A utility for crawling historical and Real-time Quotes data of China stocks
Project description
easy to use as most of the data returned are pandas DataFrame objects
can be easily saved as csv, excel or json files
can be inserted into MySQL or Mongodb
Target Users
financial market analyst of World
learners of financial data analysis with pandas/NumPy
people who are interested in financial data
Installation
pip install blueonion
Upgrade
pip install blueonion –upgrade
Quick Start
import blueonion as ts pro = ts.pro_api('dfcf7cda6b195dc2966a4baeab0fcaea4b809edb6c10e70a') pro.query('esgData', isin='AEA006101017', pageSize=2, pageNo=2) pro.query('fundData', isin='AEA006101017') pro.query('equityData', isin='AEA006101017')
return:
open high close low volume p_change ma5 date 2012-01-11 6.880 7.380 7.060 6.880 14129.96 2.62 7.060 2012-01-12 7.050 7.100 6.980 6.900 7895.19 -1.13 7.020 2012-01-13 6.950 7.000 6.700 6.690 6611.87 -4.01 6.913 2012-01-16 6.680 6.750 6.510 6.480 2941.63 -2.84 6.813 2012-01-17 6.660 6.880 6.860 6.460 8642.57 5.38 6.822 2012-01-18 7.000 7.300 6.890 6.880 13075.40 0.44 6.788 2012-01-19 6.690 6.950 6.890 6.680 6117.32 0.00 6.770 2012-01-20 6.870 7.080 7.010 6.870 6813.09 1.74 6.832
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