# financelite
financelite is a lightweight stock information tool that takes every complicated features out.
It only focuses on providing simple and intuitive, yet informative stock information.
Currently, financelite is in a rapidly-evolving state. While I'll try to stay within the boundaries,
please understand your implementation may have to change in the future upgrades.
# Installation
`pip install financelite`
# Example Usage
### News
```python
from financelite import News
from financelite.exceptions import NoNewsFoundException
news = News()
try:
news.get_news(ticker="gme", count=5)
# returns 5 GME-related news
except NoNewsFoundException:
# raised if there aren't any news associated with the ticker.
pass
```
### Stock
```python
from financelite import Stock
from financelite.exceptions import DataRequestException
stock = Stock(ticker="gme")
try:
stock.get_chart(interval="1d", range="5d")
# returns statistics for 5 days, with 1 day interval
stock.get_live()
# returns GME's live price and currency
stock.get_hist(data_range="1wk")
# returns 1 week worth of closed price data
except DataRequestException:
# raised if ticker, interval, or range values are wrong
pass
except ValueError:
# raised if get_hist's days is <= 1 or not int
pass
```
### Group
```python
from financelite import Group, Stock
from financelite.exceptions import TickerNotInGroupException, DataRequestException, \
ItemNotValidException
# You can add tickers to the group like this
group = Group()
group.add_ticker("gme") # it takes in str value, then creates a Stock object with the ticker.
group.add_ticker("bb")
group.add_ticker("amc")
# or you can initialize the group with Stock objects
bb = Stock(ticker="bb")
gme = Stock(ticker="gme")
group = Group([bb, gme])
group.list_tickers()
# returns list of tickers represented as strings
try:
group.remove_ticker("ac.to")
except TickerNotInGroupException:
# raised if ticker does not exist within the group
pass
try:
group.get_quotes(cherrypicks=["symbol", "shortName", "regularMarketPrice"])
# returns a dictionary with only those keys
group.get_quotes(cherrypicks=["symbol", "shortName", "regularMarketPrice"], exclude=True)
# returns a dictionary with keys except these keys
except DataRequestException:
# raised if the data request was not successful. Usually means invalid ticker.
pass
except ItemNotValidException:
# raised if any item in the cherrypicks list is invalidd
pass
```
# Special Thanks
* [yahoo! finance](https://finance.yahoo.com/) for providing awesome websites and APIs.
* [Andrew Treadway](https://github.com/atreadw1492) for providing an open source package for processing finance data.
