import os
import requests
import pandas as pd
import plotly.graph_objects as go
import streamlit as st

st.set_page_config(layout="wide")

# you need to sign up at FMP API to get the API key, then put it in the respective environment variable
apikey = os.environ["FMP_API_KEY"]

def parse_json(url):
    resp = requests.get(url)
    resp.raise_for_status()
    return pd.DataFrame(resp.json())

def fmt(val):
    if abs(val) >= 1e9: return f"${val/1e9:.1f}B"
    if abs(val) >= 1e6: return f"${val/1e6:.1f}M"
    if abs(val) >= 1e3: return f"${val/1e3:.0f}K"
    return f"${val:.0f}"

def draw_balance_sankey(balance_sheet, symbol, height, font_size):
    # define all Sankey flows (left is source, right is target)
    flows = [
        # Current Assets
        ("Cash and Cash Equivalents",            "Total Current Assets",            balance_sheet["cashAndCashEquivalents"]),
        ("Short-Term Investments",               "Total Current Assets",            balance_sheet["shortTermInvestments"]),
        ("Net Receivables",                      "Total Current Assets",            balance_sheet["netReceivables"]),
        ("Inventory",                            "Total Current Assets",            balance_sheet["inventory"]),
        ("Prepaids",                             "Total Current Assets",            balance_sheet["prepaids"]),
        # NOTE: Other Current Assets may sometimes overlap with some of the above lines
        ("Other Current Assets",                 "Total Current Assets",            balance_sheet["otherCurrentAssets"]),
    
        # Non-Current Assets
        ("Property, Plant and Equipment, Net",   "Total Non-Current Assets",        balance_sheet["propertyPlantEquipmentNet"]),
        ("Goodwill",                             "Total Non-Current Assets",        balance_sheet["goodwill"]),
        ("Intangible Assets",                    "Total Non-Current Assets",        balance_sheet["intangibleAssets"]),
        ("Long-Term Investments",                "Total Non-Current Assets",        balance_sheet["longTermInvestments"]),
        ("Tax Assets",                           "Total Non-Current Assets",        balance_sheet["taxAssets"]),
        ("Other Non-Current Assets",             "Total Non-Current Assets",        balance_sheet["otherNonCurrentAssets"]),
    
        # ... to Total Assets
        ("Total Current Assets",                 "Total Assets",                    balance_sheet["totalCurrentAssets"]),
        ("Total Non-Current Assets",             "Total Assets",                    balance_sheet["totalNonCurrentAssets"]),
    
        # Total Assets to ...
        ("Total Assets",                         "Total Liabilities",               balance_sheet["totalLiabilities"]),
        ("Total Assets",                         "Total Stockholders' Equity",      balance_sheet["totalStockholdersEquity"]),
    
        # Current Liabilities
        ("Total Liabilities",                    "Total Current Liabilities",       balance_sheet["totalCurrentLiabilities"]),
        ("Total Current Liabilities",            "Tax Payables",                    balance_sheet["taxPayables"]),
        ("Total Current Liabilities",            "Short-Term Debt",                 balance_sheet["shortTermDebt"]),
        ("Total Current Liabilities",            "Capital Lease Obligations (Current)", balance_sheet["capitalLeaseObligationsCurrent"]),
        ("Total Current Liabilities",            "Deferred Revenue (Current)",      balance_sheet["deferredRevenue"]),
        ("Total Current Liabilities",            "Other Current Liabilities",       balance_sheet["otherCurrentLiabilities"]),
        ("Total Current Liabilities",            "Accounts Payable",                balance_sheet["accountPayables"]),
        ("Total Current Liabilities",            "Other Payables",                  balance_sheet["otherPayables"]),
        ("Total Current Liabilities",            "Accrued Expenses",                balance_sheet["accruedExpenses"]),
    
        # Non-Current Liabilities
        ("Total Liabilities",                    "Total Non-Current Liabilities",   balance_sheet["totalNonCurrentLiabilities"]),
        ("Total Non-Current Liabilities",        "Long-Term Debt",                  balance_sheet["longTermDebt"]),
        ("Total Non-Current Liabilities",        "Capital Lease Obligations (Non-Current)", balance_sheet["capitalLeaseObligationsNonCurrent"]),
        ("Total Non-Current Liabilities",        "Deferred Revenue (Non-Current)",  balance_sheet["deferredRevenueNonCurrent"]),
        ("Total Non-Current Liabilities",        "Deferred Tax Liabilities (Non-Current)", balance_sheet["deferredTaxLiabilitiesNonCurrent"]),
        ("Total Non-Current Liabilities",        "Other Non-Current Liabilities",   balance_sheet["otherNonCurrentLiabilities"]),
    
        # Equity
        ("Total Stockholders' Equity",           "Common Stock",                    balance_sheet["commonStock"]),
        ("Total Stockholders' Equity",           "Retained Earnings",               balance_sheet["retainedEarnings"]),
        ("Total Stockholders' Equity",           "Accumulated Other Comprehensive Income (Loss)", balance_sheet["accumulatedOtherComprehensiveIncomeLoss"]),
        ("Total Stockholders' Equity",           "Additional Paid-In Capital",      balance_sheet["additionalPaidInCapital"]),
        ("Total Stockholders' Equity",           "Other Stockholders' Equity",      balance_sheet["otherTotalStockholdersEquity"]),
    ]
    
    
    # need to adjust flow to make negative values easier to read
    adjusted_flows = []
    for src, tgt, val in flows:
        if val >= 0:
            # positive: keep direction, color green
            adjusted_flows.append((src, tgt, val, 'rgba(50,200,50,0.6)'))
        else:
            # negative: reverse direction, color red
            adjusted_flows.append((tgt, src, -val, 'rgba(200,50,50,0.6)'))
    
    # for labelling later, first we store the source and target names
    labels = []
    for src, tgt, _ in flows:
        if src not in labels: labels.append(src)
        if tgt not in labels: labels.append(tgt)
    
    # map label to its actual balance‐sheet value for annotation
    node_values = {
        "Cash and Cash Equivalents":                         balance_sheet["cashAndCashEquivalents"],
        "Short-Term Investments":                            balance_sheet["shortTermInvestments"],
        "Net Receivables":                                   balance_sheet["netReceivables"],
        "Inventory":                                         balance_sheet["inventory"],
        "Prepaids":                                          balance_sheet["prepaids"],
        "Other Current Assets":                              balance_sheet["otherCurrentAssets"],
        "Total Current Assets":                              balance_sheet["totalCurrentAssets"],
        "Property, Plant and Equipment, Net":                balance_sheet["propertyPlantEquipmentNet"],
        "Goodwill":                                          balance_sheet["goodwill"],
        "Intangible Assets":                                 balance_sheet["intangibleAssets"],
        "Long-Term Investments":                             balance_sheet["longTermInvestments"],
        "Tax Assets":                                        balance_sheet["taxAssets"],
        "Other Non-Current Assets":                          balance_sheet["otherNonCurrentAssets"],
        "Total Non-Current Assets":                          balance_sheet["totalNonCurrentAssets"],
        "Total Assets":                                      balance_sheet["totalAssets"],
    
        "Total Liabilities":                                 balance_sheet["totalLiabilities"],
        "Total Current Liabilities":                         balance_sheet["totalCurrentLiabilities"],
        "Tax Payables":                                      balance_sheet["taxPayables"],
        "Short-Term Debt":                                   balance_sheet["shortTermDebt"],
        "Capital Lease Obligations (Current)":               balance_sheet["capitalLeaseObligationsCurrent"],
        "Deferred Revenue (Current)":                        balance_sheet["deferredRevenue"],
        "Other Current Liabilities":                         balance_sheet["otherCurrentLiabilities"],
    
        "Accounts Payable":                                  balance_sheet["accountPayables"],
        "Other Payables":                                    balance_sheet["otherPayables"],
        "Accrued Expenses":                                  balance_sheet["accruedExpenses"],
    
        "Total Non-Current Liabilities":                     balance_sheet["totalNonCurrentLiabilities"],
        "Long-Term Debt":                                    balance_sheet["longTermDebt"],
        "Capital Lease Obligations (Non-Current)":           balance_sheet["capitalLeaseObligationsNonCurrent"],
        "Deferred Revenue (Non-Current)":                    balance_sheet["deferredRevenueNonCurrent"],
        "Deferred Tax Liabilities (Non-Current)":            balance_sheet["deferredTaxLiabilitiesNonCurrent"],
        "Other Non-Current Liabilities":                     balance_sheet["otherNonCurrentLiabilities"],
    
        "Total Stockholders' Equity":                        balance_sheet["totalStockholdersEquity"],
        "Common Stock":                                      balance_sheet["commonStock"],
        "Retained Earnings":                                 balance_sheet["retainedEarnings"],
        "Accumulated Other Comprehensive Income (Loss)":     balance_sheet["accumulatedOtherComprehensiveIncomeLoss"],
        "Additional Paid-In Capital":                        balance_sheet["additionalPaidInCapital"],
        "Other Stockholders' Equity":                        balance_sheet["otherTotalStockholdersEquity"],
    }
    
    # for formatting, annotate labels with $ amounts and take care of billions, millions, thousands
    def fmt(val): 
        if abs(val) >= 1e9: return f"${val/1e9:.1f}B"
        if abs(val) >= 1e6: return f"${val/1e6:.1f}M"
        if abs(val) >= 1e3: return f"${val/1e3:.0f}K"
        return f"${val:.0f}"
    
    # put the sorce and target values in labels
    labels = []
    for s, t, _, _ in adjusted_flows:
        if s not in labels: labels.append(s)
        if t not in labels: labels.append(t)
    
    idx = {label:i for i,label in enumerate(labels)}
    source = [ idx[s] for s, t, _, _ in adjusted_flows ] # index of sources for sankey input
    target = [ idx[t] for s, t, _, _ in adjusted_flows ] # index of target for sankey input
    value  = [     v   for _, _, v, _ in adjusted_flows ]
    colors = [     c   for _, _, _, c in adjusted_flows ]
    
    label_with_values = []
    for label in labels:
        val = node_values[label]          
        base = label.replace(" (Current)", "")\
                    .replace(" (Non-Current)", "") # saves some printing space
        if val < 0:
            base += " [NEGATIVE]" # just to make negatives more obvious in the label               
        label_with_values.append(f"{base} ({fmt(val)})")

    fig = go.Figure(go.Sankey(
        arrangement="snap",
        node = dict(label=label_with_values, pad=15, thickness=20),
        link = dict(source=source, target=target, value=value, color=colors)
    ))
    fig.update_layout(
        title_text=f"Balance Sheet Sankey — {symbol}",
        height=height,
        font_size=font_size
    )
    return fig

def draw_income_sankey(income_statement, symbol, height, font_size):
    flows = [
        # Revenue─
        ("Revenue",               "Cost of Revenue",                      income_statement["costOfRevenue"]),
        ("Revenue",               "Gross Profit",                         income_statement["grossProfit"]),
    
        # Gross Profit
        ("Gross Profit",          "Operating Income",                     income_statement["operatingIncome"]),
        ("Gross Profit",          "Operating Expenses",                   income_statement["operatingExpenses"]),
    
        # Operating Expenses
        ("Operating Expenses",    "Research & Development Expenses",      income_statement["researchAndDevelopmentExpenses"]),
        # ("Operating Expenses",    "General & Administrative Expenses",   income_statement["generalAndAdministrativeExpenses"]), # already in SG&A
        # ("Operating Expenses",    "Selling & Marketing Expenses",        income_statement["sellingAndMarketingExpenses"]), # already in SG&A
        ("Operating Expenses",    "SG&A Expenses",                        income_statement["sellingGeneralAndAdministrativeExpenses"]), 
        ("Operating Expenses",    "Other Operating Expenses",             income_statement["otherExpenses"]),   
    
        # Pretax Income
        ("Pretax Income",         "Income Tax Expense",                   income_statement["incomeTaxExpense"]),
        ("Pretax Income",         "Net Income",                           income_statement["netIncome"]),
        ("Pretax Income",         "Interest Expense",                     income_statement["interestExpense"]),  
        # this value is recorded as negative in API, but we do not need to reverse the flow like in balance sheet
        # because it decreases the pretax income so we put it together at the same side with all the tax expenses
        ("Pretax Income",         "Non-Operating Income Excl. Interest", -income_statement["nonOperatingIncomeExcludingInterest"]), 
        ("Pretax Income",         "Total Other Income & Expenses Net",    income_statement["totalOtherIncomeExpensesNet"]),
        ("Pretax Income",         "Other Adjustments to Net Income",      income_statement["otherAdjustmentsToNetIncome"]),
    
        # Other Income that goes into Pretax Income
        ("Operating Income",      "Pretax Income",                        income_statement["operatingIncome"]),
        ("Net Interest Income",   "Pretax Income",                        income_statement["netInterestIncome"]),
        ("Interest Income",       "Pretax Income",                        income_statement["interestIncome"]),
    ]
    
    
    # need to adjust flow to make negative values easier to read
    adjusted_flows = []
    for src, tgt, val in flows:
        if val >= 0:
            # positive: keep direction, color green
            adjusted_flows.append((src, tgt, val, 'rgba(50,200,50,0.6)'))
        else:
            # negative: reverse direction, color red
            adjusted_flows.append((tgt, src, -val, 'rgba(200,50,50,0.6)'))
    
    # for labelling later, first we store the source and target names
    labels = []
    for src, tgt, _ in flows:
        if src not in labels: labels.append(src)
        if tgt not in labels: labels.append(tgt)
    
    # map label to its actual balance‐sheet value for annotation
    node_values = {
        "Revenue":                           income_statement["revenue"],
        "Cost of Revenue":                   income_statement["costOfRevenue"],
        "Gross Profit":                      income_statement["grossProfit"],
    
        "Operating Income":                  income_statement["operatingIncome"],
        "Operating Expenses":                income_statement["operatingExpenses"],
        "Research & Development Expenses":   income_statement["researchAndDevelopmentExpenses"],
        #"General & Administrative Expenses": income_statement["generalAndAdministrativeExpenses"], # already in SG&A
        #"Selling & Marketing Expenses":      income_statement["sellingAndMarketingExpenses"], # already in SG&A
        "SG&A Expenses":                     income_statement["sellingGeneralAndAdministrativeExpenses"],
        "Other Operating Expenses":          income_statement["otherExpenses"],
    
        "Net Interest Income":               income_statement["netInterestIncome"],
        "Interest Income":                   income_statement["interestIncome"],
        "Interest Expense":                  income_statement["interestExpense"],
        "Non-Operating Income Excl. Interest":-income_statement["nonOperatingIncomeExcludingInterest"],
        "Total Other Income & Expenses Net": income_statement["totalOtherIncomeExpensesNet"],
    
        "Pretax Income":                     income_statement["incomeBeforeTax"],
        "Income Tax Expense":                income_statement["incomeTaxExpense"],
        "Net Income":                        income_statement["netIncome"],
        "Other Adjustments to Net Income":   income_statement["otherAdjustmentsToNetIncome"],
        "Bottom Line Net Income":            income_statement["bottomLineNetIncome"],
    }
    
    # for formatting, annotate labels with $ amounts and take care of billions, millions, thousands
    def fmt(val): 
        if abs(val) >= 1e9: return f"${val/1e9:.1f}B"
        if abs(val) >= 1e6: return f"${val/1e6:.1f}M"
        if abs(val) >= 1e3: return f"${val/1e3:.0f}K"
        return f"${val:.0f}"
    
    # put the sorce and target values in labels
    labels = []
    for s, t, _, _ in adjusted_flows:
        if s not in labels: labels.append(s)
        if t not in labels: labels.append(t)
    
    idx = {label:i for i,label in enumerate(labels)}
    source = [ idx[s] for s, t, _, _ in adjusted_flows ] # index of sources for sankey input
    target = [ idx[t] for s, t, _, _ in adjusted_flows ] # index of target for sankey input
    value  = [     v   for _, _, v, _ in adjusted_flows ]
    colors = [     c   for _, _, _, c in adjusted_flows ]
    
    label_with_values = []
    for label in labels:
        val = node_values[label]          
        base = label.replace(" (Current)", "")\
                    .replace(" (Non-Current)", "") # saves some printing space
        if val < 0:
            base += " [NEGATIVE]" # just to make negatives more obvious in the label               
        label_with_values.append(f"{base} ({fmt(val)})")

    fig = go.Figure(go.Sankey(
        arrangement="snap",
        node = dict(label=label_with_values, pad=15, thickness=20),
        link = dict(source=source, target=target, value=value, color=colors)
    ))
    fig.update_layout(
        title_text=f"Income Statement Sankey — {symbol}",
        height=height,
        font_size=font_size
    )
    return fig

def draw_cashflow_sankey(cash_flow, symbol, height, font_size):
    flows = [
        # Operating Activities (Inflow)
        ("Net Income",                             "Operating Activities",                 cash_flow["netIncome"]),
        ("Depreciation & Amortization",            "Operating Activities",                 cash_flow["depreciationAndAmortization"]),
        ("Deferred Income Tax",                    "Operating Activities",                 cash_flow["deferredIncomeTax"]),
        ("Stock-Based Compensation",               "Operating Activities",                 cash_flow["stockBasedCompensation"]),
        ("Change in Working Capital",              "Operating Activities",                 cash_flow["changeInWorkingCapital"]),
        ("Accounts Receivables Δ",                 "Operating Activities",                 cash_flow["accountsReceivables"]),
        ("Inventory Δ",                            "Operating Activities",                 cash_flow["inventory"]),
        ("Accounts Payable Δ",                     "Operating Activities",                 cash_flow["accountsPayables"]),
        #("Other Working Capital Δ",                "Operating Activities",                 cash_flow["otherWorkingCapital"]), # overlap with some lines
        ("Other Non-Cash Items",                   "Operating Activities",                 cash_flow["otherNonCashItems"]),
        ("Operating Activities",                   "Net Cash Inflow (Operating)",       cash_flow["netCashProvidedByOperatingActivities"]),
    
        # Investing Activities (Outflow)
        ("Investments in PP&E",                    "Investing Activities",                 cash_flow["investmentsInPropertyPlantAndEquipment"]),
        ("Acquisitions, Net",                      "Investing Activities",                 cash_flow["acquisitionsNet"]),
        ("Purchases of Investments",               "Investing Activities",                 cash_flow["purchasesOfInvestments"]),
        ("Sales/Maturities of Investments",        "Investing Activities",                 cash_flow["salesMaturitiesOfInvestments"]),
        ("Other Investing Activities",             "Investing Activities",                 cash_flow["otherInvestingActivities"]),
        ("Investing Activities",                   "Net Cash Outflow (Investing)",       cash_flow["netCashProvidedByInvestingActivities"]),
    
        # Financing Activities (Outflow)
        ("Net Debt Issuance",                      "Financing Activities",                 cash_flow["netDebtIssuance"]),
        #("Long-Term Net Debt Issuance",            "Financing Activities",                 cash_flow["longTermNetDebtIssuance"]), # already under net debt
        #("Short-Term Net Debt Issuance",           "Financing Activities",                 cash_flow["shortTermNetDebtIssuance"]), # already under net debt
        #("Net Stock Issuance",                     "Financing Activities",                 cash_flow["netStockIssuance"]),
        ("Net Common Stock Issuance",              "Financing Activities",                 cash_flow["netCommonStockIssuance"]),
        #("Common Stock Issuance",                  "Financing Activities",                 cash_flow["commonStockIssuance"]), # already under net common stock issuance
        #("Common Stock Repurchased",               "Financing Activities",                 cash_flow["commonStockRepurchased"]), # already under net common stock issuance
        ("Net Preferred Stock Issuance",           "Financing Activities",                 cash_flow["netPreferredStockIssuance"]),
        ("Net Dividends Paid",                     "Financing Activities",                 cash_flow["netDividendsPaid"]),
        #("Common Dividends Paid",                  "Financing Activities",                 cash_flow["commonDividendsPaid"]),  # already under net dividends paid
        #("Preferred Dividends Paid",               "Financing Activities",                 cash_flow["preferredDividendsPaid"]), # already under net dividends paid
        ("Other Financing Activities",             "Financing Activities",                 cash_flow["otherFinancingActivities"]),
        ("Financing Activities",                   "Net Cash Outflow (Financing)",       cash_flow["netCashProvidedByFinancingActivities"]),
    
        # Combine In and Out Flows
        ("Net Cash Inflow (Operating)",         "Net Change in Cash",                   cash_flow["netCashProvidedByOperatingActivities"]),
        ("Net Cash Outflow (Investing)",         "Net Change in Cash",                   cash_flow["netCashProvidedByInvestingActivities"]),
        ("Net Cash Outflow (Financing)",         "Net Change in Cash",                   cash_flow["netCashProvidedByFinancingActivities"]),
        ("Effect of Forex on Cash",                "Net Change in Cash",                   cash_flow["effectOfForexChangesOnCash"]),
    
        # Beginning & Change → Ending Balance
        ("Cash at Beginning of Period",            "Cash at End of Period",                cash_flow["cashAtBeginningOfPeriod"]),
        ("Net Change in Cash",                     "Cash at End of Period",                cash_flow["netChangeInCash"]),
    ]
    
    adjusted_flows = []
    for src, tgt, val in flows:
        if val >= 0:
            adjusted_flows.append((src, tgt, val, 'rgba(50,200,50,0.6)'))
        else:
            # reverse direction for readability
            adjusted_flows.append((tgt, src, -val,    'rgba(200,50,50,0.6)'))
    
    
    labels = []
    for s, t, _, _ in adjusted_flows:
        if s not in labels: labels.append(s)
        if t not in labels: labels.append(t)
    
    node_values = { lbl: cash_flow[
        {
          "Net Income": "netIncome",
          "Depreciation & Amortization": "depreciationAndAmortization",
          "Deferred Income Tax": "deferredIncomeTax",
          "Stock-Based Compensation": "stockBasedCompensation",
          "Change in Working Capital": "changeInWorkingCapital",
          "Accounts Receivables Δ": "accountsReceivables",
          "Inventory Δ": "inventory",
          "Accounts Payable Δ": "accountsPayables",
          "Other Working Capital Δ": "otherWorkingCapital",
          "Other Non-Cash Items": "otherNonCashItems",
          "Operating Activities": "netCashProvidedByOperatingActivities",
          "Investments in PP&E": "investmentsInPropertyPlantAndEquipment",
          "Acquisitions, Net": "acquisitionsNet",
          "Purchases of Investments": "purchasesOfInvestments",
          "Sales/Maturities of Investments": "salesMaturitiesOfInvestments",
          "Other Investing Activities": "otherInvestingActivities",
          "Investing Activities": "netCashProvidedByInvestingActivities",
          "Net Debt Issuance": "netDebtIssuance",
          "Long-Term Net Debt Issuance": "longTermNetDebtIssuance",
          "Short-Term Net Debt Issuance": "shortTermNetDebtIssuance",
          "Net Stock Issuance": "netStockIssuance",
          "Net Common Stock Issuance": "netCommonStockIssuance",
          "Common Stock Issuance": "commonStockIssuance",
          "Common Stock Repurchased": "commonStockRepurchased",
          "Net Preferred Stock Issuance": "netPreferredStockIssuance",
          "Net Dividends Paid": "netDividendsPaid",
          "Common Dividends Paid": "commonDividendsPaid",
          "Preferred Dividends Paid": "preferredDividendsPaid",
          "Other Financing Activities": "otherFinancingActivities",
          "Financing Activities": "netCashProvidedByFinancingActivities",
          "Net Cash Inflow (Operating)": "netCashProvidedByOperatingActivities",
          "Net Cash Outflow (Investing)": "netCashProvidedByInvestingActivities",
          "Net Cash Outflow (Financing)": "netCashProvidedByFinancingActivities",
          "Effect of Forex on Cash": "effectOfForexChangesOnCash",
          "Net Change in Cash": "netChangeInCash",
          "Cash at Beginning of Period": "cashAtBeginningOfPeriod",
          "Cash at End of Period": "cashAtEndOfPeriod",
        }[lbl]
    ] for lbl in labels }
    
    
    def fmt(val):
        if abs(val) >= 1e9: return f"${val/1e9:.1f}B"
        if abs(val) >= 1e6: return f"${val/1e6:.1f}M"
        if abs(val) >= 1e3: return f"${val/1e3:.0f}K"
        return f"${val:.0f}"
    
    
    idx     = { lbl:i for i,lbl in enumerate(labels) }
    source  = [ idx[s] for s, t, _, _ in adjusted_flows ]
    target  = [ idx[t] for s, t, _, _ in adjusted_flows ]
    value   = [     v   for _, _, v, _ in adjusted_flows ]
    colors  = [     c   for _, _, _, c in adjusted_flows ]
    
    label_with_values = []
    for lbl in labels:
        val  = node_values[lbl]
        base = lbl
        if val < 0: base += " [NEGATIVE]"
        label_with_values.append(f"{base} ({fmt(val)})")

    fig = go.Figure(go.Sankey(
        arrangement="snap",
        node = dict(label=label_with_values, pad=15, thickness=20),
        link = dict(source=source, target=target, value=value, color=colors)
    ))
    fig.update_layout(
        title_text=f"Cash Flow Statement Sankey — {symbol}",
        height=height,
        font_size=font_size
    )
    return fig


st.title("Financial Sankeys")

symbol = st.sidebar.text_input("Ticker symbol", "AMZN").upper()

# sidebar controls
bs_height = st.sidebar.slider("Balance Sheet height", 500, 1500, 800)
bs_font   = st.sidebar.slider("Balance Sheet font size", 5, 15, 10)
is_height = st.sidebar.slider("Income Statement height", 500, 1500, 600)
is_font   = st.sidebar.slider("Income Statement font size", 5, 15, 10)
cf_height = st.sidebar.slider("Cash Flow Statement height", 500, 1500, 800)
cf_font   = st.sidebar.slider("Cash Flow Statement font size", 5, 15, 10)

# where the data came from
st.sidebar.markdown("## [Financial Modeling Prep API](https://site.financialmodelingprep.com/?utm_source=medium&utm_medium=medium&utm_campaign=damian8)\
\n\nFinancial statements are obtained from the FinancialModelingPrep API, feel free to sign up\
[here](https://site.financialmodelingprep.com/?utm_source=medium&utm_medium=medium&utm_campaign=damian8)\
    if you wish.")

if symbol:
    # Balance Sheet
    st.header(f"Balance Sheet — {symbol}")
    try:
        df_bs = parse_json(f"https://financialmodelingprep.com/stable/balance-sheet-statement?symbol={symbol}&apikey={apikey}")
        balance_sheet = df_bs.iloc[0]
        fig_bs = draw_balance_sankey(balance_sheet, symbol.upper(), bs_height, bs_font)
        st.plotly_chart(fig_bs, use_container_width=True)
    except Exception as e:
        st.error(f"{e}")

    # Income Statement
    st.header(f"Income Statement — {symbol}")
    try:
        df_is = parse_json(f"https://financialmodelingprep.com/stable/income-statement?symbol={symbol}&apikey={apikey}")
        income_statement = df_is.iloc[0]
        fig_is = draw_income_sankey(income_statement, symbol.upper(), is_height, is_font)
        st.plotly_chart(fig_is, use_container_width=True)
    except Exception as e:
        st.error(f"{e}")

    # Cash Flow Statement
    st.header(f"Cash Flow Statement — {symbol}")
    try:
        df_cf = parse_json(f"https://financialmodelingprep.com/stable/cash-flow-statement?symbol={symbol}&apikey={apikey}")
        cash_flow = df_cf.iloc[0]
        fig_cf = draw_cashflow_sankey(cash_flow, symbol.upper(), cf_height, cf_font)
        st.plotly_chart(fig_cf, use_container_width=True)
    except Exception as e:
        st.error(f"{e}")