pbharrin / alpha-compiler Goto Github PK

Hi, I was following the instructions for installing on window, but after running the script load_quandl_sf1.py I got the error "No bundle registered with the name 'sep' "

Updated with zipline ingest, set my quandl key properly but could not solve it.
Thank you for any help.

Hey @pbharrin, I did all the necessary modifications, and as I ran load_quandl_sf1.py, I got the error below.

Loading Extensions

Traceback (most recent call last):
File "/Users/zukangy/Desktop/Eonum/alpha-compiler/alphacompiler/data/load_quandl_sf1.py", line 218, in
num_tickers = num_tkrs_in_bundle(BUNDLE_NAME)
File "/Users/zukangy/Desktop/Eonum/alpha-compiler/alphacompiler/data/load_quandl_sf1.py", line 181, in num_tkrs_in_bundle
return len(get_ticker_sid_dict_from_bundle(bundle_name))
File "/Users/zukangy/Desktop/Eonum/alpha-compiler/alphacompiler/util/zipline_data_tools.py", line 95, in get_ticker_sid_dict_from_bundle
all_equities = get_tickers_from_bundle(bundle_name)
File "/Users/zukangy/Desktop/Eonum/alpha-compiler/alphacompiler/util/zipline_data_tools.py", line 69, in get_tickers_from_bundle
lifetimes = bundle_data.asset_finder._compute_asset_lifetimes()
TypeError: _compute_asset_lifetimes() missing 1 required positional argument: 'country_codes'

Process finished with exit code 1

do you have any recommendations or what the country_code should be?

Hi Peter,

I quite enjoy playing with your site http://alphacompiler.com/. I looked through this repo and I don't see any code that actually compiles "101" style alphas to zipline pipeline factors. I suppose that's intentional 😄 . I'd like to include an alpha compiler of this sort in my package alphatools. Would you be willing to open source your code? If not, would you provide some general advice on how you did this? Lexer, parser, etc.

Thanks,
Jonathan

Hi @pbharrin . It is a wonderful blog and I enjoyed ingesting the fundamental data into zipline. I was wondering how I can access the file sector_etf_data.csv mentioned in risk_data_prep and also factor_loadings.h5?

I've used the sep script to ingest the sep data set from a dump and it works but with some warnings:

a total of 8639 securities were loaded into this bundle
/Users/phil/miniconda3/envs/p3zip/lib/python3.5/site-packages/zipline/data/us_equity_pricing.py:931: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  if not issubdtype(actual, expected):
[2018-03-27 04:38:36.511868] WARNING: UsEquityPricing: Couldn't compute ratio for dividend {'ex_date': numpy.datetime64('2008-01-02T00:00:00.000000000'), 'amount': nan, 'sid': 220}
[2018-03-27 04:38:36.513775] WARNING: UsEquityPricing: Couldn't compute ratio for dividend {'ex_date': numpy.datetime64('2008-01-02T00:00:00.000000000'), 'amount': 0.1, 'sid': 257}
[2018-03-27 04:38:36.514156] WARNING: UsEquityPricing: Couldn't compute ratio for dividend {'ex_date': numpy.datetime64('2008-01-02T00:00:00.000000000'), 'amount': nan, 'sid': 303}
[2018-03-27 04:38:36.514422] WARNING: UsEquityPricing: Couldn't compute ratio for dividend {'ex_date': numpy.datetime64('2008-01-02T00:00:00.000000000'), 'amount': 0.18, 'sid': 538}
[2018-03-27 04:38:36.514710] WARNING: UsEquityPricing: Couldn't compute ratio for dividend {'ex_date': numpy.datetime64('2008-01-02T00:00:00.000000000'), 'amount': 0.24, 'sid': 579}
...

and then when I try to use it with the simple pipeline engine I get this:

~/miniconda3/envs/p3zip/lib/python3.5/site-packages/zipline/data/us_equity_pricing.py in load_adjustments(self, columns, dates, assets)
   1302             list(columns),
   1303             dates,
-> 1304             assets,
   1305         )
   1306 

~/miniconda3/envs/p3zip/lib/python3.5/site-packages/zipline/data/_adjustments.pyx in zipline.data._adjustments.load_adjustments_from_sqlite()

~/miniconda3/envs/p3zip/lib/python3.5/site-packages/zipline/data/_adjustments.pyx in zipline.data._adjustments.load_adjustments_from_sqlite()

TypeError: a float is required

any ideas?

I managed to ingest, see pull request, but than load_quandl_sf1.py did not work.
Th issue is this:

lifetimes = bundle_data.asset_finder._compute_asset_lifetimes(frozenset([str("US")]))
TypeError: _compute_asset_lifetimes() takes 1 positional argument but 2 were given

(ml4t_p8) carsten@MacBook-Pro-2 ~ % python /Users/carsten/Documents/Python/My_Python_Models/ML-Factor_invest/load_quandl_sf1.py
Loading Extensions

Traceback (most recent call last):
File "/Users/carsten/Documents/Python/My_Python_Models/ML-Factor_invest/load_quandl_sf1.py", line 219, in
num_tickers = num_tkrs_in_bundle(BUNDLE_NAME)
File "/Users/carsten/Documents/Python/My_Python_Models/ML-Factor_invest/load_quandl_sf1.py", line 182, in num_tkrs_in_bundle
return len(get_ticker_sid_dict_from_bundle(bundle_name))
File "/Users/carsten/anaconda3/envs/ml4t_p8/lib/python3.8/site-packages/Alpha_Compiler-0.1-py3.8.egg/alphacompiler/util/zipline_data_tools.py", line 96, in get_ticker_sid_dict_from_bundle
all_equities = get_tickers_from_bundle(bundle_name)
File "/Users/carsten/anaconda3/envs/ml4t_p8/lib/python3.8/site-packages/Alpha_Compiler-0.1-py3.8.egg/alphacompiler/util/zipline_data_tools.py", line 70, in get_tickers_from_bundle
lifetimes = bundle_data.asset_finder._compute_asset_lifetimes(frozenset([str("US")]))
TypeError: _compute_asset_lifetimes() takes 1 positional argument but 2 were given
(ml4t_p8) carsten@MacBook-Pro-2 ~ %

Thanks for sharing this with the world!

I'm working on some algos locally using zipline and had trouble reproducing the sector data that is available on quantopian. I spent a decent amount of trying on my own, somehow came across this and was up and running in an hour.

a couple changes/suggestions (take as you wish!)

doesn't require a local hardcoded path

BASE_PATH = "{}/".format(os.path.dirname(os.path.realpath(__file__)))

doesn't require a separate loading of the data. pipeline will load if needed.

    def __init__(self, *args, **kwargs):
        try:
            self.data = np.load(BASE_PATH + SID_FILE)
        except OSError as e:
            # File not found, let's create and try again
            create_sid_table_from_file()
            self.data = np.load(BASE_PATH + SID_FILE)

Hey, @pbharrin, I was implementing your way of loading the fundamentals data, and after a series of modifications, as I tried to run load_quandl_sf1.py, it says no file named /Users/xxx/.../SHARADAR_SF1_2daa4baaad2a300c166b5c0f7e546bd1.csv'.

In order to fix it, I manually created the csv file and put it into the right folder, but I got another error message saying that

pandas.errors.EmptyDataError: No columns to parse from file

I am wondering what the dump file is in the load_quandl_sf1.py?

best,