[Tutor] Can tempfile.NamedTemporaryFile(delete=False) be used to create *permanent* uniquely named files?
Use case: I want to allow a user of my Solitaire Scorekeeper program to be able to give any name he wants to each game of solitaire he wishes to record. My thought for permanent storage of each game's parameters is to use a dictionary to map the user-chosen game names to a unique json filename. This way I hope no shenanigans can occur with weird characters/non-printing characters. My initial thought was to just have a sequence of game names with incrementing numerical suffixes: game_0, game_1, ... , game_n. But this would require the program to keep track of what the next available numerical suffix is. Additionally, if a user chooses to delete a game, then there would be a gap in the numerical sequence of the game filenames. I find such a gap aesthetically displeasing and would probably go to additional efforts to reuse such deleted filenames, so there would be no such "gaps". So I am now wondering if using tempfile.NamedTemporaryFile(delete=False) would solve this problem nicely? As I am not very familiar with this library, are there any unforeseen issues I should be made aware of? Would this work equally well on all operating systems? TIA! -- boB ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When are "__init__.py" files needed and not needed in a project?
On Sat, Oct 20, 2018 at 11:21 PM Alex Kleider wrote: > > On 2018-10-20 14:52, boB Stepp wrote: > > > >> > In case it helps, my current project structure is: > >> > > >> > ~/Projects/solitaire_scorekeeper/# I left off the actual project > >> > folder in my original email > >> > data/ > >> > docs/ > >> > tests/ > >> > .git/ > >> > main.py > >> > .gitignore > > > I'm curious to know where under the above structure you keep your code > files? (...or is all your code within main.py?) For this project, I am hoping that in the end there will not be a lot of code, so I am currently putting all code in main.py. If this gets too unwieldy I will move all refactored source code files into a new "src" subdirectory. -- boB ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When are "__init__.py" files needed and not needed in a project?
On 2018-10-20 14:52, boB Stepp wrote: > In case it helps, my current project structure is: > > ~/Projects > data/ > docs/ > tests/ > .git/ > main.py > .gitignore I'm curious to know where under the above structure you keep your code files? (...or is all your code within main.py?) ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
[Tutor] What is the best way for a program suite to know where it is installed?
I was just re-reading the entire thread at https://www.mail-archive.com/tutor@python.org/msg77864.html And I have asked similar questions previous to that thread. I still do not have a satisfactory answer for the subject line's question that both makes sense to me and seems to be good programming practice. And that works for any OS that the program suite is installed under. A constantly recurring situation I am having is a programming project with a nested directory structure. Usually I will have "tests" and "data" folders nested under the top level project folder. There may be others as well depending on the complexity of the project I am attempting. As far as I can tell, I cannot make any assumptions about what the current working directory is when a user starts the program. So how can one of my programs *know* what the absolute path is to, say, the top level of the program suite? If I could always reliably determine this by my program's code, every other location could be determined from the known nested structure of the program suite. [But I have a dim recollection that either Ben or Cameron thought relying on the "known nested structure" is brittle at best.] So far the best method I've come up with is to make use of "__file__" for the initiating program file. But from past discussions I am not certain this is the *best* way. Is the *best* way going to get me into best techniques for installing and distributing programs? If so, this strikes me as a huge mess to dive into! TIA! -- boB ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] sftp in python without using pysftp or paramiko
On 20/10/18 21:07, Asad wrote: > hi All , > > I am looking to create a python script which logs in to the server and > copies the fie from ftp to local system .: The obvious answer is use pysftp. But your subject says you don't want to do that. So the next option is for you to write your own version of pysftp, duplicating all the things the author of that module did. Of course for a non generic solution you only need a fraction of the code, and you could use something like pyexpect or an ssh module to reduce the effort. > sftp a...@us.com 2100 > > password : xxx > > sftp> cd /to_dir > sftp > get file1 > sftp >exit > > Please advice . I'd advise using the available modules. But if that really is impossible use the next level down. Reinventing the wheel is a painful waste of time that usually only serves to increase your respect for the inventor of said wheel. -- Alan G Author of the Learn to Program web site http://www.alan-g.me.uk/ http://www.amazon.com/author/alan_gauld Follow my photo-blog on Flickr at: http://www.flickr.com/photos/alangauldphotos ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
[Tutor] sftp in python without using pysftp or paramiko
hi All , I am looking to create a python script which logs in to the server and copies the fie from ftp to local system .: sftp a...@us.com 2100 password : xxx sftp> cd /to_dir sftp > get file1 sftp >exit Please advice . -- Asad Hasan +91 9582111698 ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When are "__init__.py" files needed and not needed in a project?
On Sat, Oct 20, 2018 at 1:36 PM Peter Otten <__pete...@web.de> wrote: > > boB Stepp wrote: > > > Linux Mint 19 Cinnamon, Python 3.6.6 [snip] > > I was expecting this error and will shortly correct it. So my > > question remains, when are "__init__.py" files needed and when are > > they not? > > I am struggling with the differences between the two types of packages > myself, so my first guess was that you accidentally found out that test > discovery doesn't work for namespace packages. However > > https://docs.python.org/dev/library/unittest.html#test-discovery > > expicitly states > > """ > Changed in version 3.4: Test discovery supports namespace packages. > """ > > Perhaps you should file a bug report. I just waded through PEP 420 describing "implicit namespace packages". I think I have a cursory understanding now, but not enough to feel confidant to file a bug report. It *seems* that with my project structure below (Note the slight correction.) if I initiate test discovery in the top level directory (The one holding main.py.) and have no __init__.py files anywhere, that my initial effort should have run the one test with the resulting error instead of running 0 tests. Can anything reading this duplicate my issue? If yes, then I will endeavour to file a bug report. But otherwise, I would suspect something screwy that I have done and am currently unaware of what it may be. > > In case it helps, my current project structure is: > > > > ~/Projects > > data/ > > docs/ > > tests/ > > .git/ > > main.py > > .gitignore Just noticed that I mistyped the top level of my project structure. It should be: ~/Projects/solitaire_scorekeeper/ etc. -- boB ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When are "__init__.py" files needed and not needed in a project?
boB Stepp wrote:
> Linux Mint 19 Cinnamon, Python 3.6.6
>
> I would have sworn that I had read, either on this list or the main
> Python list, that in the most recent versions of Python 3 that
> "__init__.py" files were no longer needed in nested project file
> structures.
If you omit the __init__.py you get a "namespace package".
Namespace packages can combine multiple directories into one package, but
will be shaded by "normal" packages.
> But when I attempted to run tests for the first time on
> my new Solitaire Scorekeeper project (Finally getting around to
> this!), I got:
>
> bob@Dream-Machine1:~/Projects/solitaire_scorekeeper$ python3 -m unittest
>
> --
> Ran 0 tests in 0.000s
>
> OK
>
> So no tests were run. So it immediately occurred to me to add an
> empty "__init__.py" file to my "tests" subfolder and got what I was
> currently expecting:
>
> bob@Dream-Machine1:~/Projects/solitaire_scorekeeper$ python3 -m unittest
> E
> ==
> ERROR: test_get_gamenames_bad_path
> (tests.tests_main.TestGameNamesMapperMethods) Test that when the method,
> get_gamenames(), is passed a path to a
> --
> Traceback (most recent call last):
> File "/home/bob/Projects/solitaire_scorekeeper/tests/tests_main.py",
> line 20, in test_get_gamenames_bad_path
> self.assertEqual(gamenames.gamenames(), {})
> NameError: name 'self' is not defined
>
> --
> Ran 1 test in 0.000s
>
> FAILED (errors=1)
>
> I was expecting this error and will shortly correct it. So my
> question remains, when are "__init__.py" files needed and when are
> they not?
I am struggling with the differences between the two types of packages
myself, so my first guess was that you accidentally found out that test
discovery doesn't work for namespace packages. However
https://docs.python.org/dev/library/unittest.html#test-discovery
expicitly states
"""
Changed in version 3.4: Test discovery supports namespace packages.
"""
Perhaps you should file a bug report.
> In case it helps, my current project structure is:
>
> ~/Projects
> data/
> docs/
> tests/
> .git/
> main.py
> .gitignore
>
> TIA!
>
___
Tutor maillist - Tutor@python.org
To unsubscribe or change subscription options:
https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] How to find optimisations for code
There are many ways to do some things. I present a fairly straightforward
method for consideration.
Synopsis. Use two dictionaries to keep track of how many times a letter can
be found in the source word and the target word.
Loop over the target letters and as soon as you find a letter that needs
more copies of that letter than are available in the source, return False.
Otherwise, return True.
Slight optimization, return False immediately if the target is too long.
Note: Remove the print statements used to show what it does when trying for
efficiency.
Note I do not claim this is fast. But for longer strings this requires one
pass over each string to set the dictionary counters and often less than one
pass over the target string to determine Truth. I can visualize many
variants but efficiency of each may vary with the data, version of Python
and so on.
Python CODE using version 3.7.0 :
"""
Function to check if string str_target is a strict subset
of str_source - but with multiple copies of a letter being unique
in what is thus not a set. In English, can the letters in str_target
be found in the required quantities with possibly some left over
when examining str_source. For example, 'level' has two l's and two e's
and can be made from 'multilevel' but not from 'evil' which has the needed
e v and l but not two copies.
"""
def sub_word(str_source, str_target):
"""
Return True/False if letters in source are enough to make target
Method: make dictionaries of number of letters in each. See if enough.
"""
# Check for trivial False condition: word too long
if len(str_target) > len(str_source) : return False
# Initialize empty dictionaries to hold leter counts.
source = {}
target = {}
# Count letters in source thgen target, initializing
# to zero if not yet present.
for letter in str_source.lower():
source[letter] = source.get(letter, 0) + 1
for letter in str_target.lower():
target[letter] = target.get(letter, 0) + 1
# During bebug phase, show what the dictionaries contain
print("SOURCE dict:", source)
print("TARGET dict:", target)
# Iterate over letters in target and return False
# if the number of instances needed exceeds what
# can be found in the source.
for key in target:
if target[key] > source.get(key, 0) : return False
# if you reached here, return True as all letters needed
# have been found.
return True
Examples of use:
>>> sub_word("multilevel", "level")
SOURCE dict: {'m': 1, 'u': 1, 'l': 3, 't': 1, 'i': 1, 'e': 2, 'v': 1}
TARGET dict: {'l': 2, 'e': 2, 'v': 1}
True
>>> sub_word("shorT", "MuchTooLong")
False
>>> sub_word("supercalifragilisticexpialidocious", "california")
SOURCE dict: {'s': 3, 'u': 2, 'p': 2, 'e': 2, 'r': 2, 'c': 3, 'a': 3, 'l':
3, 'i': 7, 'f': 1, 'g': 1, 't': 1, 'x': 1, 'd': 1, 'o': 2}
TARGET dict: {'c': 1, 'a': 2, 'l': 1, 'i': 2, 'f': 1, 'o': 1, 'r': 1, 'n':
1}
False
>>> sub_word("supercalifragilisticexpialidocious", "fragile")
SOURCE dict: {'s': 3, 'u': 2, 'p': 2, 'e': 2, 'r': 2, 'c': 3, 'a': 3, 'l':
3, 'i': 7, 'f': 1, 'g': 1, 't': 1, 'x': 1, 'd': 1, 'o': 2}
TARGET dict: {'f': 1, 'r': 1, 'a': 1, 'g': 1, 'i': 1, 'l': 1, 'e': 1}
True
>>> sub_word("devil", "vile")
SOURCE dict: {'d': 1, 'e': 1, 'v': 1, 'i': 1, 'l': 1}
TARGET dict: {'v': 1, 'i': 1, 'l': 1, 'e': 1}
True
-Original Message-
From: Tutor On Behalf Of
Peter Otten
Sent: Saturday, October 20, 2018 3:02 AM
To: tutor@python.org
Subject: Re: [Tutor] How to find optimisations for code
Steven D'Aprano wrote:
> We don't need to check that the individual letters are the same,
> because checking the counts will suffice. If they are not the same,
> one string will have (let's say) two A's while the other will have
> none, and the counts will be different.
Another great optimisation is solving the actual problem ;)
The OP isn't looking for anagrams, he wants to know if string2 can be spelt
with the characters in string1:
abba, abacus --> True (don't care about the extra b, c, u, s) abba, baab
--> True (don't care about character order) abba, bab --> False (bab is
missing an a)
___
Tutor maillist - Tutor@python.org
To unsubscribe or change subscription options:
https://mail.python.org/mailman/listinfo/tutor
___
Tutor maillist - Tutor@python.org
To unsubscribe or change subscription options:
https://mail.python.org/mailman/listinfo/tutor
[Tutor] When are "__init__.py" files needed and not needed in a project?
Linux Mint 19 Cinnamon, Python 3.6.6
I would have sworn that I had read, either on this list or the main
Python list, that in the most recent versions of Python 3 that
"__init__.py" files were no longer needed in nested project file
structures. But when I attempted to run tests for the first time on
my new Solitaire Scorekeeper project (Finally getting around to
this!), I got:
bob@Dream-Machine1:~/Projects/solitaire_scorekeeper$ python3 -m unittest
--
Ran 0 tests in 0.000s
OK
So no tests were run. So it immediately occurred to me to add an
empty "__init__.py" file to my "tests" subfolder and got what I was
currently expecting:
bob@Dream-Machine1:~/Projects/solitaire_scorekeeper$ python3 -m unittest
E
==
ERROR: test_get_gamenames_bad_path (tests.tests_main.TestGameNamesMapperMethods)
Test that when the method, get_gamenames(), is passed a path to a
--
Traceback (most recent call last):
File "/home/bob/Projects/solitaire_scorekeeper/tests/tests_main.py",
line 20, in test_get_gamenames_bad_path
self.assertEqual(gamenames.gamenames(), {})
NameError: name 'self' is not defined
--
Ran 1 test in 0.000s
FAILED (errors=1)
I was expecting this error and will shortly correct it. So my
question remains, when are "__init__.py" files needed and when are
they not?
In case it helps, my current project structure is:
~/Projects
data/
docs/
tests/
.git/
main.py
.gitignore
TIA!
--
boB
___
Tutor maillist - Tutor@python.org
To unsubscribe or change subscription options:
https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] How to find optimisations for code
Steven D'Aprano wrote: > We don't need to check that the individual letters are the same, because > checking the counts will suffice. If they are not the same, one string > will have (let's say) two A's while the other will have none, and the > counts will be different. Another great optimisation is solving the actual problem ;) The OP isn't looking for anagrams, he wants to know if string2 can be spelt with the characters in string1: abba, abacus --> True (don't care about the extra b, c, u, s) abba, baab --> True (don't care about character order) abba, bab --> False (bab is missing an a) ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
