[Tutor] Python 3: string to decimal conversion

[US]

Thanks everyone for all your help. This solved my problem with
parenthesis and $ signs in the data:

if not row[4]:
                    pass
                else:
                    try:
                        expenses[ts.Date(row[0]).month] +=
decimal.Decimal(row[4].strip('()$ ,').replace(',',''))
                    except decimal.InvalidOperation as e:
                        print("unexpected expenses value:  %r" % (row[4]))

On Mon, May 23, 2016 at 5:06 AM, Peter Otten <__peter__ at web.de> wrote:
> US wrote:
>
>> Thank you both for suggesting a way to handle errors. I have run the
>> suggested code. What I learned is that all the values (not only empty
>> cells) seem to be invalid for decimal.Decimal function.
>>
>> I tried the float() function instead of decimal.Decimal and got an
>> error message: could not convert string to float: '($75.59)'.
>>
>> I also checked the type of values in row[4]. All the values passed on
>> to decimal.Decimal () function are indeed of string type...
>>
>> Is there anything I can do to the formatting of the csv file to make
>> it 'readable' for decimal.Decimal function?
>>
>> Here is my updated code along with the output I got from running it:
>>
>> ----------------------------------------------------
>> code:
>> import numpy as np
>> import csv
>> import timestring as ts
>> import decimal
>>
>> months= [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
>> expenses = {x: decimal.Decimal() for x in months}
>> income = {x: decimal.Decimal() for x in months}
>> test = []
>>
>> exp_cat = []
>> income_cat = []
>>
>> files =['export.csv']
>>
>> with open("budgetfile.csv","wt") as fw:
>>     writer = csv.writer(fw)
>>     for file in files:
>>         with open(file, newline ='' ) as csvfile:
>>             records = csv.reader(csvfile)
>>             print("Processing file {}. \n" .format(file))
>>             header = next(records)
>>             for row in records:
>>                 print("row[4] =", repr(row[4]), "value type =",
>>                 type(row[4]))
>>
>>                 if not row[4]:
>>                     pass
>>                 else:
>>                     try:
>>                         expenses[ts.Date(row[0]).month] +=
>> decimal.Decimal(row[4])
>>                     except decimal.InvalidOperation as e:
>>                         print("unexpected expenses value:  %r" %
>>                         (row[4],))
>
>> last 4 lines of output:
>> [4] = '($10.00)' value type = <class 'str'>
>> unexpected expenses value:  '($10.00)'
>> row[4] = '($287.42)' value type = <class 'str'>
>> unexpected expenses value:  '($287.42)'
>
> Perhaps you should use a custom conversion routine like to_decimal() below:
>
> class MissingValue(ValueError):
>     pass
>
>
> @contextlib.contextmanager
> def expect(exc):
>     """Ensure that an excption of type `exc` was raised.
>
>     Helper for the doctests.
>     """
>     try:
>         yield
>     except exc:
>         pass
>     except:
>         raise AssertionError(
>             "Wrong exception type (expected {})".format(exc))
>     else:
>         raise AssertionError("Exception was not raised")
>
>
> def to_decimal(s):
>     """
>     >>> with expect(MissingValue):
>     ...     to_decimal("   ")
>     >>> with expect(ValueError):
>     ...     to_decimal("42")
>     >>> to_decimal("$12.34")
>     Decimal('12.34')
>     >>> to_decimal("($34.56)")
>     Decimal('-34.56')
>     >>> with expect(ValueError):
>     ...     to_decimal("foo")
>     >>> with expect(ValueError):
>     ...     to_decimal("$bar")
>     >>> with expect(ValueError):
>     ...     to_decimal("($baz)")
>     """
>     s = s.strip()  # remove leading/trailing whitespace
>     if not s:
>         raise MissingValue("Empty amount")
>     if s.startswith("(") and s.endswith(")"):
>         sign = -1
>         s = s[1:-1]  # remove parens
>     else:
>         sign = 1
>     if not s.startswith("$"):
>         raise ValueError("No leading $ found")
>     s = s[1:]  # remove $
>     try:
>         value = decimal.Decimal(s)
>     except decimal.InvalidOperation as err:
>         raise ValueError(err.args[0]) from None
>     return sign * value
>
>
> That way you can spell out explicitly what the allowed values may look like,
> and if (e. g.) you want to allow for grouping you can easily add another
> preprocessing step to remove the commas. Use it like so in your code:
>
> ...
> for row in records:
>     try:
>         amount = to_decimal(row[4])
>     except ValueError as err:
>         print(err, file=sys.stderr)
>     else:
>         ...  # add amount to expenses
> ...
>
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