Re: Zipline ingest reading wrong data

[Freddie Vargus]

Hi Mosfiqur,

I believe there is a fix on GitHub that is yet to be merged: https://github.com/quantopian/zipline/pull/2223.

Once that is merged, if you were to run the latest Zipline version (installed via GitHub), then it shouldn't be an issue anymore.

On Fri, Oct 5, 2018 at 1:35 PM Mosfiqur Rahman <where.is....@gmail.com> wrote:

Hi,

   I'm trying to ingest 18 symbols in my custom-csvdir-bundle. After ingesting while I'm trying to print out the price. It's showing me the same value for two different symbols. In this case. A  and CDNA. However, if I remove CDNA from the data bundle, then A is picking the values of NTRA and NVTA so on, which means picking the symbols with last character 'A'.

Here are my code and files:

from IPython.core.display import display, HTML

display(HTML("<style>.container { width:100% !important; }</style>"))

from zipline.api import order, record, symbol

import pandas as pd

from datetime import datetime

from zipline.api import sid

def initialize(context):

    pass

def handle_data(context, data):

    record(A=data.current(symbol('A'), 'price'))

    record(CDNA=data.current(symbol('CDNA'), 'close'))

    record(BRKR=data.current(symbol('BRKR'), 'close'))

    record(DGX=data.current(symbol('DGX'), 'close'))

    record(DHR=data.current(symbol('DHR'), 'close'))

    record(DXCM=data.current(symbol('DXCM'), 'close'))

    record(EXAS=data.current(symbol('EXAS'), 'close'))

    record(ILMN=data.current(symbol('ILMN'), 'close'))

    record(LH=data.current(symbol('LH'), 'close'))

    record(MYGN=data.current(symbol('MYGN'), 'close'))

    record(NEO=data.current(symbol('NEO'), 'close'))

    record(NTRA=data.current(symbol('NTRA'), 'close'))

    record(NVTA=data.current(symbol('NVTA'), 'close'))

    record(PHG=data.current(symbol('PHG'), 'close'))

    record(PKI=data.current(symbol('PKI'), 'close'))

    record(PRAH=data.current(symbol('PRAH'), 'close'))

    record(QGEN=data.current(symbol('QGEN'), 'close'))

    record(TMO=data.current(symbol('TMO'), 'close'))

    record(TTOO=data.current(symbol('TTOO'), 'close'))

%zipline --bundle=custom-csvdir-bundle --start 2016-8-1 --end 2016-10-3

A	BRKR	CDNA	DGX	DHR	DXCM	EXAS	ILMN	LH	MYGN	NEO	NTRA	NVTA	PHG	PKI	PRAH	QGEN	TMO	TTOO	algo_volatility	algorithm_period_return	alpha	benchmark_period_return	benchmark_volatility	beta	capital_used	ending_cash	ending_exposure	ending_value	excess_return	gross_leverage	long_exposure	long_value	longs_count	max_drawdown	max_leverage	net_leverage	orders	period_close	period_label	period_open	pnl	portfolio_value	positions	returns	sharpe	short_exposure	short_value	shorts_count	sortino	starting_cash	starting_exposure	starting_value	trading_days	transactions	treasury_period_return
2016-08-01 20:00:00+00:00	4.800	24.81	4.800	86.24	81.50	92.65	18.110	170.65	139.63	31.48	8.520	13.04	8.40	26.39	56.69	47.08	26.80	159.56	7.04	NaN	0.0	NaN	-0.000829	NaN	NaN	0.0	10000000.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0.0	0.0	0.0	[]	2016-08-01 20:00:00+00:00	2016-08	2016-08-01 13:31:00+00:00	0.0	10000000.0	[]	0.0	None	0.0	0.0	0	None	10000000.0	0.0	0.0	1	[]	0.0
2016-08-02 20:00:00+00:00	4.680	24.72	4.680	85.24	80.93	92.78	17.750	166.92	139.38	30.82	8.370	13.05	8.36	26.36	55.91	46.90	26.74	156.44	6.11	0.0	0.0	0.0	-0.007235	0.062657	0.0	0.0	10000000.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0.0	0.0	0.0	[]	2016-08-02 20:00:00+00:00	2016-08	2016-08-02 13:31:00+00:00	0.0	10000000.0	[]	0.0	None	0.0	0.0	0	None	10000000.0	0.0	0.0	2	[]	0.0
2016-08-03 20:00:00+00:00	4.850	21.79	4.850	85.65	80.98	90.87	18.290	165.05	140.13	31.42	8.530	12.97	8.53	26.28	55.75	48.25	26.59	156.00	6.14	0.0	0.0	0.0	-0.004329	0.074585	0.0	0.0	10000000.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0.0	0.0	0.0	[]	2016-08-03 20:00:00+00:00	2016-08	2016-08-03 13:31:00+00:00	0.0	10000000.0	[]	0.0	None	0.0	0.0	0	None	10000000.0	0.0	0.0	3	[]	0.0
2016-08-04 20:00:00+00:00	4.850	21.77	4.850	85.80	81.12	91.50	19.000	165.66	140.09	31.11	8.320	13.10	8.44	26.36	55.72	49.13	26.61	156.42	6.79	0.0	0.0	0.0	-0.003271	0.064050	0.0	0.0	10000000.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0.0	0.0	0.0	[]	2016-08-04 20:00:00+00:00	2016-08	2016-08-04 13:31:00+00:00	0.0	10000000.0	[]	0.0	None	0.0	0.0	0	None	10000000.0	0.0	0.0	4	[]	0.0
2016-08-05 20:00:00+00:00	4.990	22.17	4.990	85.68	81.50	91.23	19.250	166.53	140.76	30.46	8.150	12.22	8.65	26.52	54.85	49.42	26.95	157.51	7.48	0.0	0.0	0.0	0.004882	0.084575	0.0	0.0	10000000.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0.0	0.0	0.0	[]	2016-08-05 20:00:00+00:00	2016-08	2016-08-05 13:31:00+00:00	0.0	10000000.0	[]	0.0	None	0.0	0.0	0	None	10000000.0	0.0	0.0	5	[]	0.0

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