Virtual API: the library for finance!¶

Virtual Finance API¶

https://coveralls.io/repos/github/hootnot/virtual-finance-API/badge.svg?branch=main

Interactive¶

Using the Jupyter notebook it is easy to experiment with the virtual_finance_api library.

Install¶

# Setup a virtual environment
$ mkdir vfa
$ cd vfa
$ python3 -m venv venv38
$ . ./venv38/bin/activate
(venv38) feite@salmay:~/vfa$

$ pip install virtual_finance_api

… Or the latest¶

With virtual_finance_api installed, it is directly available via the commandline:

$ virtual_finance_api --help
Usage: vfapi [OPTIONS] COMMAND [ARGS]...

  Virtual Finance API commandline app.

Options:
  --help  Show this message and exit.

Commands:
  financials
  history
  holders
  profile     Profile.

… additional help on the history command:

vfapi history --help
Usage: vfapi history [OPTIONS] TICKER

Options:
  --period [1d|5d|1mo|3mo|6mo|1y|2y|5y|10y|ytd|max]
  --interval [1m|2m|5m|15m|30m|60m|90m|1h|1d|5d|1wk|1mo|3mo]
  --csv
  --help                          Show this message and exit.

So, lets query for some history for IBM …

$ vfapi history IBM
                           Open        High         Low       Close   Volume
2021-03-01 14:30:00  120.349998  122.320000  119.860001  120.739998  5714500
2021-03-02 14:30:00  120.739998  121.900002  120.260002  120.330002  4522200
2021-03-03 14:30:00  120.500000  122.629997  119.980003  122.360001  7396200
2021-03-04 14:30:00  122.000000  123.220001  118.760002  120.110001  8062100
2021-03-05 14:30:00  120.639999  123.750000  120.250000  122.830002  6944900
2021-03-08 14:30:00  122.989998  126.849998  122.879997  124.809998  7236600
2021-03-09 14:30:00  125.400002  126.430000  124.160004  124.180000  5608200
2021-03-10 14:30:00  125.050003  128.240005  124.610001  127.870003  7243500
2021-03-11 14:30:00  128.089996  128.639999  126.779999  127.139999  5145000
2021-03-12 14:30:00  127.190002  127.680000  126.610001  127.610001  4009600
2021-03-15 13:30:00  127.769997  128.750000  127.540001  128.580002  3420600
2021-03-16 13:30:00  128.279999  128.520004  127.339996  128.240005  4630400
2021-03-17 13:30:00  128.460007  129.490005  127.489998  129.029999  4244800
2021-03-18 13:30:00  128.940002  131.000000  127.790001  130.059998  5834600
2021-03-19 13:30:00  130.020004  130.440002  128.529999  128.899994  9830600
2021-03-22 13:30:00  128.500000  130.720001  127.889999  130.550003  4164900
2021-03-23 13:30:00  130.440002  131.559998  129.800003  130.460007  4356400
2021-03-24 13:30:00  130.949997  132.110001  130.570007  130.619995  4005000
2021-03-25 13:30:00  130.330002  133.240005  129.770004  133.070007  5554000
2021-03-26 13:30:00  133.289993  136.479996  133.119995  136.380005  5562500
2021-03-29 13:30:00  135.979996  137.070007  135.509995  135.860001  4620900

The Virtual Finance API provides access to data from financial sites as if it is accessing a REST-API. Currently covered:

yahoo ‘endpoints’ to get:

financials

history

holders

options

profile

screener

screeners

yahooindex

business inisder ‘endpoint’:

fetch ISIN code

yfinance compatibility ‘endpoints’

standardized JSON ‘endpoints’

With request-classes for these endpoints, getting data is as easy as:

>>> import json
>>> import virtual_finance_api as fa
>>> import virtual_finance_api.endpoints.yahoo as yh

>>> client = fa.Client()
>>> r = yh.Holders('IBM')
>>> rv = client.request(r)
# lets get the 'major' holders from that JSON response
>>> print(json.dumps(rv['major'], indent=2))

{
   "0": {
     "0": "0.13%",
     "1": "58.58%",
     "2": "58.66%",
     "3": "2561"
   },
   "1": {
     "0": "% of Shares Held by All Insider",
     "1": "% of Shares Held by Institutions",
     "2": "% of Float Held by Institutions",
     "3": "Number of Institutions Holding Shares"
   }
}

With the extensions.stdjson endpoints this looks like:

>>> import virtual_finance_api.extensions.stdjson.endpoints as je
>>> client = fa.Client()
>>> r = je.Holders('IBM')
>>> rv = client.request(r)
# lets get the 'major' holders from that JSON response
>>> print(json.dumps(rv['major'], indent=2))

[
  [
    "0.13%",
    "% of Shares Held by All Insider"
  ],
  [
    "58.25%",
    "% of Shares Held by Institutions"
  ],
  [
    "58.33%",
    "% of Float Held by Institutions"
  ],
  [
    "2696",
    "Number of Institutions Holding Shares"
  ]
]

It make more sense to group the information. The base classes simply pass the JSON data the way it is scraped from the source URL. Derived classes can be used to transform this data. The extension.stdjson performs this task.

Yfinance compatibility¶

There is a compatibility layer with Yfinance too. It provides requests derived from the base requests, extended with properties that give the same information as Yfinance does.

The Holders-example from above becomes:

>>> import json
>>> import virtual_finance_api as fa
>>> import virtual_finance_api.compat.yfinance.endpoints as yf

>>> client = fa.Client()
>>> r = yf.Holders('IBM')
>>> rv = client.request(r)
>>> # lets get the 'major' holders from that JSON response
>>> print(r.major)


        0                                      1
0   0.13%        % of Shares Held by All Insider
1  58.58%       % of Shares Held by Institutions
2  58.66%        % of Float Held by Institutions
3    2561  Number of Institutions Holding Shares

>>> # or, that same information from the dataframe in JSON
>>> # (dump, load, dump to 'pretty print')
>>> print(json.dumps(json.loads(r.major.to_json()), indent=2))
{
   "0": {
     "0": "0.13%",
     "1": "58.58%",
     "2": "58.66%",
     "3": "2561"
   },
   "1": {
     "0": "% of Shares Held by All Insider",
     "1": "% of Shares Held by Institutions",
     "2": "% of Float Held by Institutions",
     "3": "Number of Institutions Holding Shares"
   }
}

>>> print(r.institutional)
                                       Holder    Shares Date Reported   % Out       Value
0                  Vanguard Group, Inc. (The)  73806391    2020-12-30  0.0826  9290748499
1                              Blackrock Inc.  62271273    2020-12-30  0.0697  7838707845
2                    State Street Corporation  51941856    2020-12-30  0.0581  6538440833
3               Geode Capital Management, LLC  13310817    2020-12-30  0.0149  1675565643
4  Charles Schwab Investment Management, Inc.  12571878    2020-12-30  0.0141  1582548002
5                  Northern Trust Corporation  10652880    2020-12-30  0.0119  1340984534
6                              Morgan Stanley   9853901    2020-12-30  0.0110  1240409057
7         Bank Of New York Mellon Corporation   9628160    2020-12-30  0.0108  1211992780
8           Norges Bank Investment Management   8865649    2020-12-30  0.0099  1116007896
9                 Bank of America Corporation   8074146    2020-12-30  0.0090  1016373498

See the https://virtual-finance-api.readthedocs.io/en/latest/?badge=latest for details.

Credits¶

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

Virtual API: the library for finance!¶

Virtual Finance API¶

Interactive¶

Install¶

… Or the latest¶

Yfinance compatibility¶

Credits¶

Indices and tables¶

Virtual Finance API

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