According to recent trends in financial data analysis area, more and more people begin to use Python in their project. The powerful packages, such as NumPy, Pandas and TensorFlow, all contribute to Python’s prevalence.
However, the I/O functions of Python can not meet people’s need of fast storing and retrieving very large amount of data. That’s why PyTables appears. You can find a fine introduction to PyTables on its official FAQ page.
PyTables is a package for managing hierarchical datasets designed to efficiently cope with extremely large amounts of data. It is …
To avoid repetition of official tutorials, I will directly show how to operate a financial database here.
- Create security node
- Add/Update security data
- Delete security node
- Retrieve data
- Get security attributes