The memory overhead of using __dict__ vs __slots__ turned out to be 147 bytes per object.

Here are my results

Using the following test script

class C(object):
#__slots__ = ('abc', 'defg')
pass

a = []
for i in xrange(1000000):
c = C()
c.abc = 1
c.defg = 2
a.append(c)

That’s quite promising. Now, if I can make that work with our in-house ORM.

One way to do this is through using Word Automation. However, another way is to do some XML manipulation, given that .dotx and .dotcx files are actually zip archives.

import xml.dom.minidom
import zipfile

def dotx2docx(src, dst)

    OLD_CONTENT_TYPE = "application/vnd.openxmlformats-officedocument.wordprocessingml.template.main+xml"
    NEW_CONTENT_TYPE = "application/vnd.openxmlformats-officedocument.wordprocessingml.document.main+xml"
    CONTENTTYPE_FILENAME = '[Content_Types].xml'
    arc_in  = zipfile.ZipFile(src, 'r')
    arc_out = zipfile.ZipFile(dst, 'w')
    for zinfo in arc_in.infolist():
        if zinfo.filename == CONTENTTYPE_FILENAME:
                doc = xml.dom.minidom.parseString(arc_in.read(CONTENTTYPE_FILENAME))
                els = doc.getElementsByTagName('Override')
                for el in els:
                    attr_contenttype = el.getAttribute('ContentType')
                    if attr_contenttype == OLD_CONTENT_TYPE:
                        if el.getAttribute('PartName') == '/word/document.xml':
                            el.setAttribute('ContentType', NEW_CONTENT_TYPE)
                arc_out.writestr(CONTENTTYPE_FILENAME, doc.toxml())
                doc.unlink()
        else:
            contents = arc_in.read(zinfo.filename)
            arc_out.writestr(zinfo.filename, contents)
    arc_in.close()
    arc_out.close()

import traceback
import logging

# somewhere in your buggy code
logging.log(1, "".join(traceback.format_stack())

However, building PIL on Cygwin Python 2.5 yields the following error message:

unable to remap C:\cygwin\bin\tk84.dll to same address as parent

Thanks to the power of Google, DataHammer has already found a resolution

C:\>cd \cygwin\bin
C:\cygwin\bin>ash
$ ./rebase -b 0x1000000000 tk84.dll

Building _sqlite3.dll on cygwin is not too difficult. If you are in a hurry, heres the download _sqlite3.dll.

Prerequisites

• /bin/cygsqlite3-0.dll
• /bin/libpython2.5.dll
• /usr/include/sqlite3.h
• /usr/include/python2.5/Python.h [et.c]

tar jxf Python-2.5.2.tar.bz2 Python-2.5.2/Modules/_sqlite/
cd Python-2.5.2/Modules/_sqlite/
gcc -shared -o _sqlite3.dll -I /usr/include/python2.5 -L /bin -lpython2.5 -lsqlite3-0 -D'MODULE_NAME="_sqlite3"' *.c
cp _sqlite3.dll /usr/lib/python2.5/lib-dynload/

download

_sqlite3.dll

Update 10 Sept 2008

Download link fixed. (Thanks Steve)

Problem #1
The $ used by Genshi for string interpolation conflicts with PHP’s $variables.

Solution #1
After 10 minutes of source diving (by the way, Genshi source is a work of art – wish I could write like that).

import genshi.template.interpolation
genshi.template.interpolation.PREFIX = '^'

from genshi.template import TextTemplate
template = TextTemplate("$this->^{foo} = 'home';")
stream = template.generate(foo="customer")
print stream

Problem #2
The generated output quotes the > into >

Solution #2
The Stream render() method takes a parameter specifying the kind of escaping.

print stream.render('text')

Overall Solution

from genshi.template import TextTemplate
import genshi.template.interpolation
genshi.template.interpolation.PREFIX = '^'
for tablename, table in specs.items():
    fd = open('controllers/%s.php' % tablename, 'w')
    template = TextTemplate(open('controllers.php', 'r'), filename='controller.php')
    print template.generate(tablename=tablename, columns=table).render('text')

import sys

class tee(file):
   def write(self, text):
     sys.stdout.write(text)
     file.write(self, text)

fd = tee("output.txt", "w")
print >> fd, "Test 1"
fd.write("Test 2\n")

$ python test.py
Test 2

$ cat output.txt
Test 1
Test 2

Using the dis module, we can tell that print >> is compiled into PRINT_ITEM_TO.

>>> def t(): print >> fd, "foo"
...
>>> import dis; dis.dis(t)
  1           0 LOAD_GLOBAL              0 (fd)
              3 DUP_TOP
              4 LOAD_CONST               1 ('foo')
              7 ROT_TWO
              8 PRINT_ITEM_TO
              9 PRINT_NEWLINE_TO
             10 LOAD_CONST               0 (None)
             13 RETURN_VALUE

and looking through ceval.c, searching for PRINT_ITEM_TO yields

 case PRINT_ITEM_TO:
    w = stream = POP();
    /* fall through to PRINT_ITEM */

case PRINT_ITEM:
    v = POP();
    if (stream == NULL || stream == Py_None) {
        w = PySys_GetObject("stdout");
        if (w == NULL) {
            PyErr_SetString(PyExc_RuntimeError,
                    "lost sys.stdout");
            err = -1;
        }
    }
    /* PyFile_SoftSpace() can exececute arbitrary code
       if sys.stdout is an instance with a __getattr__.
       If __getattr__ raises an exception, w will
       be freed, so we need to prevent that temporarily. */
    Py_XINCREF(w);
    if (w != NULL && PyFile_SoftSpace(w, 0))
        err = PyFile_WriteString(" ", w);
    if (err == 0)
        err = PyFile_WriteObject(v, w, Py_PRINT_RAW);

Any ideas why?

• Andromeda
• Django Admin
• Dataphor

  Promises: User interface “hints” integrated with the data model

• Naked Objects
• MS Access and Query By Form
• I like how CodeIgniter makes it possible to compose declarative data validations e.g. “valid_email|matches[email_confirm]|min_length[6]“
• We need standard ValueConverters for currency, URL, dates and email addresses
• Someone should write an essay on why database synchronization for off-line applications is a bad idea, and why journaling works better
• More ideas here – There are no attributes – CQL sounds cool

What are your thoughts here? Are there any other notable projects in a similar vein?

1. Setting up a Linq DataContext

   MyDatabaseContext db = new MyDatabaseContext(MyConnectionString); // or MyDatabaseContext db = new MyDatabaseContext();
 

2. Basic LINQ Expression

   var AnIQueryable = from Customer in db.Customers
where Customer.FirstName.StartsWith("m")
select Customer; 


3. Logging the generated queries

   db.Log = Console.out

   The previous example translates into a LIKE operator:

   SELECT [t0].[CustomerID], [t0].[FirstName] AS [FirstName]
FROM [dbo].[Customer] AS [t0]
WHERE [t0].[FirstName] LIKE @p0

4. LINQ with Aggregates

   var AverageRuns =(from Master in this.db.Masters select Master.Runs).Average()
   

   The SQL generated isn’t too shabby either:

   SELECT AVG([t0].[Runs]) AS [value]
   FROM [dbo].[Master] AS [t0]

5. LINQ grouped aggregates

   
      var categories =
         from p in products
         group p by p.Category into g
         select new
                 {Category = g.Key,
                  AveragePrice = g.Group.Average(p => p.UnitPrice)
                  };
   

6. Lambda Expressions

   • Map

     db.Customers.Select(customer => master.Customer.LastName.length)

   • Filter

     db.Customers.Where(customer => customer.LastName.StartsWith("M")

   • Reduce / Fold

     
double[] doubles = { 1.7, 2.4, 3.5, 8.9 };
double result = doubles.Aggregate(0.0, (d1, d2) => d1+d2);


     Note: You can’t use Aggregate directly on IQueryable from database contexts. Instead,
     
var arr_masters = this.db.Masters.ToArray();
var totalRuns = arr_masters.Aggregate
(0, // seed
(int accum, MyDB.Master master) => accum + master.Runs
);


7. Updating Database

   
   this.Validate();
   this.masterBindingSource.EndEdit();
   db.SubmitChanges();
   

8. How to cheat

   Use Microsoft’s 101 LINQ samples