Hi Patrick and everyone, I resolved the issue. It’s working well. The pointers to where to add print statements was very helpful. The problem was the account name for the existing transactions was not correct and I fixed it and now it is able to train and predict.
Thanks again. Jonathan > On May 21, 2021, at 6:24 AM, 'Patrick Ruckstuhl' via Beancount > <[email protected]> wrote: > > Probably the easiest examples are for the data driven tests you can find here > > https://github.com/beancount/smart_importer/tree/master/tests/data > <https://github.com/beancount/smart_importer/tree/master/tests/data> > > The simples of them probably > > https://github.com/beancount/smart_importer/blob/master/tests/data/multiaccounts.beancount > > <https://github.com/beancount/smart_importer/blob/master/tests/data/multiaccounts.beancount> > > > On 20.05.2021 19:03, Hawrylyshen, Alan wrote: >> MIght it be simpler to (sorry for suggesting the obvious) try a toy example >> data set to get things up and working? >> I didn't take too much effort to get the smart_importer wrapping my >> importers... so I imagine this is something relatively simple. >> Ideally there'd be a test case in the smart_importer repository already? >> >> Thanks >> Alan >> >> On Thu, 20 May 2021 at 13:34, 'Patrick Ruckstuhl' via Beancount >> <[email protected] <mailto:[email protected]>> wrote: >> So if I see this correctly, after the filtering of the training data, there >> is never any data left. >> >> The logic looks like this >> >> def training_data_filter(self, txn): >> """Filter function for the training data.""" >> found_import_account = False >> for pos in txn.postings: >> if pos.account not in self.open_accounts: >> return False >> if self.account == pos.account: >> found_import_account = True >> return found_import_account or not self.account >> >> >> >> And from the printout you have something in self.account. So if I see this >> correctly, either none of your training data is matching the account or the >> account is actually no longer open. >> >> Maybe worth printing out the self.open_accounts and maybe even >> debugging/logging some stuff in that training_data_filter code >> >> >> >> Regards, >> >> Patrick >> >> >> >> On 20.05.2021 02:02, Jonathan Goldman wrote: >> >>> Hi Patrick, >>> >>> Thanks for the suggestions. I started doing this. Here is what I'm seeing: >>> >>> ------CHECKPOINT1------- >>> 1353 >>> 1133 >>> 0 >>> ------CHECKPOINT2------- >>> [] >>> ---__call__---- >>> Assets:US:Banks:Checking:myBank >>> ------CHECKPOINT1------- >>> 1353 >>> 1133 >>> 0 >>> ------CHECKPOINT2------- >>> [] >>> ---__call__---- >>> Assets:US:Banks:Checking:myBank >>> >>> Here is the code I added to predictory.py: >>> #beg >>> >>> print('---__call__----') >>> print(self.account) >>> #print(existing_entries) >>> >>> #end >>> >>> with self.lock: >>> self.define_pipeline() >>> self.train_pipeline() >>> return self.process_entries(imported_entries) >>> >>> def load_open_accounts(self, existing_entries): >>> """Return map of accounts which have been opened but not closed.""" >>> account_map = {} >>> if not existing_entries: >>> return >>> >>> for entry in beancount_sorted(existing_entries): >>> # pylint: disable=isinstance-second-argument-not-valid-type >>> >>> if isinstance(entry, Open): >>> account_map[entry.account] = entry >>> elif isinstance(entry, Close): >>> account_map.pop(entry.account) >>> >>> self.open_accounts = account_map >>> >>> def load_training_data(self, existing_entries): >>> """Load training data, i.e., a list of Beancount entries.""" >>> training_data = existing_entries or [] >>> self.load_open_accounts(existing_entries) >>> #beg1 >>> >>> print('------CHECKPOINT1-------') >>> print(len(training_data)) >>> #end1 >>> >>> training_data = list(filter_txns(training_data)) >>> print(len(training_data)) >>> length_all = len(training_data) >>> training_data = [ >>> txn for txn in training_data if self.training_data_filter(txn) >>> ] >>> print(len(training_data)) >>> #beg2 >>> >>> print('------CHECKPOINT2-------') >>> print(training_data) >>> #beg2 >>> >>> -------- >>> I'm trying to check now that every account in the config file is present in >>> my beancount file. I noticed one missing and that changed what was in the >>> training_data but still getting the warning about training data being >>> empty. I'll keep digging as best I can but definitely can use any >>> additional help. >>> >>> On Wed, May 19, 2021 at 3:16 AM 'Patrick Ruckstuhl' via Beancount >>> <[email protected] <mailto:[email protected]>> wrote: >>> Hi Jonathan, >>> >>> >>> >>> Let's try to figure this out. In smart importer can you printout the >>> following stuff >>> >>> >>> >>> in smart_importer/predictor.py >>> >>> >>> >>> in __call__ around line 64 >>> >>> print(self.account) >>> >>> print(existing_entries) >>> >>> >>> >>> in load_training_data around line 91 >>> >>> print(training_data) >>> >>> and around line 95 >>> >>> print(training_data) >>> >>> >>> >>> That should give an idea where the information is "lost". Depending on >>> where the information is lost, you can then dig a bit deeper into what is >>> happening. >>> >>> >>> >>> Regards, >>> >>> Patrick >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> On 18.05.2021 13:14, Jonathan Goldman wrote: >>>> Thanks Red. >>>> >>>> bean-query works fine on my input file which now has >1000 transactions . >>>> >>>> Ready with 1344 directives (2266 postings in 1133 transactions). >>>> beancount> >>>> >>>> I still get the error. I'm not sure what is causing and not sure how to >>>> debug it. The only other issue I recall seeing was some error with >>>> fund_info or something in getting prices but I thought it was an unrelated >>>> issue. >>>> >>>> Do you or does anyone have some suggestions on where/how to debug. E.g. I >>>> should print some variables to STDOUT at such and such point inside >>>> smart_importer code or inside bean-extract. >>>> >>>> thanks, >>>> Jonathan >>>> >>>> >>>> >>>> On Mon, May 17, 2021 at 9:34 PM [email protected] >>>> <mailto:[email protected]> <[email protected] >>>> <mailto:[email protected]>> wrote: >>>> A minimum of two transactions should suffice for smart_importer. More will >>>> increase prediction quality, but two should suffice. I can't tell what's >>>> happening at your end, but you're likely ending up with zero transactions >>>> for some reason. Run bean-query on the file you pass to "-f" of >>>> bean-extract. >>>> >>>> beancount-reds-importers supports smart_importer out of the box for >>>> banking, that shouldn't be an issue AFAICT. >>>> >>>> >>>> >>>> On Wednesday, May 12, 2021 at 10:23:14 PM UTC-7 [email protected] >>>> <mailto:[email protected]> wrote: >>>> Thanks for suggestions @Patrick and Alan. My beancount file has about 64 >>>> Asset accounts. It has about 41 expense accounts. I have only 2 months of >>>> labelled banking transactions (about 42 transactions) all associated with >>>> one bank account and various expense accounts. >>>> >>>> I had thought that some transactions were relatively deterministic (same $ >>>> amount and same description like rent/mortgage) and I was under the >>>> impression that only a few months of data are needed to get going. >>>> >>>> Perhaps I'll just go back to manually labelling data for now and trying >>>> again later or after I see more posts/explanation of smart_importer. I'm >>>> not well-versed enough with smart_importer to debug what is happening. >>>> >>>> On Thu, May 13, 2021 at 3:04 AM Alan H <[email protected] <>> wrote: >>>> I get this error when there are insufficient entries in the journal to >>>> teach the smart_importer how to file new transactions. Specifically there >>>> are no matches for payees or narrations. >>>> >>>> Is that the case? Try adding a dummy transaction that matches the >>>> narration in the import file. >>>> >>>> Alan >>>> >>>> >>>> On Wednesday, May 12, 2021 at 12:24:55 PM UTC+1 [email protected] <> >>>> wrote: >>>> Hm, actually that looks ok, it has the existing_entries on the interface. >>>> But to be honest I'm not super familiar with how the apply hook is hooking >>>> this in, so there might be an issue. >>>> >>>> Maybe someone more familiar with this can respond on that. >>>> >>>> >>>> >>>> Otherwise if you could install smart_importer from git and then maybe add >>>> a bit more debug output in >>>> >>>> hooks.py and predictor.py to make sure that the existing entries arrive, >>>> this would give a better idea how to progress. >>>> >>>> >>>> >>>> On 12.05.2021 13:17, [email protected] <> wrote: >>>>> Thank you. I think that is it. >>>>> >>>>> I'm using reds-importers and I see >>>>> site-packages/beancount_reds_importers/libimport/banking.py and it has >>>>> this entry: >>>>> >>>>> def extract(self, file, existing_entries=None): >>>>> >>>>> I think this importer tool needs to be updated to support the >>>>> smart_importer. >>>>> >>>>> On Wednesday, May 12, 2021 at 11:11:37 PM UTC+12 [email protected] <> >>>>> wrote: >>>>> I just remembered something. The issue could be that the importer you're >>>>> trying to use does not have the new interface and instead still uses the >>>>> old (legacy) interface. >>>>> >>>>> the new one looks like this >>>>> >>>>> >>>>> >>>>> def extract(self, file, existing_entries): >>>>> >>>>> the old one looks like this >>>>> >>>>> def extract(self, file): >>>>> >>>>> >>>>> >>>>> Smart importer uses the existing_entries for training its model. >>>>> >>>>> >>>>> >>>>> Regards, >>>>> >>>>> Patrick >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> On 12.05.2021 12:20, [email protected] <> wrote: >>>>>> Just checked and I got the same result. I can add some debugging code in >>>>>> the config file perhaps. I'm not very experienced with beancount or >>>>>> smart_importer so not sure what to look for. >>>>>> >>>>>> bean-extract -e journal/accounts.beancount jonathan_smart.import >>>>>> ~/staging/mydata.qfx > ~/staging/dud.txt >>>>>> >>>>>> gives 2 printouts of >>>>>> >>>>>> Cannot train the machine learning model because the training data is >>>>>> empty. >>>>>> >>>>>> Cannot train the machine learning model because the training data is >>>>>> empty. >>>>>> >>>>>> On Wednesday, May 12, 2021 at 7:15:19 PM UTC+12 [email protected] <> >>>>>> wrote: >>>>>> Can you try -e instead of -f that's what I use >>>>>> >>>>>> >>>>>> On May 12, 2021 8:31:36 AM GMT+02:00, "[email protected] <>" >>>>>> <[email protected] <>> wrote: >>>>>> Thanks for the suggestion @Patrick. I just tried changing that but still >>>>>> doesn't work. I get the exact same behavior if I >>>>>> call it with an empty file....seems >>>>>> the -f option doesn't make bean-extract behave as expected for me. Here >>>>>> is my call: >>>>>> >>>>>> bean-extract -f journal/myledger.beancount jonathan_smart.import >>>>>> ~/staging/62090_818496_1013051ofxdl.qfx > ~/staging/dud.txt >>>>>> >>>>>> I get these messages: >>>>>> Cannot train the machine learning model because the training data is >>>>>> empty. >>>>>> >>>>>> Cannot train the machine learning model because the training data is >>>>>> empty. >>>>>> >>>>>> >>>>>> On Wednesday, May 12, 2021 at 5:31:25 PM UTC+12 [email protected] <> >>>>>> wrote: >>>>>> Hi, >>>>>> >>>>>> I think your setup looks good, the smart importer hook is in there as >>>>>> otherwise you would not get the errors about not able to train. >>>>>> >>>>>> I think the issue is on your call >>>>>> >>>>>> >>>>>> >>>>>> bean-extract jonathan_smart.import ~/staging/new_bank_data.qfx -f >>>>>> journal/myledger.beancount > ~/staging/dud.txt >>>>>> >>>>>> >>>>>> >>>>>> My guess is that the -f argument needs to come before you specify the >>>>>> importconfig and the location, so >>>>>> >>>>>> >>>>>> >>>>>> bean-extract -f journal/myledger.beancount jonathan_smart.import >>>>>> ~/staging/new_bank_data.qfx > ~/staging/dud.txt >>>>>> >>>>>> >>>>>> >>>>>> Regards, >>>>>> >>>>>> Patrick >>>>>> >>>>>> >>>>>> On 12.05.2021 01:58, [email protected] <> wrote: >>>>>>> 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 >>>>>>> <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 >>>>>>> >>>>>> >>>>>>> -- >>>>>>> You received this message because you are subscribed to the Google >>>>>>> Groups "Beancount" group. >>>>>>> To unsubscribe from this group and stop receiving emails from it, send >>>>>>> an email to [email protected] <>. >>>>>>> To view this discussion on the web visit >>>>>>> https://groups.google.com/d/msgid/beancount/820ef641-8178-47d1-9e97-afbc709e6a83n%40googlegroups.com >>>>>>> >>>>>>> <https://groups.google.com/d/msgid/beancount/820ef641-8178-47d1-9e97-afbc709e6a83n%40googlegroups.com?utm_medium=email&utm_source=footer>. >>>>>> -- >>>>>> You received this message because you are subscribed to the Google >>>>>> Groups "Beancount" group. >>>>>> To unsubscribe from this group and stop receiving emails from it, send >>>>>> an 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