People speak highly of sentdex's Quantopian tutorial videos: https://pythonprogramming.net/finance-programming-python-zipline-quantopian-intro/ and there are also Dan Dunn's official tutorials: https://www.youtube.com/playlist?list=PLRFLF1OxMm_XpxC3VkDKOuEdWvBtxUI-U , not to mention the lecture series (which is more about finance in general): https://www.quantopian.com/lectures

Thanks Simon.

I've already watched all of the Sentdex videos (they are excellent), taken a Python course and watched most of Dan Dunn's tutorials. I'll be at Quantcon and am taking the factor class the day after. I have a lot of work to do between now and then.

The areas I keep having problems with are 1) the use of pandas data frames don't seem to be consistent (because I'm missing something) in Quantopian and 2) the use of content.X in functions and how it's passed between functions.

For example, if I want to call a function (in minute mode) that calculates some statistics after the first bar after the open, I create a function called heavy_calcs. In initialize, I create a schedule function that calls this function 1 minute after the open. Such as:

def heavy_calcs (context, data):
stock = context.stock
context.AvgRange = history(30, '1d', 'high')[stock] - history(30, '1d', 'low')[stock].mavg(30)
context.Gap = history(1, '1d', 'price')[stock] - history(0, '1d', 'open_price')[stock]

I then want this data (AvgRange and Gap) to be available in the handle_data function. This is where I keep getting hung up.

When I try to build an algo with the above function, it builds fine, however it throws an error at the line with context.AvgRange when I try to run a backtest.

Yo Trading Gangster.

Just came across your post and thought I could help you out.

The reason why handle_data is failing is probably because it is attempting to run before heavy_calcs has had the opportunity to calculate context.AvgRange! I suggest you do the following:

def before_trading_start(context,data):
context.trade = False

def heavy_calcs (context, data):
stock = context.stock
context.AvgRange = history(30, '1d', 'high')[stock] - history(30, '1d', 'low')[stock].mavg(30)
context.Gap = history(1, '1d', 'price')[stock] - history(0, '1d', 'open_price')[stock]
if context.AvgRange > 0:
context.trade = True

def handle_data(context, data):
if context.trade:
[INSERT LOGIC HERE]

Hi Trading Gangster,

Just wanted to ask - did you have any luck finding a tutor? How is you progress today? Please let us know.

Thank you!