other:python:jyp_steps
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other:python:jyp_steps [2017/03/08 09:48] jypeter Rewrote the netcdf part to add a link to the tuto for new people |
other:python:jyp_steps [2019/05/23 14:41] jypeter [Useful reference pages] Added help for the 'legend' |
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| - [[https://docs.scipy.org/doc/numpy-dev/user/numpy-for-matlab-users.html|Numpy for Matlab users]] | - [[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) | - [[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 really nice [[https://docs.scipy.org/doc/numpy/user/quickstart.html|numpy 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 | ||
| - Numpy User Guide | - Numpy User Guide | ||
| Line 120: | Line 120: | ||
| [20, 21, -1, -1, 24, 25, 26, 27, 28, 29]]) | [20, 21, -1, -1, 24, 25, 26, 27, 28, 29]]) | ||
| </code></note> | </code></note> | ||
| + | |||
| + | ==== Extra numpy information ==== | ||
| + | |||
| + | * More information about array indexing: | ||
| + | * Examples: | ||
| + | * {{ :other:python:indirect_indexing_2.py.txt |}}: Take a vertical slice in a 3D zyx array, along a varying y 'path' | ||
| + | * [[https://docs.scipy.org/doc/numpy/user/basics.indexing.html|Indexing]] (//index arrays//, //boolean index arrays//, //np.newaxis//, //Ellipsis//, //variable numbers of indices//, ...) | ||
| + | * [[https://docs.scipy.org/doc/numpy/user/quickstart.html#fancy-indexing-and-index-tricks|Fancy indexing]] and [[https://docs.scipy.org/doc/numpy/user/quickstart.html#the-ix-function|the ix_() function]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html|Indexing (in the numpy reference manual)]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.indexing.html#routines-indexing|Indexing routines]] | ||
| + | * More information about arrays: | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.array-creation.html#routines-array-creation|Array creation routines]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.array-manipulation.html|Array manipulation routines]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/maskedarray.html|Masked arrays]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.ma.html|Masked array operations]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/user/misc.html#ieee-754-floating-point-special-values|Dealing with special numerical values]] (//Nan//, //inf//) | ||
| + | * If you know that your data has missing values, it is cleaner and safer to handle them with [[https://docs.scipy.org/doc/numpy/reference/maskedarray.html|masked arrays]]! | ||
| + | * [[https://docs.scipy.org/doc/numpy/user/misc.html#how-numpy-handles-numerical-exceptions|Handling numerical exceptions]] | ||
| + | * [[https://docs.scipy.org/doc/numpy/reference/routines.err.html|Floating point error handling]] | ||
| ===== cdms2 and netCDF4 ===== | ===== cdms2 and netCDF4 ===== | ||
| Line 129: | Line 148: | ||
| ==== cdms2 ==== | ==== cdms2 ==== | ||
| - | Summary: cdms2 can read/write netCDF files (and read //grads// dat+ctl files) and provides a higher level interface than netCDF4. Unfortunately, cdms2 is only available in the [[other:python:starting#uv-cdat|UV-CDAT distribution]], and distributions where somebody has installed some version of //cdat-lite//. When you can use cdms2, you also have access to //cdtime//, that is very useful for handling time axis data. | + | Summary: cdms2 can read/write netCDF files (and read //grads// dat+ctl files) and provides a higher level interface than netCDF4. cdms2 is available in the [[other:python:starting#uv-cdat|UV-CDAT distribution]], and can theoretically be installed independently of UV-CDAT (e.g. it will be installed when you install [[https://cmor.llnl.gov/mydoc_cmor3_conda/|CMOR in conda)]]. When you can use cdms2, you also have access to //cdtime//, that is very useful for handling time axis data. |
| How to get started: | How to get started: | ||
| Line 135: | Line 154: | ||
| - the tutorial is in French (soooorry!) | - the tutorial is in French (soooorry!) | ||
| - you have to replace //cdms// with **cdms2**, and //MV// with **MV2** (sooorry about that, the tutorial was written when CDAT was based on //Numeric// instead of //numpy// to handle array data) | - you have to replace //cdms// with **cdms2**, and //MV// with **MV2** (sooorry about that, the tutorial was written when CDAT was based on //Numeric// instead of //numpy// to handle array data) | ||
| - | - read the [[http://uv-cdat.llnl.gov/documentation/cdms/cdms.html|official cdms documentation]] | + | - read the [[http://cdms.readthedocs.io/en/docstanya/index.html|official cdms documentation]] (link may change) |
| - | - ask questions and get answers on the [[http://uvcdat.askbot.com/questions/|UV-CDAT askbot]] | + | |
| ==== netCDF4 ==== | ==== netCDF4 ==== | ||
| - | Summary: netCDF4 can read/write netCDF files and is available in most python distributions | + | Summary: //netCDF4 can read/write netCDF files and is available in most python distributions// |
| Where: [[http://unidata.github.io/netcdf4-python/]] | Where: [[http://unidata.github.io/netcdf4-python/]] | ||
| + | ===== CDAT-related resources ===== | ||
| + | |||
| + | Some links, in case they can't be found easily on the [[https://uv-cdat.llnl.gov|UV-CDAT]] web site... | ||
| + | |||
| + | * [[https://uv-cdat.llnl.gov/tutorials.html|Tutorials in ipython notebooks]] | ||
| + | * [[http://cdat-vcs.readthedocs.io/en/latest/|VCS: Visualization Control System]] | ||
| + | * [[https://github.com/CDAT/vcs/issues/238|Colormaps in vcs examples]] | ||
| + | * [[https://github.com/CDAT/cdat-site/blob/master/eztemplate.md|EzTemplate Documentation]] | ||
| ===== Matplotlib ===== | ===== Matplotlib ===== | ||
| Line 152: | Line 178: | ||
| Where: [[http://matplotlib.org|Matplotlib web site]] | Where: [[http://matplotlib.org|Matplotlib web site]] | ||
| - | The documentation is good, but not always easy to use. A good way to start with matplotlib is to: | + | Help on //stack overflow//: [[https://stackoverflow.com/questions/tagged/matplotlib|matplotlib help]] |
| + | |||
| + | The documentation is good, but not always easy to use. <wrap hi>A good way to start with matplotlib</wrap> is to: | ||
| - Look at the [[http://matplotlib.org/gallery.html|matplotlib gallery]] to get an idea of all you can do with matplotlib. Later, when you need to plot something, come back to the gallery to find some examples that are close to what you need and click on them to get the sources | - Look at the [[http://matplotlib.org/gallery.html|matplotlib gallery]] to get an idea of all you can do with matplotlib. Later, when you need to plot something, come back to the gallery to find some examples that are close to what you need and click on them to get the sources | ||
| - Use the free hints provided by JY! | - Use the free hints provided by JY! | ||
| - a Matplotlib //Figure// is a graphical window in which you make your plots... | - a Matplotlib //Figure// is a graphical window in which you make your plots... | ||
| - a Matplotlib //Axis// is a plot inside a Figure... [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|More details]] | - a Matplotlib //Axis// is a plot inside a Figure... [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|More details]] | ||
| + | - some resources for having multiple plots on the same figure | ||
| + | * [[https://matplotlib.org/gallery/recipes/create_subplots.html#sphx-glr-gallery-recipes-create-subplots-py|Easily creating subplots]] | ||
| + | * [[https://matplotlib.org/gallery/index.html#subplots-axes-and-figures|Subplots, axes and figures]] gallery | ||
| + | * [[https://matplotlib.org/tutorials/intermediate/gridspec.html#sphx-glr-tutorials-intermediate-gridspec-py|Customizing Figure Layouts Using GridSpec and Other Functions]], [[https://matplotlib.org/tutorials/intermediate/constrainedlayout_guide.html|constrained layout]] and [[https://matplotlib.org/tutorials/intermediate/tight_layout_guide.html|tight layout]] | ||
| + | * [[http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure|parts of a figure]] | ||
| - some examples are more //pythonic// (ie object oriented) than others, some example mix different styles of coding, all this can be confusing. Try to [[http://matplotlib.org/faq/usage_faq.html#coding-styles|use an object oriented way of doing things]]! | - some examples are more //pythonic// (ie object oriented) than others, some example mix different styles of coding, all this can be confusing. Try to [[http://matplotlib.org/faq/usage_faq.html#coding-styles|use an object oriented way of doing things]]! | ||
| - | - sometimes the results of the python/matplolib commands are displayed directly, sometimes not. It depends if you are in [[http://matplotlib.org/faq/usage_faq.html#what-is-interactive-mode|interactive or non-interactive]] mode | + | - it may be hard to (remember how to) work with colors. Some examples from the [[http://matplotlib.org/gallery.html|Gallery]] can help you! |
| + | * [[https://matplotlib.org/examples/pylab_examples/leftventricle_bulleye.html|leftventricle_bulleye.py]]: associating different types of colormaps to a plot and colorbar | ||
| + | * [[https://matplotlib.org/examples/api/colorbar_only.html|colorbar_only.py]]: the different types of colorbars (or plotting only a colorbar) | ||
| + | * [[https://matplotlib.org/examples/color/colormaps_reference.html|colormaps_reference.py]]: pre-defined colormaps | ||
| + | * [[https://matplotlib.org/examples/color/named_colors.html|named_colors.py]]: named colors | ||
| + | * More details about the colors below, in the [[#graphics_related_resources|Resources section]] | ||
| + | - sometimes the results of the python/matplolib commands are displayed immediately, sometimes not. It depends if you are in [[http://matplotlib.org/faq/usage_faq.html#what-is-interactive-mode|interactive or non-interactive]] mode | ||
| + | - if your matplotlib is executed in a batch script, it will generate an error when trying to create (''show()'') a plot, because matplotlib expects to be able to display the figure on a screen by default. | ||
| + | * Check how you can [[https://matplotlib.org/faq/howto_faq.html?highlight=web#generate-images-without-having-a-window-appear|generate images offline]] | ||
| - the documentation may mention [[http://matplotlib.org/faq/usage_faq.html#what-is-a-backend|backends]]. What?? Basically, you use python commands to create a plot, and the backend is the //thing// that will render your plot on the screen or in a file (png, pdf, etc...) | - the documentation may mention [[http://matplotlib.org/faq/usage_faq.html#what-is-a-backend|backends]]. What?? Basically, you use python commands to create a plot, and the backend is the //thing// that will render your plot on the screen or in a file (png, pdf, etc...) | ||
| + | - if you don't see a part of what you have plotted, maybe it's hidden behind other elements! Use the [[https://matplotlib.org/examples/pylab_examples/zorder_demo.html|zorder parameter]] to explicitly specify the plotting order/layers | ||
| - Read the [[http://www.labri.fr/perso/nrougier/teaching/matplotlib/|Matplotlib tutorial by Nicolas Rougier]] | - Read the [[http://www.labri.fr/perso/nrougier/teaching/matplotlib/|Matplotlib tutorial by Nicolas Rougier]] | ||
| - Download the [[http://matplotlib.org/contents.html|pdf version of the manual]]. **Do not print** the 2800+ pages of the manual! Read the beginner's guide (Chapter //FIVE// of //Part II//) and have a super quick look at the table of contents of the whole document. | - Download the [[http://matplotlib.org/contents.html|pdf version of the manual]]. **Do not print** the 2800+ pages of the manual! Read the beginner's guide (Chapter //FIVE// of //Part II//) and have a super quick look at the table of contents of the whole document. | ||
| + | |||
| + | ==== Useful reference pages ==== | ||
| + | |||
| + | * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html|plot(...)]]: Plot y versus x as lines and/or markers | ||
| + | * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.scatter.html|scatter(...)]]: A scatter plot of y vs x with varying marker size and/or color | ||
| + | * The ''plot'' function will be faster for scatterplots where markers don't vary in size or color | ||
| + | * [[https://matplotlib.org/api/_as_gen/matplotlib.lines.Line2D.html|line]] parameters | ||
| + | * ''linestyle'': ''solid'', ''None'', [[https://matplotlib.org/api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_linestyle|other]] ([[https://matplotlib.org/examples/lines_bars_and_markers/line_styles_reference.html|default styles example]], [[https://matplotlib.org/examples/lines_bars_and_markers/linestyles.html|custom styles example]]) | ||
| + | * [[https://matplotlib.org/api/markers_api.html|marker types]] | ||
| + | * ''fillstyle'': ''full'', ''None'', [[https://matplotlib.org/gallery/lines_bars_and_markers/marker_fillstyle_reference.html|other]] | ||
| + | * Other attributes: ''markersize'', ''markerfacecolor'' (and ''markerfacecoloralt'' for dual color markers), ''markeredgecolor'', ''markeredgewidth'' | ||
| + | * [[https://matplotlib.org/api/colors_api.html|colors]] | ||
| + | * [[https://matplotlib.org/gallery/color/color_demo.html|color demo]] | ||
| + | * [[https://matplotlib.org/examples/color/named_colors.html|named colors]] | ||
| + | * [[https://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.legend|legend(...)]] ([[https://matplotlib.org/examples/pylab_examples/legend_demo3.html|legend demo]]) | ||
| + | * The legend will //show// the lines (or other objects) that were associated with a //label// with the ''label='' keyword when creating/updating a plot | ||
| + | * If there are some elements of a plot that you do not want to associate with a legend (e.g. there are several lines with the same color and markers, but you want to plot the legend only once), do not specify a ''label='' keyword for these elements, or add a ''_'' at the front of the label strings | ||
| + | * The legend is positioned somewhere (that can be specified) **inside** the plot. In order to place a legend **outside** the plot, use the ''bbox_to_anchor'' parameter | ||
| + | * the parameters of ''bbox_to_anchor'' are in normalized coordinates of the current (sub)plot: | ||
| + | * ''(0, 0)'' is the lower left corner of the plot, and ''(1, 1)'' the upper right corner | ||
| + | * ''legend(... bbox_to_anchor=(1.05, 1.), loc='upper left', ...)'' will put the upper left corner of the legend slightly right (''(1.05, 1.)'') of the upper right corner (''(1, 1)'') of the plot | ||
| + | * if the legend is outside of the plot, you have to **explicitly provide enough space for the legend on the page** | ||
| + | * e.g. with [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots_adjust.html|subplots_adjust]], ''plt.subplots_adjust(right=0.75)'' will make all the plots use 75% on the left of the page, and leave 25% on the right for the legend | ||
| + | |||
| + | ==== Misc Matplotlib tricks ==== | ||
| + | |||
| + | * Specifying the background color of a plot (e.g. when plotting a masked variable and you don't want the masked areas to be white) | ||
| + | * ''# make the background dark gray (call this before the contourf)''\\ ''plt.gca().patch.set_color('.25')''\\ ''plt.contourf(d)''\\ ''plt.show()'' | ||
| + | * [[https://stackoverflow.com/questions/9797520/masking-part-of-a-contourf-plot-in-matplotlib|trick source]] | ||
| + | |||
| + | ===== Graphics related resources ===== | ||
| + | |||
| + | * [[http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003833|Ten Simple Rules for Better Figures]] | ||
| + | * [[https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/|Top 50 matplotlib Visualizations]] | ||
| + | * [[http://seaborn.pydata.org/|Seaborn]] is a library for making attractive and informative statistical graphics in Python, built on top of matplotlib | ||
| + | * See also: [[https://www.datacamp.com/community/tutorials/seaborn-python-tutorial| | ||
| + | Python Seaborn Tutorial For Beginners]] | ||
| + | * Working with colors | ||
| + | * [[https://matplotlib.org/users/colormaps.html|Choosing colormaps]] | ||
| + | * [[https://matplotlib.org/cmocean/|Beautiful colormaps for oceanography: cmocean]] | ||
| + | * [[http://colorbrewer2.org|ColorBrewer 2.0]] is a tool that can help you understand, and experiment with //sequential//, //diverging// and //qualitative// colormaps | ||
| + | |||
| ===== Basemap ===== | ===== Basemap ===== | ||
| - | <note warning>It seems that basemap is going to be slowly phased out, in favor of [[#cartopy]]\\ More information in this [[https://github.com/matplotlib/basemap/issues/267|basemap github issue]] | + | <note warning>Basemap is going to be slowly phased out, in favor of [[#cartopy]]\\ More information in this: |
| + | * [[https://github.com/SciTools/cartopy/issues/920|cartopy github issue]] | ||
| + | * [[https://github.com/matplotlib/basemap/issues/267|basemap github issue]] | ||
| </note> | </note> | ||
| - | Summary: Basemap is an extension of Matplotlib that you can use for plotting maps, using different projections | + | Summary: //Basemap is an extension of Matplotlib that you can use for plotting maps, using different projections// |
| Where: [[http://matplotlib.org/basemap/|Basemap web site]] | Where: [[http://matplotlib.org/basemap/|Basemap web site]] | ||
| + | |||
| + | Help on //stack overflow//: [[https://stackoverflow.com/questions/tagged/matplotlib-basemap|basemap help]] | ||
| How to use basemap? | How to use basemap? | ||
| Line 179: | Line 267: | ||
| - look at the [[http://matplotlib.org/basemap/api/basemap_api.html#module-mpl_toolkits.basemap|detailed official documentation]] | - look at the [[http://matplotlib.org/basemap/api/basemap_api.html#module-mpl_toolkits.basemap|detailed official documentation]] | ||
| - | ===== Cartopy ===== | + | ===== Cartopy + Iris ===== |
| - | Summary: //Cartopy makes use of the powerful PROJ.4, numpy and shapely libraries and has a simple and intuitive drawing interface to matplotlib for creating publication quality maps// | + | Summary: //Cartopy is a Python package for advanced map generation with a simple matplotlib interface// and //Iris is a Python package for analysing and visualising meteorological and oceanographic data sets// |
| - | Where: [[http://scitools.org.uk/cartopy/docs/latest/|Cartopy web site]] | + | Where: [[http://scitools.org.uk/cartopy/docs/latest/|Cartopy]] and [[http://scitools.org.uk/iris/index.html|Iris]] web sites |
| + | Examples: | ||
| + | * [[http://scitools.org.uk/cartopy/docs/latest/gallery.html|Gallery on the Cartopy web site]] | ||
| + | * [[http://scitools.org.uk/iris/docs/latest/gallery.html|Gallery on the Iris web site]] | ||
| + | * [[http://scitools.org.uk/iris/docs/latest/examples/index.html|Examples on the Iris web site]] | ||
| + | |||
| + | Help on //stack overflow//: [[https://stackoverflow.com/questions/tagged/cartopy|cartopy help]] | ||
| + | |||
| + | ===== Maps and projections resources ===== | ||
| + | |||
| + | ==== About projections ==== | ||
| + | |||
| + | * [[https://egsc.usgs.gov/isb//pubs/MapProjections/projections.html|Map projections from USGS poster]] | ||
| + | * [[https://pubs.usgs.gov/pp/1395/report.pdf|Map projections - A working manual (USGS)]] | ||
| + | |||
| + | ==== Libraries ==== | ||
| + | |||
| + | * Projections in vcs | ||
| + | * [[http://matplotlib.org/basemap/users/mapsetup.html|Projections in basemap]] | ||
| + | * [[https://scitools.org.uk/cartopy/docs/latest/crs/projections.html|Projections in cartopy]] | ||
| + | |||
| + | |||
| + | ===== 3D resources ===== | ||
| + | |||
| + | * [[https://ipyvolume.readthedocs.io/en/latest/|Ipyvolume]] | ||
| + | * [[https://zulko.wordpress.com/2012/09/29/animate-your-3d-plots-with-pythons-matplotlib/|Animate your 3D plots with Python’s Matplotlib]] | ||
| + | * [[https://stackoverflow.com/questions/26796997/how-to-get-vertical-z-axis-in-3d-surface-plot-of-matplotlib|How to get vertical Z axis in 3D surface plot of Matplotlib?]] | ||
| + | |||
| + | ===== Data file formats ===== | ||
| + | |||
| + | We list here some resources about non-NetCDF data formats that can be useful | ||
| + | |||
| + | ==== json files ==== | ||
| + | |||
| + | More and more applications use //json files// as configuration files or as a mean to use text files to exchange data (through serialization/deserialization ). | ||
| + | |||
| + | //json// files look basically like a **list of (nested) python dictionaries** that would have been dumped to a text file | ||
| + | |||
| + | * [[https://docs.python.org/2/library/json.html|json module]] documentation | ||
| + | * [[https://realpython.com/python-json/|Working With JSON Data in Python]] tutorial | ||
| + | * example script: ''/home/users/jypeter/CDAT/Progs/Devel/beaugendre/nc2json.py'' | ||
| + | * A compact (not easy to read...) //json// file can be pretty-printed with\\ ''cat file.json | python -m json.tool | less'' | ||
| + | |||
| + | ==== LiPD files ==== | ||
| + | |||
| + | Resources for //Linked PaleoData//: | ||
| + | * [[http://linked.earth/projects/lipd/|LiPD]] | ||
| + | * [[https://doi.org/10.5194/cp-12-1093-2016|Technical note: The Linked Paleo Data framework – | ||
| + | a common tongue for paleoclimatology]] @ GMD | ||
| + | * [[https://github.com/nickmckay/LiPD-utilities|LiPD-utilities]] @ github | ||
| + | |||
| + | ==== BagIt files ==== | ||
| + | |||
| + | //BagIt//, a set of hierarchical file layout conventions for storage and transfer of arbitrary digital content. | ||
| + | |||
| + | * [[https://tools.ietf.org/html/draft-kunze-bagit-16|The BagIt File Packaging Format]] | ||
| + | * [[https://github.com/LibraryOfCongress/bagger|Bagger]] (BagIt GUI) | ||
| + | * [[https://github.com/LibraryOfCongress/bagit-python|bagit-python]] | ||
| ===== Pandas ===== | ===== Pandas ===== | ||
| Line 204: | Line 349: | ||
| This is **a really nice and useful document** that is regularly updated and used for the [[https://www.euroscipy.org/|EuroScipy]] tutorials. You will learn more things about python, numpy and matplotlib, debugging and optimizing scripts, and also learn about using python for statistics, image processing, machine learning, washing dishes (this is just to check if you have read this page), etc... | This is **a really nice and useful document** that is regularly updated and used for the [[https://www.euroscipy.org/|EuroScipy]] tutorials. You will learn more things about python, numpy and matplotlib, debugging and optimizing scripts, and also learn about using python for statistics, image processing, machine learning, washing dishes (this is just to check if you have read this page), etc... | ||
| - | ===== Quick Reference ===== | + | ===== Quick Reference and cheat sheets ===== |
| * The nice and convenient Python 2.7 Quick Reference: [[http://rgruet.free.fr/PQR27/PQR2.7_printing_a4.pdf|pdf]] - [[http://rgruet.free.fr/PQR27/PQR2.7.html|html]] | * The nice and convenient Python 2.7 Quick Reference: [[http://rgruet.free.fr/PQR27/PQR2.7_printing_a4.pdf|pdf]] - [[http://rgruet.free.fr/PQR27/PQR2.7.html|html]] | ||
| + | * A possibly more [[http://iysik.com/PQR2.7/PQR2.7.html|up-date-version]] | ||
| + | * Python 3 [[https://perso.limsi.fr/pointal/python:abrege|Quick reference]] and [[https://perso.limsi.fr/pointal/python:memento|Cheat sheet]] | ||
| + | |||
| + | * [[https://www.cheatography.com/weidadeyue/cheat-sheets/jupyter-notebook/pdf_bw/|Jupyter Notebook Keyboard Shortcuts]] | ||
| + | |||
| + | ===== Misc tutorials ===== | ||
| + | |||
| + | * [[https://pyformat.info/|PyFormat]]: //With this site we try to show you the most common use-cases covered by the old and new style string formatting API with practical examples// | ||
| ===== Some good coding tips ===== | ===== Some good coding tips ===== | ||
| Line 235: | Line 388: | ||
| 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'' | 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'' | ||
| + | |||
| + | ===== Using a Python IDE ===== | ||
| + | |||
| + | **IDE** = //Integrated Development Environment// | ||
| + | |||
| + | There are lots of ways to use Python and develop scripts, from using a lightweight approach (your favorite text editor with builtin python syntax highlighting, e.g. **emacs** and ''python -i myscript.py'') to a full-fledged IDE. You'll find below some IDE related links | ||
| + | |||
| + | * [[https://www.datacamp.com/community/tutorials/data-science-python-ide|Top 5 Python IDEs For Data Science]] | ||
| + | * [[http://noeticforce.com/best-python-ide-for-programmers-windows-and-mac|Python IDE: The10 Best IDEs for Python Programmers]] | ||
| + | * [[https://www.techbeamers.com/best-python-ide-python-programming/|Get the Best Python IDE]] | ||
| + | * [[https://wiki.python.org/moin/IntegratedDevelopmentEnvironments]] | ||
| + | |||
| + | ==== Spyder ==== | ||
| + | |||
| + | * [[https://github.com/spyder-ide/spyder|Home page]] | ||
| + | * [[http://pythonhosted.org/spyder/|Documentation]] | ||
| + | |||
| ===== Improving the performance of your code ===== | ===== Improving the performance of your code ===== | ||
other/python/jyp_steps.txt · Last modified: 2024/03/07 10:15 by jypeter
