goquantdata

Python client library for Go Quant Financial Data Services


Install
pip install goquantdata==0.0.6

Documentation

GO Quant Data Client API v1

Build local csv database and get stock daily open, high, low, close, volume. Client also support all original API function of quandl and jqdata.

version 0.0.4

Install

pip install goquantdata

Usage

Quick Start

Example 1. Build Local DB and Get symbol open, close, high, low, volume

from datetime import datetime
import goquantdata
from os.path import expanduser
import goquantdata.local.private_config as cfg

client = goquantdata.LocalClient(db_dir=expanduser("~") + '/data/localdb/',
                                 key_quandl=cfg.CONFIG_QUANDL['api_key'],
                                 jq_password=cfg.CONFIG_JQDATA['password'],
                                 jq_username=cfg.CONFIG_JQDATA['username'],
                                 key_alpha_vantage=cfg.CONFIG_ALPHA_VANTAGE['api_key'])
start_date = datetime.strptime("20190102", "%Y%m%d")
end_date = datetime.strptime("20190120", "%Y%m%d")
ids_us = ["AAPL", "AMD", "TD"]
ids_cn = ["ZN9999.XSGE", "ZC9999.XZCE"]

client.build_db(start_date=start_date,
                end_date=end_date,
                ids_us=ids_us,
                ids_cn=ids_cn)

df = client.get_price(market="us",
                      ids=["TD", "AMD"],
                      start_date=start_date,
                      end_date=end_date)
print(df)

df = client.get_price(market="cn",
                      ids=["ZC9999.XZCE"],
                      start_date=start_date,
                      end_date=end_date)
print(df)

Example 2. use original sdk function To use original sdk function, for jqdata use "jq_{name of function}", for quandl, use "ql_{name of function}"

# use original sdk function
df = client.jq_get_price(security=["601228.XSHG"],
                         start_date=start_date,
                         end_date=end_date,
                         frequency='daily',
                         fields=None,
                         skip_paused=False,
                         fq='pre',
                         count=None)
print(df)

Output Format

  • get_price return dataframe
symbol date open high low close volume market
AAPL 2017-01-03 114.369701 114.893155 113.342546 114.715378 28781865.0 us

Data Source

Market Client Type Default Universe Source
cn stock local xshg300 JQData
us stock local sp500 Alpha Vantage