forcedtypes 0.1

Force crappy data into python type.

# forcedtypes

Force crappy data into Python type. Yeah, I know It sounds strange but It could be useful sometimes. Ohh, did I mention that It is working with Py2 and Py3.

Supported types:

- t.Bool -> `bool`
- t.Int -> `long` in PY2, `int` in PY3
- t.Float -> `float`
- t.Date -> `datetime.date`
- t.Datetime -> `datetime.datetime`
- t.Str -> `unicode` in PY2, `str` in PY3

### How to install

You can use `easy_install` or `pip` to install the package.

$ easy_install forcedtypes

### Examples

Let's see some examples for this awesomeness.

>>> import forcedtypes as t

##### 1. Date parsing

>>> t.Date('3/4/15')
datetime.date(2015, 3, 4)

>>> t.Date('3/4/15', dayfirst=True)
datetime.date(2015, 4, 3)

##### 2. String to boolean

>>> t.Bool('yes') == t.Bool('t') == t.Bool(1.0) == True
True

##### 3. Float with unique separator

If you want to convert `3,400` to `float` It will give you error:

>>> float('3,400')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: could not convert string to float: '3,400'

The `forcedtypes` package makes it easier.

>>> t.Float('3,400')
3.4

>>> t.Float('3,400', locale='de_DE')
3.4

>>> t.Float('3,400', locale='en_US')
3400.0

##### 4. Eliminate empty strings

>>> t.Str(' ') is None
True

##### 5. Use for type enforcement

If you have a file like this one,

1;3.4;Item 1.
3;55.6;Item 2.
4;44,5;
6;77.5;Item 4.

You can use this script ...

import forcedtypes as t

with open('file.csv','r', encoding='utf-8') as fd:
for line in fd.readlines():
id, price, name = map(lambda x,: x[0](x[1]),
zip([int, t.Float, t.Str], line.split(';')))
print(repr(id), repr(price), repr(name))

... to get the correct result:

1 3.4 'Item 1.\n'
3 55.6 'Item 2.\n'
4 44.5 None
6 77.5 'Item 4.'