Skip to main content

Washing machine hoses

When our home inspector went through he mentioned to me that I should replace the existing rubber hoses on the washing machine with steel-reinforced ones. I wondered if washing machine hoses were specially prone to fail, perhaps something to do with the intermittent nature of the load (if you look at the hoses when the washing machine runs, they jerk as the machine draws water in phases). I also began to wonder if dishwasher hoses suffered from the same problem.

A quick search brought up two documents, one from a community association underwriter - which I assume insures people with rental properties. The other document I found was from an insurance association serving hotels and inns. The first one claims that steel-reinforced hoses are no better than rubber hoses since the hoses are damaged at the connection. The other one suggests that steel-reinforced hoses may be better than regular rubber hoses but all hoses should be replaced every five years or so.

I could not find reasons why these hoses were more susceptible to rupturing and why the dish washer water connection does not suffer from the same maintenance issue.


Labels:

Comments

Post a Comment

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...
Post a Comment
Read more

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...
Post a Comment
Read more