TraderBob/markets.py at main · southpawbob/TraderBob · GitHub

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import requests
import requests_cache
import json
import time
import pandas as pd
from nicegui import ui
import plotly.graph_objects as go

#session = CachedSession('demo_cache', cache_control=True)
#session = CachedSession('demo_cache', )
requests_cache.install_cache('cache')

def convert_numbers_to_strings(obj):
    if isinstance(obj, float):
        return str(obj)
    return obj

def fetch_all_markets():

    url = "https://api.coingecko.com/api/v3/coins/markets?vs_currency=usd&per_page=250&sparkline=true&price_change_percentage=1h%2C24h%2C7d%2C14d%2C30d%2C200d%2C1y&precision=full"
    headers = {
        "accept": "application/json",
        "x-cg-demo-api-key": "CG-ULEXj9kgbnAK2kGvieVgsDBL"
    }
    page_num = 1
    dfAll = pd.DataFrame();
    all_data = []
    while True:
        params = {"page": page_num}
        response = requests.get(url, headers=headers, params=params)
        print("request page: ", page_num)
        data = json.loads(response.text)
        if not data:
            break
        df = pd.DataFrame(data)
       # df = pd.read_json(response.text)
        dfAll = pd.concat([df,dfAll])
        all_data.extend(data)
        page_num += 1
        #time.sleep(1)  # Respect rate limits (e.g., 10-30 calls per minute)
    dfAll.to_pickle("markets.pkl")
    print(f"Total coins fetched: {len(all_data)}")
    return

def fetch_all_coins():

    url = "https://api.coingecko.com/api/v3/coins/list?include_platform=true"
    headers = {
        "accept": "application/json",
        #"x-cg-demo-api-key": "CG-ULEXj9kgbnAK2kGvieVgsDBL"
    }
    response = requests.get(url, headers=headers)
    df_coins = pd.read_json(response.text)
    df_coins.to_pickle("coins.pkl")
    return

def fetch_coins_simple(coinIds):
    url = "https://api.coingecko.com/api/v3/simple/price?vs_currencies=usd&include_market_cap=true&include_24hr_vol=true&include_24hr_change=true&include_last_updated_at=true&precision=full"
    headers = {
        "accept": "application/json",
        #"x-cg-demo-api-key": "CG-ULEXj9kgbnAK2kGvieVgsDBL"
    }
    url += f"&ids={coinIds}"

    response = requests.get(url, headers=headers)
    print(response.text)
    df_coins = pd.read_json(response.text)
    df_coins.to_pickle("coins_simple.pkl")
    return

def create_market_table(df):
    columns = ['id', 'symbol', 'name', 'current_price', 'market_cap', 'total_volume', 'price_change_percentage_24h']
    # Create a ColumnDataSource from the Pandas DataFrame
    source = ColumnDataSource(df)
    # Define table columns
    columns = [TableColumn(field=col, title=col) for col in columns]

    # Create DataTable widget
    data_table = DataTable(source=source, columns=columns, width=400, height=280, sizing_mode='stretch_both')
    return data_table

def create_simple_table(df):
    columns = ['usd', 'usd_market_cap', 'usd_24h_vol', 'usd_24h_change', 'last_updated_at']
    # Create a ColumnDataSource from the Pandas DataFrame
    source = ColumnDataSource(df)
    # Define table columns
    columns = [TableColumn(field=col, title=col) for col in columns]

    # Create DataTable widget
    data_table = DataTable(source=source, columns=columns, width=400, height=280, sizing_mode='stretch_both')
    return data_table

#fetch_all_markets()
#fetch_all_coins()

df = pd.read_pickle("markets.pkl")
df_coins = pd.read_pickle("coins.pkl")

df = df_coins.merge(df, on = 'id', how = 'left')
df = df[df['platforms'].apply(lambda x: "solana" in x)]
df = df[df['market_cap'].apply(lambda x: x > 0)]
df = df[df['total_volume'].apply(lambda x: x > 10000)]
df = df[df['price_change_percentage_24h'].apply(lambda x: x > 10)]

coinIds = ''
coinTotal = 0
for index, row in df.iterrows():
    if (coinTotal > 0):
        coinIds += "%2C"
    coinIds += f"{row['id']}"
    coinTotal+=1

print (f"Total coins: {coinTotal}")

#print(df["sparkline_in_7d"].iloc[0])
for index, row in df.iterrows():
    with ui.row():
        label = ui.label(row['id'])

        values = row["sparkline_in_7d"].get('price')
        #df2=pd.DataFrame({'x': , 'y':  })
        #row.add_slot(ui.plotly(df2.plot('x', 'y')))
        fig = go.Figure([go.Scatter(x=list(range(168)), y=values)])
        fig.update_layout(margin=dict(l=0, r=0, t=0, b=0))
        ui.plotly(fig).classes('w-full h-40')

#
row = ui.row()
#row.add_slot(ui.label('label 1'))
#values = df["sparkline_in_7d"].iloc[0].get('price')
#df2=pd.DataFrame({'x': range(1,169), 'y': values })
#row.add_slot(ui.plotly(df2.plot('x', 'y')))


ui.run(show=False)