QuantConnect's LEAN engine is primarily written in C#, and its Python functionality is achieved through a C# to Python interoperation layer. This means that the Python version of LEAN accesses the C# methods. Therefore, the Python methods in LEAN are essentially the same as the C# methods.

You can find the LEAN class documentation here. Although this documentation is for C#, you should be able to access all of the C# methods in LEAN using Python.

For Python-specific information, you can refer to the Python and LEAN section in the QuantConnect documentation. This section explains how Python interacts with the LEAN engine and provides some examples.

Additionally, you can check out the tutorials provided by QuantConnect. These tutorials cover the QuantConnect API in both C# and Python.

Lastly, you can also refer to the LEAN API documentation for a comprehensive list of all methods and properties.

Please note that Python in LEAN is not exactly the same as standard Python due to the interoperation with C#. For example, named parameters are not supported when your Python code calls C#/.NET code inside LEAN. However, named parameters are not ignored when Python code calls other Python code since then, the entire execution happens in the Python runtime.

Here is an example of how to use the History method in Python:

from datetime import datetime 
eurusd_test = qb.History(["EURUSD"],datetime(2018,8,1,10,0),datetime(2018,8,2,10,0),Resolution.Minute)

In this example, qb.History is a method call to the LEAN engine. The returned object is a MemoizingEnumerable which is a raw C# type accessible in Python. You can directly enumerate this object with standard Python for loops, or to convert it to a native type, wrap the object in the list().