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https://github.com/codez0mb1e/resistance.git
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Remove redundant
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codez0mb1e
parent
138587cd6b
commit
aa7d45380b
@ -1,29 +0,0 @@
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# %%
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import numpy as np
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import pandas as pd
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import time
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from binance.client import Client
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# %%
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api_key = "****"
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secret_key = "***"
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client = Client(api_key, secret_key)
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# %%
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coins_response = client.get_all_coins_info()
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coins_df = pd.DataFrame.from_dict(coins_response, orient='columns')
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# %%
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pairs_list = coins_df.coin.apply(lambda x: f"{x}USDT")
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client.get_historical_klines(
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'BTCUSDT',
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interval=Client.KLINE_INTERVAL_1HOUR,
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start_str='2022-04-21',
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end_str='2022-04-22'
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)
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@ -267,6 +267,44 @@
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"# Sort output by Close_time\n",
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"candles_1h_df.sort_values('Close_time')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### (Optional) Use Binance API"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# %%\n",
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"import pandas as pd \n",
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"from binance.client import Client\n",
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"\n",
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"\n",
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"# %%\n",
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"api_key = \"****\"\n",
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"secret_key = \"***\"\n",
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"\n",
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"client = Client(api_key, secret_key)\n",
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"\n",
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"\n",
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"# %%\n",
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"coins_response = client.get_all_coins_info()\n",
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"coins_df = pd.DataFrame.from_dict(coins_response, orient='columns')\n",
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"\n",
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"\n",
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"# %%\n",
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"pairs_list = coins_df.coin.apply(lambda x: f\"{x}USDT\") \n",
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"client.get_historical_klines(\n",
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" 'BTCUSDT', \n",
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" interval=Client.KLINE_INTERVAL_1HOUR,\n",
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" start_str='2022-04-21', \n",
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" end_str='2022-04-22'\n",
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")"
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]
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}
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],
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"metadata": {
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@ -285,7 +323,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.13"
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"version": "3.9.12"
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},
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"orig_nbformat": 4,
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"vscode": {
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@ -1,168 +0,0 @@
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# %% Import dependencies
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import os
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from dataclasses import dataclass
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from typing import Dict, Union
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import pandas as pd
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import httpx
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from sqlalchemy import types
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from azure import AzureDbConnection, ConnectionSettings
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# %% Data models
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@dataclass
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class AssetInfo:
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FIGI: str
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Ticker: str
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Title: Union[str, None]
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Description: Union[str, None]
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AssetType: str = 'Cryptocurrency'
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SourceId: str = 'OpenFigi API'
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Version: str = 'v202206'
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def as_dict(self) -> Dict[str, str]:
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return {'Figi': self.FIGI, 'Ticker': self.Ticker}
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# %% FIGI provider
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class OpenFigiProvider:
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"""
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OpenFigi API provider
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References:
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https://www.openfigi.com/assets/local/figi-allocation-rules.pdf
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https://www.openfigi.com/search
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"""
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@staticmethod
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def _send_request(ticker: str, asset_type: str) -> pd.DataFrame:
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api_url = f'https://www.openfigi.com/search/query?facetQuery=MARKET_SECTOR_DES:%22{asset_type}%22&num_rows=100&simpleSearchString={ticker}&start=0'
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response = httpx.get(api_url)
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json_response = response.json()
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return pd.DataFrame.from_dict(json_response['result'], orient='columns')
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@staticmethod
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def _find_figi(df: pd.DataFrame, field_name: str) -> Union[str, None]:
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if len(df) == 0 or field_name not in df.columns:
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return None
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result = df[field_name].dropna().unique()
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if (len(result) != 1):
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print(f'[WARN] Multiple ({len(result)}) FIGI records was found')
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return None
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return result[0]
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@staticmethod
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def _find_name(df: pd.DataFrame) -> Union[str, None]:
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if len(df) == 0 or 'DS002_sd' not in df.columns:
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return None
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result = df['DS002_sd'].dropna().unique()
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if (len(result) != 1):
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print(f'[WARN] Multiple ({len(result)}) name records was found')
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return None
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return result[0]
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def search(self, ticker: str, asset_type: str = 'Curncy') -> Union[AssetInfo, None]:
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"""Return FIGI for pair"""
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response_df = OpenFigiProvider._send_request(ticker, asset_type)
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figi = OpenFigiProvider._find_figi(response_df, 'kkg_pairFIGI_sd')
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if figi is None:
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base_quote = ticker.split('-')[0]
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print(f'[INFO] {ticker} > Try to search using base quote {base_quote}')
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response_df = OpenFigiProvider._send_request(base_quote, asset_type)
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figi = OpenFigiProvider._find_figi(response_df, 'kkg_baseAssetFigi_sd')
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if figi is None:
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return None
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return AssetInfo(figi, ticker, None, None)
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#%%
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figi_provider = OpenFigiProvider()
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assert figi_provider.search('WAX-USD') == None
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assert figi_provider.search('ABCD') == None
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# %% Tests
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expected_pairs = {
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'BNB-USD': 'KKG000007HZ5',
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'ETH-USD': 'BBG00J3NBWD7',
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'BTC-USD': 'BBG006FCL7J4',
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'SOL-USD': 'BBG013WVY457',
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'UNI-USD': 'BBG013TZFVW3',
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'SUSHI-USD': 'KKG0000010W1',
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'AVAX-USD': 'KKG000007J36'
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}
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for k, v in expected_pairs.items():
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actual = figi_provider.search(k)
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print(actual.as_dict())
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assert (
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isinstance(actual, AssetInfo)
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and actual.FIGI == v
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and actual.Ticker == k
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)
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# %% Get assets for searching figi
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pair_names = [x[:-4] for x in os.listdir("../data")]
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def insert_dash(text: str, position: int) -> str:
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if '-' not in text:
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return text[:position] + '-' + text[position:]
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else:
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return text
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usd_pairs = [
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insert_dash(s.upper(), 3)
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for s in pair_names if "usd" in s
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]
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print(usd_pairs[1:10])
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# %%
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figi_provider = OpenFigiProvider()
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pair_figi_list = [figi_provider.search(p) for p in usd_pairs]
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# %% ----
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conn_settings = ConnectionSettings(server='****.database.windows.net', database='market-data-db', username='<user>', password='****')
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db_conn = AzureDbConnection(conn_settings)
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db_conn.connect()
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for t in db_conn.get_tables():
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print(t)
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# %%
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db_mapping = {
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'Figi': types.CHAR(length=12),
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'Ticker': types.VARCHAR(length=12)
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}
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figi_df = pd.DataFrame([t.as_dict() for t in pair_figi_list if isinstance(t, AssetInfo)])
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db_conn.insert(figi_df, 'figi', db_mapping)
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# %%
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db_conn.dispose()
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print('Completed')
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