Stocksera API
This is the official API for Stocksera. Visit Stocksera at https://github.com/guanquann/Stocksera.
Installation
The package can easily be installed in your terminal by entering
pip install stocksera
Import the package
import stocksera
Get data from social media
social = stocksera.Social()
Get total mentions/ mentions of a stock on wallstreetbets
df = social.wsb_mentions(days=1, ticker="AAPL")
| Params |
Required |
Default |
Description |
| days |
No |
1 |
number days ago |
| ticker |
No |
|
stock symbol |
Get total number of puts/calls mentions on wallstreetbets
df = social.wsb_options(days=1)
| Params |
Required |
Default |
Description |
| days |
No |
1 |
number days ago |
Get subreddit count on Reddit
df = social.subreddit(days=50, ticker="GME")
| Params |
Required |
Default |
Description |
| days |
No |
100 |
number days ago |
| ticker |
Yes |
GME |
stock symbol |
Get current trending stocks/ ranking and watchlist count of a stock in stocktwits
df = social.stocktwits(ticker="AAPL")
| Params |
Required |
Default |
Description |
| ticker |
No |
|
stock symbol |
Get stocks related data
stock = stocksera.Stock()
Get SEC fillings of a stock
df = stock.sec_fillings(ticker="AAPL", date_from="2022-01-01", date_to="2022-01-31")
| Params |
Required |
Default |
Description |
| ticker |
Yes |
AAPL |
stock symbol |
| date_from |
No |
|
YYYY-MM-DD |
| date_to |
No |
|
YYYY-MM-DD |
Get news sentiment of a stock
df = stock.news_sentiment(ticker="AAPL")
| Params |
Required |
Default |
Description |
| ticker |
Yes |
AAPL |
stock symbol |
Get recent insider trading of all tickers/ insider trading of a stock
df = stock.insider_trading(limit=500, ticker="AAPL", date_from="2022-01-01", date_to="2022-01-31")
| Params |
Required |
Default |
Description |
| limit |
No |
500 |
last n records |
| ticker |
No |
AAPL |
stock symbol |
| date_from |
No |
|
YYYY-MM-DD |
| date_to |
No |
|
YYYY-MM-DD |
Get recent insider trading analysis
df = stock.latest_insider_trading_summary()
Get stocks with high short volume/ short volume of a stock
df = stock.short_volume(ticker="AAPL", date_from="2022-01-01", date_to="2022-01-31")
| Params |
Required |
Default |
Description |
| ticker |
No |
|
stock symbol |
| date_from |
No |
|
YYYY-MM-DD |
| date_to |
No |
|
YYYY-MM-DD |
Get stocks with consistently high FTD/ FTD of a stock
df = stock.ftd(ticker="AAPL", date_from="2022-01-01", date_to="2022-01-31")
| Params |
Required |
Default |
Description |
| ticker |
No |
|
stock symbol |
| date_from |
No |
|
YYYY-MM-DD |
| date_to |
No |
|
YYYY-MM-DD |
Get number of shares available and borrow fees of a stock
df = stock.borrowed_shares(ticker="AAPL")
| Params |
Required |
Default |
Description |
| ticker |
No |
AAPL |
stock symbol |
Get government trades data
government = stocksera.Government()
Get all senate trades/ trades of a specific person/ trades of a specific ticker
df = government.senate(ticker="AAPL", name="Thomas H Tuberville", date_from="2022-01-01", date_to="2022-01-31")
| Params |
Required |
Default |
Description |
| ticker |
No |
|
stock symbol |
| name |
No |
|
name of person |
| date_from |
No |
|
YYYY-MM-DD |
| date_to |
No |
|
YYYY-MM-DD |
Get all house trades/ trades of a specific person/ trades of a specific ticker
df = government.house(ticker="AAPL", name="Nancy Pelosi", state="CA", date_from="2022-01-01", date_to="2022-01-31")
| Params |
Required |
Default |
Description |
| ticker |
No |
|
stock symbol |
| name |
No |
|
name of person |
| state |
No |
|
district code |
| date_from |
No |
|
YYYY-MM-DD |
| date_to |
No |
|
YYYY-MM-DD |
Get ETF data
etf = stocksera.ETF()
Get market indices
df = etf.market_summary(market_type="snp500")
| Params |
Required |
Default |
Description |
| market_type |
Yes |
snp500 |
snp500/nasdaq100/dia/wsb |
Get economic data
economy = stocksera.Economy()
Get reverse repo
df = economy.reverse_repo(days=100)
| Params |
Required |
Default |
Description |
| days |
No |
100 |
number days ago |
Get daily treasury
df = economy.daily_treasury(days=100)
| Params |
Required |
Default |
Description |
| days |
No |
100 |
number days ago |
Get inflation
df = economy.inflation()
Get initial jobless claims
df = economy.jobless_claims(days=100)
| Params |
Required |
Default |
Description |
| days |
No |
100 |
number days ago |
Get retail sales
df = economy.retail_sales(days=100)
| Params |
Required |
Default |
Description |
| days |
No |
100 |
number days ago |
Get stock related news
news = stocksera.News()
Get recent market news
df = news.market_news()
Get trading halts
df = news.trading_halts()
Get other interesting data
discover = stocksera.Discover()
Get Jim Cramer trades
df = discover.jim_cramer(ticker="AAPL", segment="featured", call="buy")
| Params |
Required |
Default |
Description |
| ticker |
No |
all |
stock symbol |
| segment |
No |
all |
featured/discussed/lightning/guest |
| call |
No |
all |
buy/positive/hold/negative/sell |
Get stocks with high short interest
df = discover.short_interest()
Get stocks with low float
df = discover.low_float()
Get upcoming and past IPOs
df = discover.ipo_calendar()
Get earnings calendar of stocks
df = discover.earnings_calendar(date_from="2022-01-01", date_to="2022-01-31")
| Params |
Required |
Default |
Description |
| date_from |
No |
|
YYYY-MM-DD |
| date_to |
No |
|
YYYY-MM-DD |
