diff --git a/.github/workflows/lint.yaml b/.github/workflows/lint.yaml new file mode 100644 index 0000000..e25f606 --- /dev/null +++ b/.github/workflows/lint.yaml @@ -0,0 +1,25 @@ +name: Python Linting + +on: [push, pull_request] + +jobs: + lint: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v2 + + - name: Set up Python + uses: actions/setup-python@v2 + with: + python-version: '3.11' + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install flake8 black + + - name: Check with Flake8 + run: flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics + + - name: Format code with Black + run: black --check . diff --git a/.gitignore b/.gitignore index 3d2a200..e5b9b43 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,6 @@ +exchanges/data_folder +exchanges/constants/.env /venv __pycache__/ .env +exchanges/*.json \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..6a1480f --- /dev/null +++ b/LICENSE @@ -0,0 +1,674 @@ +GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If the program does terminal interaction, make it output a short +notice like this when it starts in an interactive mode: + + Siwa-lite Copyright (C) 2023 Adam + This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w' and `show c' should show the appropriate +parts of the General Public License. Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. \ No newline at end of file diff --git a/all_feeds.py b/all_feeds.py index 4edeccb..4aedc35 100644 --- a/all_feeds.py +++ b/all_feeds.py @@ -4,11 +4,11 @@ Test = test_feed.Test MCAP1000 = mcap1000.MCAP1000 -#NOTE: this is a dict of all feed classes that SIWA can run, keyed by feed name +# NOTE: this is a dict of all feed classes that SIWA can run, keyed by feed name # this is used in endpoint.py to route requests to the correct feed # -#TO ENABLE OR DISABLE A FEED, ADD OR REMOVE IT FROM THIS DICT +# TO ENABLE OR DISABLE A FEED, ADD OR REMOVE IT FROM THIS DICT all_feeds = { Test.NAME: Test, MCAP1000.NAME: MCAP1000, - } +} diff --git a/apis/coingecko.py b/apis/coingecko.py index 7b24890..1b03af3 100644 --- a/apis/coingecko.py +++ b/apis/coingecko.py @@ -17,6 +17,7 @@ class CoinGeckoAPI(CryptoAPI): extract_market_cap(data: Dict[str, Any]) -> Dict[float, Dict[str, str]]: Extracts market cap data from API response. """ + VS_CURRENCY = "usd" ORDER = "market_cap_desc" PAGE = 1 @@ -31,8 +32,7 @@ def __init__(self) -> None: Constructs all the necessary attributes for the CoinGeckoAPI object. """ super().__init__( - url="https://api.coingecko.com/api/v3/coins/markets", - source='coingecko' + url="https://api.coingecko.com/api/v3/coins/markets", source="coingecko" ) @utils.handle_request_errors @@ -92,7 +92,7 @@ def get_market_caps_of_list(self, tokens: List[str]) -> Dict[str, float]: """ market_caps = {} - tokens_comma_sep = ','.join(tokens) + tokens_comma_sep = ",".join(tokens) parameters = { "vs_currency": self.VS_CURRENCY, @@ -107,7 +107,7 @@ def get_market_caps_of_list(self, tokens: List[str]) -> Dict[str, float]: name = d.get(self.NAME_KEY) last_updated = d.get(self.LAST_UPDATED_KEY) market_caps[market_cap] = { - 'name': name, - 'last_updated': last_updated, + "name": name, + "last_updated": last_updated, } return market_caps diff --git a/apis/coinmarketcap.py b/apis/coinmarketcap.py index 48b9397..c527c59 100644 --- a/apis/coinmarketcap.py +++ b/apis/coinmarketcap.py @@ -33,10 +33,10 @@ def __init__(self) -> None: """ Constructs all the necessary attributes for the CoinMarketCapAPI object. """ - source = 'coinmarketcap' + source = "coinmarketcap" super().__init__( url="https://pro-api.coinmarketcap.com/v1/cryptocurrency/listings/latest", - source=source + source=source, ) self.headers = { self.CMC_PRO_API_KEY: self.get_api_key(source), @@ -53,12 +53,8 @@ def get_data(self, N: int) -> Dict[str, Any]: Returns: Dict[str, Any]: A dictionary with data fetched from API. """ - parameters = { - self.LIMIT: N - } - response = requests.get( - self.url, headers=self.headers, params=parameters - ) + parameters = {self.LIMIT: N} + response = requests.get(self.url, headers=self.headers, params=parameters) data = response.json() return data @@ -96,12 +92,8 @@ def get_market_cap_of_token(self, id: int) -> Dict[str, float]: Dict[str, float]: A dictionary with market cap as keys and other metadata as values. """ url = "https://pro-api.coinmarketcap.com/v1/cryptocurrency/quotes/latest" - parameters = { - self.ID: id - } - response = requests.get( - url, headers=self.headers, params=parameters - ) + parameters = {self.ID: id} + response = requests.get(url, headers=self.headers, params=parameters) data = response.json() market_cap_data = {} @@ -111,9 +103,9 @@ def get_market_cap_of_token(self, id: int) -> Dict[str, float]: last_updated = token_data[self.LAST_UPDATED] market_cap = token_data[self.QUOTE][self.USD][self.MARKET_CAP] market_cap_data = { - 'name': name, - 'market_cap': market_cap, - 'last_updated': last_updated, + "name": name, + "market_cap": market_cap, + "last_updated": last_updated, } return market_cap_data @@ -131,9 +123,9 @@ def get_market_caps_of_list(self, ids: List[int]) -> Dict[str, Dict[str, Any]]: for id in ids: mcap_data = self.get_market_cap_of_token(id) if mcap_data: - market_caps[mcap_data['market_cap']] = { - 'name': mcap_data['name'], - 'last_updated': mcap_data['last_updated'] + market_caps[mcap_data["market_cap"]] = { + "name": mcap_data["name"], + "last_updated": mcap_data["last_updated"], } time.sleep(0.2) # To prevent hitting API rate limits diff --git a/apis/coinpaprika.py b/apis/coinpaprika.py index 2bfec92..173ad21 100644 --- a/apis/coinpaprika.py +++ b/apis/coinpaprika.py @@ -25,10 +25,11 @@ def __init__(self) -> None: """ Constructs all the necessary attributes for the CoinPaprikaAPI object. """ - self.ohlc_url = "https://api.coinpaprika.com/v1/coins/{coin_id}/ohlcv/latest" # noqa E501 + self.ohlc_url = ( + "https://api.coinpaprika.com/v1/coins/{coin_id}/ohlcv/latest" # noqa E501 + ) super().__init__( - url="https://api.coinpaprika.com/v1/coins", - source='coinpaprika' + url="https://api.coinpaprika.com/v1/coins", source="coinpaprika" ) @utils.handle_request_errors @@ -49,17 +50,18 @@ def get_data(self, N: int) -> List[Dict[str, Any]]: data = response.json() else: raise requests.exceptions.RequestException( - f"Received status code {response.status_code} " - f"for URL: {self.url}" + f"Received status code {response.status_code} " f"for URL: {self.url}" ) # Sorting the coins by market cap # Also filtering out coins with rank 0 (junk values in API response) - filtered_data = [coin for coin in data if coin['rank'] != 0] - sorted_data = sorted(filtered_data, key=lambda coin: coin['rank'])[:N] + filtered_data = [coin for coin in data if coin["rank"] != 0] + sorted_data = sorted(filtered_data, key=lambda coin: coin["rank"])[:N] return sorted_data @utils.handle_request_errors - def extract_market_cap(self, data: List[Dict[str, Any]]) -> Dict[float, Dict[str, Any]]: + def extract_market_cap( + self, data: List[Dict[str, Any]] + ) -> Dict[float, Dict[str, Any]]: """ Extracts market cap data from API response. @@ -87,7 +89,7 @@ def extract_market_cap(self, data: List[Dict[str, Any]]) -> Dict[float, Dict[str name = coin["name"] last_updated = 0 # Updated every 5 mins as per docs: https://api.coinpaprika.com/#tag/Coins/paths/~1coins~1%7Bcoin_id%7D~1ohlcv~1today~1/get # noqa E501 - market_cap = coin_info[0]['market_cap'] + market_cap = coin_info[0]["market_cap"] market_data[market_cap] = { "name": name, "last_updated": last_updated, diff --git a/apis/crypto_api.py b/apis/crypto_api.py index 6f9cafe..5e6aa76 100644 --- a/apis/crypto_api.py +++ b/apis/crypto_api.py @@ -20,7 +20,7 @@ class CryptoAPI: Abstract method to extract market cap data. """ - API_KEYS_FILE = 'api_keys.json' + API_KEYS_FILE = "api_keys.json" def __init__(self, url: str, source: str) -> None: """ @@ -52,9 +52,7 @@ def fetch_mcap_by_list(self, tokens: List[str]) -> Dict[str, float]: # Store market data in the database utils.create_market_cap_database() - utils.store_market_cap_data( - market_data=market_data, source=self.source - ) + utils.store_market_cap_data(market_data=market_data, source=self.source) return market_data def fetch_mcap_by_rank(self, N: int) -> dict: @@ -77,9 +75,7 @@ def fetch_mcap_by_rank(self, N: int) -> dict: # Store market data in the database utils.create_market_cap_database() - utils.store_market_cap_data( - market_data=market_data, source=self.source - ) + utils.store_market_cap_data(market_data=market_data, source=self.source) return market_data def get_data(self, N: int) -> Any: diff --git a/apis/cryptocompare.py b/apis/cryptocompare.py index 5d73c53..90acdef 100644 --- a/apis/cryptocompare.py +++ b/apis/cryptocompare.py @@ -37,7 +37,7 @@ def __init__(self) -> None: """ super().__init__( url="https://min-api.cryptocompare.com/data/top/mktcapfull", - source='cryptocompare' + source="cryptocompare", ) @utils.handle_request_errors @@ -66,8 +66,7 @@ def get_data(self, N: int, buffer: int = 2) -> Dict[str, Any]: data = response.json() else: raise requests.exceptions.RequestException( - f"Received status code {response.status_code} " - f"for URL: {self.url}" + f"Received status code {response.status_code} " f"for URL: {self.url}" ) missing_count = 0 for coin in data[self.DATA]: @@ -118,7 +117,7 @@ def get_market_caps_of_list(self, tokens: List[str]) -> Dict[str, Dict[str, Any] """ url = "https://min-api.cryptocompare.com/data/pricemultifull" tokens_upper = [token.upper() for token in tokens] - tokens_comma_sep = ','.join(tokens_upper) + tokens_comma_sep = ",".join(tokens_upper) parameters = { self.FSYMS: tokens_comma_sep, self.TSYMS: self.USD, @@ -133,7 +132,7 @@ def get_market_caps_of_list(self, tokens: List[str]) -> Dict[str, Dict[str, Any] market_cap = data[self.RAW][token][self.USD][self.MKTCAP] last_updated = data[self.RAW][token][self.USD][self.LAST_UPDATE] market_caps[market_cap] = { - 'name': token, - 'last_updated': last_updated, + "name": token, + "last_updated": last_updated, } return market_caps diff --git a/apis/unisat.py b/apis/unisat.py index 5897dc6..d38fd1f 100644 --- a/apis/unisat.py +++ b/apis/unisat.py @@ -7,22 +7,164 @@ # import json # from pathlib import Path -# Adapted from: +# Adapted from: # https://docs.unisat.io/dev/unisat-developer-service/ # https://open-api.unisat.io/swagger.html +# Headers +headers = { + "accept": "application/json", + "Authorization": "Bearer 593b09946ab4c0749af07064803c7868c179e86162bf94c4b23a2b157f67c967", +} + +URL = "https://open-api.unisat.io/v1/indexer/" + + +def get_blockchain_info(): + url = URL + "blockchain/info" + response = requests.get(url, headers=headers) + return response + + +def get_block_txs(height): + url = URL + f"block/{height}/txs" + response = requests.get(url, headers=headers) + return response + + +def get_tx_info(txid): + url = URL + f"tx/{txid}" + response = requests.get(url, headers=headers) + return response + + +def get_inscription_utxo(address): + url = URL + f"address/{address}/inscription-utxo-data" + response = requests.get(url, headers=headers) + return response + + +def get_inscription_info(inscriptionid): + url = URL + f"inscription/info/{inscriptionid}" + response = requests.get(url, headers=headers) + return response + + +def get_brc20_list(start=0, limit=100): + url = URL + "brc20/list" + f"?start={start}&limit={limit}" + response = requests.get(url, headers=headers) + return response + + +def get_brc20_status(start=0, limit=10, sort="holders", complete="yes"): + """ + sort by (holders/deploy/minted/transactions) + filter by (yes/no) + """ + url = ( + URL + + "brc20/status" + + f"?start={start}&limit={limit}&sort={sort}&complete={complete}" + ) + response = requests.get(url, headers=headers) + return response + + +def get_brc20_ticker_info(ticker): + url = URL + f"brc20/{ticker}/info" + response = requests.get(url, headers=headers) + return response + + +def get_brc20_holders(ticker): + url = URL + f"brc20/{ticker}/holders" + response = requests.get(url, headers=headers) + return response + + +def get_brc20_ticker_history(ticker, txid, type, start=0, limit=100): + """ + type: inscribe-deploy, inscribe-mint, inscribe-transfer, transfer, send, receive + """ + url = ( + URL + f"brc20/{ticker}/tx/{txid}" + f"?type={type}&start={start}&limit={limit}" + ) + response = requests.get(url, headers=headers) + return response + + +def get_history_by_height(height, start=0, limit=100): + url = URL + f"brc20/history-by-height/{height}" + f"?start={start}&limit={limit}" + response = requests.get(url, headers=headers) + return response + + +def get_brc20_tx_history(ticker, txid, start=0, limit=100): + url = URL + f"brc20/{ticker}/tx/{txid}/history" + f"?start={start}&limit={limit}" + response = requests.get(url, headers=headers) + return response + + +def get_address_brc20_summary(address, start=0, limit=100): + url = URL + f"address/{address}/brc20/summary" + f"?start={start}&limit={limit}" + response = requests.get(url, headers=headers) + return response + + +def get_address_brc20_summary_by_height(address, height, start=0, limit=100): + url = ( + URL + + f"address/{address}/brc20/summary-by-height/{height}" + + f"?start={start}&limit={limit}" + ) + response = requests.get(url, headers=headers) + return response + + +def get_address_brc20_ticker_info(address, ticker): + url = URL + f"address/{address}/brc20/{ticker}/info" + response = requests.get(url, headers=headers) + return response + + +def get_address_brc20_history(address, start=0, limit=100): + url = URL + f"address/{address}/brc20/history" + f"?start={start}&limit={limit}" + response = requests.get(url, headers=headers) + return response + + +def get_address_brc20_history_by_ticker(address, ticker, type, start=0, limit=100): + """ + type: inscribe-deploy, inscribe-mint, inscribe-transfer, transfer, send, receive + """ + url = ( + URL + + f"address/{address}/brc20/{ticker}/history" + + f"?type={type}&start={start}&limit={limit}" + ) + response = requests.get(url, headers=headers) + return response + + +def get_transferable_inscriptions(address, ticker): + url = URL + f"address/{address}/brc20/{ticker}/transferable-inscriptions" + response = requests.get(url, headers=headers) + return response + + # Load environment variables from .env file load_dotenv() + + class UnisatAPI: - def __init__(self): - api_key = os.environ.get('UNISAT_API_KEY') + api_key = os.environ.get("UNISAT_API_KEY") if api_key is None: - raise ValueError('UNISAT_API_KEY environment variable is not set') - self.base_url = 'https://open-api.unisat.io/v1/indexer/' + raise ValueError("UNISAT_API_KEY environment variable is not set") + self.base_url = "https://open-api.unisat.io/v1/indexer/" self.headers = { - 'accept': 'application/json', - 'Authorization': f'Bearer {api_key}' + "accept": "application/json", + "Authorization": f"Bearer {api_key}", } self.api_key = api_key @@ -30,85 +172,112 @@ def _make_request(self, endpoint, params=None): url = self.base_url + endpoint response = requests.get(url, headers=self.headers, params=params) return response - + def get_best_block_height(self): - return self._make_request('brc20/bestheight') + return self._make_request("brc20/bestheight") def get_blockchain_info(self): - return self._make_request('blockchain/info') + return self._make_request("blockchain/info") def get_block_txs(self, height): - return self._make_request(f'block/{height}/txs') + return self._make_request(f"block/{height}/txs") def get_tx_info(self, txid): - return self._make_request(f'tx/{txid}') + return self._make_request(f"tx/{txid}") def get_inscription_utxo(self, address): - return self._make_request(f'address/{address}/inscription-utxo-data') + return self._make_request(f"address/{address}/inscription-utxo-data") def get_inscription_info(self, inscriptionId): - return self._make_request(f'inscription/info/{inscriptionId}') + return self._make_request(f"inscription/info/{inscriptionId}") def get_brc20_list(self, start=0, limit=100): - return self._make_request(f'brc20/list', {'start': start, 'limit': limit}) + return self._make_request(f"brc20/list", {"start": start, "limit": limit}) - def get_brc20_status(self, start=0, limit=10, sort='holders', complete='yes'): - ''' + def get_brc20_status(self, start=0, limit=10, sort="holders", complete="yes"): + """ sort by (holders/deploy/minted/transactions) - filter by (yes/no) - ''' - return self._make_request(f'brc20/status', {'start': start, 'limit': limit, 'sort': sort, 'complete': complete}) + filter by (yes/no) + """ + return self._make_request( + f"brc20/status", + {"start": start, "limit": limit, "sort": sort, "complete": complete}, + ) def get_brc20_ticker_info(self, ticker): - return self._make_request(f'brc20/{ticker}/info') + return self._make_request(f"brc20/{ticker}/info") def get_brc20_holders(self, ticker): - return self._make_request(f'brc20/{ticker}/holders') + return self._make_request(f"brc20/{ticker}/holders") def get_brc20_ticker_history(self, ticker, height, type, start=0, limit=100): - ''' - type: inscribe-deploy, inscribe-mint, inscribe-transfer, transfer, send, receive - ''' - return self._make_request(f'brc20/{ticker}/history', {'type': type, 'start': start, 'height': height, 'limit': limit}) + """ + type: inscribe-deploy, inscribe-mint, inscribe-transfer, transfer, send, receive + """ + return self._make_request( + f"brc20/{ticker}/history", + {"type": type, "start": start, "height": height, "limit": limit}, + ) def get_history_by_height(self, height, start=0, limit=100): - return self._make_request(f'brc20/history-by-height/{height}', {'start': start, 'limit': limit}) + return self._make_request( + f"brc20/history-by-height/{height}", {"start": start, "limit": limit} + ) def get_brc20_tx_history(self, ticker, txid, type, start=0, limit=100): - return self._make_request(f'brc20/{ticker}/tx/{txid}/history', {'type': type, 'start': start, 'limit': limit}) + return self._make_request( + f"brc20/{ticker}/tx/{txid}/history", + {"type": type, "start": start, "limit": limit}, + ) def get_address_brc20_summary(self, address, start=0, limit=100): - return self._make_request(f'address/{address}/brc20/summary', {'start': start, 'limit': limit}) + return self._make_request( + f"address/{address}/brc20/summary", {"start": start, "limit": limit} + ) def get_address_brc20_summary_by_height(self, address, height, start=0, limit=100): - return self._make_request(f'address/{address}/brc20/summary-by-height/{height}', {'start': start, 'limit': limit}) + return self._make_request( + f"address/{address}/brc20/summary-by-height/{height}", + {"start": start, "limit": limit}, + ) def get_address_brc20_ticker_info(self, address, ticker): - return self._make_request(f'address/{address}/brc20/{ticker}/info') + return self._make_request(f"address/{address}/brc20/{ticker}/info") def get_address_brc20_history(self, address, start=0, limit=100): - return self._make_request(f'address/{address}/brc20/history', {'start': start, 'limit': limit}) + return self._make_request( + f"address/{address}/brc20/history", {"start": start, "limit": limit} + ) - def get_address_brc20_history_by_ticker(self, address, ticker, type, start=0, limit=100): - ''' + def get_address_brc20_history_by_ticker( + self, address, ticker, type, start=0, limit=100 + ): + """ type: inscribe-deploy, inscribe-mint, inscribe-transfer, transfer, send, receive - ''' - return self._make_request(f'address/{address}/brc20/{ticker}/history', {'type': type, 'start': start, 'limit': limit}) + """ + return self._make_request( + f"address/{address}/brc20/{ticker}/history", + {"type": type, "start": start, "limit": limit}, + ) def get_transferable_inscriptions(self, address, ticker): - return self._make_request(f'address/{address}/brc20/{ticker}/transferable-inscriptions') - + return self._make_request( + f"address/{address}/brc20/{ticker}/transferable-inscriptions" + ) + + def main(): unisat_api = UnisatAPI() # print(unisat_api.get_best_block_height().json()) response = unisat_api.get_brc20_ticker_history("ordi", 826827, "inscribe-transfer") print(response.json()["data"]) parent_directory = os.path.dirname(os.path.abspath(__file__)) - json_directory = os.path.join(parent_directory, 'json') + json_directory = os.path.join(parent_directory, "json") os.makedirs(json_directory, exist_ok=True) - json_file_path = os.path.join(json_directory, 'get_brc20_tx_history.json') - with open(json_file_path, 'w') as file: + json_file_path = os.path.join(json_directory, "get_brc20_tx_history.json") + with open(json_file_path, "w") as file: json.dump(response.json()["data"], file, indent=4) + if __name__ == "__main__": - main() \ No newline at end of file + main() diff --git a/apis/utils.py b/apis/utils.py index 3455764..63ba715 100644 --- a/apis/utils.py +++ b/apis/utils.py @@ -10,6 +10,7 @@ class MissingDataException(Exception): """Raised when the expected data is missing in an API response""" + pass @@ -18,13 +19,11 @@ def convert_timestamp_to_unixtime(timestamp): Takes a timestamp e.g. '2022-08-11T09:10:12.364Z' and returns a unix time 1660209012.364 """ - unix_datetime = datetime.datetime.strptime( - timestamp, '%Y-%m-%dT%H:%M:%S.%f%z' - ) + unix_datetime = datetime.datetime.strptime(timestamp, "%Y-%m-%dT%H:%M:%S.%f%z") return unix_datetime.timestamp() -def create_market_cap_database(db_path: str = 'data.db') -> None: +def create_market_cap_database(db_path: str = "data.db") -> None: """ Creates a SQLite database (if not exists) to store market cap data. @@ -45,8 +44,7 @@ def create_market_cap_database(db_path: str = 'data.db') -> None: def store_market_cap_data( - market_data: Dict[float, Dict[str, Any]], - source: str, db_path: str = 'data.db' + market_data: Dict[float, Dict[str, Any]], source: str, db_path: str = "data.db" ) -> None: """ Stores market cap data into the SQLite database. @@ -62,14 +60,13 @@ def store_market_cap_data( cursor.execute( "INSERT INTO market_cap_data (name, market_cap, last_updated_time, load_time, source)" "VALUES (?, ?, ?, ?, ?)", - (md['name'], market_cap, md['last_updated'], int(time.time()), source)) + (md["name"], market_cap, md["last_updated"], int(time.time()), source), + ) conn.commit() conn.close() -def handle_request_errors( - func: Callable[..., Any] -) -> Callable[..., Optional[Any]]: +def handle_request_errors(func: Callable[..., Any]) -> Callable[..., Optional[Any]]: """ Decorator function to handle request errors. @@ -79,6 +76,7 @@ def handle_request_errors( Returns: Callable[..., Optional[Any]]: The decorated function. """ + @wraps(func) def wrapper(*args, **kwargs): try: @@ -87,6 +85,7 @@ def wrapper(*args, **kwargs): print("Error occurred while making the API request:", str(e)) print("Warning: Continuing with the rest of the execution.") return None + return wrapper diff --git a/constants.py b/constants.py index f773c56..2546a17 100644 --- a/constants.py +++ b/constants.py @@ -3,98 +3,111 @@ from datetime import datetime from pathlib import Path -DEBUG = True #show debug messages in CLI +DEBUG = True # show debug messages in CLI WEBSERVER_THREADS = 1 -HEADER = '\033[95m' -OKBLUE = '\033[94m' -OKCYAN = '\033[96m' -OKGREEN = '\033[92m' -WARNING = '\033[93m' -FAIL = '\033[91m' -ENDC = '\033[0m' -BOLD = '\033[1m' -UNDERLINE = '\033[4m' -NOUNDERLINE = '\033[0m' - -DATA_DIR = 'data' -TEST_DIR = 'test' -LOGGING_FILE = 'data_feeds.db' -DATEFORMAT = '%Y-%m-%d %H:%M:%S.%f %z' -DATA_EXT = '.csv' -LINE_START = '>' - -FEED_NAME = 'feed_name' -DATA_POINT = 'data_point' -TIME_STAMP = 'time_stamp' +HEADER = "\033[95m" +OKBLUE = "\033[94m" +OKCYAN = "\033[96m" +OKGREEN = "\033[92m" +WARNING = "\033[93m" +FAIL = "\033[91m" +ENDC = "\033[0m" +BOLD = "\033[1m" +UNDERLINE = "\033[4m" +NOUNDERLINE = "\033[0m" + +DATA_DIR = "data" +TEST_DIR = "test" +LOGGING_FILE = "data_feeds.db" +DATEFORMAT = "%Y-%m-%d %H:%M:%S.%f %z" +DATA_EXT = ".csv" +LINE_START = ">" + +FEED_NAME = "feed_name" +DATA_POINT = "data_point" +TIME_STAMP = "time_stamp" PROJECT_PATH = Path(os.path.dirname(os.path.realpath(__file__))) DATA_PATH = PROJECT_PATH / DATA_DIR TEST_PATH = PROJECT_PATH / TEST_DIR LOGGING_PATH = DATA_PATH / LOGGING_FILE -LOGGING_FORMAT = ('%(asctime)s:%(thread)d - %(name)s - %(levelname)s - %(message)s') +LOGGING_FORMAT = "%(asctime)s:%(thread)d - %(name)s - %(levelname)s - %(message)s" + def start_message(feed): - return f'\n{HEADER}Starting {UNDERLINE}{feed.NAME}{NOUNDERLINE} {HEADER}data feed!{ENDC}' + return f"\n{HEADER}Starting {UNDERLINE}{feed.NAME}{NOUNDERLINE} {HEADER}data feed!{ENDC}" + def stop_message(feed): - return f'\n{OKCYAN}Shutting down {UNDERLINE}{feed.NAME}{NOUNDERLINE} {OKCYAN}...{ENDC}' + return ( + f"\n{OKCYAN}Shutting down {UNDERLINE}{feed.NAME}{NOUNDERLINE} {OKCYAN}...{ENDC}" + ) + def init_time_message(cls): - return f'\nSiwa init time: {datetime.fromtimestamp(cls.init_time).strftime(DATEFORMAT)}' + return f"\nSiwa init time: {datetime.fromtimestamp(cls.init_time).strftime(DATEFORMAT)}" + get_color = lambda x: OKGREEN if x else FAIL -get_word = lambda x: '' if x else 'not ' +get_word = lambda x: "" if x else "not " + def get_starttime_string(feed): - if (hasattr(feed, 'START_TIME') and feed.START_TIME): - #ensure START_TIME exists and is not None before trying to convert + if hasattr(feed, "START_TIME") and feed.START_TIME: + # ensure START_TIME exists and is not None before trying to convert dt_from_timestamp = datetime.fromtimestamp(feed.START_TIME) human_readable_time_str = dt_from_timestamp.strftime(DATEFORMAT) - return f'{human_readable_time_str}' + return f"{human_readable_time_str}" else: - #if START_TIME not initialized (i.e. because "start gauss" not issued yet) - #(e.g. when calling `status` command before having ever started a feed) - return f'[NEVER]' + # if START_TIME not initialized (i.e. because "start gauss" not issued yet) + # (e.g. when calling `status` command before having ever started a feed) + return f"[NEVER]" + def status_message(feed): x = feed.ACTIVE - return f'{get_color(x)}{feed.NAME}{ENDC} with id {feed.ID} is {get_word(x)}active, with {feed.COUNT} data points served since {get_starttime_string(feed)}' + return f"{get_color(x)}{feed.NAME}{ENDC} with id {feed.ID} is {get_word(x)}active, with {feed.COUNT} data points served since {get_starttime_string(feed)}" + #################### COINGECKo#################### -PRICE = 'current_price' +PRICE = "current_price" -#ids -USDC = 'usd-coin' -BUSD = 'binance-usd' -TETHER = 'tether' -DAI = 'dai' -DOGE = 'dogecoin' -SHIBA = 'shiba-inu' -BABYDOGE = 'baby-doge-coin' -DOGELON = 'dogelon-mars' -SHIBASWAP = 'bone-shibaswap' +# ids +USDC = "usd-coin" +BUSD = "binance-usd" +TETHER = "tether" +DAI = "dai" +DOGE = "dogecoin" +SHIBA = "shiba-inu" +BABYDOGE = "baby-doge-coin" +DOGELON = "dogelon-mars" +SHIBASWAP = "bone-shibaswap" #################### WEB3 #################### -#CHAINS -ARBITRUM_GOERLI = 'arbitrum_goerli' -ARBITRUM_MAINNET = 'arbitrum_mainnet' -ETHEREUM_MAINNET = 'ethereum_mainnet' +# CHAINS +ARBITRUM_GOERLI = "arbitrum_goerli" +ARBITRUM_MAINNET = "arbitrum_mainnet" +ETHEREUM_MAINNET = "ethereum_mainnet" # POKT -POKT_PORTAL_ID = 'a609ace3fe0c00927e127927' -POKT_ARBITRUM = 'arbitrum-one' -POKT_ETHEREUM = 'eth-mainnet' +POKT_PORTAL_ID = "a609ace3fe0c00927e127927" +POKT_ARBITRUM = "arbitrum-one" +POKT_ETHEREUM = "eth-mainnet" # RPC Endpoints -ARBITRUM_GOERLI_RPC = 'https://goerli-rollup.arbitrum.io/rpc' -ARBITRUM_MAINNET_RPC = f'https://{POKT_ARBITRUM}.gateway.pokt.network/v1/lb/{POKT_PORTAL_ID}' -ETHEREUM_MAINNET_RPC = f'https://{POKT_ETHEREUM}.gateway.pokt.network/v1/lb/{POKT_PORTAL_ID}' +ARBITRUM_GOERLI_RPC = "https://goerli-rollup.arbitrum.io/rpc" +ARBITRUM_MAINNET_RPC = ( + f"https://{POKT_ARBITRUM}.gateway.pokt.network/v1/lb/{POKT_PORTAL_ID}" +) +ETHEREUM_MAINNET_RPC = ( + f"https://{POKT_ETHEREUM}.gateway.pokt.network/v1/lb/{POKT_PORTAL_ID}" +) # Addresses: -TRANSLUCENT_GAUSS_ARBITRUM_GOERLI = '0xB39AC20b8b0C840a863ceB58A29b597022d98Bf5'#'0x77f85f243dCd2A69F20c2A98F1ef993DC4492A51' +TRANSLUCENT_GAUSS_ARBITRUM_GOERLI = "0xB39AC20b8b0C840a863ceB58A29b597022d98Bf5" #'0x77f85f243dCd2A69F20c2A98F1ef993DC4492A51' # TRANSLUCENT_GAUSS_ARBITRUM_MAINNET = None # ABIs below diff --git a/exchanges/__init__.py b/exchanges/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/exchanges/constants/__init__.py b/exchanges/constants/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/exchanges/constants/urls.py b/exchanges/constants/urls.py new file mode 100644 index 0000000..f0627c6 --- /dev/null +++ b/exchanges/constants/urls.py @@ -0,0 +1,6 @@ +BINANCE_API_OPTIONS_URL = "https://eapi.binance.com" +BINANCE_API_FUTURES_URL = "https://fapi.binance.com" +BINANCE_API_SPOT_URL = "https://api.binance.com" +ByBit_API_URL = "https://api.bybit.com/v2/public/symbols" +OKX_API_URL = "https://www.okex.com/api/spot/v3/instruments" +KRAKEN_API_URL = "https://api.kraken.com/0/public/AssetPairs" diff --git a/exchanges/constants/utils.py b/exchanges/constants/utils.py new file mode 100644 index 0000000..fd16dc9 --- /dev/null +++ b/exchanges/constants/utils.py @@ -0,0 +1,5 @@ +DEBUG_LIMIT = None # None or int value +SPREAD_MULTIPLIER = 10 +SPREAD_MIN = 0.0005 +RANGE_MULT = 2.5 +Index_Maturity = 30 / 365 diff --git a/exchanges/exchange_manager.py b/exchanges/exchange_manager.py new file mode 100644 index 0000000..da5d8c9 --- /dev/null +++ b/exchanges/exchange_manager.py @@ -0,0 +1,77 @@ +import json +from typing import Tuple + +import ccxt +import logging + +import pandas as pd +from pandas import DataFrame + +from exchanges.fetchers.binance_fetcher import BinanceFetcher +from exchanges.handlers.future_and_options_handler import MergeMarketHandler + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +class ExchangeManager: + def __init__(self, exchange_id, pairs_to_load, market_types): + self.exchange_id = exchange_id + self.pairs_to_load = pairs_to_load + self.market_types = market_types + self.exchange = getattr(ccxt, exchange_id)() + self.binance_fetcher = BinanceFetcher() + self.merge_market_handler = MergeMarketHandler(self.exchange, market_types) + self.options_data = pd.DataFrame() + self.futures_data = pd.DataFrame() + + def fetch_binance_symbols(self): + binance_option_symbols = self.binance_fetcher.fetch_options_symbols() + return binance_option_symbols + + def load_specific_pairs(self) -> tuple[DataFrame, DataFrame] | None | DataFrame: + try: + if self.exchange_id == "binance": + binance_option_symbols = self.fetch_binance_symbols() + data = { + "BTC/USD:BTC": { + "option": binance_option_symbols, + "future": None, + } + } + return self.handle_market_type(data) + + all_markets = self.exchange.load_markets() + markets_df = pd.DataFrame(all_markets).T + filtered_markets = self.filter_markets(markets_df) + return self.handle_market_type(filtered_markets) + except Exception as e: + logger.error(f"Error loading specific pairs: {e}") + return pd.DataFrame() + + def filter_markets(self, markets_df: pd.DataFrame) -> dict: + filtered_markets = {} + for pair in self.pairs_to_load: + base, quote = pair.split(":")[0].split("/") + for market_type in self.market_types: + filtered_df = markets_df[ + (markets_df["base"] == base) + & (markets_df["quote"] == quote) + & (markets_df["type"] == market_type) + ] + symbols = filtered_df["symbol"].tolist() + if pair not in filtered_markets: + filtered_markets[pair] = {} + filtered_markets[pair][market_type] = symbols + return filtered_markets + + def handle_market_type( + self, loaded_markets: dict + ) -> tuple[DataFrame, DataFrame] | None: + dataframe = None + for pair in self.pairs_to_load: + future_symbols = loaded_markets.get(pair, {}).get("future", []) + option_symbols = loaded_markets.get(pair, {}).get("option", []) + dataframe = self.merge_market_handler.handle(option_symbols, future_symbols) + + return dataframe diff --git a/exchanges/fetchers/binance_fetcher.py b/exchanges/fetchers/binance_fetcher.py new file mode 100644 index 0000000..f96a4f9 --- /dev/null +++ b/exchanges/fetchers/binance_fetcher.py @@ -0,0 +1,118 @@ +import pandas as pd + +from exchanges.constants.urls import ( + BINANCE_API_OPTIONS_URL, + BINANCE_API_FUTURES_URL, + BINANCE_API_SPOT_URL, +) + +import logging +import requests + +# Assuming BINANCE_API_OPTIONS_URL and BINANCE_API_FUTURES_URL are defined elsewhere + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +class BinanceFetcher: + @staticmethod + def get_response(url): + try: + with requests.Session() as session: + response = session.get(url) + if response.status_code == 200: + return response.json() + else: + logger.error( + f"Failed to fetch data from {url}: {response.status_code}" + ) + return None + except Exception as e: + logger.error(f"Exception occurred while fetching data from {url}: {e}") + return None + + @staticmethod + def fetch_options_symbols(): + data = BinanceFetcher.get_response( + BINANCE_API_OPTIONS_URL + "/eapi/v1/exchangeInfo" + )["optionSymbols"] + data_df = pd.DataFrame(data) + # all symbols with BTC- + symbols = data_df["symbol"].loc[data_df["symbol"].str.contains("BTC-")] + return symbols.tolist() + + @staticmethod + def fetch_futures_symbols(): + url = f"{BINANCE_API_FUTURES_URL}/fapi/v1/premiumIndex" + data = BinanceFetcher.get_response(url) + if data: + return [ + res["symbol"] for res in data if "BTCUSDT_" in res.get("symbol", "") + ] + return [] + + @staticmethod + def fetch_mark_price_futures(): + symbols = BinanceFetcher.fetch_futures_symbols() + mark_prices = [] # This will hold dictionaries + for symbol in symbols: + data = BinanceFetcher.get_response( + BINANCE_API_FUTURES_URL + f"/fapi/v1/depth?symbol={symbol}" + ) + + bids_df = pd.DataFrame(data["bids"], columns=["price", "quantity"]).astype( + {"price": "float"} + ) + asks_df = pd.DataFrame(data["asks"], columns=["price", "quantity"]).astype( + {"price": "float"} + ) + + # Get maximum bid and minimum ask + best_bid = bids_df["price"].max() + best_ask = asks_df["price"].min() + + forward_price = (best_bid + best_ask) / 2 + expiry = symbol.split("_")[1] + + mark_prices.append( + { + "symbol": symbol, + "forward_price": forward_price, + "expiry": expiry, + } + ) + + mark_prices_df = pd.DataFrame(mark_prices) + return mark_prices_df + + @staticmethod + def fetch_mark_price_options(): + mark_prices_options = BinanceFetcher.get_response( + BINANCE_API_OPTIONS_URL + "/eapi/v1/mark" + ) + mark_prices_options_df = pd.DataFrame(mark_prices_options) + mark_prices_options_df = mark_prices_options_df.loc[ + mark_prices_options_df["symbol"].str.contains("BTC-") + ] + + return mark_prices_options_df + + @staticmethod + def fetch_mark_price_options(): + mark_prices_options = BinanceFetcher.get_response( + BINANCE_API_OPTIONS_URL + "/eapi/v1/mark" + ) + mark_prices_options_df = pd.DataFrame(mark_prices_options) + mark_prices_options_df = mark_prices_options_df.loc[ + mark_prices_options_df["symbol"].str.contains("BTC-") + ] + + return mark_prices_options_df + + @staticmethod + def fetch_spot_price(symbol: str = "BTCUSDT"): + spot_price = BinanceFetcher.get_response( + BINANCE_API_SPOT_URL + f"/api/v3/ticker/price?symbol={symbol}" + ) + return float(spot_price["price"]) diff --git a/exchanges/fetchers/future_fetcher.py b/exchanges/fetchers/future_fetcher.py new file mode 100644 index 0000000..3285514 --- /dev/null +++ b/exchanges/fetchers/future_fetcher.py @@ -0,0 +1,79 @@ +from datetime import datetime +import ccxt +import numpy as np +import pandas as pd + + +class FutureFetcher: + def __init__(self, exchange): + self.exchange = exchange + + def fetch_future_market_symbols(self, symbol: str) -> list[str]: + load_markets = self.exchange.load_markets() + load_markets_df = pd.DataFrame(load_markets).transpose() + future_symbols = load_markets_df[ + (load_markets_df["future"] == True) + & (load_markets_df["symbol"].str.contains(f"{symbol}/USD")) + & (load_markets_df["symbol"].str.contains(f":{symbol}")) + ].index.to_list() + return future_symbols + + def fetch_future_orderbook(self, symbol: str) -> dict: + order_book = self.exchange.fetch_order_book(symbol) + bids_df = pd.DataFrame( + order_book["bids"], columns=["price", "quantity"] + ).astype({"price": "float"}) + asks_df = pd.DataFrame( + order_book["asks"], columns=["price", "quantity"] + ).astype({"price": "float"}) + best_bid = bids_df["price"].max() + best_ask = asks_df["price"].min() + + forward_price = (best_bid + best_ask) / 2 + expiry = symbol.split("-")[1] + return { + "symbol": symbol, + "forward_price": forward_price, + "expiry": expiry, + } + + def fetch_spot_price(self, symbol: str = "BTC/USDT"): + ticker = self.exchange.fetch_ticker(symbol) + return ticker["last"] + + def fetch_implied_interest_rate(self, symbol: str) -> dict: + orderbook = self.fetch_future_orderbook(symbol) + forward_price = orderbook["forward_price"] + expiry_str = orderbook["expiry"] + + expiry_date = datetime.strptime(expiry_str, "%y%m%d") # Corrected format here + today = datetime.now() + days_to_expiry = (expiry_date - today).days + years_to_expiry = days_to_expiry / 365.25 + + spot_price = self.fetch_spot_price() + + if years_to_expiry == 0: + implied_interest_rate = 0 + else: + implied_interest_rate = ( + np.log(forward_price) - np.log(spot_price) + ) / years_to_expiry + + return { + "symbol": symbol, + "expiry": expiry_str, + "implied_interest_rate": implied_interest_rate, + "days_to_expiry": days_to_expiry, + "years_to_expiry": years_to_expiry, + } + + def fetch_all_implied_interest_rates(self, symbols: list[str]) -> pd.DataFrame: + data = [self.fetch_implied_interest_rate(symbol) for symbol in symbols] + rates_data = pd.DataFrame(data) + + rates_data["expiry"] = pd.to_datetime(rates_data["expiry"], format="%y%m%d") + # expiry in human readable format + rates_data["expiry"] = rates_data["expiry"].dt.strftime("%Y-%m-%d") + + return rates_data diff --git a/exchanges/fetchers/option_fetcher.py b/exchanges/fetchers/option_fetcher.py new file mode 100644 index 0000000..1e998b5 --- /dev/null +++ b/exchanges/fetchers/option_fetcher.py @@ -0,0 +1,161 @@ +import logging +from datetime import time, datetime + +import ccxt +import numpy as np +import pandas as pd +import requests +from pandas import Timestamp +from pandas._libs import NaTType + +from exchanges.fetchers.binance_fetcher import BinanceFetcher + + +class OptionFetcher: + def __init__(self, exchange): + self.exchange = exchange + self.binance_fetcher = BinanceFetcher() + + def fetch_market_data( + self, market_symbols: list[str], exchange_name: str + ) -> pd.DataFrame: + """ + Fetches market data for a given list of market symbols from a specified exchange and processes it using pandas. + Args: + market_symbols: A list of symbols in the format recognized by the exchange. + exchange_name: String representing the exchange name ('deribit', 'okx', 'binance'). + Returns: + pd.DataFrame: DataFrame with processed market data for each option contract. + """ + try: + all_tickers = self.exchange.fetch_tickers(market_symbols) + tickers_df = pd.DataFrame(all_tickers).transpose() + if exchange_name == "Deribit": + return self.process_deribit_data(tickers_df) + elif exchange_name == "OKX": + return self.process_okx_data(tickers_df) + elif exchange_name == "Binance": + return self.process_binance_data(tickers_df) + else: + logging.error(f"Unsupported exchange: {exchange_name}") + return pd.DataFrame() + except Exception as e: + logging.error(f"Error fetching tickers from {exchange_name}: {e}") + return pd.DataFrame() + + def process_deribit_data(self, df: pd.DataFrame) -> pd.DataFrame: + info_df = pd.json_normalize(df["info"]) + df = df.reset_index(drop=True) + + df["bid"] = pd.to_numeric(df["bid"], errors="coerce").fillna(0.0) + df["ask"] = pd.to_numeric(df["ask"], errors="coerce").fillna(0.0) + + df["mark_price"] = pd.to_numeric(info_df["mark_price"], errors="coerce").fillna( + 0.0 + ) + + underlying_prices = pd.to_numeric( + info_df["underlying_price"], errors="coerce" + ).fillna(0.0) + + df["bid"] *= underlying_prices + df["ask"] *= underlying_prices + df["mark_price"] *= underlying_prices + + return df[ + [ + "symbol", + "bid", + "ask", + "mark_price", + ] + ] + + def process_okx_data(self, df: pd.DataFrame) -> pd.DataFrame: + response = requests.get( + "https://www.okx.com/api/v5/public/mark-price?instType=OPTION" + ) + mark_prices = response.json()["data"] + mark_prices_df = pd.DataFrame(mark_prices) + mark_prices_df["symbol"] = mark_prices_df["instId"].apply( + self.convert_inst_id_to_symbol + ) + mark_prices_df.rename(columns={"markPx": "mark_price"}, inplace=True) + df["underlying_price"] = self.exchange.fetch_ticker("BTC/USDT")["last"] + df["bid"] *= df["underlying_price"] + df["ask"] *= df["underlying_price"] + + df = df.merge(mark_prices_df[["symbol", "mark_price"]], on="symbol", how="left") + df["mark_price"] = pd.to_numeric(df["mark_price"], errors="coerce").fillna(0.0) + df["mark_price"] *= df["underlying_price"] + + return df[ + [ + "symbol", + "bid", + "ask", + "mark_price", + ] + ] + + def process_binance_data(self, df: pd.DataFrame) -> pd.DataFrame: + df["symbol"] = df["symbol"].apply(self.convert_usdt_to_usd) + df["bid"] = df["info"].apply(lambda x: float(x.get("bidPrice", 0))) + df["ask"] = df["info"].apply(lambda x: float(x.get("askPrice", 0))) + + mark_price = self.binance_fetcher.fetch_mark_price_options() + mark_price["symbol"] = mark_price["symbol"].apply(self.transform_symbol_format) + mark_price.rename(columns={"markPrice": "mark_price"}, inplace=True) + mark_price["mark_price"] = pd.to_numeric( + mark_price["mark_price"], errors="coerce" + ).fillna(0.0) + + df = df.merge(mark_price, on="symbol", how="left") + + return df[ + [ + "symbol", + "bid", + "ask", + "mark_price", + ] + ] + + @staticmethod + def convert_inst_id_to_symbol(inst_id: str) -> str: + parts = inst_id.split("-") + currency = f"{parts[0]}/{parts[1]}" # e.g., BTC/USD + date = parts[2][:2] + parts[2][2:4] + parts[2][4:] # Reformat date + strike_price = parts[3] + option_type = parts[4] + + symbol = f"{currency}:{parts[0]}-{date}-{strike_price}-{option_type}" + return symbol + + @staticmethod + def transform_symbol_format(symbol): + parts = symbol.split("-") + return f"{parts[0]}/USD:USD-{parts[1]}-{parts[2]}-{parts[3]}" + + @staticmethod + def convert_usdt_to_usd(symbol: str) -> str: + parts = symbol.split(":") + converted_parts = [part.replace("USDT", "USD") for part in parts] + converted_symbol = ":".join(converted_parts) + return converted_symbol + + @staticmethod + def get_strike_price_and_option_type(symbol: str) -> tuple[str, str]: + parts = symbol.split("-") + strike_price = parts[-2] + option_type = parts[-1] + return strike_price, option_type + + +if __name__ == "__main__": + exchange = ccxt.okx() + option_fetcher = OptionFetcher(exchange) + market_symbols = ["BTC-240329-15000-P", "BTC-240329-20000-C"] + exchange_name = "OKX" + option_fetcher.fetch_market_data(market_symbols, exchange_name) + print("Market data fetched and processed successfully!") diff --git a/exchanges/filtering.py b/exchanges/filtering.py new file mode 100644 index 0000000..2a246c6 --- /dev/null +++ b/exchanges/filtering.py @@ -0,0 +1,269 @@ +class Filtering: + def __init__(self, options_data): + self.options_data = options_data + # self.F = F + # self.RANGE_MULT = RANGE_MULT + # self.minimum_bid_threshold = minimum_bid_threshold + self.Fimp = None + self.K_ATM = None + + def calculate_Fimp(self, call_data, put_data): + """ + Calculate the implied forward price based on call and put option data. + + Parameters: + call_data (list): List of call option data. + put_data (list): List of put option data. + + Returns: + float: Implied forward price. + """ + if not call_data or not put_data: + return 0 + + implied_forward_price = None + + for call_option in call_data: + call_price = call_option.get("mid_price") + if call_price is None: + continue + + min_price_diff = float("inf") + selected_put_option = None + + for put_option in put_data: + put_price = put_option.get("mid_price") + if put_price is None: + continue + + price_diff = abs(call_price - put_price) + if price_diff < min_price_diff: + min_price_diff = price_diff + selected_put_option = put_option + + if selected_put_option is not None: + strike_price = self.find_min_difference_strike(call_data, put_data) + forward_price = self.calculate_forward_price(call_option, put_option) + implied_forward_price = strike_price + forward_price * ( + call_price - put_price + ) + break + + return implied_forward_price if implied_forward_price is not None else 0 + + def extract_strike_price(self, option_symbol): + """ + Extract the strike price from the option symbol. + + Parameters: + option_symbol (str): Symbol representing the option. + + Returns: + float: Strike price. + """ + symbol_parts = option_symbol.split("-") + if len(symbol_parts) < 3: + return 0 + + strike_price_str = symbol_parts[-2] + + try: + strike_price = float(strike_price_str) + return strike_price + except ValueError: + return 0 + + def calculate_forward_price(self, call_option, put_option): + """ + Calculate the forward price based on call and put option data. + + Parameters: + call_option (dict): Call option data. + put_option (dict): Put option data. + + Returns: + float: Forward price. + """ + call_price = call_option.get("mark_price") + put_price = put_option.get("mark_price") + + if call_price is None or put_price is None: + return 0 + + average_mark_price = (call_price + put_price) / 2 + return average_mark_price + + def find_min_difference_strike(self, call_data, put_data): + """ + Find the strike price with the minimum difference in mid prices between call and put options. + + Parameters: + call_data (list): List of call option data. + put_data (list): List of put option data. + + Returns: + float: Strike price with the minimum price difference. + """ + min_diff_strike = None + min_price_diff = float("inf") + + for call_option in call_data: + call_price = call_option.get("mid_price") + if call_price is None: + continue + + for put_option in put_data: + put_price = put_option.get("mid_price") + if put_price is None: + continue + + price_diff = abs(call_price - put_price) + if price_diff < min_price_diff: + min_price_diff = price_diff + min_diff_strike = self.extract_strike_price( + call_option.get("symbol") + ) + + return min_diff_strike + + def set_ATM_strike(self, call_data, put_data): + """ + Find the strike price with the minimum difference in mid prices between call and put options. + + Parameters: + call_data (list): List of call option data. + put_data (list): List of put option data. + + Returns: + float: Strike price with the minimum price difference. + """ + # Extract strike prices from options_data + Fimp = self.calculate_Fimp(call_data, put_data) + + # Find the strikes less than Fimp + option_strikes = [ + self.extract_strike_price(option["symbol"]) for option in self.options_data + ] + strikes_less_than_Fimp = [strike for strike in option_strikes if strike < Fimp] + + # Set the largest strike that is less than Fimp as ATM strike K_ATM for near and next-term options + self.K_ATM = max(strikes_less_than_Fimp) + + return self.K_ATM + + def select_OTM_options(self, call_data, put_data): + """ + Select out-of-the-money (OTM) options with respect to the ATM strike price for each set of near and next-term options. + If both call and put options are selected for the same strike (i.e., K_ATM), then take the average of them. + + Parameters: + call_data (list): List of call option data. + put_data (list): List of put option data. + + Returns: + dict: Dictionary containing OTM options for each set of near and next-term options. + """ + # Calculate K_ATM + K_ATM = self.set_ATM_strike(call_data, put_data) + + # Filter strikes less than K_ATM + option_strikes = [ + self.extract_strike_price(option["symbol"]) + for option in call_data + put_data + ] + strikes_less_than_K_ATM = [ + strike for strike in option_strikes if strike < K_ATM + ] + + # Initialize a dictionary to store OTM options + OTM_options = {} + + # Select OTM options for each set of near and next-term options + for strike in strikes_less_than_K_ATM: + if strike != K_ATM: + # For strikes different from K_ATM, select OTM options based on mid-price + call_OTM = next( + ( + call + for call in call_data + if self.extract_strike_price(call["symbol"]) == strike + ), + None, + ) + put_OTM = next( + ( + put + for put in put_data + if self.extract_strike_price(put["symbol"]) == strike + ), + None, + ) + + if call_OTM and put_OTM: + call_price = call_OTM.get("mid_price", 0) + put_price = put_OTM.get("mid_price", 0) + OTM_options[strike] = (call_price + put_price) / 2 + else: + # For K_ATM, take the average of both call and put prices if they exist + call_ATM = next( + ( + call + for call in call_data + if self.extract_strike_price(call["symbol"]) == K_ATM + ), + None, + ) + put_ATM = next( + ( + put + for put in put_data + if self.extract_strike_price(put["symbol"]) == K_ATM + ), + None, + ) + + if call_ATM and put_ATM: + call_price = call_ATM.get("mid_price", 0) + put_price = put_ATM.get("mid_price", 0) + OTM_options[K_ATM] = (call_price + put_price) / 2 + + return OTM_options + + def filter_options_by_strike_range(self): + # Calculate Kmin and Kmax + Kmin = self.Fimp / self.RANGE_MULT + Kmax = self.Fimp * self.RANGE_MULT + + # Filter options within the strike range + filtered_options = [ + option for option in self.options_data if Kmin < option["strike"] < Kmax + ] + return filtered_options + + def filter_options_by_bid_price(self, options): + # Eliminate options after observing five consecutive bid prices below the threshold + filtered_options = [] + consecutive_below_threshold = 0 + + for option in sorted(options, key=lambda x: x["strike"]): + if option["bid_price"] > self.minimum_bid_threshold: + filtered_options.append(option) + consecutive_below_threshold = 0 + else: + consecutive_below_threshold += 1 + if consecutive_below_threshold < 5: + filtered_options.append(option) + else: + break # Stop adding options once we hit five below the threshold + + return filtered_options + + def execute(self): + self.calculate_Fimp() + self.set_ATM_strike() + otm_options = self.select_OTM_options() + strike_filtered_options = self.filter_options_by_strike_range() + final_filtered_options = self.filter_options_by_bid_price( + strike_filtered_options + ) + return final_filtered_options diff --git a/exchanges/handlers/__init__.py b/exchanges/handlers/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/exchanges/handlers/future_and_options_handler.py b/exchanges/handlers/future_and_options_handler.py new file mode 100644 index 0000000..6773e92 --- /dev/null +++ b/exchanges/handlers/future_and_options_handler.py @@ -0,0 +1,37 @@ +from typing import List + +import pandas as pd + +from exchanges.fetchers.future_fetcher import FutureFetcher +from exchanges.fetchers.option_fetcher import OptionFetcher +from exchanges.processing import Processing + + +class MergeMarketHandler: + def __init__(self, exchange, market_types): + self.exchange = exchange + self.future_data_fetcher = FutureFetcher(exchange) + self.options_data_fetcher = OptionFetcher(exchange) + self.market_types = market_types + self.processing = Processing() + + + """ + Fetches the options and future market data for the given exchange and market types (e.g. "BTC"). + """ + def handle( + self, options_market: List[str] + ) -> tuple[pd.DataFrame, pd.DataFrame]: + options_data = self.options_data_fetcher.fetch_market_data( + options_market, str(self.exchange) + ) + options_data = self.processing.eliminate_invalid_quotes(options_data) + + """ + First, we fetch the future market symbols for the given exchange and market types (e.g. "BTC"). + Then, we fetch all the implied interest rates for the future market symbols. + """ + futures_symbols = self.future_data_fetcher.fetch_future_market_symbols("BTC") + future_data = self.future_data_fetcher.fetch_all_implied_interest_rates(futures_symbols) + + return options_data, future_data diff --git a/exchanges/main.py b/exchanges/main.py new file mode 100644 index 0000000..e9e097f --- /dev/null +++ b/exchanges/main.py @@ -0,0 +1,36 @@ +import logging + +import pandas as pd +import matplotlib.pyplot as plt + +from exchanges.managers.binance_manager import BinanceManager +from exchanges.managers.okx_manager import OKXManager +from exchanges.processing import Processing +from managers.deribit_manager import DeribitManager + +# Configure logging +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +def main(): + try: + deribit = DeribitManager(pairs_to_load=["BTC/USD:BTC"], market_types=["option"]) + binance = BinanceManager( + pairs_to_load=["BTC/USD:BTC"], market_types=["option", "future"] + ) + okx = OKXManager(pairs_to_load=["BTC/USD:BTC"], market_types=["option"]) + global_orderbook_options = pd.DataFrame() + global_orderbook_futures = pd.DataFrame() + + for manager in [binance, deribit]: + options, futures = manager.load_specific_pairs() + global_orderbook_options = pd.concat([global_orderbook_options, options]).reset_index(drop=True) + global_orderbook_futures = pd.concat([global_orderbook_futures, futures]).reset_index(drop=True) + + except Exception as e: + logger.error(f"An unexpected error occurred in the main function: {e}") + + +if __name__ == "__main__": + main() diff --git a/exchanges/managers/__init__.py b/exchanges/managers/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/exchanges/managers/__pycache__/binance_manager.cpython-311.pyc b/exchanges/managers/__pycache__/binance_manager.cpython-311.pyc new file mode 100644 index 0000000..3e7271b Binary files /dev/null and b/exchanges/managers/__pycache__/binance_manager.cpython-311.pyc differ diff --git a/exchanges/managers/binance_manager.py b/exchanges/managers/binance_manager.py new file mode 100644 index 0000000..dd3f2af --- /dev/null +++ b/exchanges/managers/binance_manager.py @@ -0,0 +1,6 @@ +from exchanges.exchange_manager import ExchangeManager + + +class BinanceManager(ExchangeManager): + def __init__(self, pairs_to_load, market_types): + super().__init__("binance", pairs_to_load, market_types) diff --git a/exchanges/managers/bybit_manager.py b/exchanges/managers/bybit_manager.py new file mode 100644 index 0000000..07b7e8f --- /dev/null +++ b/exchanges/managers/bybit_manager.py @@ -0,0 +1,6 @@ +from exchanges.exchange_manager import ExchangeManager + + +class BybitManager(ExchangeManager): + def __init__(self, pairs_to_load, market_types): + super().__init__("bybit", pairs_to_load, market_types) diff --git a/exchanges/managers/deribit_manager.py b/exchanges/managers/deribit_manager.py new file mode 100644 index 0000000..42cb655 --- /dev/null +++ b/exchanges/managers/deribit_manager.py @@ -0,0 +1,6 @@ +from exchanges.exchange_manager import ExchangeManager + + +class DeribitManager(ExchangeManager): + def __init__(self, pairs_to_load, market_types): + super().__init__("deribit", pairs_to_load, market_types) diff --git a/exchanges/managers/okx_manager.py b/exchanges/managers/okx_manager.py new file mode 100644 index 0000000..ca3d95e --- /dev/null +++ b/exchanges/managers/okx_manager.py @@ -0,0 +1,6 @@ +from exchanges.exchange_manager import ExchangeManager + + +class OKXManager(ExchangeManager): + def __init__(self, pairs_to_load, market_types): + super().__init__("okx", pairs_to_load, market_types) diff --git a/exchanges/processing.py b/exchanges/processing.py new file mode 100644 index 0000000..7d92998 --- /dev/null +++ b/exchanges/processing.py @@ -0,0 +1,227 @@ +import json +from datetime import datetime + +import numpy as np +import pandas as pd +from scipy.interpolate import interp1d + +from exchanges.constants.utils import SPREAD_MIN, SPREAD_MULTIPLIER, RANGE_MULT + + +class Processing: + @staticmethod + def calculate_yield_curve(dataframe): + """ + Calculates the average interest rate for each expiry date in a pandas DataFrame. + + Parameters: + - dataframe: A pandas DataFrame containing at least two columns: 'expiry' and 'implied_interest_rate'. + + Returns: + - A pandas DataFrame containing the average implied interest rate for each unique expiry date. + """ + dataframe = dataframe.sort_values(by="expiry", ascending=False) + + grouped = ( + dataframe.groupby("expiry")["implied_interest_rate"].mean().reset_index() + ) + + return grouped[ + ["expiry", "implied_interest_rate", "days_to_expiry", "years_to_expiry"] + ] + + @staticmethod + def build_interest_rate_term_structure(df): + # Group by expiry date and calculate the average implied interest rate for each expiry + interest_rate_term_structure = df.groupby("expiry")["rimp"].mean().reset_index() + + # Rename columns for clarity + interest_rate_term_structure.rename( + columns={"rimp": "average_implied_interest_rate"}, inplace=True + ) + + return interest_rate_term_structure + + @staticmethod + def filter_near_next_term_options(df): + df["expiry"] = df["symbol"].apply( + lambda x: datetime.strptime(x.split("-")[1], "%y%m%d") + ) + index_maturity_days = 30 + today = datetime.now() + near_term_options = df[(df["expiry"] - today).dt.days <= index_maturity_days] + next_term_options = df[(df["expiry"] - today).dt.days > index_maturity_days] + return near_term_options, next_term_options + + @staticmethod + def eliminate_invalid_quotes(df): + df = df[ + (df["ask"] > df["bid"]) + & (df["mark_price"] >= df["bid"]) + & (df["mark_price"] <= df["ask"]) + & (df["mark_price"] > 0) + ] + return df + + @staticmethod + def process_quotes(df: pd.DataFrame) -> pd.DataFrame: + df = df.copy() + df["bid_spread"] = df["mark_price"] - df["bid"] + df["ask_spread"] = df["ask"] - df["mark_price"] + + df["bid_spread"] = df["bid_spread"].apply(lambda x: x if x > 0 else 0) + df["ask_spread"] = df["ask_spread"].apply(lambda x: x if x > 0 else 0) + + # Calculate total spread + df["spread"] = df["bid_spread"] + df["ask_spread"] + + MAS = df[["bid_spread", "ask_spread"]].min(axis=1) * SPREAD_MULTIPLIER + + # Calculate GMS + GMS = SPREAD_MIN * SPREAD_MULTIPLIER + + df = df[(df["spread"] <= GMS) | (df["spread"] <= MAS)] + + df["strike"] = df["symbol"].apply(lambda x: int(x.split("-")[2])) + df["option_type"] = df["symbol"].apply(lambda x: x[-1]) + + df["mid_price"] = (df["bid"] + df["ask"]) / 2 + return df + + @staticmethod + def calculate_implied_forward_price(df): + calls = df[df["option_type"] == "C"] + puts = df[df["option_type"] == "P"] + combined = calls[["strike", "mid_price"]].merge( + puts[["strike", "mid_price"]], on="strike", suffixes=("_call", "_put") + ) + combined["mid_price_diff"] = abs( + combined["mid_price_call"] - combined["mid_price_put"] + ) + min_diff_strike = combined.loc[combined["mid_price_diff"].idxmin()] + forward_price = df.loc[ + df["strike"] == min_diff_strike["strike"], "mark_price" + ].iloc[0] + Fimp = min_diff_strike["strike"] + forward_price * ( + min_diff_strike["mid_price_call"] - min_diff_strike["mid_price_put"] + ) + return Fimp + + @staticmethod + def filter_and_sort_options(df, Fimp): + KATM = df[df["strike"] < Fimp]["strike"].max() + RANGE_MULT = 2.5 + Kmin = Fimp / RANGE_MULT + Kmax = Fimp * RANGE_MULT + calls_otm = df[(df["strike"] > KATM) & (df["option_type"] == "C")] + puts_otm = df[(df["strike"] < KATM) & (df["option_type"] == "P")] + otm_combined = pd.concat([calls_otm, puts_otm]) + otm_filtered = otm_combined[ + (otm_combined["strike"] > Kmin) & (otm_combined["strike"] < Kmax) + ] + otm_sorted = otm_filtered.sort_values(by="strike") + tick_size = df[df["bid"] > 0]["bid"].min() + consecutive_threshold = 5 + consecutive_count = 0 + to_drop = [] + for index, row in otm_sorted.iterrows(): + if row["bid"] <= tick_size: + consecutive_count += 1 + to_drop.append(index) + else: + consecutive_count = 0 + if consecutive_count >= consecutive_threshold: + break + otm_final = otm_sorted.drop(to_drop) + otm_final["Fimp"] = Fimp + otm_final["KATM"] = KATM + # time to expiry in years + current_date = datetime.now() + otm_final["years_to_expiry"] = ( + otm_final["expiry"] - current_date + ).dt.days / 365.25 + + return otm_final + + @staticmethod + def calculate_wij(strike_prices_df, interest_rates_df): + interest_rates_df["expiry"] = pd.to_datetime(interest_rates_df["expiry"]) + strike_prices_df["expiry"] = pd.to_datetime(strike_prices_df["expiry"]) + + strike_prices_df.sort_values(by=["expiry", "strike"], inplace=True) + + merged_df = strike_prices_df.merge( + interest_rates_df, on="expiry", how="left", suffixes=("_x", "_y") + ) + + merged_df["K_prev"] = merged_df["strike"].shift(1) + merged_df["K_next"] = merged_df["strike"].shift(-1) + + merged_df["Delta_K"] = (merged_df["K_next"] - merged_df["K_prev"]) / 2 + merged_df["Delta_K"].fillna(method="bfill", inplace=True) + merged_df["Delta_K"].fillna(method="ffill", inplace=True) + + + merged_df["w_ij"] = ( + np.exp(merged_df["implied_interest_rate"] * merged_df["years_to_expiry"]) + * merged_df["Delta_K"] + ) / (merged_df["strike"] ** 2) + return merged_df + + @staticmethod + def calculate_sigma_it_squared_for_all(w_ij_df): + T_i = w_ij_df['years_to_expiry'].mean() + F_i = w_ij_df['Fimp'].mean() + K_i_ATM = w_ij_df['KATM'].mean() + + sigma_squared = (1 / T_i) * ( + np.sum(0.5 * w_ij_df['w_ij'] * w_ij_df['mid_price']) - + ((F_i / K_i_ATM) - 1) ** 2 * len(w_ij_df) + ) + + return sigma_squared + @staticmethod + def find_missing_expiries(options_df, futures_df): + options_expiries = options_df["expiry"].unique() + futures_expiries = futures_df["expiry"].unique() + missing_expiries = sorted(list(set(options_expiries) - set(futures_expiries))) + return missing_expiries + + @staticmethod + def interpolate_implied_interest_rates(futures_df, missing_expiries): + futures_df["expiry_ordinal"] = pd.to_datetime(futures_df["expiry"]).apply( + lambda x: x.toordinal() + ) + missing_expiries_ordinal = [ + pd.to_datetime(date).toordinal() for date in missing_expiries + ] + + interp_func = interp1d( + futures_df["expiry_ordinal"], + futures_df["implied_interest_rate"], + kind="linear", + fill_value="extrapolate", + ) + + interpolated_rates = interp_func(missing_expiries_ordinal) + + interpolated_rates_df = pd.DataFrame( + {"expiry": missing_expiries, "implied_interest_rate": interpolated_rates} + ) + + return interpolated_rates_df + + @staticmethod + def calculate_delta_K(df): + df = df.sort_values(by="strike").reset_index(drop=True) + print(df) + delta_K = pd.Series(dtype=float) + delta_K[0] = df.loc[1, "strike"] - df.loc[0, "strike"] + delta_K[df.index[-1]] = ( + df.loc[df.index[-1], "strike"] - df.loc[df.index[-1] - 1, "strike"] + ) + + for i in range(1, len(df) - 1): + delta_K[i] = (df.loc[i + 1, "strike"] - df.loc[i - 1, "strike"]) / 2 + + return delta_K diff --git a/exchanges/raw_implied_variance.py b/exchanges/raw_implied_variance.py new file mode 100644 index 0000000..0541292 --- /dev/null +++ b/exchanges/raw_implied_variance.py @@ -0,0 +1,177 @@ +import numpy as np + + +class RawImpliedVariance: + def calculate_implied_variance( + self, F_i, K_i_ATM, strikes, option_prices, r_i, T_i, delta_K + ): + # Precompute constant + discount_factor = np.exp(r_i * T_i) + + # Explicitly convert delta_K elements to float + delta_K = np.array(delta_K, dtype=float) + + # Ensure that all arrays have the same length + min_length = min(len(strikes), len(option_prices), len(delta_K)) + strikes = np.array(strikes[:min_length], dtype=float) + option_prices = np.array(option_prices[:min_length], dtype=float) + + # Log-linear extrapolation + Kmin, Kmax = min(strikes), max(strikes) + extrapolated_strikes = np.logspace(np.log10(Kmin), np.log10(Kmax), num=1000) + extrapolated_option_prices = np.interp( + extrapolated_strikes, strikes, option_prices + ) + + # Log-linear piece-wise interpolation + interpolated_strikes = np.logspace(np.log10(Kmin), np.log10(Kmax), num=1000) + interpolated_option_prices = np.interp( + interpolated_strikes, strikes, option_prices + ) + + # Update strikes and option prices + strikes = np.concatenate([strikes, extrapolated_strikes, interpolated_strikes]) + option_prices = np.concatenate( + [option_prices, extrapolated_option_prices, interpolated_option_prices] + ) + + # Reshape arrays to have the same shape for broadcasting + discount_factor = discount_factor.reshape((1,)) + strikes = strikes.reshape((len(strikes), 1)) + option_prices = option_prices.reshape((len(option_prices), 1)) + + # Vectorized operations with broadcasting + weights = discount_factor * (delta_K / strikes**2) + sum_term = np.sum(weights * option_prices) + + # Calculate the implied variance using the formula + implied_variance = (1 / T_i) * (2 * sum_term - ((F_i / K_i_ATM) - 1) ** 2) + + return implied_variance + + def interpolate_variance(self, T_NEAR, T_NEXT, T_INDEX=30 / 365): + """ + Calculate the weights for the near and next term variances based on the given times to maturity. + + Parameters: + T_NEAR (list): List containing Time to maturity for the near term. + T_NEXT (list): List containing Time to maturity for the next term. + T_INDEX (list): List containing Time to maturity for the index. + + Returns: + tuple: A tuple containing the weights for the near term (omega_NEAR) and the next term (omega_NEXT). + """ + if len(T_NEAR) != len(T_NEXT) or len(T_NEXT) != len(T_INDEX): + raise ValueError("Input lists must have the same length") + + omega_NEAR_t = [ + (T_NEXT[i] - T_INDEX[i]) + / (T_NEXT[i] - T_NEAR[i] + 1e-9) + / (T_INDEX[i] + 1e-9) + for i in range(len(T_NEAR)) + ] + omega_NEXT_t = [ + (T_INDEX[i] - T_NEAR[i]) + / (T_NEXT[i] - T_NEAR[i] + 1e-9) + / (T_NEXT[i] + 1e-9) + for i in range(len(T_NEAR)) + ] + + return omega_NEAR_t, omega_NEXT_t + + def calculate_raw_implied_variance( + self, omega_NEAR_t, sigma2_NEAR_t, omega_NEXT_t, sigma2_NEXT_t + ): + """ + Calculate the raw value of implied variance at the index maturity. + + Parameters: + omega_NEAR_t (float): Weight for the near term variance. + sigma2_NEAR_t (float): Near term variance. + omega_NEXT_t (float): Weight for the next term variance. + sigma2_NEXT_t (float): Next term variance. + + Returns: + float: The raw value of implied variance at the index maturity. + """ + sigma2_RAW_t = omega_NEAR_t * sigma2_NEAR_t + omega_NEXT_t * sigma2_NEXT_t + return sigma2_RAW_t + + def calculate_ewma(self, lambda_param, sigma2_SMOOTH_t_minus_1, sigma2_RAW_t): + """ + Calculate the Exponentially-Weighted Moving Average (EWMA) of raw implied variance. + + Parameters: + lambda_param (float): The smoothing parameter lambda. + sigma2_SMOOTH_t_minus_1 (float): The previous value of the smoothed implied variance. + sigma2_RAW_t (float): The raw implied variance at time t. + + Returns: + float: The smoothed implied variance at time t. + """ + sigma2_SMOOTH_t = ( + lambda_param * sigma2_SMOOTH_t_minus_1 + (1 - lambda_param) * sigma2_RAW_t + ) + return sigma2_SMOOTH_t + + def calculate_ewma_recursive( + self, lambda_param, tau, sigma2_SMOOTH_previous, sigma2_RAW_history + ): + """ + Calculate the Exponentially-Weighted Moving Average (EWMA) of raw implied variance recursively. + + Parameters: + lambda_param (float): The smoothing parameter lambda. + tau (int): The number of periods over which the half-life is defined. + sigma2_SMOOTH_previous (float): The smoothed variance at time t-tau. + sigma2_RAW_history (list of float): The raw implied variances from time t-tau to t-1. + + Returns: + float: The smoothed implied variance at time t. + """ + ewma = lambda_param**tau * sigma2_SMOOTH_previous + for i in range(tau): + ewma += (1 - lambda_param) * (lambda_param**i) * sigma2_RAW_history[i] + return ewma + + def calculate_lambda_with_half_life(self, tau): + """ + Calculate the smoothing parameter lambda based on the specified half-life tau. + + Parameters: + tau (float): The half-life of the exponentially-weighted moving average in seconds. + + Returns: + float: The calculated smoothing parameter lambda. + """ + lambda_param = np.exp(-np.log(2) / tau) + return lambda_param + + def calculate_xVIV(self, sigma_smooth_t): + """ + Calculate the xVIV value based on the given smoothed variance at time t. + + Parameters: + sigma_smooth_t (float): The smoothed variance at time t. + + Returns: + float: The calculated xVIV value. + """ + return 100 * np.sqrt(sigma_smooth_t**2) + + def calculate_katm_strike(self, strikes, option_prices): + """ + Calculate the ATM strike based on the given strikes and option prices. + + Parameters: + strikes (list of float): The strikes of the options. + option_prices (list of float): The prices of the options. + + Returns: + float: The calculated ATM strike. + """ + # Find the index of the minimum value in the option prices + min_index = np.argmin(option_prices) + + # Return the strike at the index + return strikes[min_index] diff --git a/feeds/crypto_indices/mcap1000.py b/feeds/crypto_indices/mcap1000.py index fa8a412..115dfa4 100644 --- a/feeds/crypto_indices/mcap1000.py +++ b/feeds/crypto_indices/mcap1000.py @@ -3,11 +3,12 @@ from apis.coinmarketcap import CoinMarketCapAPI as coinmarketcap from apis.coingecko import CoinGeckoAPI as coingecko + # from apis.cryptocompare import CryptoCompareAPI as cryptocompare class MCAP1000(DataFeed): - NAME = 'mcap1000' + NAME = "mcap1000" ID = 2 HEARTBEAT = 180 DATAPOINT_DEQUE = deque([], maxlen=100) @@ -15,20 +16,20 @@ class MCAP1000(DataFeed): @classmethod def process_source_data_into_siwa_datapoint(cls): - ''' - Process data from multiple sources - ''' + """ + Process data from multiple sources + """ res = [] for source in [ # cryptocompare, coinmarketcap, - coingecko + coingecko, ]: market_data = source().fetch_mcap_by_rank(cls.N) if market_data is None: continue mcaps = sorted(list(market_data.keys()), reverse=True) - res.append(sum(mcaps[:cls.N])) + res.append(sum(mcaps[: cls.N])) if sum(res) == 0: return cls.DATAPOINT_DEQUE[-1] # Should fail if DEQUE is empty else: diff --git a/feeds/data_feed.py b/feeds/data_feed.py index c218a8d..49d6fa4 100644 --- a/feeds/data_feed.py +++ b/feeds/data_feed.py @@ -1,4 +1,4 @@ -#stdlib +# stdlib import os import time import logging @@ -8,33 +8,33 @@ from datetime import datetime, timezone from dataclasses import dataclass -#third party +# third party import pandas as pd -#our stuff +# our stuff import constants as c #'%(asctime)s:%(thread)d - %(name)s - %(levelname)s - %(message)s') -logger = logging.getLogger('SQLLogger') +logger = logging.getLogger("SQLLogger") logger.setLevel(logging.INFO) -logger.propagate = False # TODO determine if undesirable +logger.propagate = False # TODO determine if undesirable + @dataclass class DataFeed: - ''' The base-level implementation for all data feeds, which should inherit from DataFeed and implement the get_data_point method as required. - ''' + """The base-level implementation for all data feeds, which should inherit from DataFeed and implement the get_data_point method as required.""" - #NOTE: all child classes must define these class-level attributes + # NOTE: all child classes must define these class-level attributes CHAIN: str NAME: str ID: int - HEARTBEAT: int #in seconds - START_TIME: float #unix timestamp + HEARTBEAT: int # in seconds + START_TIME: float # unix timestamp DATAPOINT_DEQUE: deque - #NOTE: the below are default attrs inherited by child classes + # NOTE: the below are default attrs inherited by child classes ACTIVE: bool = False - COUNT: int = 0 #number of data points served since starting + COUNT: int = 0 # number of data points served since starting DATA_KEYS = (c.FEED_NAME, c.TIME_STAMP, c.DATA_POINT) @classmethod @@ -43,39 +43,39 @@ def get_data_dir(cls): @classmethod def start(cls): - ''' flag feed as active so it can start receiving/processing data ''' + """flag feed as active so it can start receiving/processing data""" cls.START_TIME = time.time() cls.ACTIVE = True @classmethod def stop(cls): - ''' stop / pause feed from receiving/processing data + """stop / pause feed from receiving/processing data for some feeds, this may involve some cleanup, disconnecting a stream etc. - and would be handled in the overridden stop() method in that specific feed''' + and would be handled in the overridden stop() method in that specific feed""" cls.ACTIVE = False @classmethod def run(cls): - ''' run the data generating function(s) + """run the data generating function(s) for some feeds this may be a loop, in others it may be handled by a library e.g. tweepy (twitter) stream - in that case there would be an overridden run() method in that feed''' + in that case there would be an overridden run() method in that feed""" while cls.ACTIVE: dp = cls.create_new_data_point() - logger.info(f'\nNext data point for {cls.NAME}: {dp}\n') + logger.info(f"\nNext data point for {cls.NAME}: {dp}\n") cls.DATAPOINT_DEQUE.append(dp) cls.COUNT += 1 time.sleep(cls.HEARTBEAT) @classmethod def create_new_data_point(cls): - ''' NOTE: this method must be implemented by the child class ''' + """NOTE: this method must be implemented by the child class""" raise NotImplementedError @classmethod def get_most_recently_stored_data_point(cls): - ''' pass ''' + """pass""" data_point = cls.DATAPOINT_DEQUE[-1] if len(cls.DATAPOINT_DEQUE) else None to_serve = (cls.NAME, time.time(), data_point) return dict(zip(cls.DATA_KEYS, to_serve)) diff --git a/feeds/test_feed.py b/feeds/test_feed.py index 7539ada..130fa03 100644 --- a/feeds/test_feed.py +++ b/feeds/test_feed.py @@ -1,12 +1,12 @@ from feeds.data_feed import DataFeed -from collections import deque +from collections import deque from dataclasses import dataclass import constants as c from numpy import random class Test(DataFeed): - NAME = 'test' + NAME = "tests" ID = 0 HEARTBEAT = 1 DATAPOINT_DEQUE = deque([], maxlen=100) diff --git a/moving_average.py b/moving_average.py index f0d32cf..2a9dd7c 100644 --- a/moving_average.py +++ b/moving_average.py @@ -17,11 +17,11 @@ y_values = [] for doc in documents: - for detail in doc.get('detail', []): # Access the 'detail' field if it exists - if detail['type'] == 'inscribe-transfer': # It can be filtered based on types - blocktime = detail['blocktime'] # Get the blocktime - satoshi = detail['satoshi'] # Get the satoshi value - + for detail in doc.get("detail", []): # Access the 'detail' field if it exists + if detail["type"] == "inscribe-transfer": # It can be filtered based on types + blocktime = detail["blocktime"] # Get the blocktime + satoshi = detail["satoshi"] # Get the satoshi value + # Convert blocktime to a datetime object and append to X values x_values.append(datetime.fromtimestamp(blocktime)) # Append satoshi to Y values @@ -32,29 +32,29 @@ # Calculate moving average using numpy's convolve function weights = np.ones(window_size) / window_size -sma_values = np.convolve(y_values, weights, mode='valid') +sma_values = np.convolve(y_values, weights, mode="valid") # Trim x_values to match the length of sma_values (since the convolution reduces the length) -sma_x_values = x_values[window_size - 1:] +sma_x_values = x_values[window_size - 1 :] # Create the plot plt.figure(figsize=(16, 8)) # Plot original Satoshi values -plt.plot_date(x_values, y_values, linestyle='solid', label='Original') +plt.plot_date(x_values, y_values, linestyle="solid", label="Original") # Plot SMA Satoshi values -plt.plot_date(sma_x_values, sma_values, linestyle='solid', color='red', label='SMA') +plt.plot_date(sma_x_values, sma_values, linestyle="solid", color="red", label="SMA") # Format the plot plt.gcf().autofmt_xdate() # Format the date on the x-axis -date_format = mdates.DateFormatter('%Y-%m-%d %H:%M:%S') +date_format = mdates.DateFormatter("%Y-%m-%d %H:%M:%S") plt.gca().xaxis.set_major_formatter(date_format) # Add titles, labels, and legend -plt.title('Satoshi Value Over Time with SMA') -plt.xlabel('DateTime') -plt.ylabel('Satoshi') +plt.title("Satoshi Value Over Time with SMA") +plt.xlabel("DateTime") +plt.ylabel("Satoshi") plt.legend() # Show the plot diff --git a/requirements.txt b/requirements.txt index c823176..49f8ee1 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,8 +2,9 @@ cmd2==2.4.3 numpy==1.24.2 pandas==1.5.3 requests==2.28.1 +ccxt==4.2.6 python-dotenv pymongo matplotlib pandas -numpy \ No newline at end of file +numpy diff --git a/research/taking_residual.py b/research/taking_residual.py index 867eb3b..08fb702 100644 --- a/research/taking_residual.py +++ b/research/taking_residual.py @@ -13,30 +13,32 @@ # If you received raw dictionary-like objects and need to normalize datetime field: for doc in documents: - if isinstance(doc['timestamp'], (int, float)): # Assuming UNIX timestamp in seconds - doc['timestamp'] = datetime.fromtimestamp(doc['timestamp']) + if isinstance(doc["timestamp"], (int, float)): # Assuming UNIX timestamp in seconds + doc["timestamp"] = datetime.fromtimestamp(doc["timestamp"]) # Convert documents to DataFrame df = pd.DataFrame(documents) # Convert 'timestamp' to datetime if necessary and set it as index -df['timestamp'] = pd.to_datetime(df['timestamp'], unit='s') # Adjust 'unit' as per requirement -df = df.set_index('timestamp') +df["timestamp"] = pd.to_datetime( + df["timestamp"], unit="s" +) # Adjust 'unit' as per requirement +df = df.set_index("timestamp") df.sort_index(inplace=True) # Calculate simple moving averages (SMA) to represent `twap_60min` and `twap_10min` -window_sizes = {'twap_60min': 60, 'twap_10min': 10} +window_sizes = {"twap_60min": 60, "twap_10min": 10} for name, window in window_sizes.items(): - df[name] = df['value'].rolling(window, min_periods=1).mean() + df[name] = df["value"].rolling(window, min_periods=1).mean() # Calculate residuals by subtracting the TWAPs from the original values for col in window_sizes.keys(): - df[f'{col}_residual'] = df['value'] - df[col] + df[f"{col}_residual"] = df["value"] - df[col] # Plot the residuals plt.figure(figsize=(12, 6)) -plt.plot(df.index, df['twap_60min_residual'], label='60-min TWAP Residuals') -plt.plot(df.index, df['twap_10min_residual'], label='10-min TWAP Residuals') +plt.plot(df.index, df["twap_60min_residual"], label="60-min TWAP Residuals") +plt.plot(df.index, df["twap_10min_residual"], label="10-min TWAP Residuals") plt.title("Residuals of BRC20 Time Series Data") plt.xlabel("Timestamp") plt.ylabel("Residual value") @@ -47,14 +49,18 @@ # Now, the df contains original data, the TWAP values, and the residuals. # You can save the DataFrame back into MongoDB, in a new collection for example: -new_collection = db['brc20_residuals'] +new_collection = db["brc20_residuals"] # Convert the DataFrame to dict and store it -residuals_dict = df[['twap_60min_residual', 'twap_10min_residual']].to_dict("records") +residuals_dict = df[["twap_60min_residual", "twap_10min_residual"]].to_dict("records") # If you wish to store them in the database, you can use insert or update # Depending on your requirement this could be: # new_collection.insert_many(residuals_dict) # or to update existing documents with new fields: for index, row in df.iterrows(): - update = {"$set": {"twap_60min_residual": row['twap_60min_residual'], - "twap_10min_residual": row['twap_10min_residual']}} - collection.update_one({"_id": row['_id']}, update) + update = { + "$set": { + "twap_60min_residual": row["twap_60min_residual"], + "twap_10min_residual": row["twap_10min_residual"], + } + } + collection.update_one({"_id": row["_id"]}, update) diff --git a/series_fetching.py b/series_fetching.py index 5d296e8..e1b204d 100644 --- a/series_fetching.py +++ b/series_fetching.py @@ -31,11 +31,12 @@ def connection_db(ticker): collection = db[ticker] # Select the collection based on the ticker name. return collection + # Connect to the database for the first BRC20 token in the list. collection = connection_db(brc20_list[0]) # Retrieve the last document from the collection, sorted by the _id field (descending). -last_document = collection.find_one({}, sort=[('_id', pymongo.DESCENDING)]) +last_document = collection.find_one({}, sort=[("_id", pymongo.DESCENDING)]) # Determine the block height from which to start processing records. start_block_height = brc20_ticker_info.json()["data"]["deployHeight"] @@ -45,18 +46,24 @@ def connection_db(ticker): # Remove the last document which is potentially partial or incomplete. collection.delete_one({"_id": last_document["_id"]}) + def store_db(): global collection # Declare the global collection variable to be used within this function. # Loop through block heights starting from the determined start block height up to the best block height. for height in range(start_block_height, best_block_height - 1): - print("Block height: ", height) # Output the current block height being processed. + print( + "Block height: ", height + ) # Output the current block height being processed. # Process each event type. for event_type in event_types: # Query the BRC20 ticker history for the current block height and event type. - respond = unisat_api.get_brc20_ticker_history(brc20_list[0], height, event_type, 0, 100).json()["data"]["detail"] + respond = unisat_api.get_brc20_ticker_history( + brc20_list[0], height, event_type, 0, 100 + ).json()["data"]["detail"] # If the response is not empty, insert the data into the MongoDB collection. if respond is not []: collection.insert_one(respond) + # Call the store_db function to start storing records into the database. store_db() diff --git a/siwa.py b/siwa.py index 1ac6935..6003a0d 100644 --- a/siwa.py +++ b/siwa.py @@ -1,4 +1,4 @@ -#stdlib +# stdlib import os import sys import logging @@ -7,10 +7,10 @@ import time from datetime import datetime, timezone -#third party +# third party import cmd2 -#our stuff +# our stuff from all_feeds import all_feeds import constants as c @@ -24,41 +24,45 @@ def get_params(): parser = argparse.ArgumentParser() parser.add_argument( - '--datafeeds', - nargs='+', + "--datafeeds", + nargs="+", default=[], - help='List of datafeeds to start, separated by commas. Call like this: python siwa.py --datafeeds feed1 feed2 feed3' + help="List of datafeeds to start, separated by commas. Call like this: python siwa.py --datafeeds feed1 feed2 feed3", ) args = parser.parse_args() datafeeds = [all_feeds[f] for f in args.datafeeds] return datafeeds + def start_feeds(feeds): - ''' start all feeds in feeds list ''' + """start all feeds in feeds list""" for feed in feeds: - #(re)activate feed / allow it to start or resume processing + # (re)activate feed / allow it to start or resume processing feed.start() - #print datafeed startup message to CLI + # print datafeed startup message to CLI print(c.start_message(feed)) - #create new thread *only if* one doesn't already exist + # create new thread *only if* one doesn't already exist if not feed.NAME in datafeed_threads: thread = threading.Thread(target=feed.run) thread.start() datafeed_threads[feed.NAME] = thread + def stop_feeds(feeds): - ''' stop *and kill thread for* all feeds in a list ''' + """stop *and kill thread for* all feeds in a list""" for feed in feeds: feed.stop() datafeed_threads[feed.NAME].join() - del(datafeed_threads[feed.NAME]) + del datafeed_threads[feed.NAME] + class Siwa(cmd2.Cmd): - ''' siwa CLI: allows user to start/stop datafeeds, list feed statuses ''' - prompt = '\nSIWA> ' + """siwa CLI: allows user to start/stop datafeeds, list feed statuses""" + + prompt = "\nSIWA> " def __init__(self): super().__init__() @@ -67,63 +71,68 @@ def __init__(self): self.init_time = time.time() self.debug = c.DEBUG if self.debug: - self.poutput(':::DEBUG MODE ENABLED:::') + self.poutput(":::DEBUG MODE ENABLED:::") def do_status(self, args: cmd2.Statement): - '''show status (active, inactive) for all datafeeds, + """show status (active, inactive) for all datafeeds, if debug enabled, also show status of threads; - inactive datafeeds merely sleep, they do not close their threads''' - #if -v then shows params too + inactive datafeeds merely sleep, they do not close their threads""" + # if -v then shows params too self.poutput(c.init_time_message(self)) for feed in all_feeds.values(): self.poutput(c.status_message(feed)) - self.poutput(f'{feed.NAME} deque len: {len(feed.DATAPOINT_DEQUE)}') + self.poutput(f"{feed.NAME} deque len: {len(feed.DATAPOINT_DEQUE)}") if c.DEBUG: threadcount = threading.active_count() - datafeed_threadcount = threading.active_count() - 1 - 1 - c.WEBSERVER_THREADS + datafeed_threadcount = ( + threading.active_count() - 1 - 1 - c.WEBSERVER_THREADS + ) endpoint_threadcount = 1 + c.WEBSERVER_THREADS - self.poutput(f''' + self.poutput( + f""" --- THREAD DEBUG INFO --- datafeed threads running: {datafeed_threadcount} total threads: {threadcount} (1 main, {endpoint_threadcount} endpoint, and {datafeed_threadcount} feeds) - feeds threads running: {list(datafeed_threads.keys()) or '[none]'}''') + feeds threads running: {list(datafeed_threads.keys()) or '[none]'}""" + ) def do_start(self, args: cmd2.Statement): - '''start specified feed, if none specified start all; - create new thread for feed if none extant''' + """start specified feed, if none specified start all; + create new thread for feed if none extant""" if args: - #start specific feed, if given + # start specific feed, if given feeds = [all_feeds[f] for f in args.arg_list] else: - #else start all feeds + # else start all feeds feeds = all_feeds.values() start_feeds(feeds) def do_stop(self, args: cmd2.Statement): - '''stop datafeed processing - (thread remains running in case we want to re-activate)''' + """stop datafeed processing + (thread remains running in case we want to re-activate)""" if args: - #stop specific feed, if given + # stop specific feed, if given feeds = [all_feeds[f] for f in args.arg_list] else: - #else stop all active feeds + # else stop all active feeds feeds = [f for f in all_feeds.values() if f.ACTIVE] for feed in feeds: self.poutput(c.stop_message(feed)) stop_feeds([feed]) - def do_quit(self,args: cmd2.Statement): + def do_quit(self, args: cmd2.Statement): """Exit the application""" - self.poutput('quitting; waiting for heartbeat timeout') + self.poutput("quitting; waiting for heartbeat timeout") for feed in all_feeds.values(): feed.stop() return True -if __name__ == '__main__': + +if __name__ == "__main__": args = get_params() if args: start_feeds(args) diff --git a/test/test_unisat.py b/test/test_unisat.py index 59d0e24..98d7ed8 100644 --- a/test/test_unisat.py +++ b/test/test_unisat.py @@ -1,3 +1,27 @@ +# from apis import unisat +# import unittest +# +# +# class TestUnisat(unittest.TestCase): +# # @classmethod +# # def setUpClass(cls): +# # # if os.path.exists(Test.get_data_dir()): +# # ... +# # # os.remove(Test.get_data_dir()) +# # +# # @classmethod +# # def tearDownClass(cls): +# # ... +# # +# # def test_get_blockchain_info(self): +# # self.assertListEqual( +# # list(unisat.get_blockchain_info().json().keys()), ["code", "msg", "data"] +# # ) +# +# +# if __name__ == "__main__": +# unittest.main() + import sys import os @@ -23,35 +47,107 @@ def tearDown(self): def test_get_blockchain_info(self): self.assertListEqual( list(self.UnisatAPI.get_blockchain_info().json()["data"].keys()), - ['chain', 'blocks', 'headers', 'bestBlockHash', 'prevBlockHash', 'difficulty', 'medianTime', 'chainwork'], + [ + "chain", + "blocks", + "headers", + "bestBlockHash", + "prevBlockHash", + "difficulty", + "medianTime", + "chainwork", + ], ) def test_get_block_txs(self): height = 824631 self.assertListEqual( list(self.UnisatAPI.get_block_txs(height).json()["data"][0].keys()), - ['txid', 'nIn', 'nOut', 'size', 'witOffset', 'locktime', 'inSatoshi', 'outSatoshi', 'nNewInscription', 'nInInscription', 'nOutInscription', 'nLostInscription', 'timestamp', 'height', 'blkid', 'idx', 'confirmations'], + [ + "txid", + "nIn", + "nOut", + "size", + "witOffset", + "locktime", + "inSatoshi", + "outSatoshi", + "nNewInscription", + "nInInscription", + "nOutInscription", + "nLostInscription", + "timestamp", + "height", + "blkid", + "idx", + "confirmations", + ], ) def test_get_block_txs(self): - txid = '45a76470f80982d769b1974181cd4f7261084ac8db3dcb1cd4547f9fe91590cf' + txid = "45a76470f80982d769b1974181cd4f7261084ac8db3dcb1cd4547f9fe91590cf" self.assertListEqual( list(self.UnisatAPI.get_tx_info(txid).json()["data"].keys()), - ['txid', 'nIn', 'nOut', 'size', 'witOffset', 'locktime', 'inSatoshi', 'outSatoshi', 'nNewInscription', 'nInInscription', 'nOutInscription', 'nLostInscription', 'timestamp', 'height', 'blkid', 'idx', 'confirmations'], + [ + "txid", + "nIn", + "nOut", + "size", + "witOffset", + "locktime", + "inSatoshi", + "outSatoshi", + "nNewInscription", + "nInInscription", + "nOutInscription", + "nLostInscription", + "timestamp", + "height", + "blkid", + "idx", + "confirmations", + ], ) def test_get_inscription_utxo(self): - address = '1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6' + address = "1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6" self.assertListEqual( list(self.UnisatAPI.get_inscription_utxo(address).json()["data"].keys()), - ['cursor', 'total', 'totalConfirmed', 'totalUnconfirmed', 'totalUnconfirmedSpend', 'utxo'], + [ + "cursor", + "total", + "totalConfirmed", + "totalUnconfirmed", + "totalUnconfirmedSpend", + "utxo", + ], ) def test_get_inscription_info(self): - inscriptionid = '75017937ad1de1f50709910aa5889be9c7d8f019a1c02922d291f9bfa9a8b0fei0' + inscriptionid = ( + "75017937ad1de1f50709910aa5889be9c7d8f019a1c02922d291f9bfa9a8b0fei0" + ) self.assertListEqual( - list(self.UnisatAPI.get_inscription_utxo(inscriptionid).json()["data"].keys()), - ['utxo', 'address', 'offset', 'inscriptionIndex', 'inscriptionNumber', 'inscriptionId', 'contentType', 'contentLength', 'contentBody', 'height', 'timestamp', 'inSatoshi', 'outSatoshi', 'brc20', 'detail'], + list( + self.UnisatAPI.get_inscription_utxo(inscriptionid).json()["data"].keys() + ), + [ + "utxo", + "address", + "offset", + "inscriptionIndex", + "inscriptionNumber", + "inscriptionId", + "contentType", + "contentLength", + "contentBody", + "height", + "timestamp", + "inSatoshi", + "outSatoshi", + "brc20", + "detail", + ], ) def test_get_brc20_list(self): @@ -59,7 +155,7 @@ def test_get_brc20_list(self): limit = 100 self.assertListEqual( list(self.UnisatAPI.get_brc20_list(start, limit).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + ["height", "total", "start", "detail"], ) def test_get_brc20_status(self): @@ -68,22 +164,49 @@ def test_get_brc20_status(self): sort = "holders" complete = "yes" self.assertListEqual( - list(self.UnisatAPI.get_brc20_status(start, limit, sort, complete).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + list( + self.UnisatAPI.get_brc20_status(start, limit, sort, complete) + .json()["data"] + .keys() + ), + ["height", "total", "start", "detail"], ) def test_get_brc20_ticker_info(self): ticker = "EFIL" self.assertListEqual( list(self.UnisatAPI.get_brc20_ticker_info(ticker).json()["data"].keys()), - ['ticker', 'holdersCount', 'historyCount', 'inscriptionNumber', 'inscriptionId', 'max', 'limit', 'minted', 'totalMinted', 'confirmedMinted', 'confirmedMinted1h', 'confirmedMinted24h', 'mintTimes', 'decimal', 'creator', 'txid', 'deployHeight', 'deployBlocktime', 'completeHeight', 'completeBlocktime', 'inscriptionNumberStart', 'inscriptionNumberEnd'], + [ + "ticker", + "holdersCount", + "historyCount", + "inscriptionNumber", + "inscriptionId", + "max", + "limit", + "minted", + "totalMinted", + "confirmedMinted", + "confirmedMinted1h", + "confirmedMinted24h", + "mintTimes", + "decimal", + "creator", + "txid", + "deployHeight", + "deployBlocktime", + "completeHeight", + "completeBlocktime", + "inscriptionNumberStart", + "inscriptionNumberEnd", + ], ) def test_get_brc20_holders(self): ticker = "EFIL" self.assertListEqual( list(self.UnisatAPI.get_brc20_holders(ticker).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + ["height", "total", "start", "detail"], ) # Need to try with correct params @@ -103,76 +226,122 @@ def test_get_history_by_height(self): start = 0 limit = 100 self.assertListEqual( - list(self.UnisatAPI.get_history_by_height(height, start, limit).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + list( + self.UnisatAPI.get_history_by_height(height, start, limit) + .json()["data"] + .keys() + ), + ["height", "total", "start", "detail"], ) def test_get_brc20_tx_history(self): ticker = "EFIL" - txid = '45a76470f80982d769b1974181cd4f7261084ac8db3dcb1cd4547f9fe91590cf' + txid = "45a76470f80982d769b1974181cd4f7261084ac8db3dcb1cd4547f9fe91590cf" start = 0 limit = 100 self.assertListEqual( - list(self.UnisatAPI.get_brc20_tx_history(ticker, txid, start, limit).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + list( + self.UnisatAPI.get_brc20_tx_history(ticker, txid, start, limit) + .json()["data"] + .keys() + ), + ["height", "total", "start", "detail"], ) def test_get_address_brc20_summary(self): - address = '1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6' + address = "1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6" start = 0 limit = 100 self.assertListEqual( - list(self.UnisatAPI.get_address_brc20_summary(address, start, limit).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + list( + self.UnisatAPI.get_address_brc20_summary(address, start, limit) + .json()["data"] + .keys() + ), + ["height", "total", "start", "detail"], ) def test_get_address_brc20_summary_by_height(self): - address = '1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6' + address = "1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6" height = 824631 start = 0 limit = 100 self.assertListEqual( - list(self.UnisatAPI.get_address_brc20_summary_by_height(address, height, start, limit).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + list( + self.UnisatAPI.get_address_brc20_summary_by_height( + address, height, start, limit + ) + .json()["data"] + .keys() + ), + ["height", "total", "start", "detail"], ) def test_get_address_brc20_ticker_info(self): - address = '1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6' + address = "1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6" ticker = "EFIL" self.assertListEqual( - list(self.UnisatAPI.get_address_brc20_ticker_info(address, ticker).json()["data"].keys()), - ['ticker', 'overallBalance', 'transferableBalance', 'availableBalance', 'availableBalanceSafe', 'availableBalanceUnSafe', 'transferableCount', 'transferableInscriptions', 'historyCount', 'historyInscriptions'], + list( + self.UnisatAPI.get_address_brc20_ticker_info(address, ticker) + .json()["data"] + .keys() + ), + [ + "ticker", + "overallBalance", + "transferableBalance", + "availableBalance", + "availableBalanceSafe", + "availableBalanceUnSafe", + "transferableCount", + "transferableInscriptions", + "historyCount", + "historyInscriptions", + ], ) def test_get_address_brc20_history(self): - address = '1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6' + address = "1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6" start = 0 limit = 100 self.assertListEqual( - list(self.UnisatAPI.get_address_brc20_history(address, start, limit).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + list( + self.UnisatAPI.get_address_brc20_history(address, start, limit) + .json()["data"] + .keys() + ), + ["height", "total", "start", "detail"], ) def test_get_address_brc20_history_by_ticker(self): - address = '1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6' + address = "1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6" ticker = "EFIL" type = "inscribe-deploy" start = 0 limit = 100 self.assertListEqual( - list(self.UnisatAPI.get_address_brc20_history_by_ticker(address, ticker, type, start, limit).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + list( + self.UnisatAPI.get_address_brc20_history_by_ticker( + address, ticker, type, start, limit + ) + .json()["data"] + .keys() + ), + ["height", "total", "start", "detail"], ) - + def test_get_transferable_inscriptions(self): - address = '1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6' + address = "1K6KoYC69NnafWJ7YgtrpwJxBLiijWqwa6" ticker = "EFIL" self.assertListEqual( - list(self.UnisatAPI.get_transferable_inscriptions(address, ticker).json()["data"].keys()), - ['height', 'total', 'start', 'detail'], + list( + self.UnisatAPI.get_transferable_inscriptions(address, ticker) + .json()["data"] + .keys() + ), + ["height", "total", "start", "detail"], ) - if __name__ == "__main__": unittest.main()