financegy 1.5

Unofficial Python library for accessing GSE (Guyana Stock Exchange) financial data

🏦 FinanceGY

FinanceGY is an unofficial Python library for accessing financial data from the Guyana Stock Exchange (GSE). It provides a simple and consistent interface for retrieving information on traded securities, recent trade data, and session details, all programmatically.

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Installation

pip install financegy

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Quick Start

import financegy

# Get a list of all traded securities
securities = financegy.get_securities()

# Get the name of a security by its ticker symbol
security_name = financegy.get_security_by_symbol("DDL")

# Get the most recent trade data for a security
recent_trade = financegy.get_recent_trade("DDL")

# Get all trade data for the most recent year
recent_year = financegy.get_security_recent_year("DDL")

# Get trade data for a specific trading session
session_trades = financegy.get_session_trades("1136")

# Get session trade data for a specific security
security_session_trade = financegy.get_security_session_trade("DDL", "1136")

# Search for securities by name or symbol
search_results = financegy.search_securities("DDL")

# Get all trades for a given year
year_trades = financegy.get_trades_for_year("DDL", "2019")

# Get historical trades within a date range - (yyyy) / (mm/yyyy) / (dd/mm/yyyy)
historical_trades = financegy.get_historical_trades(
    symbol="DDL",
    start_date="01/06/2020",
    end_date="01/2022"
)

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Data Retrieval

Function	Description
get_securities()	Returns a list of all currently traded securities on the GSE.
get_security_by_symbol(symbol: str)	Retrieves the full name of a security using its ticker symbol (e.g., "DDL" → "Demerara Distillers Limited").
get_recent_trade(symbol: str)	Returns the most recent trade information for the given security.
get_security_recent_year(symbol: str)	Fetches all trade data for the most recent year of the selected security.
get_session_trades(session: str)	Retrieves trade data for all securities during a specific trading session.
get_security_session_trade(symbol: str, session: str)	Retrieves trade data for a specific security in a given trading session.
search_securities(query: str)	Searches for securities whose names or ticker symbols match the given query.
get_trades_for_year(symbol: str, year: str)	Returns all trade records for a specific security during a given year.
get_historical_trades(symbol: str, start_date: str, end_date: str)	Fetches historical trade data for a security within the specified date range (dd/mm/yyyy, mm/yyyy, yyyy format).

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Data Utilities

Function	Description
to_dataframe(data)	Converts a list (or dictionary) of trade data into a Pandas DataFrame for easy analysis. Raises TypeError if the data is not properly formatted.
save_to_csv(data, filename: str = "output.csv", path: str = None)	Saves the given data to a CSV file. By default, the file is saved to the current working directory. Returns True after saving successfully.
save_to_excel(data, filename: str = "output.xlsx", path: str = None)	Saves the given data to an Excel .xlsx file. By default, the file is saved to the current working directory. Returns True after saving successfully.

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Caching System

FinanceGY includes a lightweight local caching system designed to speed up repeated requests and reduce unnecessary calls.

Whenever you call a data retrieval function (such as get_securities() or get_recent_trade()), FinanceGY automatically checks whether a cached response already exists for that specific query:

• If a valid cache file (less than 7 days old since sessions are held once per week) is found, the result is returned instantly from the cache.
• If the cache is missing, disabled, or older than one week, FinanceGY fetches fresh data from the GSE and updates the cache automatically.

All cache files are stored in a local cache/ directory as small JSON files containing the retrieved data and a timestamp.

You can manually clear all cached data at any time:

import financegy

financegy.clear_cache()

This will delete all cached files and force the next data request to fetch fresh data directly from the source.

If you prefer to bypass the cache for a specific call, simply pass use_cache=False to any function. For example:

# Force a fresh fetch from the GSE, ignoring cached data
recent_trade = financegy.get_recent_trade("DDL", use_cache=False)

By default, caching is enabled for all supported functions unless explicitly turned off.

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License

This project is licensed under the MIT License

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Example Use Case

import financegy

ddl_recent = financegy.get_security_recent("DDL")
print(ddl_recent)