feat(Data): downloading data for pre-defined tickers

fetch-data.py

@@ -1,42 +0,0 @@
-# %%
-import requests
-import pandas as pd
-
-AV_API_KEY = 'UY5VGSWBE88SHGI6'
-CC_API_KEY = 'bfb8b5f54b21354608020a6654b370617b2fcabd2c8c2ce04ab881682a1d9dc9'
-
-# %%
-def get_crypto_price_crypto_compare(symbol, exchange, days):
-    api_url = f'https://min-api.cryptocompare.com/data/v2/histoday?fsym={symbol}&tsym={exchange}&limit={days}&api_key={CC_API_KEY}'
-    raw = requests.get(api_url).json()
-    df = pd.DataFrame(raw['Data']['Data'])[['time', 'high', 'low', 'open']].set_index('time')
-    df.index = pd.to_datetime(df.index, unit = 's')
-    return df
-
-ada = get_crypto_price_crypto_compare('ADA', 'USD', 1500)
-ada
-
-
-# %%
-
-def get_crypto_price_av(symbol, exchange, start_date = None):
-    api_url = f'https://www.alphavantage.co/query?function=DIGITAL_CURRENCY_DAILY&symbol={symbol}&market={exchange}&apikey={AV_API_KEY}'
-    raw_df = requests.get(api_url).json()
-    df = pd.DataFrame(raw_df['Time Series (Digital Currency Daily)']).T
-    df = df.rename(columns = {'1a. open (USD)': 'open', '2a. high (USD)': 'high', '3a. low (USD)': 'low', '4a. close (USD)': 'close', '5. volume': 'volume'})
-    for i in df.columns:
-        df[i] = df[i].astype(float)
-    df.index = pd.to_datetime(df.index)
-    df = df.iloc[::-1].drop(['1b. open (USD)', '2b. high (USD)', '3b. low (USD)', '4b. close (USD)', '6. market cap (USD)'], axis = 1)
-    if start_date:
-        df = df[df.index >= start_date]
-    return df
-
-btc = get_crypto_price_av(symbol = 'BTC', exchange = 'USD', start_date = '2018-01-01')
-btc
-
-
-
-# %%
-
-# %%

fetch_data.py

@@ -0,0 +1,20 @@
+#%%
+import pandas as pd
+from utils.get_prices import get_crypto_price_crypto_compare, get_stock_price_av
+
+#%%
+crypto_tickers = ["BTC", "ETH", "BNB", "ADA", "SOL", "XRP", "DOT", "LTC", "UNI", "TRX", "FIL"]
+etf_tickers = ["GLD", "IEF", "TLT", "SPY", "QQQ"]
+tickers = crypto_tickers + etf_tickers
+
+#%%
+for ticker in tickers:
+    print("Fetching ", ticker)
+    if ticker in crypto_tickers:
+        df = get_crypto_price_crypto_compare(ticker, "USD", 1500)
+    else:
+        df = get_stock_price_av(ticker, "2017-11-10")  
+    df.to_csv(f"data/{ticker}.csv", index=True)
+
+
+# %%

utils/get_prices.py

@@ -0,0 +1,60 @@
+# %%
+import requests
+import pandas as pd
+
+AV_API_KEY = 'UY5VGSWBE88SHGI6'
+CC_API_KEY = 'bfb8b5f54b21354608020a6654b370617b2fcabd2c8c2ce04ab881682a1d9dc9'
+
+# %%
+def get_crypto_price_crypto_compare(symbol: str, exchange: str, days: int) -> pd.DataFrame:
+    api_url = f'https://min-api.cryptocompare.com/data/v2/histoday?fsym={symbol}&tsym={exchange}&limit={days}&api_key={CC_API_KEY}'
+    raw = requests.get(api_url).json()
+    df = pd.DataFrame(raw['Data']['Data'])[['time', 'high', 'low', 'open', 'close']].set_index('time')
+    df.index = pd.to_datetime(df.index, unit = 's')
+    df.sort_index(inplace = True, ascending= True)
+    return df
+
+ada = get_crypto_price_crypto_compare('ADA', 'USD', 1500)
+ada
+
+
+# %%
+
+def get_crypto_price_av(symbol: str, exchange: str, start_date = None) -> pd.DataFrame:
+    api_url = f'https://www.alphavantage.co/query?function=DIGITAL_CURRENCY_DAILY&symbol={symbol}&market={exchange}&apikey={AV_API_KEY}'
+    raw_df = requests.get(api_url).json()
+    df = pd.DataFrame(raw_df['Time Series (Digital Currency Daily)']).T
+    df = df.rename(columns = {'1a. open (USD)': 'open', '2a. high (USD)': 'high', '3a. low (USD)': 'low', '4a. close (USD)': 'close', '5. volume': 'volume'})
+    for i in df.columns:
+        df[i] = df[i].astype(float)
+    df.index = pd.to_datetime(df.index)
+    df = df.iloc[::-1].drop(['1b. open (USD)', '2b. high (USD)', '3b. low (USD)', '4b. close (USD)', '6. market cap (USD)'], axis = 1)
+    if start_date:
+        df = df[df.index >= start_date]
+    df.sort_index(inplace = True, ascending= True)
+    return df
+
+def get_stock_price_av(symbol: str, start_date: str = None) -> pd.DataFrame:
+    api_url = f'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol={symbol}&outputsize=full&apikey={AV_API_KEY}'
+    raw_df = requests.get(api_url).json()
+    df = pd.DataFrame(raw_df['Time Series (Daily)']).T
+    df = df.rename(columns = {'1. open': 'open', '2. high': 'high', '3. low': 'low', '4. close': 'close', '5. adjusted close': 'adj_close', '6. volume': 'volume'})
+    for i in df.columns:
+        df[i] = df[i].astype(float)
+    df.index = pd.to_datetime(df.index)
+    df = df.iloc[::-1].drop(['7. dividend amount', '8. split coefficient'], axis = 1)
+    if start_date:
+        df = df[df.index >= start_date]
+    df.sort_index(inplace = True, ascending= True)
+    return df
+
+
+
+# %%
+# btc = get_crypto_price_av(symbol = 'BTC', exchange = 'USD', start_date = '2018-01-01')
+# btc
+
+# %%
+
+# spy = get_stock_price_av(symbol = 'SPY', start_date = '2018-01-01')
+# spy