# Finance Scrapers
A pypi package to scrape stock information from different finance sites. Currently supports [Yahoo Finance](finance.yahoo.com).
## Installation
To install, [Download the PyPi package](https://pypi.org/project/finance-scrapers/0.0.2/#files) _or_,
```
pip install finance-scrapers
```
To upgrade to the latest version,
```
pip install --upgrade finance-scrapers
```
## Usage
Scrape stock information:
```python
from finance_scrapers import YahooFinance
# the tickers of the stocks you want to scrape
tickers = ['schb', 'googl', 'nflx']
# run the scraper
scraper = YahooFinance(tickers)
all_stock_info = scraper.stock_info
```
<br>
Scrape stock information and __display__ to terminal:
```python
from finance_scrapers import YahooFinance
# the tickers of the stocks you want to scrape
tickers = ['schb', 'googl', 'nflx']
# display data found from stocks
scraper = YahooFinance(tickers)
scraper.display_data()
# display custom data
sample_data = {"name": "Mandy-cyber", "love": "food"}
scraper.display(sample_data)
```
<details>
<summary>Example</summary>
{
"AXP": {
"Ask": "171.39 x 800",
"PE Ratio (TTM)": "17.95",
"Open": "172.17",
"Earnings Date": "Jul 21, 2023",
"Volume": "Jul 06, 2023",
"Market Cap": "127.169B",
"Avg. Volume": "186.00",
"52 Week Range": "130.65 - 182.15",
"Forward Dividend & Yield": "2.40 (1.36%)",
"Day's Range": "167.42 - 173.34",
"Previous Close": "177.11",
"EPS (TTM)": "9.53",
"Bid": "171.28 x 1000"
},
"SCHB": {
"Ask": "53.07 x 1000",
"PE Ratio (TTM)": "21.73",
"Open": "53.12",
"YTD Daily Total Return": "18.99%",
"Volume": "0.03%",
"Net Assets": "23B",
"Avg. Volume": "2009-11-03",
"52 Week Range": "40.92 - 53.43",
"Beta (5Y Monthly)": "1.01",
"Day's Range": "52.88 - 53.12",
"Previous Close": "52.92",
"Yield": "1.47%",
"Bid": "53.06 x 2200"
},
"NKE": {
"Ask": "108.85 x 1800",
"PE Ratio (TTM)": "33.80",
"Open": "108.00",
"Earnings Date": "Sep 27, 2023 - Oct 02, 2023",
"Volume": "Jun 02, 2023",
"Market Cap": "167.816B",
"Avg. Volume": "127.70",
"52 Week Range": "82.22 - 131.31",
"Forward Dividend & Yield": "1.36 (1.26%)",
"Day's Range": "107.54 - 109.24",
"Previous Close": "107.53",
"EPS (TTM)": "3.23",
"Bid": "108.83 x 1200"
}
}
</details>
<br>
Scrape stock information and __download__ to a file:
```python
from finance_scrapers import YahooFinance
# the tickers of the stocks you want to scrape
tickers = ['schb', 'googl', 'nflx']
scraper = YahooFinance(tickers)
# download data
scraper.download_data(file_type="json", file_path="sample.json", overwrite=False) # or,
scraper.download_data("markdown", "sample.md") # or,
scraper.download_data("csv", "sample.csv") # or,
scraper.download_data("excel", "sample.xlsx")
```
<sub>Examples of these downloads can be found <a href="https://github.com/Mandy-cyber/Finance-Scrapers/tree/main/samples">here</a></sub>
<br>
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"description": "# Finance Scrapers\r\nA pypi package to scrape stock information from different finance sites. Currently supports [Yahoo Finance](finance.yahoo.com).\r\n\r\n## Installation\r\nTo install, [Download the PyPi package](https://pypi.org/project/finance-scrapers/0.0.2/#files) _or_,\r\n```\r\npip install finance-scrapers\r\n```\r\nTo upgrade to the latest version,\r\n```\r\npip install --upgrade finance-scrapers\r\n```\r\n\r\n## Usage\r\nScrape stock information:\r\n```python\r\nfrom finance_scrapers import YahooFinance\r\n\r\n# the tickers of the stocks you want to scrape\r\ntickers = ['schb', 'googl', 'nflx']\r\n\r\n# run the scraper\r\nscraper = YahooFinance(tickers)\r\nall_stock_info = scraper.stock_info\r\n```\r\n\r\n<br>\r\n\r\nScrape stock information and __display__ to terminal:\r\n```python\r\nfrom finance_scrapers import YahooFinance\r\n\r\n# the tickers of the stocks you want to scrape\r\ntickers = ['schb', 'googl', 'nflx']\r\n\r\n# display data found from stocks\r\nscraper = YahooFinance(tickers)\r\nscraper.display_data()\r\n\r\n# display custom data\r\nsample_data = {\"name\": \"Mandy-cyber\", \"love\": \"food\"}\r\nscraper.display(sample_data)\r\n```\r\n\r\n<details>\r\n <summary>Example</summary>\r\n\r\n\r\n {\r\n \"AXP\": {\r\n \"Ask\": \"171.39 x 800\",\r\n \"PE Ratio (TTM)\": \"17.95\",\r\n \"Open\": \"172.17\",\r\n \"Earnings Date\": \"Jul 21, 2023\",\r\n \"Volume\": \"Jul 06, 2023\",\r\n \"Market Cap\": \"127.169B\",\r\n \"Avg. Volume\": \"186.00\",\r\n \"52 Week Range\": \"130.65 - 182.15\",\r\n \"Forward Dividend & Yield\": \"2.40 (1.36%)\",\r\n \"Day's Range\": \"167.42 - 173.34\",\r\n \"Previous Close\": \"177.11\",\r\n \"EPS (TTM)\": \"9.53\",\r\n \"Bid\": \"171.28 x 1000\"\r\n },\r\n \"SCHB\": {\r\n \"Ask\": \"53.07 x 1000\",\r\n \"PE Ratio (TTM)\": \"21.73\",\r\n \"Open\": \"53.12\",\r\n \"YTD Daily Total Return\": \"18.99%\",\r\n \"Volume\": \"0.03%\",\r\n \"Net Assets\": \"23B\",\r\n \"Avg. Volume\": \"2009-11-03\",\r\n \"52 Week Range\": \"40.92 - 53.43\",\r\n \"Beta (5Y Monthly)\": \"1.01\",\r\n \"Day's Range\": \"52.88 - 53.12\",\r\n \"Previous Close\": \"52.92\",\r\n \"Yield\": \"1.47%\",\r\n \"Bid\": \"53.06 x 2200\"\r\n },\r\n \"NKE\": {\r\n \"Ask\": \"108.85 x 1800\",\r\n \"PE Ratio (TTM)\": \"33.80\",\r\n \"Open\": \"108.00\",\r\n \"Earnings Date\": \"Sep 27, 2023 - Oct 02, 2023\",\r\n \"Volume\": \"Jun 02, 2023\",\r\n \"Market Cap\": \"167.816B\",\r\n \"Avg. Volume\": \"127.70\",\r\n \"52 Week Range\": \"82.22 - 131.31\",\r\n \"Forward Dividend & Yield\": \"1.36 (1.26%)\",\r\n \"Day's Range\": \"107.54 - 109.24\",\r\n \"Previous Close\": \"107.53\",\r\n \"EPS (TTM)\": \"3.23\",\r\n \"Bid\": \"108.83 x 1200\"\r\n }\r\n }\r\n\r\n\r\n</details>\r\n\r\n<br>\r\n\r\nScrape stock information and __download__ to a file:\r\n```python\r\nfrom finance_scrapers import YahooFinance\r\n\r\n# the tickers of the stocks you want to scrape\r\ntickers = ['schb', 'googl', 'nflx']\r\n\r\nscraper = YahooFinance(tickers)\r\n\r\n# download data\r\nscraper.download_data(file_type=\"json\", file_path=\"sample.json\", overwrite=False) # or,\r\nscraper.download_data(\"markdown\", \"sample.md\") # or,\r\nscraper.download_data(\"csv\", \"sample.csv\") # or,\r\nscraper.download_data(\"excel\", \"sample.xlsx\")\r\n```\r\n\r\n<sub>Examples of these downloads can be found <a href=\"https://github.com/Mandy-cyber/Finance-Scrapers/tree/main/samples\">here</a></sub>\r\n\r\n<br>\r\n",
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