_main_chart_data(
     collateral_token_underlying_symbol: str,
     debt_token_underlying_symbol: str,
 ) -> pd.DataFrame:
+    """
+    Generates financial chart data based on token prices, liquidity, and debt information.
+    Takes five parameters and 
+    Returns: A DataFrame containing calculated token prices and liquidable debt data.
+    """
     collateral_token_underlying_address = get_underlying_address(
         token_parameters=state.token_parameters.collateral,
         underlying_symbol=collateral_token_underlying_symbol,
@@ -64,6 +74,10 @@ def get_main_chart_data(
         data[f"{amm}_debt_token_supply"] = 0
 
     def compute_supply_at_price(collateral_token_price: float):
+        """
+        Computes the token supply for each AMM at a given collateral token price and
+        Returns: the token supplied by AMM and total supply across all AMMs.
+        """
         supplies = {
             amm: swap_amms.get_supply_at_price(
                 collateral_token_underlying_symbol=collateral_token_underlying_symbol,
@@ -79,7 +93,7 @@ def compute_supply_at_price(collateral_token_price: float):
     supplies_and_totals = data["collateral_token_price"].apply(compute_supply_at_price)
     for amm in AMMS:
         data[f"{amm}_debt_token_supply"] = supplies_and_totals.apply(
-            lambda x: x[0][amm]
+            lambda x, amm=amm: x[0][amm]
         )
     data["debt_token_supply"] = supplies_and_totals.apply(lambda x: x[1])
 
@@ -92,6 +106,10 @@ def get_main_chart_figure(
     debt_token: str,
     collateral_token_price: float,
 ) -> plotly.graph_objs.Figure:
+    """
+    Generates a plotly figure for the main chart the function takes in four paramters and
+    Returns: A Plotly figure object for the chart.
+    """
     color_map_protocol = {
         "liquidable_debt_at_interval_zkLend": "#fff7bc",  # light yellow
         "liquidable_debt_at_interval_Nostra Alpha": "#fec44f",  # yellow
@@ -143,11 +161,12 @@ def get_main_chart_figure(
     # Update layout for the stacked bar plot and the separate trace
     figure.update_layout(
         barmode="stack",
-        title=f"Liquidable debt and the corresponding supply of {debt_token} at various price intervals of {collateral_token}",
+        title=f"Liquidable debt and the corresponding supply of {debt_token}"
+        f" at various price intervals of {collateral_token}",
         xaxis_title=f"{collateral_token} Price (USD)",
         yaxis_title="Volume (USD)",
         legend_title="Legend",
-        yaxis2=dict(overlaying="y", side="left", matches="y"),
+        yaxis2={"overlaying": 'y', "side": 'left', "matches": 'y'},
     )
 
     # Add the vertical line and shaded region for the current price
@@ -177,6 +196,10 @@ def get_bar_chart_figures(
 ) -> tuple[
     plotly.graph_objs.Figure, plotly.graph_objs.Figure, plotly.graph_objs.Figure
 ]:
+    """
+    Generates a bar chart figures for supply, collateral, and debt stats and then
+    Returns: A tuple of three objects (supply, collateral, and debt charts).
+    """
     underlying_addresses_to_decimals = {
         x.address: int(math.log10(x.decimal_factor)) for x in TOKEN_SETTINGS.values()
     }
@@ -281,6 +304,10 @@ def get_bar_chart_figures(
 def get_specific_loan_usd_amounts(
     loan: pd.DataFrame,
 ) -> tuple[pd.DataFrame, pd.DataFrame]:
+    """
+    This function gets the loan amount in usd and then it
+    Returns: A tuple containing two DataFrames with specific loan USD amounts.
+    """
     underlying_addresses_to_decimals = {
         x.address: int(math.log10(x.decimal_factor)) for x in TOKEN_SETTINGS.values()
     }

apps/dashboard_app/charts/utils.py

@@ -1,3 +1,7 @@
+"""
+This moudel process and transform liquidity, loan, and chart data for protocols.
+"""
+
 import logging
 import math
 from collections import defaultdict
@@ -77,19 +81,21 @@ def parse_token_amounts(raw_token_amounts: str) -> dict[str, float]:
 
 def create_stablecoin_bundle(data: dict[str, pd.DataFrame]) -> dict[str, pd.DataFrame]:
     """
-    Creates a stablecoin bundle by merging relevant DataFrames for collateral tokens and debt tokens.
+    Creates a stablecoin bundle by merging relevant DataFrames for collateral tokens and debt
+    tokens.
 
-    For each collateral token specified in `src.settings.COLLATERAL_TOKENS`, this function finds the
-    relevant stablecoin pairs from the provided `data` dictionary and merges the corresponding DataFrames
-    based on the 'collateral_token_price' column. It combines the debt and liquidity data for multiple
-    stablecoin pairs and adds the result back to the `data` dictionary under a new key.
+    For each collateral token specified in `src.settings.COLLATERAL_TOKENS`, this function finds 
+    the relevant stablecoin pairs from the provided `data` dictionary and merges the corresponding
+    Dataframes based on the 'collateral_token_price' column. It combines the debt and liquidity 
+    data for multiple stablecoin pairs and adds the result back to the `data` dictionary under a 
+    new key.
 
     Parameters:
-    data (dict[str, pandas.DataFrame]): A dictionary where the keys are token pairs and the values are
-                                        corresponding DataFrames containing price and supply data.
+    data (dict[str, pandas.DataFrame]): A dictionary where the keys are token pairs and the values
+     are corresponding DataFrames containing price and supply data.
 
-    Returns:
-    dict[str, pandas.DataFrame]: The updated dictionary with the newly created stablecoin bundle added.
+    Returns: dict[str, pandas.DataFrame]: 
+    The updated dictionary with the newly created stablecoin bundle added.
     """
 
     # Iterate over all collateral tokens defined in the settings
@@ -109,7 +115,7 @@ def create_stablecoin_bundle(data: dict[str, pd.DataFrame]) -> dict[str, pd.Data
 
             if df.empty:
                 # Log a warning if the DataFrame is empty and skip to the next pair
-                logging.warning(f"Empty DataFrame for pair: {pair}")
+                logging.warning("Empty DataFrame for pair: %s", pair)
                 continue
 
             if combined_df is None:
@@ -232,10 +238,11 @@ def transform_main_chart_data(
     for protocol in protocols:
         protocol_main_chart_data = protocol_main_chart_data_mapping[protocol]
         if protocol_main_chart_data is None or protocol_main_chart_data.empty:
-            logging.warning(f"No data for pair {current_pair} from {protocol}")
+            logging.warning("No data for pair %s from %s", current_pair, protocol)
             collateral_token, debt_token = current_pair.split("-")
             st.subheader(
-                f":warning: No liquidable debt for the {collateral_token} collateral token and the {debt_token} debt token exists on the {protocol} protocol."
+                f":warning: No liquidable debt for the {collateral_token} collateral token and "
+                f"the {debt_token} debt token exists on the {protocol} protocol."
             )
             continue
 

apps/dashboard_app/dashboard.py

@@ -1,3 +1,7 @@
+"""
+This script loads data and runs the dashboard.
+"""
+
 import logging
 from dashboard_app.charts import Dashboard
 from dashboard_app.helpers.load_data import DashboardDataHandler

apps/dashboard_app/data_conector.py

@@ -1,3 +1,7 @@
+"""
+This is module connects to a PostgreSQL database and fetches data. 
+"""
+
 import os
 
 import pandas as pd
@@ -8,6 +12,9 @@
 
 
 class DataConnector:
+    """
+    Handles database connection and fetches data.
+    """
     REQUIRED_VARS = ("DB_USER", "DB_PASSWORD", "DB_HOST", "DB_PORT", "DB_NAME")
     ZKLEND_SQL_QUERY = """
         SELECT

apps/dashboard_app/helpers/ekubo.py

@@ -1,3 +1,8 @@
+"""
+A module that interacts with an API to fetch the latest
+liquidity data and applies it to a dataframe.
+"""
+
 import logging
 import time
 
@@ -6,6 +11,10 @@
 
 
 class EkuboLiquidity:
+    """
+     Fetches data from a liquidity API and send it to the dataframe which updates the
+     liquidity of a token pair. 
+    """
     URL = "http://178.32.172.153/orderbook/"
     DEX = "Ekubo"
     LOWER_BOUND_VALUE = 0.95
@@ -61,7 +70,7 @@ def apply_liquidity_to_dataframe(
                 data=liquidity,
                 price=price,
                 price_diff=price_diff,
-                bids=True if bids_or_asks["type"] == "bids" else False,
+                bids = bids_or_asks["type"] == "bids",
             ),
         )
         self.data["debt_token_supply"] += self.data["Ekubo_debt_token_supply"]

apps/dashboard_app/helpers/load_data.py

@@ -1,3 +1,7 @@
+"""
+This module loads and handle the data.
+"""
+
 import asyncio
 import logging
 import math
@@ -69,7 +73,7 @@ def _init_zklend_state(self) -> ZkLendState:
         zklend_state.interest_rate_models.debt = zklend_interest_rate_data["debt"].iloc[
             0
         ]
-        logger.info(f"Initialized ZkLend state in {monotonic() - start:.2f}s")
+        logger.info("Initialized ZkLend state in %.2fs", monotonic() - start)
 
         return zklend_state
 

apps/dashboard_app/helpers/loans_table.py

@@ -1,3 +1,6 @@
+"""
+This module organizes and handles the loan data in a tabular manner.
+"""
 
 import pandas as pd
 from data_handler.handlers.loan_states.nostra_alpha.events import NostraAlphaState
@@ -8,9 +11,14 @@
 
 
 def get_protocol(state: State) -> str:
+    """
+    Takes a parameter of State which gets the loan entities and 
+    returns the string.
+    """
     return state.get_protocol_name
 
 
+
 def get_loans_table_data(
     state: State,
     prices: Prices,
@@ -41,7 +49,7 @@ def get_loans_table_data(
             debt_interest_rate_model=state.interest_rate_models.debt,
             prices=prices,
         )
-        if isinstance(state, NostraAlphaState) or isinstance(state, NostraMainnetState):
+        if isinstance(state, (NostraAlphaState, NostraMainnetState)):
             risk_adjusted_debt_usd = loan_entity.compute_debt_usd(
                 risk_adjusted=True,
                 debt_token_parameters=state.token_parameters.debt,
@@ -97,6 +105,11 @@ def get_supply_function_call_parameters(
     protocol: str,
     token_addresses: list[str],
 ) -> tuple[list[str], str]:
+    """
+    Takes two parameters of name of protocol and token address and then
+    Returns a tuple which the first element is the list of token address and
+    the second is supply function name
+    """
     if protocol == "zkLend":
         return token_addresses, "felt_total_supply"
     if protocol in {"Nostra Alpha", "Nostra Mainnet"}: