ehtycuact
commented
5 years ago Same issue here. Looking for a way to stop this whole mechanics either by providing the data from another source (a file, etc.) or just remove it completely.
Closed MarikoKujo closed 4 years ago
ehtycuact
commented
5 years ago Same issue here. Looking for a way to stop this whole mechanics either by providing the data from another source (a file, etc.) or just remove it completely.
tibkiss
commented
5 years ago IEX has deprecated the old API in favor of the new one: https://iextrading.com/developer/#sunset-schedule
iexcloud.io offers the chart endpoint used in zipline, but user registration is required to obtain a token for the service.
tibkiss
commented
5 years ago My temporal fix (on zipline-live, which is branched off from 1.1.0):
diff --git a/zipline/data/benchmarks.py b/zipline/data/benchmarks.py
index 45137428..72d9c3cc 100644
--- a/zipline/data/benchmarks.py
+++ b/zipline/data/benchmarks.py
@@ -30,8 +30,10 @@ def get_benchmark_returns(symbol):
The data is provided by IEX (https://iextrading.com/), and we can
get up to 5 years worth of data.
"""
+ IEX_TOKEN = 'pk_TOKEN_COMES_HERE’ # FIXME: move to param
r = requests.get(
- 'https://api.iextrading.com/1.0/stock/{}/chart/5y'.format(symbol)
+ 'https://cloud.iexapis.com/stable/stock/{}/chart/5y?token={}'.format(
+ symbol, IEX_TOKEN)
)
data = json.loads(r.text)
MarikoKujo
commented
5 years ago Inspired by this comment in #1951, here is the workaround for people who does NOT need benchmarks at all:
By default, zipline downloads benchmark data by making an http request in get_benchmark_returns() in zipline/data/benchmarks.py. It returns a pd.Series which will be saved to a csv file by ensure_benchmark_data() in zipline/data/loaders.py. So we can create a dummy benchmark file by setting all data entries to zero.
First, replace benchmarks.py with:
import pandas as pd
from trading_calendars import get_calendar
def get_benchmark_returns(symbol, first_date, last_date):
cal = get_calendar('NYSE')
dates = cal.sessions_in_range(first_date, last_date)
data = pd.DataFrame(0.0, index=dates, columns=['close'])
data = data['close']
return data.sort_index().iloc[1:]Then in loaders.py, replace
data = get_benchmark_returns(symbol)
with
data = get_benchmark_returns(symbol, first_date, last_date)
In this example NYSE is used, but it also works when I use AlwaysOpenCalendar in my backtest, so I did not try to change it to some other calendar.
This is only a hack. In the long run I would suggest to change the benchmark downloading method to request other API in case you would like to use benchmarks in the future.
SeungYong-Baek
commented
5 years ago @MarikoKujo Thank you for your comment again. Today morning, I did the test with your hack. Unfortunately, It doesn't worked in my environment. I haven't found the cause yet. I am going to try again with your hack carefully. Thank you very much.
@tibkiss I did the test with your fix. After fail, I noticed your environment is very different from my environment. Thank you very much.
shlomiku
commented
5 years ago here's a fix that goes back to yahoo as a benchmark source. replace this method in benchmarks.py and don't forget to change the call to it in loader.py
import numpy as np
import pandas as pd
import pandas_datareader.data as pd_reader
def get_benchmark_returns(symbol, first_date, last_date):
"""
Get a Series of benchmark returns from Yahoo associated with `symbol`.
Default is `SPY`.
Parameters
----------
symbol : str
Benchmark symbol for which we're getting the returns.
The data is provided by Yahoo Finance
"""
data = pd_reader.DataReader(
symbol,
'yahoo',
first_date,
last_date
)
data = data['Close']
data[pd.Timestamp('2008-12-15')] = np.nan
data[pd.Timestamp('2009-08-11')] = np.nan
data[pd.Timestamp('2012-02-02')] = np.nan
data = data.fillna(method='ffill')
return data.sort_index().tz_localize('UTC').pct_change(1).iloc[1:]@MarikoKujo @shlomikushchi
I did the test with MarikoKujo's and shlomikushchi 's temporary fix. Unfortunately, It doesn't worked in my environment. Two fixes showed the same error. I think that the cause of error is my different environment from yours. So, I need to investigate more my environment. Thank you so much.
/home/seungyong/zipline/lib/python3.5/site-packages/empyrical/stats.py:704: RuntimeWarning: invalid value encountered in true_divide out=out, /home/seungyong/zipline/lib/python3.5/site-packages/empyrical/stats.py:790: RuntimeWarning: invalid value encountered in true_divide np.divide(average_annual_return, annualized_downside_risk, out=out) Traceback (most recent call last): File "pandas/_libs/index.pyx", line 449, in pandas._libs.index.DatetimeEngine.get_loc File "pandas/_libs/hashtable_class_helper.pxi", line 811, in pandas._libs.hashtable.Int64HashTable.get_item File "pandas/_libs/hashtable_class_helper.pxi", line 817, in pandas._libs.hashtable.Int64HashTable.get_item KeyError: 1421625600000000000
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "./console-test.py", line 58, in
zipper-123
commented
5 years ago This seems to have a few issues going now so Ill weigh in on the most commented one.
I tried all of the workarounds with no luck.
Replacing the get_bencmark_returns() method just defers to other null references down the line.
Fixing the IEX API defers to the treasury data failing for me. Since I am using BTC data, OHLCV.
Is there any supported way to backtest crypto currency data? Are the benchmark and treasury data pulls really that crucial?
AndreasClenow
commented
5 years ago @zipper-123 Perhaps you have a faulty cached file. Remember that ensure_benchmark_data in loader.py first attempts to read from disk. That happened to my while I was tinkering with a solution.
I ended up implementing a minor variation of the solution suggested by @marketneutral to sidestep the issue until it's properly fixed. I kept the signature of get_benchmark_returns, and just used a wider date range than I'll ever need.
In benchmark_py
def get_benchmark_returns(symbol):
cal = get_calendar('NYSE')
first_date = datetime(1930,1,1)
last_date = datetime(2030,1,1)
dates = cal.sessions_in_range(first_date, last_date)
data = pd.DataFrame(0.0, index=dates, columns=['close'])
data = data['close']
return data.sort_index().iloc[1:]And bypassing the cache in loader.py
"""
if data is not None:
return data
"""
grobbie94
commented
5 years ago Another fix is getting a free IEX api key and altering the API request in benchmarks.py
r= requests.get(
"https://cloud.iexapis.com/stable/stock/{}/chart/5y?chartCloseOnly=True&token={}".format(symbol, IEX_KEY)
)@tibkiss @grobbie94 Thank you for your fix. It works well for my script.
elliotvilhelm
commented
5 years ago jesus christ .. just spent two hours on this
ghost
commented
5 years ago Has the solution been found for this?
shlomiku
commented
5 years ago yes... mine is not a temporary fix. it's a solution. I'm working with it for more than a month
mikebardpython
commented
5 years ago getting the same error, tried all the solutions on this thread as well as the one here
is there a solution forthcoming?
weu39843
commented
5 years ago Getting the same error using local data (csv -> DataFrame -> panel) and it's not clear to me how your fix works @shlomikushchi as I'm not using yahoo data. Maybe you have an idea how to tweak your code in order to fix the problem when using local data.
jecker7
commented
5 years ago This is still not working. @weu39843 I'm having the same issue with local data as well, passing a CSV as a DataFrame. When trying @AndreasClenow solution and all the others I get the following error:
Traceback (most recent call last):
File "<stdin>", line 39, in <module>
File "/usr/local/lib/python3.6/dist-packages/zipline/utils/run_algo.py", line 430, in run_algorithm
blotter=blotter,
File "/usr/local/lib/python3.6/dist-packages/zipline/utils/run_algo.py", line 188, in _run
trading_days=trading_calendar.schedule[start:end].index,
File "/usr/local/lib/python3.6/dist-packages/zipline/finance/trading.py", line 103, in __init__
self.bm_symbol,
File "/usr/local/lib/python3.6/dist-packages/zipline/data/loader.py", line 149, in load_market_data
environ,
File "/usr/local/lib/python3.6/dist-packages/zipline/data/loader.py", line 201, in ensure_benchmark_data
environ)
File "/usr/local/lib/python3.6/dist-packages/zipline/data/loader.py", line 324, in _load_cached_data
data = from_csv(path)
File "/usr/local/lib/python3.6/dist-packages/zipline/data/loader.py", line 307, in from_csv
squeeze=True,
File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 562, in parser_f
return _read(filepath_or_buffer, kwds)
File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 325, in _read
return parser.read()
File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 815, in read
ret = self._engine.read(nrows)
File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 1387, in read
index, names = self._make_index(data, alldata, names)
File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 1030, in _make_index
index = self._agg_index(index)
File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 1111, in _agg_index
arr = self._date_conv(arr)
File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 2272, in converter
lib.try_parse_dates(strs, dayfirst=dayfirst))
File "/usr/local/lib/python3.6/dist-packages/pandas/util/decorators.py", line 91, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/pandas/tseries/tools.py", line 291, in to_datetime
unit=unit, infer_datetime_format=infer_datetime_format)
File "/usr/local/lib/python3.6/dist-packages/pandas/tseries/tools.py", line 427, in _to_datetime
return _convert_listlike(arg, box, format)
File "/usr/local/lib/python3.6/dist-packages/pandas/tseries/tools.py", line 398, in _convert_listlike
require_iso8601=require_iso8601
File "pandas/tslib.pyx", line 2134, in pandas.tslib.array_to_datetime (pandas/tslib.c:41972)
File "pandas/tslib.pyx", line 2269, in pandas.tslib.array_to_datetime (pandas/tslib.c:40684)
File "pandas/tslib.pyx", line 2229, in pandas.tslib.array_to_datetime (pandas/tslib.c:39919)
File "pandas/src/datetime.pxd", line 141, in datetime._string_to_dts (pandas/tslib.c:85631)
SystemError: <class 'str'> returned a result with an error set
<class 'str'> returned a result with an error set@jecker7 when you say passing a local csv, do you mean that you provide a DataPanel as the data parameter for _zipline.runalgorith?
That way of providing data is no longer supported and Q are strongly recommending against using it. I didn't try that method in quite some time, after they told me a couple of years ago not to use it.
I'd suggest using the regular bundle/ingest process to read your csv.
sinnergarden
commented
5 years ago @shlomikushchi I tried your solution, it works well for me!! Thanks
BTW, what is the point of doing the following operations:
data[pd.Timestamp('2008-12-15')] = np.nan
data[pd.Timestamp('2009-08-11')] = np.nan
data[pd.Timestamp('2012-02-02')] = np.nan@sinnergarden glad to hear that it was copied from the original zipline code. before zipline moved to IEX they used pd.DataReader. they used google and not yahoo. but I copied the code from their solution and switched to yahoo.
nateGeorge
commented
5 years ago Zipline will have to move their datasource for SPY data somewhere else besides IEX, or change the setup to require an API key. Another way to fix is:
ipython, import zipline, zipline.__file__pk_numbers... below), and change the requests line to: token = 'pk_numbersnumbersnumbers'
r = requests.get(
'https://cloud.iexapis.com/stable/stock/{}/chart/5y?token={}'.format(symbol, token)
)I guess it's the nature of the beast with financial data that it's hard to find for free...but annoying.
suitablyquantified
commented
5 years ago It would make far more sense for the benchmark routines to use a symbol from a bundle rather than any hardcoded external source.
nateGeorge
commented
5 years ago @stocktrader8888 no free bundles on Quandl have SPY (default benchmark I think). Could get it with the yfinance package, but that requires the latest pandas and zipline can't use latest pandas.
nateGeorge
commented
5 years ago Plus IEX only has 5y of history for SPY which is pretty weak. yfinance could get everything
AndreasClenow
commented
5 years ago My take on solution:
Put proper error handling in place. No vital functionality requires benchmark data, and there's no reason for a full on crash if it can't be reached. Just print a warning message and move on with the backtest.
A hard coded benchmark from a hard coded source makes no sense. Using the SPY as bench doesn't make sense either, in particular since this api call doesn't seem to take dividends into account. If you really need a bm, have the symbol and bundle configurable.
People who are serious enough about backtesting to bother with setting up a local Zipline are not very likely to rely on Yahoo, Quandle, Google or other free sources, and they are very likely to use proper benchmarks instead of price series of an ETF.
DavisOwen
commented
4 years ago @AndreasClenow
Just curious, what would be a good source for S&P 500 benchmark data, or other benchmarks that you use?
DavisOwen
commented
4 years ago I like Andreas' suggestion, namely that not having benchmark data should be a warning rather than an error. There should also, as he said, be an option for users to provide their own csv/dataframe as benchmark data.
Looking at the code, the TradingEnvironment object is where the benchmark returns are ultimately loaded. I'm not sure where TradingEnvironment gets used by zipline, but I could Imagine a good way to do this would be to add a class method setter to TE where you just provide a benchmark dataframe manually. This seems like it would require the least overhead.
However, referencing the first suggestion, I'm not sure what the expected behavior of zipline should be if there is no benchmark data found. It could be non-trivial to run a test without a benchmark. A workaround to this has been discussed above, where you can simply pass a dataframe of all zeros, but this certainly isn't elegant either. It would be nice to be able to circumvent this entirely, but I think for now the best solution is find some sort of consistent (albeit low quality) data source for zipline to use (like google, yahoo, etc.)
I suggest creating a PR for adding @shlomikushchi 's change in the meantime, and further discussing detail on the TradingEnvironment change I added above. I can make the branch if you'd like.
EDIT: It actually looks like a commit was made that addresses this issue (intentionally or not). It's not on the current pip or conda repos for zipline. But it is on the master branch of zipline.
https://github.com/quantopian/zipline/commit/ce2a2363f8fd05724120de3f667134daa37f7d8b
@ssanderson added an argument to run_algorithm called benchmark_returns. If you just run your algorithm with run_algorithm(), you can dowload your own benchmark in csv, run pd.read_csv() to load, and pass it to run_algorithm as benchmark_data. The only issue I'm running into now is I'm not sure the exact format that benchmark_data expects. Looking at _load_cache_data in loader.py, it looksl like this is the command you should run to read the csv, but I'm still having some issues.
pd.read_csv(
path,
parse_dates=[0],
index_col=0,
header=None,
# Pass squeeze=True so that we get a series instead of a frame.
squeeze=True,
).tz_localize('UTC')If anyone knows the proper formatting for benchmark data we can basically close this issue as people can just provide their own benchmark on a per-test basis.
EDIT 2:
I got it to work. In the process I discovered that there has been an attempt to allow custom benchmark data via creating a bundle with csvdir and adding it to set_benchmarks in initialize.
https://stackoverflow.com/questions/44199678/how-to-manually-provide-a-benchmark-in-zipline
https://www.zipline.io/bundles.html
However, I don't like this because it requires you to have a specific ohlcvs data and seems like a lot of overhead.
If you want a custom benchmark, just use the current master branch of zipline and pass benchmark_returns as an argument to run_algorithm. The format of benchmark returns is a pandas series with the adj. close (or whatever data you want) as the data and the Timestamp as the index.
AndreasClenow
commented
4 years ago @DavisOwen The question is if any free online data source is really reliable enough. Just a few years ago, it seemed like Yahoo Finance was rock solid... APIs change, providers remove data, anything can happen. Quandl seemed like a good solution until they started removing free data and moving it to premium.
Also keep in mind here that using the 'regular' S&P price index is nonsensical and misleading. That's what most retail traders would use, because that's what most retail traders are familiar with. But it will be greatly misleading. It doesn't contain reinvested dividends and therefore will have a massive error factor over time, making your strategy look great.
Even some banks and fund managers run this little trick. Compare yourself to the price index, and you look great. Not illegal, just deceptive. The difference over time is really enormous.
For the same reason, using the SPY as a benchmark is equally deceptive.
What you need to use is the total return index, in this case the S&P 500 TR.
DavisOwen
commented
4 years ago @AndreasClenow Thanks for the info, I honestly never even considered the accuracy of using SPY, you make a great point about the dividends.
If I can get some feedback from the devs on my comment above, I truly think allowing the user to manually inject their own csv benchmark file into the backtest seems like the best solution at this point, as it doesn't rely on API's and allows the user to use any data they like.
k-s30011
commented
4 years ago @zipper-123 Perhaps you have a faulty cached file. Remember that ensure_benchmark_data in loader.py first attempts to read from disk. That happened to my while I was tinkering with a solution. I ended up implementing a minor variation of the solution suggested by @marketneutral to sidestep the issue until it's properly fixed. I kept the signature of get_benchmark_returns, and just used a wider date range than I'll ever need. In benchmark_py def get_benchmark_returns(symbol): cal = get_calendar('NYSE') first_date = datetime(1930,1,1) last_date = datetime(2030,1,1) dates = cal.sessions_in_range(first_date, last_date) data = pd.DataFrame(0.0, index=dates, columns=['close']) data = data['close'] return data.sort_index().iloc[1:]
And bypassing the cache in loader.py """ if data is not None: return data """
Hey Andreas, when you say bypassing the cache in loader.py. do we put the quotation marks for each line of
""" If data is not None: return data """ ??
AndreasClenow
commented
4 years ago The triple quote is a block comment, meaning that everything between will be disabled.
"""
anything between the triple quotes will be interpreted as a comment, not executed as code.
print("This will not be printed")
"""
print("This will be printed")The triple quote is a block comment, meaning that everything between will be disabled. """ anything between the triple quotes will be interpreted as a comment, not executed as code. print("This will not be printed") """ print("This will be printed")
ah I see, got it. I've managed to set up zipline with the help of your book and the following the trend forum. After hours of looking through GitHub, Following the Trend forum and your book trading evolved, I've finally managed to run the 'First Zipline Backtest' code.
It ran the codes somewhat smooth and produced the graphs. However, now I have this notification below the kernel. (In a red box)
"C:\Users\name\Anaconda3\envs\zip35\lib\site-packages\empyrical\stats.py:704: RuntimeWarning: invalid value encountered in true_divide out=out, C:\Users\name\Anaconda3\envs\zip35\lib\site-packages\empyrical\stats.py:790: RuntimeWarning: invalid value encountered in true_divide np.divide(average_annual_return, annualized_downside_risk, out=out)"
Is this a big problem? and will it cause me further problems down the line?
If anyone could help me understand why it's happening and if there's a solution for it, I'd be greatful.
Thank you.
zoakes
commented
4 years ago I can't get this to work, getting the same error: [JSONDecodeError: Expecting value: line 1 column 1 (char 0)] -- I tried all the 'hack' fixes I saw, and none resolved the issue. Does this API just not work? I don't really know what to do if it lacks it's core functionality.
tibkiss
commented
4 years ago @zoakes : the solution I posted works for me in production for months now. Check this out: https://github.com/quantopian/zipline/issues/2480#issuecomment-502798293
zoakes
commented
4 years ago I tried a few of these — including the ones changing Benchmarks.py in libs, no luck so far.
What solution worked in production code ?
Zach
Get Outlook for iOShttps://aka.ms/o0ukef
From: Tibor Kiss notifications@github.com Sent: Tuesday, November 19, 2019 11:22:48 PM To: quantopian/zipline zipline@noreply.github.com Cc: Zach Mazz zach_oakes@outlook.com; Mention mention@noreply.github.com Subject: Re: [quantopian/zipline] Getting benckmark data via IEX API does not work anymore (#2480)
@zoakeshttps://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fzoakes&data=02%7C01%7C%7C3f511908cd034130668408d76d79af36%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637098241699220579&sdata=847cPzaNbJm8nKfNfh3H%2BokiAnptuYDv%2Brpz80UnoJE%3D&reserved=0 : the solution I posted works for me in production for months now. Check this out: #2480 (comment)https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fquantopian%2Fzipline%2Fissues%2F2480%23issuecomment-502798293&data=02%7C01%7C%7C3f511908cd034130668408d76d79af36%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637098241699230584&sdata=xhcMFDF5yf4wpChkbEhn%2FVuOvGoJQuPN3TbJ1iVEL2s%3D&reserved=0
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHubhttps://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fquantopian%2Fzipline%2Fissues%2F2480%3Femail_source%3Dnotifications%26email_token%3DALPUCIEVLFFOMQXJ5RZW2I3QUTCSRA5CNFSM4HYSHEN2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEEQX4RY%23issuecomment-555843143&data=02%7C01%7C%7C3f511908cd034130668408d76d79af36%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637098241699240589&sdata=xZpaMm8xvjSCaAabA4aueTcNuFn6H7QncJ%2FBTPQauNM%3D&reserved=0, or unsubscribehttps://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FALPUCIHWTZB3BEEVGMLXHCTQUTCSRANCNFSM4HYSHENQ&data=02%7C01%7C%7C3f511908cd034130668408d76d79af36%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637098241699250601&sdata=erlknTQj8mKrzQ7O0ciJ2N%2FrsfElml2wfESDp6vtMNU%3D&reserved=0.
caot
commented
4 years ago caot
commented
4 years ago My temporal fix (on zipline-live, which is branched off from 1.1.0):
diff --git a/zipline/data/benchmarks.py b/zipline/data/benchmarks.py index 45137428..72d9c3cc 100644 --- a/zipline/data/benchmarks.py +++ b/zipline/data/benchmarks.py @@ -30,8 +30,10 @@ def get_benchmark_returns(symbol): The data is provided by IEX (https://iextrading.com/), and we can get up to 5 years worth of data. """ + IEX_TOKEN = 'pk_TOKEN_COMES_HERE’ # FIXME: move to param r = requests.get( - 'https://api.iextrading.com/1.0/stock/{}/chart/5y'.format(symbol) + 'https://cloud.iexapis.com/stable/stock/{}/chart/5y?token={}'.format( + symbol, IEX_TOKEN) ) data = json.loads(r.text)
The 'Publishable' Token can be used from https://iexcloud.io/
a2926z
commented
4 years ago @zipper-123 Perhaps you have a faulty cached file. Remember that ensure_benchmark_data in loader.py first attempts to read from disk. That happened to my while I was tinkering with a solution.
I ended up implementing a minor variation of the solution suggested by @marketneutral to sidestep the issue until it's properly fixed. I kept the signature of get_benchmark_returns, and just used a wider date range than I'll ever need.
In benchmark_py
def get_benchmark_returns(symbol): cal = get_calendar('NYSE') first_date = datetime(1930,1,1) last_date = datetime(2030,1,1) dates = cal.sessions_in_range(first_date, last_date) data = pd.DataFrame(0.0, index=dates, columns=['close']) data = data['close'] return data.sort_index().iloc[1:]And bypassing the cache in loader.py
""" if data is not None: return data """
how can i bypass the cache? Where exactly should i paste the code? Sorry just learning and thank you.
carstenf
commented
4 years ago @shlomikushchi
looks like your permanent solution is working for me. Just a question, you wrote "don't forget to change the call to it in loader.py" Do i have to change something in the original loader.py file? and if yes -> what do I need to change?
Thanks
bernino
commented
4 years ago My temporal fix (on zipline-live, which is branched off from 1.1.0):
diff --git a/zipline/data/benchmarks.py b/zipline/data/benchmarks.py index 45137428..72d9c3cc 100644 --- a/zipline/data/benchmarks.py +++ b/zipline/data/benchmarks.py @@ -30,8 +30,10 @@ def get_benchmark_returns(symbol): The data is provided by IEX (https://iextrading.com/), and we can get up to 5 years worth of data. """ + IEX_TOKEN = 'pk_TOKEN_COMES_HERE’ # FIXME: move to param r = requests.get( - 'https://api.iextrading.com/1.0/stock/{}/chart/5y'.format(symbol) + 'https://cloud.iexapis.com/stable/stock/{}/chart/5y?token={}'.format( + symbol, IEX_TOKEN) ) data = json.loads(r.text)
This resolved it for me (had to +import json though).
Any chance this will be in the official release?
carstenf
commented
4 years ago here's a fix that goes back to yahoo as a benchmark source. replace this method in benchmarks.py and don't forget to change the call to it in loader.py
import numpy as np import pandas as pd import pandas_datareader.data as pd_reader def get_benchmark_returns(symbol, first_date, last_date): """ Get a Series of benchmark returns from Yahoo associated with `symbol`. Default is `SPY`. Parameters ---------- symbol : str Benchmark symbol for which we're getting the returns. The data is provided by Yahoo Finance """ data = pd_reader.DataReader( symbol, 'yahoo', first_date, last_date ) data = data['Close'] data[pd.Timestamp('2008-12-15')] = np.nan data[pd.Timestamp('2009-08-11')] = np.nan data[pd.Timestamp('2012-02-02')] = np.nan data = data.fillna(method='ffill') return data.sort_index().tz_localize('UTC').pct_change(1).iloc[1:]
Hi
I changed the benchmark.py and loader.py accordingly....
Inside the code I set:
def initialize(context): set_benchmark(symbol('SPY'))
which gives an error: 'Symbol 'SPY' was not found.'
using 'AAPL' as anSymbol gives no error.
Than
returns, positions, transactions, benchmark_rets = pf.utils.extract_rets_pos_txn_from_zipline(perf) pf.create_returns_tear_sheet(returns, benchmark_rets)
gives again an error: ValueError: not enough values to unpack (expected 4, got 3)
so it did not find: benchmark_rets
I think I'm using this wrong with zipline.run_algorithm How is the correct usage, I'm googling around since hours but can't find an example to use zipline.run_algorithm with a benchmark, basically the original solution.
Could someone please share the correct usage. Thank you very much
shlomiku
commented
4 years ago @carstenf you don't need to call set_benchmark(symbol('SPY')) it's a default in zipline.
the bundle you use doesn't include SPY so it's not a known symbol
carstenf
commented
4 years ago @shlomikushchi
ok, understood, thanks.
I'm not getting any more errors. I get a benchmark if I use set_benchmark(symbol('SPY')), because I included it now in the bundle.
But I don't get a benchmark if I want to pull it from benchmark.py.
I did the changes in benchmark.py(copied you fix), and I changed one line in the loader.py:
data = get_benchmark_returns(symbol,first_date, last_date). ....should be ok...but no benchmark...something missing?
and were is the benchmark symbol defined? Might be a good idea to use ^SP500TR, it's the total return of the S&P500, as Andreas suggested.
thanks
shlomiku
commented
4 years ago benchmark symbol is defined in loader.py: load_market_data()
ssanderson
commented
4 years ago Hey all. I'm taking a look at this this morning.
ssanderson
commented
4 years ago We've got a bunch of issues related to the IEX-sourced benchmark data failing. In the interest of having a single canonical location for the issue, I'm closing this in favor of the newly added https://github.com/quantopian/zipline/issues/2627. Feel free to comment there if there's information I've missed from this thread.
awesomefrank
commented
4 years ago here's a fix that goes back to yahoo as a benchmark source. replace this method in benchmarks.py and don't forget to change the call to it in loader.py
import numpy as np import pandas as pd import pandas_datareader.data as pd_reader def get_benchmark_returns(symbol, first_date, last_date): """ Get a Series of benchmark returns from Yahoo associated with `symbol`. Default is `SPY`. Parameters ---------- symbol : str Benchmark symbol for which we're getting the returns. The data is provided by Yahoo Finance """ data = pd_reader.DataReader( symbol, 'yahoo', first_date, last_date ) data = data['Close'] data[pd.Timestamp('2008-12-15')] = np.nan data[pd.Timestamp('2009-08-11')] = np.nan data[pd.Timestamp('2012-02-02')] = np.nan data = data.fillna(method='ffill') return data.sort_index().tz_localize('UTC').pct_change(1).iloc[1:]
Thank you @shlomikushchi The solution works very well for me.
zoakes
commented
4 years ago I’m not able to find loader.py file — hows that possible ?
Anyone have a path to it by chance ?
Zach
Get Outlook for iOShttps://aka.ms/o0ukef
From: awesomefrank notifications@github.com Sent: Wednesday, March 4, 2020 12:13:56 PM To: quantopian/zipline zipline@noreply.github.com Cc: Zach Mazz zach_oakes@outlook.com; Mention mention@noreply.github.com Subject: Re: [quantopian/zipline] Getting benckmark data via IEX API does not work anymore (#2480)
here's a fix that goes back to yahoo as a benchmark source. replace this method in benchmarks.py and don't forget to change the call to it in loader.py
import numpy as np import pandas as pd import pandas_datareader.data as pd_reader
def get_benchmark_returns(symbol, first_date, last_date):
"""
Get a Series of benchmark returns from Yahoo associated with symbol.
Default is SPY.
Parameters
----------
symbol : str
Benchmark symbol for which we're getting the returns.
The data is provided by Yahoo Finance
"""
data = pd_reader.DataReader(
symbol,
'yahoo',
first_date,
last_date
)
data = data['Close']
data[pd.Timestamp('2008-12-15')] = np.nan
data[pd.Timestamp('2009-08-11')] = np.nan
data[pd.Timestamp('2012-02-02')] = np.nan
data = data.fillna(method='ffill')
return data.sort_index().tz_localize('UTC').pct_change(1).iloc[1:]Thank you @shlomikushchihttps://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fshlomikushchi&data=02%7C01%7C%7C681668adb70445608d1108d7c067ce5c%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637189424377455029&sdata=xUqug511h3s2xt3m%2FTsoKCPRs%2F1afHK2zq4vC4g8Y78%3D&reserved=0 The solution works very well for me.
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHubhttps://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fquantopian%2Fzipline%2Fissues%2F2480%3Femail_source%3Dnotifications%26email_token%3DALPUCIETFFDQUCB2KWAOZPTRF2K6JA5CNFSM4HYSHEN2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOENZLJ6Y%23issuecomment-594719995&data=02%7C01%7C%7C681668adb70445608d1108d7c067ce5c%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637189424377455029&sdata=Zm1GtpfLOEmgNCuHF9%2BqorCtkJz648H51VAY4BNqJoo%3D&reserved=0, or unsubscribehttps://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FALPUCID4BLTZ7OLNF7QNJPLRF2K6JANCNFSM4HYSHENQ&data=02%7C01%7C%7C681668adb70445608d1108d7c067ce5c%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637189424377465037&sdata=l1DnsxWz5qkcYyy%2FhEtJhkqeCHQzJOoQNRZu1d%2Fjhbk%3D&reserved=0.
awesomefrank
commented
4 years ago I’m not able to find loader.py file — hows that possible ? Anyone have a path to it by chance ? Zach Get Outlook for iOShttps://aka.ms/o0ukef … ____ From: awesomefrank notifications@github.com Sent: Wednesday, March 4, 2020 12:13:56 PM To: quantopian/zipline zipline@noreply.github.com Cc: Zach Mazz zach_oakes@outlook.com; Mention mention@noreply.github.com Subject: Re: [quantopian/zipline] Getting benckmark data via IEX API does not work anymore (#2480) here's a fix that goes back to yahoo as a benchmark source. replace this method in benchmarks.py and don't forget to change the call to it in loader.py import numpy as np import pandas as pd import pandas_datareader.data as pd_reader def get_benchmark_returns(symbol, first_date, last_date): """ Get a Series of benchmark returns from Yahoo associated with
symbol. Default isSPY. Parameters ---------- symbol : str Benchmark symbol for which we're getting the returns. The data is provided by Yahoo Finance """ data = pd_reader.DataReader( symbol, 'yahoo', first_date, last_date ) data = data['Close'] data[pd.Timestamp('2008-12-15')] = np.nan data[pd.Timestamp('2009-08-11')] = np.nan data[pd.Timestamp('2012-02-02')] = np.nan data = data.fillna(method='ffill') return data.sort_index().tz_localize('UTC').pct_change(1).iloc[1:] Thank you @shlomikushchihttps://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fshlomikushchi&data=02%7C01%7C%7C681668adb70445608d1108d7c067ce5c%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637189424377455029&sdata=xUqug511h3s2xt3m%2FTsoKCPRs%2F1afHK2zq4vC4g8Y78%3D&reserved=0 The solution works very well for me. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHubhttps://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fquantopian%2Fzipline%2Fissues%2F2480%3Femail_source%3Dnotifications%26email_token%3DALPUCIETFFDQUCB2KWAOZPTRF2K6JA5CNFSM4HYSHEN2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOENZLJ6Y%23issuecomment-594719995&data=02%7C01%7C%7C681668adb70445608d1108d7c067ce5c%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637189424377455029&sdata=Zm1GtpfLOEmgNCuHF9%2BqorCtkJz648H51VAY4BNqJoo%3D&reserved=0, or unsubscribehttps://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FALPUCID4BLTZ7OLNF7QNJPLRF2K6JANCNFSM4HYSHENQ&data=02%7C01%7C%7C681668adb70445608d1108d7c067ce5c%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637189424377465037&sdata=l1DnsxWz5qkcYyy%2FhEtJhkqeCHQzJOoQNRZu1d%2Fjhbk%3D&reserved=0.
..\site-packages\zipline\data
adamhadani
commented
4 years ago slight variation on one of the posted answers to use the new IEX Cloud API endpoint. this one will read your token from env var IEX_CLOUD_API_TOKEN:
--- benchmarks.py 2020-03-16 19:45:33.000000000 -0700
+++ benchmarks_new.py 2020-03-16 19:48:08.000000000 -0700
@@ -12,10 +12,15 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+from os import getenv
+
import pandas as pd
import requests
+IEX_CLOUD_API_TOKEN = getenv("IEX_CLOUD_API_TOKEN", "<IEX_CLOUD_API_TOKEN>")
+
+
def get_benchmark_returns(symbol):
"""
Get a Series of benchmark returns from IEX associated with `symbol`.
@@ -30,7 +35,7 @@
get up to 5 years worth of data.
"""
r = requests.get(
- 'https://api.iextrading.com/1.0/stock/{}/chart/5y'.format(symbol)
+ "https://cloud.iexapis.com/stable/stock/{}/chart/5y?chartCloseOnly=True&token={}".format(symbol, IEX_CLOUD_API_TOKEN)
)
data = r.json()Can apply by saving the above to a file benchmarks.patch and then invoke in the directory of the original benchmarks.py (e.g. <virtualenv_root>/lib/python3.5/site-packages/zipline/data/):
$ patch < benchmarks.patch
Zipline uses IEX API to get benchmark data in
benchmarks.py:However, according to the IEX FAQ page, the chart api was already removed on June 15, 2019. Currently, using this api to try to download any stock data such as SPY will return nothing but an HTTP 403 error. The functions of deprecated APIs are now transferred to their new API, IEX Cloud, which requires a unique token per user in any request. Any idea how to fix this issue in the long run?