tessa 0.2.0

Find financial assets and get their price history without worrying about different APIs or rate limiting.

tessa

Find financial assets and get their price history without worrying about different APIs or rate limiting.

tessa is a small package to help you easily search asset identifiers (e.g., tickers) and retrieve price information for assets in different categories such as stocks, crypto, etfs, etc.

tessa builds on investpy and pycoingecko and offers a simplified and somewhat unified interface. This applies especially to investpy, which for some reason has different ways of finding assets and accessing the respective data.

Why these two packages? investpy offers high-quality data for most categories from investing.com. However, investing.com lacks on the crypto side, so crypto data is retrieved using pycoingecko from Coingecko's API.

Importantly, tessa makes sure to be nice to the sites being accessed and tries to prevent users from being blocked by 429 rate limiting errors by 1) caching results upon retrieval and 2) keeping track of request timestamps and waiting appropriate amounts of time if necessary.

Main functions

• search: Search for an asset in all sources and types.
• price_history: Retrieve the full history of an asset as a dataframe.
• price_point_strict: Get an asset's price at a certain point in time. Fail if no price found.
• price_point: Same, but find the nearest price if the given point in time has no price.
• price_latest: Get an asset's latest price.

Usage examples

>>> from tessa import price_history, search, price_point, price_latest

# Ex 1, easy – Get straightforward price information:
>>> df, currency = price_history("AAPL", "stock", "united states")
>>> price_point("SAPG", "stock", "2015-12-25", "germany" )
# (Will return price at 2015-12-23.)
>>> price_point_strict("SAPG", "stock", "2015-12-25", "germany" )
# (Will raise a KeyError.)
>>> price_latest("ethereum", "crypto")

# Ex 2, medium – Find ticker and get price information for some 
# lesser-known stock, e.g. the original Roche:
>>> res = search("roche", "switzerland")
    2 of investing_stocks_by_full_name
    2 of investing_stocks_by_name
    1 of investing_funds_by_name
    ...
>>> res["investing_stocks_by_name"]
# -> Ticker is ROG
df, currency = price_history("ROG", "stock", country="switzerland")

# Ex 3, medium – Find Coingecko id and get price information for a
# more obscure token:
>>> res = search("jenny")
    1 of coingecko_other_symbol
    2 of coingecko_other_name
>>> res["coingecko_other_name"]
# ...
>>> df, currency = price_history("jenny-metaverse-dao-token", "crypto")

# Ex 4, medium – Find an ETF:
>>> res = search("carbon")
# ...
>>> res["investing_etfs_by_full_name"]
# ...
>>> df, currency = price_history("VanEck Vectors Low Carbon Energy", "etf", "united states")

# Ex 5, medium – Search in a selection of countries and products:
>>> res = search("renewable", countries=["united states", "canada", "mexico"], products=["etfs", "funds", "indices"])
# ...

# Ex 6, advanced – Find a stock that is not (yet?) exposed on investpy:
>>> price_history("PINS", "stock", "united states")
# Produces an error
>>> res = search("pinterest")
    2 of investing_searchobj_other
>>> res["investing_searchobj_other"]
['{"id_": 1127189, "name": "Pinterest Inc", "symbol": "PINS", "country": "united states", "tag": "/equities/pinterest-inc", "pair_type": "stocks", "exchange": "NYSE"}',
 '{"id_": 1177341, "name": "Pinterest Inc", "symbol": "PINS-RM", "country": "russia", "tag": "/equities/pinterest-inc?cid=1177341", "pair_type": "stocks", "exchange": "Moscow"}']
 >>> df, currency = price_history(res["investing_searchobj_other"][0], "searchobj")
 # ...

How to install

pip install tessa

Prerequisites

See pyproject.toml. Major prerequisites are the investpy and pycoingecko packages.

Future Work

This if an initial version. There are a number of ideas on how to extend. Please leave your suggestions and comments in the Issues section.