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https://github.com/alttch/finac

Finac - financial accounting for humans
https://github.com/alttch/finac

accounting double-entry-accounting double-entry-bookkeeping finance financial fintech library python python3

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Finac - financial accounting for humans

Host: GitHub
URL: https://github.com/alttch/finac
Owner: alttch
License: mit
Created: 2019-10-22T01:41:29.000Z (about 5 years ago)
Default Branch: master
Last Pushed: 2023-06-13T20:43:02.000Z (over 1 year ago)
Last Synced: 2024-10-07T14:36:02.602Z (3 months ago)
Topics: accounting, double-entry-accounting, double-entry-bookkeeping, finance, financial, fintech, library, python, python3
Language: Python
Homepage:
Size: 469 KB
Stars: 39
Watchers: 7
Forks: 6
Open Issues: 0
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE

Awesome Lists containing this project

README

# Finac - financial accounting for humans

Finac is a library and function set for Jupyter/ipython, which provides the
double-entry bookkeeping database.

Finac is simple, open and free. It can work with SQLite or any database
supported by SQLAlchemy (tested: SQLite, MySQL, PostgreSQL).

WARNING: SQLAlchemy 2 is NOT SUPPORTED until stabilized. If SQLAlchemy 2 is
required for other projects, run Finac in a dedicated virtual environment.

Finac can be used either in the interactive mode with
[Jupyter](https://jupyter.org/), [Spyder-IDE](https://www.spyder-ide.org/),
ipython or other similar environment or Finac library can be embedded into 3rd
party projects. The library can be used in accounting applications and is
useful for fin-tech services.

Finac supports multiple currencies, simple transactions, double-entry
bookkeeping transactions, watches overdrafts, balance limits and has got many
useful features, which make accounting simple and fun.

## Install

```bash
pip3 install finac
```

Sources: https://github.com/alttch/finac

Documentation: https://finac.readthedocs.io/

## Updating

# from 0.4.10

```sql
ALTER TABLE transact ADD service bool;
UPDATE transact SET service=true WHERE d_created<'1970-01-03';
ALTER TABLE transact ADD FOREIGN KEY(chain_transact_id)
REFERENCES transact(id) ON DELETE SET null;
```

# from 0.3.x

Starting from 0.4, Finac uses DateTime columns for:

* asset_rate.d
* transact.d
* transact.d_created
* transact.deleted

Depending to the database type, it's REQUIRED to convert these columns to
either DATETIME (SQLite, for MySQL DATETIME(6) recommended) or TIMESTAMPTZ
(PostgreSQL, with timezone).

## How to use in interactive mode

Finac database contains 3 entity types:

* **asset** currency, ISIN, stock code etc., currencies "USD" and "EUR" are
created automatically. Finac does not separate assets into currencies,
property and other. This allows creating applications for various areas using
the single library.

* **account** bank account, counterparty account, tax account, special account
etc. Everything is accounts :)

* **transaction** movements from (credit) / to (debit) and between accounts

Assets have got **rates** - the value of one asset, relative to other.

Transactions can be simple (no counterparty) or classic double-entry
bookkeeping (between debit and credit account).

```python
import finac as f
# init finac,
f.init('/tmp/test.db')
# create a couple of accounts
f.account_create('acc1', 'USD')
f.account_create('acc2', 'USD')
f.account_create('depo', 'USD', 'saving')
# import initial balance with a simple transaction
f.tr('acc1', 10000, tag='import')
# move some assets to other accounts
f.mv(dt='acc2', ct='acc1', amount=2000)
f.mv(dt='depo', ct='acc1', amount=3000)
```

```python
# display statement for acc1
f.ls('acc1')
```

```
id amount cparty tag note created completed
-----------------------------------------------------------------------------
7 10 000.00 import 2019-10-26 03:04:02 2019-10-26 03:04:02
8 -2 000.00 ACC2 2019-10-26 03:04:02 2019-10-26 03:04:02
9 -3 000.00 DEPO 2019-10-26 03:04:02 2019-10-26 03:04:02
-----------------------------------------------------------------------------
Debit turnover: 10 000.00, credit turnover: 5 000.00

Net profit/loss: 5 000.00 USD
```

```python
# display summary for all accounts
f.ls()
```

```
account type asset balance balance USD
-------------------------------------------------
ACC1 current USD 5 000.00 5 000.00
ACC2 current USD 2 000.00 2 000.00
DEPO saving USD 3 000.00 3 000.00
-------------------------------------------------
Total: 10 000.00 USD
```

```python
# display summary only for current accounts
f.ls(tp='current')
```

```
account type asset balance balance USD
-------------------------------------------------
ACC1 current USD 5 000.00 5 000.00
ACC2 current USD 2 000.00 2 000.00
-------------------------------------------------
Total: 7 000.00 USD
```

```python
# display assets pie chart, (wrapper for matplotlib.pyplot, requires Jupyter,
# Spyder-IDE or a similar interactive environment)
f.pie()
```

Note: when addressing currencies and accounts both in interactive and API mode,
account and asset codes should be used as object identifiers. **All codes are
case-insensitive**.

Inside database Finac uses numeric IDs to connect objects, so the codes can be
changed without any problems.

## Special features

### Lazy exchange

Finac can automatically move assets between accounts having different
currencies if exchange rate is set or specified in the transaction details:

```python
# create EUR account
f.account_create('acc5', 'eur')
# set exchange rate (in real life you would probably use cron job)
f.asset_set_rate('eur/usd', value=1.1)
f.mv(dt='acc5', ct='acc1', amount=100)
```

hoorah, account acc5 have got 100 EUR! And exchange rate was 1.1. Check it:

>>> f.ls('acc1')

```
id amount cparty tag note created completed
-----------------------------------------------------------------------------
..............
..............
14 -110.00 2019-10-26 03:15:41 2019-10-26 03:15:41
-----------------------------------------------------------------------------
```

>>> f.ls('acc5')

```
id amount cparty tag note created completed
-----------------------------------------------------------------------
15 100.00 2019-10-26 03:15:41 2019-10-26 03:15:41
-----------------------------------------------------------------------
Debit turnover: 100.00, credit turnover: 0.00

Net profit/loss: 100.00 EUR
```

As shown, there is no a counterparty account in the lazy exchange. This feature
is useful for personal accounting and special applications, but for
professional accounting, create counterparty exchange accounts should be
created and buy-sell transactions should be performed between them.

### Targets

Targets is a feature I have created Finac for. Consider there are account
balances in a bank and in the accounting. They differ in some amount and this
need to be recorded in the accounting with a single transaction.

But the problem is: there is a lot of transactions which should be sum up. Or
the difference between bank balance and accounting must be calculated manually.
Pretty common, eh? Don't do this, Finac has got targets.

Specifying targets instead of amount asks Finac to calculate transaction amount
by itself.

After the previous operation, there is *4,890.00* USD on "acc1" and consider
all except $1000 should be moved to "acc2". Let us do it:

>>> f.mv(dt='acc2', ct='acc1', target_ct=1000)

```
id amount cparty tag note created completed
-----------------------------------------------------------------------------
......
......
16 -3 890.00 ACC2 2019-10-26 03:25:56 2019-10-26 03:25:56
-----------------------------------------------------------------------------
Debit turnover: 10 000.00, credit turnover: 9 000.00

Net profit/loss: 1 000.00 USD

```

The transaction amount is automatically calculated. Lazy people are happy :)

If the debit account balance target should be specified, *target_dt*
function argument can be used. Note: calculated transaction amount must be
always greater than zero (if credit account target higher than its current
balance is specified, *ValueError* is raised)

For simple transactions (*f.tr(...))*), use *target=*.

### Transaction templates

Example: there is a repeating payment orders in a bank, which pay office
utility bills every 5th day of month, plus automatically move $100 to a saving
account. To fill this into accounting, YAML transaction template can be
used:

```yaml
transactions:
- account: acc1
amount: 200
tag: electricity
note: energy company deposit
- account: acc1
amount: 800
tag: rent
note: office rent
- dt: depo
ct: acc1
amount: 200
tag: savings
note: rainy day savings
```

then create a cron job which calls *f.transaction_apply("/path/to/file.yml")*
and that is it.

Actually, transaction templates are useful for any repeating operations. The
same arguments, as for the core functions, can be specified.

### Number formatting

Finac does not use system locale. If amounts and targets are inputted as
strings, they can be specified in any format and Finac tries converting strings
into float numeric automatically. The following values for amounts and
targets are valid and are automatically parsed:

* 1 000,00 = 1000.0
* 1,000.00 = 1000.0
* 1.000,00 = 1000.0
* 1,000.00 = 1000.0
* 10,0 = 10.0
* 10.0 = 10.0

### Passive accounts

If account is passive, its assets are decremented from totals. To create
passive account, *passive* argument must be used:

```python
f.account_create('passive1', 'usd', passive=True)
```

Accounts of types "tax", "supplier" and "finagent" are passive by default.

### Data multiplier

Depending on data, it may be useful to store numeric values in the database as
integers instead of floats. Finac library has got a built-in data multiplier
feature. To enable it, set *multiplier=N* in *finac.init()* method, e.g.
*multiplier=1000*. This makes Finac to store integers into tables and use the
max precision of 3 digits after comma.

Note: table fields must be manually converted to numeric/integer types. In
production databases the field values must be also manually multiplied.

Full list of tables and fields, required to be converted, is available in the
dict *finac.core.multiply_fields*.

Note: the multiplier can be used only with integer and numeric(X) field types,
as core conversion functions always return rounded value.

## How to embed Finac library into own project

See [Finac documentation](https://finac.readthedocs.io/) for core function API
details.

## Client-server mode and HTTP API

See [Finac documentation](https://finac.readthedocs.io/) for server mode and
HTTP API details.

## Enterprise server and support

Want to integrate Finac into an own enterprise app or service? Need a support?
Check [Finac Enterprise Server](https://www.altertech.com/products/fes/).