ofxtools 0.3.7.2

DESCRIPTION
====
ofxtools is a Python library for working with Open Financial Exchange (OFX)
data - both OFXv1 (SGML) and OFXv2 (pure XML) - which is the standard format
for downloading financial information from banks and stockbrokers.

ofxtools has no external dependencies beyond stdlib, and is compatible with
Python version 2.7+ and 3.1+.

The primary facilities provided include:
* The OFXClient class; which dowloads OFX statements from the Internet
* The OFXTree class; which parses OFX data into a standard ElementTree
structure for further processing in Python.
* The OFXResponse class; which validates and converts OFX data parsed by
OFXParser into Python types and exposes them through more Pythonic
attribute access (e.g. OFXResponse.statements[0].ledgerbal)

Also included is the ofxtools.ofxalchemy subpackage, with versions of
OFXTree and OFXResponse that can parse OFX formatted data and persist it
into an SQL database.

ofxalchemy depends on [the SQLAlchemy package][http://www.sqlalchemy.org].
You'll need the upcoming version 1.0 of SQLAlchemy, which is still in
development and can be obtained from [the SQLAlchemy code repository]
(https://bitbucket.org/zzzeek/sqlalchemy).

INSTALLATION
====
Use the Python user installation scheme:
`python setup.py install --user`

In addition to the Python package, this will also install a script 'ofxget'
in ~/.local/bin, and its sample configuration file in ~/.config/ofxtools .

To use ofxalchemy, you'll need to install SQLAlchemy via:
`pip install sqlalchemy`
or
`easy_install sqlalchemy`
or download and install the package from
[the SQLAlchemy website][http://www.sqlalchemy.org]
or from [PyPI][https://pypi.python.org]


BASIC USAGE TO DOWNLOAD OFX
====
1) Copy ~/.config/ofxtools/ofxget_example.cfg to ~/.config/ofxtools/ofxget.cfg and edit.
Add a section for your financial institution, including URL,
account information, login, etc.
See comments within.
2) Execute ofxget with appropriate arguments, e.g.
`# ofxget amex stmt -s 20140101 -e 20140630 > foobar.ofx`
See the --help for explanation of the script options


PARSER USAGE EXAMPLE
====
>>> from ofxtools import OFXTree
>>> tree = OFXTree()
>>> tree.parse('stmtrs.ofx')
>>> response = tree.convert()
>>> response
<OFXResponse fid='1001' org='NCH' dtserver='2005-10-29 10:10:03' len(statements)=1 len(securities)=0>
>>> stmt = response.statements[0]
>>> stmt
<BankStatement account=<BANKACCTFROM acctid='999988' accttype='CHECKING' bankid='121099999'> currency=USD ledgerbal=<LEDGERBAL balamt='200.29' dtasof='2005-10-29 11:20:00'> availbal=<AVAILBAL balamt='200.29' dtasof='2005-10-29 11:20:00'> len(other_balances)=0 len(transactions)=2>
>>> stmt.transactions[-1]
<STMTTRN dtposted='2005-10-20 00:00:00' trntype='ATM' trnamt='-300.00' fitid='00003' dtuser='2005-10-20 00:00:00'>


SQL PERSISTENCE EXAMPLE
====
>>> # Housekeeping to set up database connection
...
>>> from ofxtools import ofxalchemy
>>> from sqlalchemy import create_engine
>>> engine = create_engine('sqlite://', echo=False)
>>> ofxalchemy.DBSession.configure(bind=engine)
>>> ofxalchemy.Base.metadata.create_all(engine)
>>> # Parse and persist the OFX data
...
>>> parser = ofxalchemy.OFXParser()
>>> parser.parse('invstmtrs.ofx')
>>> parser.instantiate()
<OFXResponse len(statements)=1 len(securities)=3>
>>> DBSession.commit()
>>> # Besides the returned OFXResponse object, persisted data can now be
>>> # accessed by querying the database. The object model follows the OFX
>>> # specification fairly closely, with data elements represented as instance
>>> # attributes, subaggregate type nesting modeled by polymorphic inheritance,
>>> # and references to other data types replaced by foreign key relationships.
>>> #
>>> # N.B. There is no database structure representing account statements
>>> # (OFX *STMT aggregates); only the transactions, balances, etc. contained
>>> # within a statement are persisted.
...
>>> from ofxtools.ofxalchemy.models import *
>>> acct = DBSession.query(ACCTFROM).one()
>>> acct
<INVACCTFROM(brokerid='121099999', acctid='999988', id='1')>
>>> acct.invbals
[<INVBAL(availcash='200.00', marginbalance='-50.00', shortbalance='0', acctfrom_id='1', dtasof='2005-08-27 01:00:00')>]
>>> # The full range of SQLAlchemy query expressions is available.
...
>>> from datetime import datetime
>>> invtrans = DBSession.query(INVTRAN).filter_by(acctfrom=acct).filter(INVTRAN.dttrade >= datetime(2005,1,1)).filter(INVTRAN.dttrade <= datetime(2005,12,31)).order_by(INVTRAN.dttrade).all()
>>> invtrans
[<BUYSTOCK(units='100', unitprice='50.00', commission='25.00', total='-5025.00', subacctsec='CASH', subacctfund='CASH', buytype='BUY', secinfo_id='1', id='1')>]
>>> # OFX text data has been validated and converted to Python types, so it
>>> # can be worked with directly.
...
>>> t = invtrans[0]
>>> assert -t.units * t.unitprice - t.commission == t.total
>>>