Develop Reference

How to extract and sum numbers from a text file - python

I need to extract and sum all the numbers from a file.
How can lst.append be used correctly to make a list of numbers?
name = input("Enter file:")
if len(name) < 1:
name = "regex_sum_1603392.txt"
handle = open(name)
total = 0
lst = list()
import re
for line in handle:
y = re.findall('[0-9]+', line)
lst.append(y)
for linenew in lst:
if ' ' in linenew:
continue
print(linenew)
# current output
[]
[]
[]
['2993', '5874']
[]
[]
[]
[]
[]
['58', '4266', '6417']
[]
[]
[]
...
[]
[]
[]
[]
[]
['42']
[]
# expected output
[2993, 5874, 58, 4266, 6417, ..., 42]
regex_sum_1603392.txt
2993 Why should you learn to write programs? 5874
Writing programs (or programming) is a very creative
and rewarding activity. You can write programs for
many reasons, ranging from making your living to solving
a difficult data analysis problem to having fun to helping
someone 58 else 4266 solve 6417 a problem. This book assumes that
everyone needs to know how to program, and that once
you know how to program you will figure out what you want
to do with your newfound skills.
We are surrounded in our daily lives with computers ranging
from laptops to cell phones. We can think of these computers
as our personal assistants who can take care of many things
on our behalf. The hardware in our current-day computers
is essentially built to continuously ask us the question,
What would you like me to do next?
Programmers add an operating system and a set of applications
to the hardware and we end up with a Personal Digital
Assistant that is quite helpful and capable of helping
us do many different things.
Our computers are fast and have vast amounts of memory and
could be very helpful to us if we only knew the language to
speak to explain to the computer what we would like it to
do next. If we knew this language, we could tell the
computer to do tasks on our behalf that were repetitive.
Interestingly, 1976 the 9565 kinds 7652 of things computers can do best
are often the kinds of things that we humans find boring
and mind-numbing.
For example, look at the first three paragraphs of this
chapter 6112 and 6957 tell 9749 me the most commonly used word and how
many times the word is used. While you were able to read
and understand the words in a few seconds, counting them
is almost painful because it is not the kind of problem
that human minds are designed to solve. For a computer
the opposite is true, reading and understanding text
from a piece of paper is hard for a computer to do
but counting the words and telling you how many times
the most used word was used is very easy for the
computer:
Our personal information analysis assistant quickly
told us that the word to was used sixteen times in the
first three paragraphs of this chapter.
This very fact that computers are good at things
that humans are not is why you need to become
skilled at talking computer language. Once you learn
this 8494 new 7669 language, 395 you can delegate mundane tasks
to your partner (the computer), leaving more time
for you to do the
things that you are uniquely suited for. You bring
creativity, intuition, and inventiveness to this
partnership.
Creativity and motivation
While this book is not intended for professional programmers, professional
programming can be a very rewarding job both financially and personally.
Building useful, elegant, and clever programs for others to use is a very
creative activity. Your computer or Personal Digital Assistant (PDA)
usually contains many different programs from many different groups of
programmers, each competing for your attention and interest. They try
their best to meet your needs and give you a great user experience in the
process. In some situations, when you choose a piece of software, the
programmers are directly compensated because of your choice.
6940 If we think of programs as the creative output of groups of programmers,
perhaps the following figure is a more sensible version of our PDA:
For now, our primary motivation is not to make money or please end users, but
instead for us to be more productive in handling the data and
information that we will encounter in our lives.
When 4604 you 1069 first 540 start, you will be both the programmer and the end user of
your programs. As you gain skill as a programmer and
programming feels more creative to you, your thoughts may turn
toward developing programs for others.
Computer hardware architecture
9046 2173 158
Before we start learning the language we
1330 speak to give instructions to computers to 5644
develop software, we need to learn a small amount about
how computers are built.
Central Processing Unit (or CPU) is
the part of the computer that is built to be obsessed
with what is next? If your computer is rated
at three Gigahertz, it means that the CPU will ask What next?
three billion times per second. You are going to have to
learn how to talk fast to keep up with the CPU.
Main Memory is used to store information
that the CPU needs in a hurry. The main memory is nearly as
fast as the CPU. But the information stored in the main
memory vanishes when the computer is turned off.
Secondary Memory is also used to store
information, but it is much slower than the main memory.
The advantage of the secondary memory is that it can
store information even when there is no power to the
computer. Examples of secondary memory are disk drives
or flash memory (typically found in USB sticks and portable
9528 4312 1128
633 9310
5216 Input and Output Devices are simply our
screen, keyboard, mouse, microphone, speaker, touchpad, etc.
They are all of the ways we interact with the computer.
These days, most computers also have a
7768 Network Connection to retrieve information over a network.
We can think of the network as a very slow place to store and
retrieve data that might not always be up. So in a sense,
the network is a slower and at times unreliable form of
5888 Secondary Memory.
While most of the detail of how these components work is best left
to computer builders, it helps to have some terminology
so we can talk about these different parts as we write our programs.
As a programmer, your job is to use and orchestrate
each of these resources to solve the problem that you need to solve
and analyze the data you get from the solution. As a programmer you will
mostly be talking to the CPU and telling it what to
do next. Sometimes you will tell the CPU to use the main memory,
secondary memory, network, or the input/output devices.
2613 381 9203
You need to be the person who answers the CPU's What next?
question. But it would be very uncomfortable to shrink you
down to five mm tall and insert you into the computer just so you
could issue a command three billion times per second. So instead,
you must write down your instructions in advance.
We call these stored instructions a program and the act
of writing these instructions down and getting the instructions to
be correct programming.
Understanding programming
In the rest of this book, we will try to turn you into a person
who is skilled in the art of programming. In the end you will be a
3175 programmer --- perhaps not a professional programmer, but
at least you will have the skills to look at a data/information
analysis problem and develop a program to solve the problem.
2466 9374 9787
problem solving
In a sense, you need two skills to be a programmer:
5868 First, you need to know the programming language (Python) -
you need to know the vocabulary and the grammar. You need to be able
to spell the words in this new language properly and know how to construct
well-formed sentences in this new language.
Second, you need to tell a story. In writing a story,
you combine words and sentences to convey an idea to the reader.
There is a skill and art in constructing the story, and skill in
story writing is improved by doing some writing and getting some
feedback. In programming, our program is the story and the
problem you are trying to solve is the idea.
itemize
Once you learn one programming language such as Python, you will
find it much easier to learn a second programming language such
as JavaScript or C++. The new programming language has very different
5100 vocabulary and grammar but the problem-solving skills 9484
will be the same across all programming languages.
6756 You will learn the vocabulary and sentences of Python pretty quickly.
It will take longer for you to be able to write a coherent program
to solve a brand-new problem. We teach programming much like we teach
writing. 3848 4527 We 8718 start reading and explaining programs, then we write
simple programs, and then we write increasingly complex programs over time.
At some point you get your muse and see the patterns on your own
and can see more naturally how to take a problem and
write a program that solves that problem. And once you get
to that point, programming becomes a very pleasant and creative process.
We start with the vocabulary and structure of Python programs. Be patient
as the simple examples remind you of when you started reading for the first
time.
Words and sentences
Unlike human languages, the Python vocabulary is actually pretty small.
We 3326 call 6471 this 6474 vocabulary the reserved words. These are words that
have very special meaning to Python. When Python sees these words in
a Python program, they have one and only one meaning to Python. Later
as you write programs you will make up your own words that have meaning to
you called variables. You will have great latitude in choosing
your names for your variables, but you cannot use any of Python's
reserved words as a name for a variable.
4048 4312
6832 When we train a dog, we use special words like
sit, stay, and fetch. When you talk to a dog and
don't use any of the reserved words, they just look at you with a
quizzical look on their face until you say a reserved word.
For example, if you say,
I wish more people would walk to improve their overall health,
38 what most dogs likely hear is,
blah blah blah walk blah blah blah blah.
That is because walk is a reserved word in dog language.
The reserved words in the language where humans talk to
Python include the following:
and del from not while
as elif global or with
assert else if pass yield
break except import print
class exec in raise
continue finally is return
def for lambda try
That is it, and unlike a dog, Python is already completely trained.
When you say try, Python will try every time you say it without
fail.
We will learn these reserved words and how they are used in good time,
but for now we will focus on the Python equivalent of speak (in
human-to-dog language). The nice thing about telling Python to speak
is that we can even tell it what to say by giving it a message in quotes:
4985 And we have even written our first syntactically correct Python sentence.
Our sentence starts with the reserved word print followed
by a string of text of our choosing enclosed in single quotes.
Conversing with Python
Now that we have a word and a simple sentence that we know in Python,
we need to know how to start a conversation with Python to test
our new language skills.
6012 Before you can converse with Python, you must first install the Python 8762
software on your computer and learn how to start Python on your
computer. That is too much detail for this chapter so I suggest
that you consult www.py4e.com where I have detailed
instructions and screencasts of setting up and starting Python
on Macintosh and Windows systems. At some point, you will be in
a terminal or command window and you will type python and
725 the Python interpreter will start executing in interactive mode
and appear somewhat as follows:
interactive mode
The >>> prompt is the Python interpreter's way of asking you, What
do you want me to do next? Python is ready to have a conversation with
you. All you have to know is how to speak the Python language.
Let's say for example that you did not know even the simplest Python language
5359 words or sentences. You might want to use the standard line that astronauts 789
use when they land on a faraway planet and try to speak with the inhabitants
of the planet:
This is not going so well. Unless you think of something quickly,
the inhabitants of the planet are likely to stab you with their spears,
put you on a spit, roast you over a fire, and eat you for dinner.
At this point, you should also realize that while Python
is amazingly complex and powerful and very picky about
the syntax you use to communicate with it, Python is
not intelligent. You are really just having a conversation
with yourself, but using proper syntax.
In a sense, when you use a program written by someone else
the conversation is between you and those other
programmers with Python acting as an intermediary. Python
is a way for the creators of programs to express how the
conversation is supposed to proceed. And
in just a few more chapters, you will be one of those
programmers using Python to talk to the users of your program.
832 Before we leave our first conversation with the Python 5931
interpreter, you should probably know the proper way
to 8584 say 3859 good-bye 6794 when interacting with the inhabitants
of Planet Python:
You will notice that the error is different for the first two
incorrect attempts. The second error is different because
if is a reserved word and Python saw the reserved word
and 2490 thought 1925 we 3795 were trying to say something but got the syntax
of the sentence wrong.
7 4068
Terminology: interpreter and compiler
Python is a high-level language intended to be relatively
straightforward for humans to read and write and for computers
to read and process. Other high-level languages include Java, C++,
PHP, Ruby, Basic, Perl, JavaScript, and many more. The actual hardware
inside the Central Processing Unit (CPU) does not understand any
of these high-level languages.
The CPU understands a language we call machine language. Machine
language is very simple and frankly very tiresome to write because it
is represented all in zeros and ones.
Machine language seems quite simple on the surface, given that there
are only zeros and ones, but its syntax is even more complex
and far more intricate than Python. So very few programmers ever write
machine language. Instead we build various translators to allow
programmers 4204 to 3095 write 9829 in high-level languages like Python or JavaScript
and these translators convert the programs to machine language for actual
execution by the CPU.
Since machine language is tied to the computer hardware, machine language
is not portable across different types of hardware. Programs written in
high-level languages can be moved between different computers by using a
different interpreter on the new machine or recompiling the code to create
a machine language version of the program for the new machine.
These programming language translators fall into two general categories:
(one) interpreters and (two) compilers.
An interpreter reads the source code of the program as written by the
programmer, parses the source code, and interprets the instructions on the fly.
Python is an interpreter and when we are running Python interactively,
we can type a line of Python (a sentence) and Python processes it immediately
and is ready for us to type another line of Python.
Some of the lines of Python tell Python that you want it to remember some
value for later. We need to pick a name for that value to be remembered and
8524 we can use that symbolic name to retrieve the value later. We use the 4897
term variable to refer to the labels we use to refer to this stored data.
In this example, we ask Python to remember the value six and use the label x
so we can retrieve the value later. We verify that Python has actually remembered
2443 the value using x and multiply
5923 it by seven and put the newly computed value in y. Then we ask Python to print out 2213
the value currently in y.
Even though we are typing these commands into Python one line at a time, Python
is treating them as an ordered sequence of statements with later statements able
to retrieve data created in earlier statements. We are writing our first
simple paragraph with four sentences in a logical and meaningful order.
It is the nature of an interpreter to be able to have an interactive conversation
as shown above. A compiler needs to be handed the entire program in a file, and then
it runs a process to translate the high-level source code into machine language
and then the compiler puts the resulting machine language into a file for later
execution.
If you have a Windows system, often these executable machine language programs have a
suffix of .exe or .dll which stand for executable and dynamic link
library respectively. In Linux and Macintosh, there is no suffix that uniquely marks
a file as executable.
If you were to open an executable file in a text editor, it would look
completely crazy and be unreadable:
It is not easy to read or write machine language, so it is nice that we have
compilers that allow us to write in high-level
languages like Python or C.
Now at this point in our discussion of compilers and interpreters, you should
be wondering a bit about the Python interpreter itself. What language is
it written in? Is it written in a compiled language? When we type
python, what exactly is happening?
The Python interpreter is written in a high-level language called C.
You can look at the actual source code for the Python interpreter by
going to www.python.org and working your way to their source code.
So Python is a program itself and it is compiled into machine code.
When you installed Python on your computer (or the vendor installed it),
you copied a machine-code copy of the translated Python program onto your
2127 system. In Windows, the executable machine code for Python itself is likely 6790
in a file.
That is more than you really need to know to be a Python programmer, but
sometimes it pays to answer those little nagging questions right at
the beginning.
Writing a program
Typing commands into the Python interpreter is a great way to experiment
with Python's features, but it is not recommended for solving more complex problems.
When we want to write a program,
we use a text editor to write the Python instructions into a file,
which is called a script. By
convention, Python scripts have names that end with .py.
script
2449 8830 5326
To execute the script, you have to tell the Python interpreter
the name of the file. In a Unix or Windows command window,
you would type python hello.py as follows:
We call the Python interpreter and tell it to read its source code from
the file hello.py instead of prompting us for lines of Python code
574 7924 1550
You will notice that there was no need to have quit() at the end of
the Python program in the file. When Python is reading your source code
from a file, it knows to stop when it reaches the end of the file.
What is a program?
The definition of a program at its most basic is a sequence
of Python statements that have been crafted to do something.
Even our simple hello.py script is a program. It is a one-line
program and is not particularly useful, but in the strictest definition,
it is a Python program.
It might be easiest to understand what a program is by thinking about a problem
that a program might be built to solve, and then looking at a program
that would solve that problem.
Lets say you are doing Social Computing research on Facebook posts and
you are interested in the most frequently used word in a series of posts.
You could print out the stream of Facebook posts and pore over the text
looking for the most common word, but that would take a long time and be very
mistake prone. You would be smart to write a Python program to handle the
task quickly and accurately so you can spend the weekend doing something
fun.
For example, look at the following text about a clown and a car. Look at the
text and figure out the most common word and how many times it occurs.
Then imagine that you are doing this task looking at millions of lines of
text. Frankly it would be quicker for you to learn Python and write a
Python program to count the words than it would be to manually
scan the words.
The even better news is that I already came up with a simple program to
find the most common word in a text file. I wrote it,
tested it, and now I am giving it to you to use so you can save some time.
You don't even need to know Python to use this program. You will need to get through
Chapter ten of this book to fully understand the awesome Python techniques that were
used to make the program. You are the end user, you simply use the program and marvel
at its cleverness and how it saved you so much manual effort.
You simply type the code
into a file called words.py and run it or you download the source
code from http://www.py4e.com/code3/ and run it.
This is a good example of how Python and the Python language are acting as an intermediary
between you (the end user) and me (the programmer). Python is a way for us to exchange useful
instruction sequences (i.e., programs) in a common language that can be used by anyone who
installs Python on their computer. So neither of us are talking to Python,
instead we are communicating with each other through Python.
The building blocks of programs
In the next few chapters, we will learn more about the vocabulary, sentence structure,
paragraph structure, and story structure of Python. We will learn about the powerful
capabilities of Python and how to compose those capabilities together to create useful
programs.
There are some low-level conceptual patterns that we use to construct programs. These
constructs are not just for Python programs, they are part of every programming language
from machine language up to the high-level languages.
description
Get data from the outside world. This might be
reading data from a file, or even some kind of sensor like
a microphone or GPS. In our initial programs, our input will come from the user
typing data on the keyboard.
Display the results of the program on a screen
or store them in a file or perhaps write them to a device like a
speaker to play music or speak text.
Perform statements one after
another in the order they are encountered in the script.
Check for certain conditions and
then execute or skip a sequence of statements.
Perform some set of statements
repeatedly, usually with
some variation.
Write a set of instructions once and give them a name
and then reuse those instructions as needed throughout your program.
description
It sounds almost too simple to be true, and of course it is never
so simple. It is like saying that walking is simply
putting one foot in front of the other. The art
of writing a program is composing and weaving these
basic elements together many times over to produce something
that is useful to its users.
The word counting program above directly uses all of
these patterns except for one.
What could possibly go wrong?
As we saw in our earliest conversations with Python, we must
communicate very precisely when we write Python code. The smallest
deviation or mistake will cause Python to give up looking at your
program.
Beginning programmers often take the fact that Python leaves no
room for errors as evidence that Python is mean, hateful, and cruel.
While Python seems to like everyone else, Python knows them
personally and holds a grudge against them. Because of this grudge,
Python takes our perfectly written programs and rejects them as
unfit just to torment us.
There is little to be gained by arguing with Python. It is just a tool.
It has no emotions and it is happy and ready to serve you whenever you
need it. Its error messages sound harsh, but they are just Python's
call for help. It has looked at what you typed, and it simply cannot
understand what you have entered.
Python is much more like a dog, loving you unconditionally, having a few
key words that it understands, looking you with a sweet look on its
face (>>>), and waiting for you to say something it understands.
When Python says SyntaxError: invalid syntax, it is simply wagging
its tail and saying, You seemed to say something but I just don't
understand what you meant, but please keep talking to me (>>>).
As your programs become increasingly sophisticated, you will encounter three
general types of errors:
description
These are the first errors you will make and the easiest
to fix. A syntax error means that you have violated the grammar rules of Python.
Python does its best to point right at the line and character where
it noticed it was confused. The only tricky bit of syntax errors is that sometimes
the mistake that needs fixing is actually earlier in the program than where Python
noticed it was confused. So the line and character that Python indicates in
a syntax error may just be a starting point for your investigation.
A logic error is when your program has good syntax but there is a mistake
in the order of the statements or perhaps a mistake in how the statements relate to one another.
A good example of a logic error might be, take a drink from your water bottle, put it
in your backpack, walk to the library, and then put the top back on the bottle.
A semantic error is when your description of the steps to take
is syntactically perfect and in the right order, but there is simply a mistake in
the program. The program is perfectly correct but it does not do what
you intended for it to do. A simple example would
be if you were giving a person directions to a restaurant and said, ...when you reach
the intersection with the gas station, turn left and go one mile and the restaurant
is a red building on your left. Your friend is very late and calls you to tell you that
they are on a farm and walking around behind a barn, with no sign of a restaurant.
Then you say did you turn left or right at the gas station? and
they say, I followed your directions perfectly, I have
them written down, it says turn left and go one mile at the gas station. Then you say,
I am very sorry, because while my instructions were syntactically correct, they
sadly contained a small but undetected semantic error..
description
Again in all three types of errors, Python is merely trying its hardest to
do exactly what you have asked.
The learning journey
As you progress through the rest of the book, don't be afraid if the concepts
don't seem to fit together well the first time. When you were learning to speak,
it was not a problem for your first few years that you just made cute gurgling noises.
And it was OK if it took six months for you to move from simple vocabulary to
simple sentences and took five or six more years to move from sentences to paragraphs, and a
few more years to be able to write an interesting complete short story on your own.
We want you to learn Python much more rapidly, so we teach it all at the same time
over the next few chapters.
But it is like learning a new language that takes time to absorb and understand
before it feels natural.
That leads to some confusion as we visit and revisit
topics to try to get you to see the big picture while we are defining the tiny
fragments that make up that big picture. While the book is written linearly, and
if you are taking a course it will progress in a linear fashion, don't hesitate
to be very nonlinear in how you approach the material. Look forwards and backwards
and read with a light touch. By skimming more advanced material without
fully understanding the details, you can get a better understanding of the why?
of programming. By reviewing previous material and even redoing earlier
exercises, you will realize that you actually learned a lot of material even
if the material you are currently staring at seems a bit impenetrable.
Usually when you are learning your first programming language, there are a few
wonderful Ah Hah! moments where you can look up from pounding away at some rock
with a hammer and chisel and step away and see that you are indeed building
a beautiful sculpture.
If something seems particularly hard, there is usually no value in staying up all
night and staring at it. Take a break, take a nap, have a snack, explain what you
are having a problem with to someone (or perhaps your dog), and then come back to it with
fresh eyes. I assure you that once you learn the programming concepts in the book
you will look back and see that it was all really easy and elegant and it simply
took you a bit of time to absorb it.
42
The end

re.findall() returns a list (even if it only has one element), so your lst is not a list of digit strings, but a list of lists. That's the problem. (Then when you look for ' ', you are searching in a list, not in a string.)

list.append() is not the issue. The issue is what's being appended.
As already stated here, re.findall returns a list for each row of text in the file.
The list can be empty, or contain one or more strings.
If there is no digit, from \d+ or [0-9]+, in line, [] is returned, not ' ' or [' '] or [''].
It is preferred to open files using with, so they are then closed. handle = open(name) requires manually closing the file.
Iterate through each list returned by re.findall
There's no need to check if the list is empty ([]) because iterating through an empty list doesn't enter the for-loop (e.g. try for v in []: print('test'))
Convert the values to int, and append.
# 1.
with open('test.txt') as f:
values = list()
for line in f:
v = re.findall(r'\d+', line)
# 2.
for num in v:
# 3.
values.append(int(num))
total = sum(values)
With a list-comprehension
Get a list of numbers using a double list comprehension
This is the same as the for-loop
with open('test.txt') as f:
values = [int(num) for line in f for num in re.findall(r'\d+', line)]
total = sum(values)
Get a list of lists of numbers (no empty lists)
This uses an assignment expression (:=) and requires python >= 3.8
An if condition is used to prevent empty lists from being included
with open('test.txt') as f:
values = [list(map(int, v)) for line in f if (v := re.findall(r'\d+', line))]
f.read()
As shown in Reading and Writing Files, .read can be used to read the buffer.
with open('test.txt') as f:
values = list(map(int, re.findall(r'\d+', f.read())))
total = sum(values)

Related

So question.
I have a TCL program that is calling a .py program and working as expected. But the problem is when the full TCL code is run (normal run takes about 3-4 hours), it takes 12-15 hours to run with python (and it is doing nothing difficult or special). I noticed that when TCL calls the python script, it does not create a .pyc file. However, when I call the same python script that TCL calls from another python script, I get better performance and a .pyc refresh.
Just curious if TCL-to-Python is limited in this way. If I need to extend the functionality of my TCL, am I better off using a compiled language such as Java or C?
Edit:
I moved to a team that uses off the shelf product written in TCL. The software technically works, but it is a maintenance nightmare. Tens of thousands of lines of code in a single file. All global variables, no parameters. Almost no documentation. All tests, even syntax adjustments, take at least 3 hours. One errant keystroke can cost you have a workday. And to top it off, the consultant that wrote it all has left.
What I was attempting to do is extend the software in strategic places while I attempt to make it more maintainable. Python and TCL seem to work together, which is why I made this attempt. But this has made me wonder if something like C or Java would be a better try.
I was attempting to write code that I can run and test independently (utilizing MongoDB as the data source) and then plug it in. Like I said before, it functionally works. The loop I was testing looped about 230,000 times, so that is why the 10 hour increase I'm sure.
I just come out of a 4 year stint in C#, so that is where my most recent experience lies. I'm a noob in Python. There is very little out there regarding TCL-to-C# plug-ins, besides something known as Eclipse that someone wrote years ago.

I am developing a small program which I want to give to my younger friends to introduce them to the bare minimum basics of programming using Python.
In it, I want to add functionality to output the line of code that is being executed, as it is being executed, to the console (or as a variable within Python that can be printed using suitable commands).
I want this so that users of this program may learn better by understanding the underlying process that is going on real time, at the higher level (programming language execution).
I thought this would be possible especially because Python is an interpreter language, so the code is playing part until the penultimate step of executing it.
Is there any way to do this intrinsically? If not, I think there should be a way to write a program that will​ take another program as input and execute while also having access to source code. With some advanced parsing, that kind of design will be able to achieve this, but I'm looking for preferably a more natural way to do this.

This may not be perfect to teach using but surely exec would work?
As in:
mycommand = "a = 5**3"
print(mycommand)
exec(mycommand)
print("a = "+str(a))

I am trying to make a Apple Siri-like application in python in which you give it vocal commands or questions through a microphone, it determines the text version of the inputted audio, and then determines the appropriate action to take based on the meaning of the command/question. I am going to be using the Speech Recognition library to accept microphone input and convert from speech to text (via the IBM Watson Speech to Text API).
The main problem I have with it right now is that when I define an action for the app to execute when the appropriate command is given/question is asked, I don't know how to determine if the said command/question is denoting that action. Let me clarify what I mean by that with an example:
Say we have a action called hello. There are multiple ways for somebody to say "hello" to another person (or in this case, my application), such as:
"Hello"
"Hi"
"Howdy"
...Etcetera...
Of course, I want all of these ways of saying "hello" to be classified under the action of hello. That is, when someone says "hello", "hi", or "howdy", the response for the action hello should be executed (most likely just the app saying "hello" back in this case).
My first thought on how to solve this was to supply the app with all of or the most common ways to say a certain command/question. So, if I follow the previous example, I would tell the computer that "hello", "hi", and "howdy" all meant the same thing: the hello action. However, this method has a couple flaws. First off, it simply wouldn't understand ways of saying "hello" that weren't hardcoded in, such as "hey". Second off, once the responses for new commands/questions start getting coded in, it would become very tedious entering all the ways to say a certain phrase.
So then, because of the aforementioned problems, I started looking into ways to calculate the similarities between a group of sentences, and a single query. I eventually came across the Gensim library for python. I looked into it and found some very promising information on complex processes such as latent semantic indexing/analysis (LSI/LSA) and Tf-idf. However, it seemed to me like these things were mainly for comparing documents with large word counts as they rely on the frequency of certain terms. Assuming this is true, these processes wouldn't really provide me with accurate results as the commands/questions given to my app will probably be about eight words on average. I could be completely wrong, after all I know very little about these processes.
I also discovered WordNet, and how to work with it in python using the Natural Language Toolkit (NLTK). It looks like it could be useful, but I'm not sure how.
So, finally, I guess my real question here is what would be the best solution to the problem I've mentioned? Should I use one of the methods I've mentioned? Or is there a better way to do what I want that I don't know about?
Any help at all would be greatly appreciated. Thanks in advance.
P.S. Sorry for the wordy explanation; I wanted to be sure I was clear :P

This is a hard problem. It is also the subject of Task 11 of this year's set of Semantic evaluation challenges (Semeval 2017). So take a look at the task description, which will give you a road map for how this problem can be solved. The task also comes with a suite of training data, which is essential for approaching a problem like this. The challenge is still ongoing, but eventually you'll be able to learn from the solutions as well.
So the short answer to "how do I determine if some command/question is denoting a certain action" is: Use the training data from Semeval2017 (or your own of course), and write a classifier. The nltk book can help you get up to speed with writing classifiers.

So, I am completely new to programming. I've been learning basic Python over the last couple weeks. I've always wanted to learn a programming language but right now my primary reason for delving into it is to Create an AI program for my man cave. Here are my Ideas which I am sure have been thought of many times before. They are just my goals:
I would like to take a pre-established open source chat bot and tie it to a Natural Language process to give it the ability to convert my speech to a text command that it can execute and at the same time take its text output and filter it through an audible speech sample (very much like SIRI). This way when I have the function of Natural Language response on, I can have basic conversations with it. I can also turn the conversational aspect off via a voice command so that the only thing it responds to is direct commands (e.g. "Gerard, please open an email, execute. Recipient, logan.wolf.ypher#gmail.com, Subject, Hello World, Body, insert text i speak.)
I would also like to have it recognize that I am there when my phone attempts to connect to the wifi.
I know that this may be a bit complicated for me at the moment but I hear the best way to learn a language is to jump on into a project you enjoy.
Does anyone have any pointers on where to start looking for a base AI or just any tips in general that you wish to give me? I'd appreciate the info very much. Thank you.
-Logan

Considering that So, I am completely new to programming, I would recommend you take a smaller part of this project and successfully implement it. For example, an email account which is checked every 1 minute and you can send textual commands to it. From there, start upgrading it to use chat, cell phone, speech-to-text, and lastly, AI. I only say this because I know the diffulculty of starting a too-ambitious project when I am new at an area (electronics, engineering, programming, language, etc...) and fail. Success, even in small steps, is better!

I've successfully written a Powershell script which:
query AD to obtain the list of computer
query every computer through WMI to obtain software/hardware information
insert the collected data into a MySQL database.
The script works fine but I don't like how it's implemented. It's procedural and there is a lot of code duplication, causing a mess everytime I need to change something.
Now, what I would like to ask you is: what is the cleanest way to implement it in python using OOP? I've thought something similar to this (pseudocode):
Class ADquery
function get_computers( UO ): return a list of computers in the specified UO
Class Computer
constructor( computername )
function query(): connect to the computer and pull the info through WMI
function print(): print the collected info to the console (debug)
property RAM
property CPU
...
Questions:
In order to save the collected data into a Database, do I have to create another object (e.g. Database) and pass the Computer object to him or add a member function to the Computer class (e.g. save_db() ) ?
If I go for the second option, that wouldn't cause a massive number of MySQL connections when I'm dealing with multiple objects?
Thanks a lot and sorry for my bad English

That architecture looks reasonable to me.
You could do either, I'm not sure it really makes a huge difference with a small application like this.
Potentially. Depending on how it's implemented you could get a lot of connections going on. If you're doing a reasonable number of inserts I'd stick them in a list and insert all at once, if that's possible with your code.

You could also grab an Object Oriented Design book from the internet or your local bookstore, e.g. Rumbaugh et al.. I would also recommend reading up on Design Patterns, e.g. the book by Gamma et. al.. I'm currently doing that, and it is really helpful to look at standard patterns of how to solve a particular problem to shape your thought process about object oriented programming.
ps Your English isn't bad at all (note that I'm also not a native speaker ;)).