From 58137a0f364042a00bbe5aa9938d234e4fa5448b Mon Sep 17 00:00:00 2001
From: Mark Aron Szulyovszky <mark.szulyovszky@gmail.com>
Date: Tue, 9 Nov 2021 12:58:05 +0100
Subject: [PATCH] feat(Data): fetch prices from cryptocompare (and
 alphavantage)

---
 .../data}/oecd_housing_prices.csv             |  0
 .../housing_preprocess.py                     |  0
 fetch-data.py                                 | 42 +++++++++++++++++++
 3 files changed, 42 insertions(+)
 rename {data => archive/data}/oecd_housing_prices.csv (100%)
 rename preprocess.py => archive/housing_preprocess.py (100%)
 create mode 100644 fetch-data.py

diff --git a/data/oecd_housing_prices.csv b/archive/data/oecd_housing_prices.csv
similarity index 100%
rename from data/oecd_housing_prices.csv
rename to archive/data/oecd_housing_prices.csv
diff --git a/preprocess.py b/archive/housing_preprocess.py
similarity index 100%
rename from preprocess.py
rename to archive/housing_preprocess.py
diff --git a/fetch-data.py b/fetch-data.py
new file mode 100644
index 0000000..378f924
--- /dev/null
+++ b/fetch-data.py
@@ -0,0 +1,42 @@
+# %%
+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
+
+
+
+# %%
+
+# %%