Skip to main content

Stork Craft Tuscany 4-in-1 Stages Crib

This is a convertible, full size, crib. It requires a moderate amount of assembly and at one point (where you attach the mattress board onto the frame) it helps to have two people, but I could do it by myself with some creative positioning. We got the natural wood version which looks very nice to us.

The construction of the crib is very good and the design is well thought out - with special consideration because it is meant to be modified at different stages of the owner's life. The main frame members are made of a solid but somewhat soft wood. Each piece is thick and strong, but fairly easy to dent, so care must be taken when working around it with metal tools or moving it. The pieces are joined using metal bolts. The bolts screw on to metal nuts embedded in the wood, allowing for repeated disassembly without wearing down the wood.

The wood was not aired out sufficiently at the factory and gave off a rather strong smell of varnish when we opened the package. I would say it took one month in a decently ventilated room (it was winter, so we kept the windows closed at night) for the odor to vanish.

The width and shape of the crib requires that it be disassembled before moving through standard sized doors.

One thing, which we did not consider, is that the baby will not need this crib in the first few months. We ended up using the crib as a rack for clothes and a place to put toys while the baby slept in the bassinet.


Comments

Popular posts from this blog

A note on Python's __exit__() and errors

Python's context managers are a very neat way of handling code that needs a teardown once you are done. Python objects have do have a destructor method ( __del__ ) called right before the last instance of the object is about to be destroyed. You can do a teardown there. However there is a lot of fine print to the __del__ method. A cleaner way of doing tear-downs is through Python's context manager , manifested as the with keyword. class CrushMe: def __init__(self): self.f = open('test.txt', 'w') def foo(self, a, b): self.f.write(str(a - b)) def __enter__(self): return self def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() return True with CrushMe() as c: c.foo(2, 3) One thing that is important, and that got me just now, is error handling. I made the mistake of ignoring all those 'junk' arguments ( exc_type, exc_val, exc_tb ). I just skimmed the docs and what popped out is that you need to return True or...

Store numpy arrays in sqlite

Use numpy.getbuffer (or sqlite3.Binary ) in combination with numpy.frombuffer to lug numpy data in and out of the sqlite3 database: import sqlite3, numpy r1d = numpy.random.randn(10) con = sqlite3.connect(':memory:') con.execute("CREATE TABLE eye(id INTEGER PRIMARY KEY, desc TEXT, data BLOB)") con.execute("INSERT INTO eye(desc,data) VALUES(?,?)", ("1d", sqlite3.Binary(r1d))) con.execute("INSERT INTO eye(desc,data) VALUES(?,?)", ("1d", numpy.getbuffer(r1d))) res = con.execute("SELECT * FROM eye").fetchall() con.close() #res -> #[(1, u'1d', <read-write buffer ptr 0x10371b220, size 80 at 0x10371b1e0>), # (2, u'1d', <read-write buffer ptr 0x10371b190, size 80 at 0x10371b150>)] print r1d - numpy.frombuffer(res[0][2]) #->[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] print r1d - numpy.frombuffer(res[1][2]) #->[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] Note that for work where data ty...