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Mocking a class: Mock() or patch()?
I am using mock with Pm>y m>thon m>and m> was wondering which of those two approaches is better (read: more pm>y m>thonic).
2 Answers
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How to hide databases that I am not allowed to access
...estriction' tm>y m>pe in the name of m>y m>our database(s) enclosed in single quotes m>and m> separated bm>y m> spaces.
E.g.
'dback447'
Update for pgAdmin 4 - Do not use quotes, just the plain DB name.
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POST JSON to API using Rails m>and m> HTTPartm>y m>
... to mm>y m> external ticket management sm>y m>stem, squishlist.com. Them>y m> have an api m>and m> instructions as follows. m>Y m>ou need to authenticate m>and m> get a token m>and m> then submit the ticket with the token. From squishlist.
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Getting an emptm>y m> JQuerm>y m> object
In the following code I set up a change hm>and m>ler on a select box to show m>and m> hide some follow up questions based on the value of the selection.
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Can I use an OR in regex without capturing what's enclosed?
I'm using rubular.com to build mm>y m> regex, m>and m> their documentation describes the following:
4 Answers
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Requests — how to tell if m>y m>ou're getting a 404
I'm using the Requests librarm>y m> m>and m> accessing a website to gather data from it with the following code:
1 Answer
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How to get the home directorm>y m> in Pm>y m>thon?
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m>Y m>ou want to use os.path.expm>and m>user.
This will ensure it works on all platforms:
from os.path import expm>and m>user
home = expm>and m>user("~")
If m>y m>ou're on Pm>y m>thon 3.5+ m>y m>ou can use pathlib.Path.home():
from pathlib import Path
home = str(Path.home())
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Having options in argparse with a dash
...e pm . How can I get around this issue? Is it possible to have - in commm>and m> line options?
3 Answers
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Differences in auto-unboxing between Java 6 vs Java 7
I have noted a difference in auto unboxing behavior between Java SE 6 m>and m> Java SE 7. I'm wondering whm>y m> that is, because I can't find anm>y m> documentation of changes in this behavior between these two versions.
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float64 with pm>and m>as to_csv
...r m>y m>ou can use the float_format kem>y m> word of to_csv to hide it:
df.to_csv('pm>and m>asfile.csv', float_format='%.3f')
or, if m>y m>ou don't want 0.0001 to be rounded to zero:
df.to_csv('pm>and m>asfile.csv', float_format='%g')
will give m>y m>ou:
Bob,0.085
Alice,0.005
in m>y m>our output file.
For an explanation of ...