On Saturday, January 4, 2020 at 3:46:09 PM UTC-8, Philip Curtis wrote:
>
> Yes, I've been wanting this for years, probably around 15!  I'm 
> experimenting with some OCR Python code but wondering if the time 
> commitment would be unrealistic for me with also learning Beancount, 
> implementing the two, working full time, and having a 3year old and another 
> on the way.
> Seems like the project for someone single living in their basement <;  
> Anyway, I'll continue to research the code.
>

Let's hope someone steps up then.
 

> So the properly understand the workflow with Beancount, with I don't 
> completely right now, one processes financial data in these steps?
> 1) Set up Beancount with all your income and expense accounts, the 
> .beancount file(s) are now available
> 2) Implement Fava with Beancont
> 3) Host all files to your own website servers
> 4) Enter financial data through your website by text entry (or Fava GUI?)
> 5) Process and graph your financial data via Fava on your website
>
> Do I have this process correct or am I way off?
>

Your steps look good, but some alternatives suggested below from personal 
experience:
3) I do not host files and Fava on a remote web server, but locally. It is 
not necessary to host remotely, and since you seem to care about data 
security, I suggest you keep everything on your machine.
Furthermore, 
4) I use the finance-dl package to automatically download all my 
transactions, as often as I want. It takes a minute. I enter very few 
transactions manually. Then, I use the beancount-import package (by the 
same author) to import the transactions into my Beancount files. This part 
is also very quick (at most 5 minutes per week). Paychecks are one class of 
transactions that require significant manual adjustment.

Hope this helps.

On Saturday, January 4, 2020 at 5:17:37 PM UTC-6, ps150pta wrote:
>>
>> FWIW about a year ago I ran some experiments passing photos of Whole 
>> Foods receipts through AWS Textract. It did pretty well but error rates are 
>> still relatively high, too high to be considered reliable enough to fit 
>> into a "user-just-confirms" workflow. Some additional work on top of 
>> Textract to build receipt-format-specific models could probably get there, 
>> tho.
>>
>> Many cos are successfully processing receipt photos on a commercial basis.
>>
>> PDFs that are machine produced are definitely processable with commodity 
>> tools, the extraction for them works quite well. 
>>
>> I suspect sometime in the next year or two someone will put together a 
>> Jupyter notebook for doing the workflow you describe, building receipt 
>> specific models on one of the ML platforms. The basic pieces are there, 
>> it's at the level of being a solveable problem for a hobbyist. 
>>
>>
>> On Sat, Jan 4, 2020, 5:12 PM Philip Curtis <[email protected]> wrote:
>>
>>> Thanks 😁
>>>
>>> Is #1 possible yet in any software technology yet?
>>>
>>> Thanks,
>>> Phil
>>>
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>>

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