When I first started reading about Python, all of the tutorials have you use Python's Interactive Mode. It is difficult to save, write long programs, or edit your existing lines (for me at least). It seems like a far more difficult way of writing Python code than opening up a code.py file and running the interpreter on that file.
python code.py
I am coming from a Java background, so I have ingrained expectations of writing and compiling files for programs. I also know that a feature would not be so prominent in Python documentation if it were not somehow useful. So what am I missing?
Let's see:
If you want to know how something works, you can just try it. There is no need to write up a file. I almost always scratch write my programs in the interpreter before coding them. It's not just for things that you don't know how they work in the programming language. I never remember what the correct arguments to range are to create, for example, [-2, -1, 0, 1]. I don't need to. I just have to fire up the interpreter and try stuff until I figure out it is range(-2, 2) (did that just now, actually).
You can use it as a calculator.
Python is a very introspective programming language. If you want to know anything about an object, you can just do dir(object). If you use IPython, you can even do object.<TAB> and it will tab-complete the methods and attributes of that object. That's way faster than looking stuff up in documentation or even in code.
help(anything) for documentation. It's way faster than any web interface.
Again, you have to use IPython (highly recommended), but you can time stuff. %timeit func1() and %timeit func2() is a common idiom to determine what is faster.
How often have you wanted to write a program to use once, and then never again. The fastest way to do this is to just do it in the Python interpreter. Sure, you have to be careful writing loops or functions (they must have the correct syntax the first time), but most stuff is just line by line, and you can play around with it.
Debugging. You don't need to put selective print statements in code to see what variables are when you write it in the interpreter. You just have to type >>> a, and it will show what a is. Nice again to see if you constructed something correctly. The building Python debugger pdb also uses the intrepeter functionality, so you can not only see what a variable is when debugging, but you can also manipulate or even change it without halting debugging.
When people say that Python is faster to develop in, I guarantee that this is a big part of what they are talking about.
Commenters: anything I am forgetting?
REPL Loops (like Python's interactive mode) provide immediate feedback to the programmer. As such, you can rapidly write and test small pieces of code, and assemble those pieces into a larger program.
You're talking about running Python in the console by simply typing "python"? That's just for little tests and for practicing with the language. It's very useful when learning the language and testing out other modules.
Of course any real software project is written in .py files and later executed by the interpreter!
The Python interpreter is a least common denominator: you can run it on multiple platforms, and it acts the same way (modulo platform-specific modules), so it's pretty easy to get a newbie going with.
It's a lot easier to tell a newbie to launch the interpreter and "do this" than to have them open a file, type in some code, save it, make it executable, make sure python is in your PATH, or use a #! line, etc etc. Scrap all of that and just launch the interpreter. For simple examples, you can't beat it. It was never meant for long programs, so if you were using it for that, you probably missed the part of the tutorial that told you "longer scripts go in a file". :)
you use the interactive interpreter to test snippets of your code before you put them into your script.
As already mentioned, the Python interactive interpreter gives a quick and dirty way to test simple Python functions and/or code snippets.
I personally use the Python shell as a very quick way to perform simple Numerical operations (provided by the math module). I have my environment setup, so that the math module is automatically imported whenever I start a Python shell. In fact, its a good way to "market" Python to non-Pythoniasts. Show them how they can use Python as a neat scientific calculator, and for simple mathematical prototyping.
One thing I use interactive mode for that others haven't mentioned: To see if a module is installed. Just fire up Python and try to import the module; if it dies, then your PYTHONPATH is broke or the module is not installed.
This is a great first step for "Hey, it's not working on my machine" or "Which Python did that get installed in, anyway" bugs.
I find the interactive interpreter very, very good for testing quick code, or to show others the Power of Python. Sometimes I use the interpreter as a handy calculator, too. It's amazing what you can do in a very short amount of time.
Aside from the built-in console, I also have to recommend Pyshell. It has auto-completion, and a decent syntax highlighting. You can also edit multiple lines of code at once. Of course, it's not perfect, but certainly better than the default python console.
When coding in Java, you almost always will have the API open in some browser window. However with the python interpreter, you can always import any module that you are thinking about using and check what it offers. You can also test the behavior of new methods that you are unsure of, to eliminate the "Oh! so THAT's how it works" as a source of bugs.
Interactive mode makes it easy to test code snippets before incorporating them into a larger program. If you use IDLE there's syntax highlighting and argument pop-ups to help you out. It's also a quick way of checking that you've figured out how to use a module without having to write a test program.
Related
I am wrting a Python application for the first time and I am using Pycharm as the slected IDE. One thing that I notice I can;t see all classses and methods for the object I am using. I have coded with intelligIdea to code Scala and Java as well. They are easier to code since code intelligence is really handy but In Python it is not convineit..
suppose I am writing
divs=innerTree.cssselect('div.story-body__inner')
when I write innerTree. Pycharm doesnt suggest cssseelct while I used to write Scala/Java with the same Idea, they suggested all available accesible classes.
Is thet any problem with my IDEA?
There are a few of possible reasons:
innerTree doesn't actually have a cssselect method. Seems obvious, but this one catches me out more often than I'd like to admit.
PyCharm doesn't know what innerTree is an instance of.
You need to clear PyCharm's cache and restart. Which is pretty much the "have you tried turning it off and on again?" of PyCharm.
Side note, you can also use IntelliJ to do everything that PyCharm does. It's a bit harder to set up, but it's easier that switching back and forth i.m.o.
I have been programming with Python for some time and noticed that it's possible to interact, for example, with MS Excel files through the library XLWT.
Now I would like to know if it's possible to use Python to control other applications, such as the Calculator.exe which is on the standard Windows path C:\Windows\system32.
Is there any way to write a script with Python, let's say, to make the calculator opening and executing 9+3=? I usually like to write some code myself first and ask for help later, but here I've no clue even if it's possible and my researches on Internet have yield only this script to launch the program:
import subprocess
subprocess.call("C:\Windows\system32\calc.exe")
Any help, suggestion or even just "no, it's not possible" would be highly appreciated.
It will always depend on the cooperativity of the other program. If it allows being tweaked, it will offer an API for this (and hopefully a documentation telling you how to use it).
This is not really a Python question because it rather depends on how the API is written. If this API comes as a C library, you will have to write at least a bit of C code to access it via Python. If it is a way of calling the program (special options, etc.) then Python will have as much or less trouble providing these as any other programming language.
Is there any existing python code obfuscating tool for Python3?
Please do not try to teach me that Python isn't the right choice if I want to hide/obfuscate my code. Or that correct licenses should protect the code instead of obfuscation...
Update: This question does not duplicate issue How do I protect Python code?: I simply ask if there is a tool to obfuscate Python. Nothing more and nothing less. (If there is none I wonder why I get so much feedback...)
No matter what you do, at some point the Python interpreter is going to be reading in unobfuscated Python byte-code. From that it is dead easy to get back to your source code (minus comments and non-obvious layout). This is why everybody says it's pretty much impossible to obfuscate Python. The fact that it's pretty much impossible to obfuscate Python implies that there are no good tools for doing so. I'm afraid it's just wishful thinking to say "I know this can't be done very effectively, but are there any tools for doing it?"
Probably the best you can do will be to encrypt your code with standard encryption tools, and write a little wrapper program in some other language that just decrypts your Python and runs your program, then deletes the unencrypted code when it's done. If you want to put way too much effort in you could probably do something with the C API and embedding the Python interpreter in a C program to feed your unencrypted Python to the interpreter only in memory, rather than files on disk.
Note that these schemes will still be relatively easy to get around, and don't work at all if what you want is to provide importable Python modules (rather than whole programs). Which is why I wouldn't expect to find anyone's already written a tool for you to do it.
I wouldn't go the obfuscating approach if I were you and rather investigate alternative ways to ship executable binary files instead of (byte)-code.
Tools that are known to me (there are probably a few others):
http://www.ohloh.net/p/py2c (converts Python into C code which you can then compile)
http://www.pyinstaller.org/
http://cx-freeze.sourceforge.net/
http://www.py2exe.org/ (Windows only)
http://svn.pythonmac.org/py2app/py2app/trunk/doc/index.html (Mac only)
I don't know how hack-proof any of those tools are, but I think it's worth taking a look.
Edit: Damnit, missed the Python 3 part. It's a little hard to help because you don't write anything about the product itself (OS, GUI, etc). If it can be also Python 2 code but you have written all your code in Python 3 already, I suggest 3to2.
I'd recommend using pyarmor.
It converts code to binary form. Only drawback would be, you need to obfuscate code for every OS separately.
There is no way to obfuscate Python code in any useful manner, and no reason why you would want to. You seem to want to obfuscate the code to protect it. That is completely pointless, as you can instead ship only the .pyc files, meaning you don't ship the source code at all. Not that shipping only .pyc files will help you, as there are uncompilers for .pyc-files.
If your program is reasonably simple and well-coded, creating executables with cx-freeze, py2exe et al, means that the .pyc files end up inside the executable file, and hence are marginally harder to find, and it's also less obvious that you use Python, so that might be help. But more importantly, it might make installation simpler for your users. They like that.
If you really want to obfuscate your code in a useful way, convert all of it to use Cython, which will create C-files you can compile. This will also speed up the program. Cython is however not fully Python compatible, so you will probably have to make changes.
And I know you don't want to hear this, but I'll say it for the benefit of others:
All of this is of course stupid and misguided. Open source is good for you. Really. You shouldn't protect your code, you should get as many eyes and hands on it as possible.
Trust me on this: Your main worry should be about getting more users, not less pirates. And you get more users by making your software better, not worse. And open source will help in that.
Pyminifier is a Python code minifier, obfuscator, and compressor.
This tool works on Python 3
Update: This project has been discontinued.
The best way to hide your code is to not release it.
Advertise a service - you receive their data then return the processed data. Transmissions can be via the web, email, DHL, pigeon, telephone, graviton pulse, ...
I am basically from the world of C language programming, now delving into the world of scripting languages like Ruby and Python.
I am wondering how to do debugging.
At present the steps I follow is,
I complete a large script,
Comment everything but the portion I
want to check
Execute the script
Though it works, I am not able to debug like how I would do in, say, a VC++ environment or something like that.
My question is, is there any better way of debugging?
Note: I guess it may be a repeated question, if so, please point me to the answer.
Your sequence seems entirely backwards to me. Here's how I do it:
I write a test for the functionality I want.
I start writing the script, executing bits and verifying test results.
I review what I'd done to document and publish.
Specifically, I execute before I complete. It's way too late by then.
There are debuggers, of course, but with good tests and good design, I've almost never needed one.
Here's a screencast on ruby debugging with ruby-debug.
Seems like the problem here is that your environment (Visual Studio) doesn't support these languages, not that these languages don't support debuggers in general.
Perl, Python, and Ruby all have fully-featured debuggers; you can find other IDEs that help you, too. For Ruby, there's RubyMine; for Perl, there's Komodo. And that's just off the top of my head.
There is a nice gentle introduction to the Python debugger here
If you're working with Python then you can find a list of debugging tools here to which I just want to add Eclipse with the Pydev extension, which makes working with breakpoints etc. also very simple.
My question is, is there any better way of debugging?"
Yes.
Your approach, "1. I complete a large script, 2. Comment everything but the portion I want to check, 3. Execute the script" is not really the best way to write any software in any language (sorry, but that's the truth.)
Do not write a large anything. Ever.
Do this.
Decompose your problem into classes of objects.
For each class, write the class by
2a. Outline the class, focus on the external interface, not the implementation details.
2b. Write tests to prove that interface works.
2c. Run the tests. They'll fail, since you only outlined the class.
2d. Fix the class until it passes the test.
2e. At some points, you'll realize your class designs aren't optimal. Refactor your design, assuring your tests still pass.
Now, write your final script. It should be short. All the classes have already been tested.
3a. Outline the script. Indeed, you can usually write the script.
3b. Write some test cases that prove the script works.
3c. Runt the tests. They may pass. You're done.
3d. If the tests don't pass, fix things until they do.
Write many small things. It works out much better in the long run that writing a large thing and commenting parts of it out.
Script languages have no differences compared with other languages in the sense that you still have to break your problems into manageable pieces -- that is, functions. So, instead of testing the whole script after finishing the whole script, I prefer to test those small functions before integrating them. TDD always helps.
There's a SO question on Ruby IDEs here - and searching for "ruby IDE" offers more.
I complete a large script
That's what caught my eye: "complete", to me, means "done", "finished", "released". Whether or not you write tests before writing the functions that pass them, or whether or not you write tests at all (and I recommend that you do) you should not be writing code that can't be run (which is a test in itself) until it's become large. Ruby and Python offer a multitude of ways to write small, individually-testable (or executable) pieces of code, so that you don't have to wait for (?) days before you can run the thing.
I'm building a (Ruby) database translation/transformation script at the moment - it's up to about 1000 lines and still not done. I seldom go more than 5 minutes without running it, or at least running the part on which I'm working. When it breaks (I'm not perfect, it breaks a lot ;-p) I know where the problem must be - in the code I wrote in the last 5 minutes. Progress is pretty fast.
I'm not asserting that IDEs/debuggers have no place: some problems don't surface until a large body of code is released: it can be really useful on occasion to drop the whole thing into a debugging environment to find out what is going on. When third-party libraries and frameworks are involved it can be extremely useful to debug into their code to locate problems (which are usually - but not always - related to faulty understanding of the library function).
You can debug your Python scripts using the included pdb module. If you want a visual debugger, you can download winpdb - don't be put off by that "win" prefix, winpdb is cross-platform.
The debugging method you described is perfect for a static language like C++, but given that the language is so different, the coding methods are similarly different. One of the big very important things in a dynamic language such as Python or Ruby is the interactive toplevel (what you get by typing, say python on the command line). This means that running a part of your program is very easy.
Even if you've written a large program before testing (which is a bad idea), it is hopefully separated into many functions. So, open up your interactive toplevel, do an import thing (for whatever thing happens to be) and then you can easily start testing your functions one by one, just calling them on the toplevel.
Of course, for a more mature project, you probably want to write out an actual test suite, and most languages have a method to do that (in Python, this is doctest and nose, don't know about other languages). At first, though, when you're writing something not particularly formal, just remember a few simple rules of debugging dynamic languages:
Start small. Don't write large programs and test them. Test each function as you write it, at least cursorily.
Use the toplevel. Running small pieces of code in a language like Python is extremely lightweight: fire up the toplevel and run it. Compare with writing a complete program and the compile-running it in, say, C++. Use that fact that you can quickly change the correctness of any function.
Debuggers are handy. But often, so are print statements. If you're only running a single function, debugging with print statements isn't that inconvenient, and also frees you from dragging along an IDE.
There's a lot of good advice here, i recommend going through some best practices:
http://github.com/edgecase/ruby_koans
http://blog.rubybestpractices.com/
http://on-ruby.blogspot.com/2009/01/ruby-best-practices-mini-interview-2.html
(and read Greg Brown's book, it's superb)
You talk about large scripts. A lot of my workflow is working out logic in irb or the python shell, then capturing them into a cascade of small, single-task focused methods, with appropriate tests (not 100% coverage, more focus on edge and corner cases).
http://binstock.blogspot.com/2008/04/perfecting-oos-small-classes-and-short.html
Since Python is a dynamic, interpreted language you don't have to compile your code before running it. Hence, it's very easy to simply write your code, run it, see what problems occur, and fix them. Using hotkeys or macros can make this incredibly quick.
So, because it's so easy to immediately see the output of your program and any errors that may occur, I haven't uses a debugger tool yet. What situations may call for using a real debugger vs. the method I currently use?
I'd like to know before I get into a situation and get frustrated because I don't know how to fix the problem.
In 30 years of programming I've used a debugger exactly 4 times. All four times were to read the core file produced from a C program crashing to locate the traceback information that's buried in there.
I don't think debuggers help much, even in compiled languages. Many people like debuggers, there are some reasons for using them, I'm sure, or people wouldn't lavish such love and care on them.
Here's the point -- software is knowledge capture.
Yes, it does have to run. More importantly, however, software has meaning.
This is not an indictment of your use of a debugger. However, I find that the folks who rely on debugging will sometimes produce really odd-looking code and won't have a good justification for what it means. They can only say "it may be a hack, but it works."
My suggestion on debuggers is "don't bother".
"But, what if I'm totally stumped?" you ask, "should I learn the debugger then?" Totally stumped by what? The language? Python's too simple for utter befuddlement. Some library? Perhaps.
Here's what you do -- with or without a debugger.
You have the source, read it.
You write small tests to exercise the library. Using the interactive shell, if possible. [All the really good libraries seem to show their features using the interactive Python mode -- I strive for this level of tight, clear simplicity.]
You have the source, add print functions.
I use pdb for basic python debugging. Some of the situations I use it are:
When you have a loop iterating over 100,000 entries and want to break at a specific point, it becomes really helpful.(conditional breaks)
Trace the control flow of someone else's code.
Its always better to use a debugger than litter the code with prints.
Normally there can be more than one point of failures resulting in a bug, all are not obvious in the first look. So you look for obvious places, if nothing is wrong there, you move ahead and add some more prints.. debugger can save you time here, you dont need to add the print and run again.
Usually when the error is buried in some function, but I don't know exactly what or where. Either I insert dozens of log.debug() calls and then have to take them back out, or just put in:
import pdb
pdb.set_trace ()
and then run the program. The debugger will launch when it reaches that point and give me a full REPL to poke around in.
Any time you want to inspect the contents of variables that may have caused the error. The only way you can do that is to stop execution and take a look at the stack.
pydev in Eclipse is a pretty good IDE if you are looking for one.
I find it very useful to drop into a debugger in a failing test case.
I add import pdb; pdb.set_trace() just before the failure point of the test. The test runs, building up a potentially quite large context (e.g. importing a database fixture or constructing an HTTP request). When the test reaches the pdb.set_trace() line, it drops into the interactive debugger and I can inspect the context in which the failure occurs with the usual pdb commands looking for clues as to the cause.
You might want to take a look at this other SO post:
Why is debugging better in an IDE?
It's directly relevant to what you're asking about.