In python, there are many libraries that can be used to get the stock market data. The most common set of data is the price volume data. These data can be used to create quant strategies, technical strategies, or very simple buy-and-hold strategies. The different Python libraries which provide stock market data are as follows:
Huge Stock Market Dataset
Historical daily prices and volumes of all U.S. stocks and ETFs
High-quality financial data is expensive to acquire and is therefore rarely shared for free. Here I provide the full historical daily price and volume data for all US-based stocks and ETFs trading on the NYSE, NASDAQ, and NYSE MKT. It's one of the best datasets of its ...
I did something similar with a friend.
We built a perl (but would work in python/R/etc) just as well, and stock by stock we used the Yahoo Finance API, which seems to have been removed in its earlier form, but through Rapid API you can access the same information. With the data we retrieved, we created a postgres database with the various stock price ...
It turns out that you actually can get this data from Yahoo! Finance, but you just need to know the numeric representation of the Chinese ticker symbols of interest.
# A tibble: 141,040 x 8
symbol date open high low close volume adjusted
<chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl&...
I think an easy way would be reverse image search. You'll get assorted "similar" images, but no clear license. Once you have a folder of images by scraping, you can manually clean them to include only charts you are looking for. (works for 100s but not 1000s)