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b51d4a0162
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3
.gitignore
vendored
3
.gitignore
vendored
@ -1 +1,2 @@
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/data/*.csv
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/data/*.csv
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/data/*.zip
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40
src/azure.py
40
src/azure.py
@ -1,16 +1,18 @@
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# %% Import dependencies ----
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from dataclasses import dataclass
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from typing import Dict, Any, Iterable
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from pandas import DataFrame
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from typing import Dict, Any
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from sqlalchemy import create_engine, inspect
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import pandas as pd
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import urllib
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# %%
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# %% Models
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@dataclass(frozen=True)
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class ConnectionSettings:
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"""Connection Settings."""
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"""Connection Settings"""
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server: str
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database: str
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username: str
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@ -19,10 +21,10 @@ class ConnectionSettings:
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timeout: int = 30
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# %% Connection
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class AzureDbConnection:
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"""
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Azure SQL database connection.
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"""
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"""Azure SQL database connection."""
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def __init__(self, conn_settings: ConnectionSettings, echo: bool = False) -> None:
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conn_params = urllib.parse.quote_plus(
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'Driver=%s;' % conn_settings.driver +
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@ -36,29 +38,29 @@ class AzureDbConnection:
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)
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conn_string = f'mssql+pyodbc:///?odbc_connect={conn_params}'
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self.db = create_engine(conn_string, echo=echo)
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self._db = create_engine(conn_string, echo=echo)
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def connect(self) -> None:
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"""Estimate connection."""
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self.conn = self.db.connect()
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"""Estimate connection"""
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self._conn = self._db.connect()
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def get_tables(self) -> Iterable[str]:
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"""Get list of tables."""
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inspector = inspect(self.db)
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def get_tables(self) -> list[str]:
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"""Get list of tables"""
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inspector = inspect(self._db)
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return [t for t in inspector.get_table_names()]
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def insert(self, inserted_data: DataFrame, target_table: str, db_mapping: Dict[str, Any], chunksize: int = 10000) -> None:
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def insert(self, inserted_data: pd.DataFrame, target_table: str, db_mapping: Dict[str, Any], chunksize: int = 10000) -> None:
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inserted_data.to_sql(
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con=self.db,
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con=self._db,
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schema='dbo',
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name=target_table,
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if_exists='append', # or replace
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if_exists='replace', # or append
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index=False,
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chunksize=chunksize,
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dtype=db_mapping
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)
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def dispose(self) -> None:
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"""Dispose opened connections."""
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self.conn.close()
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self.db.dispose()
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"""Dispose opened connections"""
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self._conn.close()
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self._db.dispose()
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@ -1,7 +1,6 @@
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#!/usr/bin/python3
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"""
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Data source: https://www.kaggle.com/code/tencars/bitfinexdataset
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"""
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@ -15,6 +14,11 @@ from azure import AzureDbConnection, ConnectionSettings
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# %%
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#> ~/apps/resistance/data
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#> kaggle datasets download tencars/392-crypto-currency-pairs-at-minute-resolution
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#> unzip 392-crypto-currency-pairs-at-minute-resolution.zip
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input_path = "../data"
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# Get names and number of available currency pairs
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@ -28,6 +32,7 @@ print(pair_names[0:50])
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usd_pairs = [s for s in pair_names if "usd" in s]
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print(usd_pairs)
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# %%
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def load_data(symbol, source=input_path):
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@ -46,12 +51,12 @@ def load_data(symbol, source=input_path):
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# %% ----
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solusd = load_data("solusd")
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solusd.tail()
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sample_df = load_data("ethusd")
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sample_df
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# %% ----
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conn_settings = ...
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db_conn = AzureDbConnection(conn_settings)
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db_conn.connect()
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@ -63,7 +68,7 @@ for t in db_conn.get_tables():
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min_candels_n = 10000
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db_mapping = {
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'FIGI': types.VARCHAR(length=12),
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'FIGI': types.CHAR(length=12),
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'open': types.DECIMAL(precision=19, scale=9),
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'high': types.DECIMAL(precision=19, scale=9),
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'close': types.DECIMAL(precision=19, scale=9),
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@ -82,14 +87,14 @@ for pair in usd_pairs:
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candles_df['FIGI'] = pair
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candles_df['time'] = candles_df.index
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candles_df['source_id'] = 128
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candles_df['version'] = 'v202204'
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candles_df['version'] = 'v202206'
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candles_df['interval'] = '1M'
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if candles_df.shape[0] > min_candels_n:
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print('{} rows from {} to {}'.format(candles_df.shape[0], min(candles_df['time']), max(candles_df['time'])))
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print(f'Starting insert {pair}...')
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db_conn.insert(candles_df, 'Cryptocurrency', db_mapping)
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db_conn.insert(candles_df, 'crypto', db_mapping)
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else:
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print(f'WARN: {pair} has only {candles_df.shape[0]} records')
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167
src/openfigi_crawler.py
Normal file
167
src/openfigi_crawler.py
Normal file
@ -0,0 +1,167 @@
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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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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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@ -1,75 +0,0 @@
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# %%
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from dataclasses import dataclass
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from typing import Optional
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import pandas as pd
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import httpx
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# %%
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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: str
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Description: Optional[str]
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AssetType: str = 'Cryptocurrency'
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SourceId: str = "OpenFigi API"
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Version: str = "v202204"
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def get_asset_info(pair: str) -> AssetInfo:
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api_url = f'https://www.openfigi.com/search/query?facetQuery=MARKET_SECTOR_DES:%22Curncy%22&num_rows=100&simpleSearchString={pair}&start=0'
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response = httpx.get(api_url)
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json_response = response.json()
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response_df = pd.DataFrame.from_dict(json_response['result'], orient='columns')
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if len(response_df) == 0:
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print(f'[WARN] {pair} not found')
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return None
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pair_figi = response_df.kkg_pairFIGI_sd.unique()
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if (len(pair_figi) != 1):
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print(f'[WARN] {len(pair_figi)} records was found for {pair}')
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else:
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print(f'[INFO] {pair} associated w/ FIGI {pair_figi[0]}')
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return pair_figi
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#%% Tests
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expected_pairs = {
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'WAX-USD': None,
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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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}
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for k, v in expected_pairs.items():
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assert get_asset_info(k) == v
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# %%
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import os
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import pandas as pd
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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 = [insert_dash(s.upper(), 3) for s in pair_names if "usd" in s]
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print(usd_pairs)
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# %%
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pair_figi_list = [get_asset_info(p) for p in usd_pairs]
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for p in usd_pairs:
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print(p)
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get_asset_info(p)
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# %%
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