I could not understand the ipython library. This url provide the common feature but I could not core-relate it. http://ipython.org/ipython-doc/stable/interactive/tutorial.html
How to I use IPython to improve my day to day python application experience?
ipython is an improved interactive prompt, not a library. It has features like tab completion and profiles which are not present in the vanilla interactive prompt (which is running python without an input file). All features are listed on the page you cited.
So, it doesn't really improve your day to day python application experience (whatever that means), but it does provide benefits during development.
Also, there is an alternative, called bpython, it has quite great features, too.
do you do any scientific computing? ipython 0.12 has new functionality called ipython notebook that's really useful for data analysis. you can easily print graphs and data inline in your browser and reload your code. You can then print it as a pdf and make a nice report.
it's also useful for learning python due to ipython's functionality. you can quickly test and understand how certain functions operate. A few particularly useful functionality aside from tab completion
object?? gives you more information about the object
%history gives you a list of all your previous commands
%debug if you hit an error, this will put you into the debugger so you can quickly debug
Related
Running on Mac Sierra, the autocompletion in Spyder (from Anaconda distribution), seems quite erratic. When used from the Ipython console, works as expected. However, when used from the editor (which is my main way of writing), is erratic. The autocompletion works (i.e. when pressing TAB a little box appears showing options) for some modules, such as pandas or matplotlib. So writing 'pd.' and hitting TAB, gets the box with options as expected. However, this does not happen with many other objects: for example, after defining a dataframe named 'df', typing 'df.' TAB shows nothing. In the Ipython console, 'df.' TAB would show the available procedures for that dataframe, such as groupby, and also its columns, etc..
So the question is threefold. First, is there any particular configuration that should be enabled to get this to work? I don't think so, given some time spent googling, but just wanna make sure. Second, could someone state what is the official word on what works and what doesn't in terms of autocompletion (e.g. what particular modules do work from the editor, and which ones doesn't?). Finally, what are the technical aspects of the differences between the editor and the Ipython console in the performance of the autocompletion with Spyder? I read something about Jedi vs. PsychoPy modules, so got curious (however, please keep in mind that although I have scientific experience, I am relatively new to computation, so please keep it reasonably simple for an educated but not expert person).
UPDATE: As a side question, it would be great to know why is the autocompletion better in Rodeo (another IDE). It is more new, has way fewer overall options than Spyder, but the autocompletion works perfectly in the editor.
(Spyder developer here)
My answers:
is there any particular configuration that should be enabled to get this to work?
In Spyder 3.1 we added the numpydoc library to improve completions of some objects (like Matplotlib figures and NumPy arrays). If Dataframe completions are not working for you (they are for me), please open an issue in our issue tracker on Github to track and solve this problem.
could someone state what is the official word on what works and what doesn't in terms of autocompletion (e.g. what particular modules do work from the editor, and which ones doesn't?)
The most difficult part is getting completions of definitions when an object is generated by functions or methods developed in C/C++/Fortran and not in Python. I mean, things like
import numpy as np
a = np.array([])
a.<TAB>
As I said, this should be working now for arrays, figures and dataframes, but it doesn't work for all libraries (and most scientific Python libraries are created in C/C++/Fortran and wrapped in Python for speed).
The problem is that the completion libraries we use (Rope and Jedi) can't deal with this case very well because array (for example) can't be introspected in a static way (i.e. without running code involving it). So we have to resort to tricks like analyzing array's docstring to see its return type and introspect that instead.
what are the technical aspects of the differences between the editor and the Ipython console in the performance of the autocompletion with Spyder?
The most important difference is that in the IPython console you have to run your code before getting completions about it. For example, please run this in a fresh IPython console
In [1]: import pandas as pd
...: df = pd.Da<Tab>
and you will see that it won't return you any completions for Da (when it obviously should return Dataframe).
But, after evaluation, it is quite simple to get completions. You can simply run
dir(pd)
to get them (that's what IPython essentially does internally).
On the other hand, Spyder's Editor doesn't have a console to run code into, so it has to get completions by running static analysis tools in your code (like Jedi and Rope). As I said, they introspect your code without running it. While they work very well for pure Python code, they have the problems I described above for compiled libraries.
And trying to evaluate the code you have in the Editor to get completions is usually not a good idea because:
It is not necessarily valid Python code all the time. For example, suppose you left an unclosed parenthesis somewhere, but you want to get completions at some other point. That should work without problems, right?
It could involve a very costly computation (e.g. loading a huge CSV in a Dataframe), so evaluating it every time to get completions (and that's a must because your code is different every time you ask for completions) could consume all your RAM in a blink.
it would be great to know why is the autocompletion better in Rodeo (another IDE)
Last time I checked (a couple of years ago), Rodeo evaluated your code to get completions. However, we'll take a look at what they are doing now to see if we can improve our completion machinery.
Autocompletion works correctly if there are NO white spaces in the project working directory path.
Autocomplete was not working for me at all.
So, I tried Tools -> Reset Sypder to factory defaults and it worked.
I am new to python. I have a very basic question. Is there a way I can execute part of a python program? ie some thing similar to Matlab where after running the code once, I can execute parts of the program
If you want something similar to Matlab, check out ipython - it comes with the goodness of python with a workflow similar to Matlab.
ipython has the concept of Notebooks which are composed of cells. These cells can be executed individually giving you the behavior you expect.
What you are looking for is called "cell" execution in MATLAB.
The Spyder python editor is in general a good approximation of MATLAB-style IDE for python. It supports executing the full script, the selected lines or a "cell" that is defined by a portion of code stating with a comment like
# %%
or
###
To get Spyder I suggest to install a scientific python distribution such as Anaconda or WinPython.
Alternatively, as pointed out by vikramls, you can embrace a more modern paradigm, convert your script to an ipython notebook and get "cell" execution for free.
PS The ipython notebook is a fantastic environment that allow to mix rich text, code and plots in a single document that is great for some workflows. On the other hand Spyder provides some unique features such as graphical variable inspector (a-la MATLAB), integrated HTML documentation and code error analysis not available in the notebook.
I use Notepad++ for writing and running Python scripts. It is a great text editor, except for debugging. Is there a way to step through the code, use break points, view variable values etc. in Notepad++ like you can in Visual Studio?
Does such a plug-in exist? Not that I know of. I agree completely with qor72 on that note.
Is it possible to create such a plugin / functionality? Possibly.
After doing some quick digging, I did find a plugin that looks promising, Python Script. In short it allows you to run python scripts that can access the NPP modules (file menus etc...) as well as the Scintilla Methods which appear to give access to things like the markers on the pages.
To accomplish such a feat I could see the task being broken into a few large blocks (I feel a new open-source project coming on...)
Using Python Script, integrate the python debugger(PDB) as mentioned by Shashi.
Using the Scintilla Methods, add trace back calls where a NPP marker is placed
Redirect PDB outputs and process them to show where the file is stopped (again using the Scintilla methods).
While at the newly created breakpoint and using PDB determine all of the variables in the current namespace. Take this info and dump it to a CMD window, or if you want to get fancy some GUI created with Tk / wxPython
Closing Thoughts
While I think it's possible to create such a plug in, it would be quite an undertaking. Along that line, you might be better off trying to find a different editor that has this built into it already and just create macros (or whatever the IDE calls them) to add in the things you like most about NPP.
Please note that I am a daily user of NPP and have been for many years so I definitely understand why you'd like to have the functionally added to NPP. One of my favorite things about NPP is the speed in which it opens and searches files... moving to a bloated IDE, IMO, would not be worth it to me.
My current work flow is to do all of my editing in NPP and just double click to run the modules. If it fails or goes off in the weeds, I launch IDLE to debug it.
I really hope someone tells me I'm wrong (I'd love to have that feature in Notepad++) but, Notepad++ is designed as a programmers editor, not an IDE. While it has a lot of cool functionality, that level of debugging isn't part of the core tool.
Not seeing anything in the npp-plugins either.
I think python debugger
is the best option if editor is not providing facility :)
Quick guide:
from pdb import set_trace as bp
code
code
bp()
code
code
At the (Pdb) prompt, enter s to step, p foo to print foo, and c to continue executing the code until hitting another breakpoint.
Have you thought of using Komodo.
It's open source and has ports for Windows, Linux and MAC (I think).
This may be an alternative, and if you want some advice from notepad++ users, have a look at the following post on this very site:
Komodo Edit and Notepad++ ::: Pros & Cons ::: Python dev
Some npp users here seemed to have made the switch for python editing running etc...
personally don't know much about debugging on Komodo but as it's an IDE so would be surprised if you couldn't do it easily
I don't really see why Shashi's answer hasn't been upvoted. For the link that he has given supplies a way to step through python scripts as the OP has requested.
So for all who don't know about the pdb module, upon importing it the pdb.set_trace() function allows one to step through the area of code after it. And it is very much similar to the visual studios method of debugging. While you're stepping through the code you are able to input a variety of commands.
One of them is p <expression> and that allows the user to print the current state of variables within the local and global scope.
I know it's 11 years on, and I'm a bit late to the game, and I know it's not Notepad++ but please do consider Visual Studio Code.
It's free, easy to install (both the editor itself plus any python interpreters it uses) and it's widely used and nowhere near as bloated as it's Visual Studio counterpart. It also appears to be the IDE of choice for a lot of Cisco-related course material.
Write your code, click to the left of code pane to insert your breakpoints click the Debugger icon (highlighted), and you're away:
What does ipython have that bpython lacks and vice versa? How do the two differ?
If you just want an interactive interpreter, bpython should be fine. Just use it until you miss some feature you liked about IPython.
There are lots of features that IPython offers over bpython:
Special threading options. I like -gthread for experimenting with PyGTK and -pylab for matplotlib.
direct invocation of shell commands. cd in IPython is quite useful.
Full readline library support -- I can use the keyboard shortcuts I am used to.
Module reload facility - You can do a deep reload of a module after you have changed your code. This is very useful for testing and debugging.
Run functions in the background in a separate task with %bg.
A whole parallel programming environment (not really a feature you expect from an interactive Python shell, but IPython offers it).
This list could be nearly arbitrarily continued. And of course there will be lots of features in bpython lacking from IPython, but you did not ask for those.
So just use the one that works for you!
IPython Notebook (since 0.12) is a killer feature.
I'm new to Python, with a background in statically typed languages including lots and lots of Java.
I decided on PyDev in eclipse as an IDE after checking features/popularity etc.
I was stunned that auto-complete doesn't seem to work properly for builtins. For example if I try automcomplete on datafile after:
datafile = open(directory+"/"+account, 'r')
datafile.
No useful methods are suggested (e.g. realines). Only things like call.
I am used to learning a language by jumping into class definitions and using lots of auto-complete to quickly view what a class will do. My PyDev 'interpreter' is set up fine with 'forced builtins'.
Is it possible to get auto-complete for builtins with PyDev? Am I approaching the IDE wrong, i.e. should have an interpreter running on the side and test stuff with it? So far the IDEs have seemed weak, e.g. IDLE segfaulted on my new mac after 2 minutes. I'd love to know what experienced Python developers do when exploring unfamiliar (builtin) modules, as this is making me reconsider my initial attraction to Python. I like a language you can learn by easy exploration!
Thanks,
In my opinion, the Python shell is a much better place to explore new modules than relying on an IDE. Don't forget, in Python you can do anything in the shell that you can do in a program, because there's no separate compilation step. And in the shell, you can use dir(x) to find all the properties and methods of x, whether x is a module, a class, or whatever.
Even better, the enhanced iPython shell does provide tab completion for all objects.
In fact because of this, many Python programmers - myself included - don't use an IDE at all, but just a simple text editor (I use VIM).
Just to keep it up to date so that new readers are not confused about the current state of Pydev - the example you gave now works in Pydev. (btw, one should avoid operating on paths manualy - use os.path.join instead)
I'd love to know what experienced
Python developers do when exploring
unfamiliar (builtin) modules
I use ipython. Ipython is an enhanced version of the interactive shell that adds tab completion and quick access to an object's doctstring. It also gives lots of other features that the standard shell does not have - you can find a summary of its features here.
Someone more knowledgeable here can give you a detailed answer. Here is a short one.
Autocomplete for a dynamically typed language can by nature never be as rich as that for a statically typed language. In the case of open for instance there is no way to figure out what will be the return type at the time of writing the code. The method signature does not include a return type unlike a statically typed language like Java. Consequently the IDE is not able to give you any hints.
You certainly should have an REPL running during any Python development. One advantage of an interpreted language is that you can test small chunks of your code on the REPL as you go along. It is also a good place to test your understanding of how built-ins and other modules work.
I work on Ubuntu so I do not know how easy or difficult it is to get IDLE running on a Mac. I usually work with the very handy iPython for REPL needs and use Pydev for other development (such as Django). You might want to give iPython a try.
You want IPython. As Daniel pointed out above, the interactive shell is a much better way to explore Python (and indeed, most other languages too).
This might help with setting it up on OSX.
You might want to take a look at WingIDE. It autocompletes your datafile correctly.
If it is unable to infer the type, you can use an assert like
assert isinstance(datafile, file)
to help the autocompleter out
I use PyDev at work so I know where you're coming from. If you're willing to consider other tools, have a look at JetBrains' PyCharm, that's my new preferred Python IDE for my own projects. No affiliation to speak of except to say I'll be picking it up when it's out of beta. :)