Thanks for looking at this module even though you aren't using it!
I followed the code that was further down on the readme page
<https://github.com/beancount/smart_importer> that describes how to convert
an existing importer.
>>
from your_custom_importer import MyBankImporter
from smart_importer import apply_hooks, PredictPayees, PredictPostings
my_bank_importer = MyBankImporter('whatever', 'config', 'is', 'needed')
apply_hooks(my_bank_importer, [PredictPostings(), PredictPayees()])
CONFIG = [ my_bank_importer, ]
>>
(my code looks just like this example)
I had thought apply_hooks would operate on the importer so when I call it
in config I can just then call the hookified bank_importer. Is this note
the case?
On Wednesday, May 12, 2021 at 1:26:27 AM UTC+12 [email protected] wrote:
> * Disclaimer * I have never actually run smart importer.
>
> Looking at the README on GitHub for smart importer it looks like you need
> to use the return object of apply_hooks in your CONFIG list.
>
> CONFIG = [ apply_hooks(MyBankImporter(account='Assets:MyBank:MyAccount'),
> [PredictPostings()]) ]
>
> In your config you apply the hooks but are not using the returned object.
>
> Hope that helps.
>
> On Tuesday, 11 May 2021 at 04:06:33 UTC+1 [email protected] wrote:
>
>> Hi,
>>
>> I'm trying to get smart_importer to work and not sure what I'm doing
>> wrong.
>>
>> *1*. I successfully have done all the required beancount setup and
>> created by own bank importer and ran it on two months of data.
>> *2.* I then manually labelled about 2 months of data from one of my
>> banks.
>> *3.* I installed smart_importer using "pip install smart_importer"
>>
>> (base) MacBook-Air:beandata jonathan$ pip show smart_importer
>>
>> Name: smart-importer
>>
>> Version: 0.3
>>
>> Summary: Augment Beancount importers with machine learning functionality.
>>
>> Home-page: https://github.com/beancount/smart_importer
>>
>> Author: Johannes Harms
>>
>> Author-email: UNKNOWN
>>
>> License: MIT
>>
>> Location: /Users/jonathan/opt/miniconda3/lib/python3.8/site-packages
>>
>> Requires: scikit-learn, beancount, numpy, scipy
>>
>> *4.* I created a new config file I called Jonathan_smart.import
>>
>>
>> base) MacBook-Air:beandata jonathan$ more jonathan_smart.import
>>
>> #!/usr/bin/env python3
>>
>> """Import configuration."""
>>
>>
>> import sys
>>
>> from os import path
>>
>>
>> sys.path.insert(0, path.join(path.dirname(__file__)))
>>
>>
>> from beancount_reds_importers import vanguard
>>
>> from myimporters.bfsfcu import bfsfcu_bank
>>
>> from myimporters.anz import anz_bank
>>
>> from fund_info import *
>>
>> from smart_importer import apply_hooks, PredictPayees, PredictPostings
>>
>>
>> myBank_smart_importer =my_bank.Importer({
>>
>> 'main_account' : 'Assets:US:Banks:Checking:myBank',
>>
>> 'account_number' : ''xxx'',
>>
>> 'transfer' :
>> 'Assets:US:Zero-Sum-Accounts:Transfers:Bank-Account',
>>
>> 'income' : 'Income:US:Interest:myBank',
>>
>> 'fees' : 'Expenses:US:Bank-Fees:myBank',
>>
>> 'rounding_error' : 'Equity:US:Rounding-Errors:Imports',
>>
>> })
>>
>>
>> apply_hooks(myBank_smart_importer, [PredictPayees(), PredictPostings()])
>>
>> CONFIG = [myBank_smart_importer, ...(other importers)]
>>
>>
>> *5*. I was following the README documentation that said write
>> bean-extract -f to invoke it on existing data. So I tried the following.*
>> Is this right?*
>>
>> bean-extract jonathan_smart.import ~/staging/new_bank_data.qfx -f
>> journal/myledger.beancount > ~/staging/dud.txt
>>
>> Cannot train the machine learning model because the training data is
>> empty.
>>
>> Cannot train the machine learning model because the training data is
>> empty.
>>
>>
>> The output is just like the normal output without all the smart_importer
>> stuff. Seems I'm doing something wrong as the staging/dud.txt doesn't have
>> any predictions.
>>
>>
>> Appreciate any assistance on this!
>>
>>
>> thanks,
>>
>> Jonathan
>>
>
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