other:python:jyp_steps
Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
|
other:python:jyp_steps [2016/01/22 17:02] jypeter More changes |
other:python:jyp_steps [2016/05/20 13:41] jypeter Added a link to 'Working with Python' at the top |
||
|---|---|---|---|
| Line 1: | Line 1: | ||
| - | ====== Following JYP's recommended steps ====== | + | ====== JYP's recommended steps for learning python ====== |
| + | |||
| + | <note tip>If you don't know which python distribution to use and how to start the python interpreter, you should first read the [[starting|Working with Python]] page</note> | ||
| As can be expected, there is **a lot** of online python documentation available, and it's easy to get lost. You can always use google to find an answer to your problem, and you will probably end up looking at lots of answers on [[http://stackoverflow.com/questions/tagged/python|Stack Overflow]] or a similar site. But it's always better to know where you can find some good documentation... and to spend some time to read the documentation | As can be expected, there is **a lot** of online python documentation available, and it's easy to get lost. You can always use google to find an answer to your problem, and you will probably end up looking at lots of answers on [[http://stackoverflow.com/questions/tagged/python|Stack Overflow]] or a similar site. But it's always better to know where you can find some good documentation... and to spend some time to read the documentation | ||
| Line 49: | Line 51: | ||
| Where: [[http://docs.scipy.org/doc/|html and pdf documentation]] | Where: [[http://docs.scipy.org/doc/|html and pdf documentation]] | ||
| - | How to get started? | + | ==== Getting started ==== |
| - always remember that indices start at ''0'' and that the last element of an array is at index ''-1''!\\ First learn about //indexing// and //slicing// by manipulating strings, as shown in [[#part1|Part 1]] above (try '''This document by JY is awesome!'[::-1]'' and '''This document by JY is awesome!'[slice(None, None, -1)]'') 8-) | - always remember that indices start at ''0'' and that the last element of an array is at index ''-1''!\\ First learn about //indexing// and //slicing// by manipulating strings, as shown in [[#part1|Part 1]] above (try '''This document by JY is awesome!'[::-1]'' and '''This document by JY is awesome!'[slice(None, None, -1)]'') 8-) | ||
| + | - if you are a Matlab user (but the references are interesting for others as well), you can read the following: | ||
| + | - [[https://docs.scipy.org/doc/numpy-dev/user/numpy-for-matlab-users.html|Numpy for Matlab users]] | ||
| + | - [[http://mathesaurus.sourceforge.net/matlab-numpy.html|NumPy for MATLAB users]] (nice, but does not seem to be maintained any more) | ||
| - read the [[https://docs.scipy.org/doc/numpy-dev/user/quickstart.html|Quickstart tutorial]] | - read the [[https://docs.scipy.org/doc/numpy-dev/user/quickstart.html|Quickstart tutorial]] | ||
| - have a quick look at the full documentation to know where things are | - have a quick look at the full documentation to know where things are | ||
| Line 56: | Line 62: | ||
| - Numpy Reference Guide | - Numpy Reference Guide | ||
| - Scipy Reference Guide | - Scipy Reference Guide | ||
| + | |||
| + | ==== Beware of the array view side effects ==== | ||
| + | |||
| + | <note warning>When you take a slice of an array, you get a **//View//** : an array that has a new shape but that still shares its data with the first array. | ||
| + | |||
| + | That is not a problem when you only read the values, but **if you change the values of the //View//, you change the values of the first array** (and vice-versa)! If that is not what want, do not forget to **make a copy** of the data before working on it! | ||
| + | |||
| + | //Views// are a good thing most of the time, so only make a copy of your data when needed, because otherwise copying a big array will just be a waste of CPU and computer memory. Anyway, it is always better to understand what you are doing... :-P | ||
| + | |||
| + | Check the example below and the [[https://docs.scipy.org/doc/numpy-dev/user/quickstart.html#copies-and-views|copies and views]] part of the quickstart tutorial. | ||
| + | |||
| + | <code python> | ||
| + | >>> import numpy as np | ||
| + | >>> a = np.arange(30).reshape((3,10)) | ||
| + | >>> a | ||
| + | array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], | ||
| + | [10, 11, 12, 13, 14, 15, 16, 17, 18, 19], | ||
| + | [20, 21, 22, 23, 24, 25, 26, 27, 28, 29]]) | ||
| + | |||
| + | >>> b = a[1, :] | ||
| + | >>> b | ||
| + | array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19]) | ||
| + | |||
| + | >>> b[3:7] = 0 | ||
| + | >>> b | ||
| + | array([10, 11, 12, 0, 0, 0, 0, 17, 18, 19]) | ||
| + | |||
| + | >>> a | ||
| + | array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], | ||
| + | [10, 11, 12, 0, 0, 0, 0, 17, 18, 19], | ||
| + | [20, 21, 22, 23, 24, 25, 26, 27, 28, 29]]) | ||
| + | |||
| + | >>> a[:, 2:4] = -1 | ||
| + | >>> a | ||
| + | array([[ 0, 1, -1, -1, 4, 5, 6, 7, 8, 9], | ||
| + | [10, 11, -1, -1, 0, 0, 0, 17, 18, 19], | ||
| + | [20, 21, -1, -1, 24, 25, 26, 27, 28, 29]]) | ||
| + | |||
| + | >>> b | ||
| + | array([10, 11, -1, -1, 0, 0, 0, 17, 18, 19]) | ||
| + | |||
| + | >>> c = a[1, :].copy() | ||
| + | >>> c | ||
| + | array([10, 11, -1, -1, 0, 0, 0, 17, 18, 19]) | ||
| + | |||
| + | >>> c[:] = 9 | ||
| + | >>> c | ||
| + | array([9, 9, 9, 9, 9, 9, 9, 9, 9, 9]) | ||
| + | |||
| + | >>> b | ||
| + | array([10, 11, -1, -1, 0, 0, 0, 17, 18, 19]) | ||
| + | |||
| + | >>> a | ||
| + | array([[ 0, 1, -1, -1, 4, 5, 6, 7, 8, 9], | ||
| + | [10, 11, -1, -1, 0, 0, 0, 17, 18, 19], | ||
| + | [20, 21, -1, -1, 24, 25, 26, 27, 28, 29]]) | ||
| + | </code></note> | ||
| ===== cdms2 and netCDF4 ===== | ===== cdms2 and netCDF4 ===== | ||
| Line 128: | Line 191: | ||
| * [[http://blog.codinghorror.com/a-pragmatic-quick-reference/|A Pragmatic Quick Reference]] | * [[http://blog.codinghorror.com/a-pragmatic-quick-reference/|A Pragmatic Quick Reference]] | ||
| + | |||
| + | ===== Debugging your code ===== | ||
| + | |||
| + | There is only so much you can do with staring at your code in your favorite text editor, and adding ''print'' lines in your code (or using [[https://docs.python.org/2/howto/logging.html#logging-basic-tutorial|logging]] instead of ''print''). The next step is to **use the python debugger**! | ||
| + | |||
| + | ==== Debugging in text mode ==== | ||
| + | |||
| + | - Start the script with: ''python -m pdb my_script.py'' | ||
| + | - Type ''run'' (or **r**) to go to the first line of the script | ||
| + | - Type ''continue'' (or **c**) to execute the script to the end, or till the first breakpoint or error is reached | ||
| + | - Use ''where'' (or **w**) to check the call stack that led to the current stop. Use ''up'' and ''down'' to navigate through the call stack and examine the values of the functions' parameters | ||
| + | - Type ''break NNN'' to stop at line NNN | ||
| + | - Use ''type(var)'' and ''print var'' to check the type and values of variables. You can also change the variables' values on the fly! | ||
| + | - Type ''run'' (or **r**) to restart the script | ||
| + | - Use ''next'' and ''step'' to execute some parts of the script line by line. If a code line calls a function: | ||
| + | * ''next'' (or **n**) will execute a function and stop on the next line | ||
| + | * ''step'' (or **s**) will stop at the first line **inside the function** | ||
| + | - Check the [[https://docs.python.org/2/library/pdb.html#debugger-commands|debugger commands]] for details, or type ''help'' in the debugger for using the built-in help | ||
| + | |||
| + | ==== Using pydebug ==== | ||
| + | |||
| + | Depending on the distribution, the editor and the programming environment you use, you may have access to a graphical version of the debugger. UV-CDAT users can use ''pydebug my_script.py'' | ||
| ===== Improving the performance of your code ===== | ===== Improving the performance of your code ===== | ||
| Line 135: | Line 220: | ||
| * **make sure that your script is not using too much memory** (the amount depends on the computer you are using)! Your script should be scalable (e.g. keeps on working even when your data gets bigger), so it's a good idea to load only the data you need in memory (e.g. not all the time steps), and learn how to load chunks of data | * **make sure that your script is not using too much memory** (the amount depends on the computer you are using)! Your script should be scalable (e.g. keeps on working even when your data gets bigger), so it's a good idea to load only the data you need in memory (e.g. not all the time steps), and learn how to load chunks of data | ||
| - | * **make sure that you are using array/vector syntax and masks**, instead of using explicit loops and tests. The numpy documentation is big, because there are lots of optimized functions to help you! If you are stuck, ask JY or somebody else who is used to numpy. | + | * **make sure that you are using array/vector syntax and masks**, instead of using explicit loops and tests. The [[#numpy_and_scipy|numpy documentation]] is big, because there are lots of optimized functions to help you! If you are stuck, ask JY or somebody else who is used to numpy. |
| If your script is still not fast enough, there is a lot you can do to improve it, without resorting to parallelization (that may introduce extra bugs rather that extra performance). See the sections below | If your script is still not fast enough, there is a lot you can do to improve it, without resorting to parallelization (that may introduce extra bugs rather that extra performance). See the sections below | ||
| Hint: before optimizing your script, you should spent some time //profiling// it, in order to only spend time improving the slow parts of your script | Hint: before optimizing your script, you should spent some time //profiling// it, in order to only spend time improving the slow parts of your script | ||
| + | |||
| + | ==== Useful packages ==== | ||
| + | |||
| + | * [[https://github.com/pydata/numexpr|Numexpr]]: //Numexpr is a **fast numerical expression evaluator for NumPy**. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python.// | ||
| + | * [[http://www.pytables.org/|PyTables]]: //PyTables is a package for managing hierarchical datasets and designed to efficiently and **easily cope with extremely large amounts of data**// | ||
| ==== Tutorials by Ian Osvald ==== | ==== Tutorials by Ian Osvald ==== | ||
| Line 149: | Line 239: | ||
| The official [[https://docs.python.org/2.7/howto/pyporting.html|Porting Python 2 Code to Python 3]] page gives the required information to make the transition from python 2 to python 3. It is still safe to use Python 2.7, so there is no rush to change to Python 3. | The official [[https://docs.python.org/2.7/howto/pyporting.html|Porting Python 2 Code to Python 3]] page gives the required information to make the transition from python 2 to python 3. It is still safe to use Python 2.7, so there is no rush to change to Python 3. | ||
| + | |||
| + | ===== What now? ===== | ||
| + | |||
| + | You can do a lot more with python! But if you have read at least a part of this page, you should be able to find and use the modules you need. Make sure you do not reinvent the wheel! Use existing packages when possible, and make sure to report bugs or errors in the documentations when you find some | ||
| /* standard page footer */ | /* standard page footer */ | ||
other/python/jyp_steps.txt · Last modified: 2024/03/07 10:15 by jypeter
