Carnets vs Python Recipes Pro

Jupyter notebooks are a powerful tool used in education and research. You can write small snippets of Python code and observe the result on screen, combine with paragraphs of text, using Markdown. Carnets provides a complete, stand-alone, implementation of Jupyter notebooks. Everything runs on your device, using the embedded Python interpreter; you do not need an internet connection. Compared to the standard version (Carnets), this app adds several packages targeted for scientific computation and learning: scipy, sklearn, seaborn and coremltools. You can switch between standard notebooks and the more modern jupyterlab using the Settings app. Of course, all the packages included with the standard app are present too: numpy, simply, matplotlib... To see the full list of installed packages, type "%pip list" in a code window. You can add more packages using "%pip install packageName", but only if they are pure Python. You can share your notebooks with other apps and also open notebooks or directories managed by other apps. Partial list of installed packages: astropy, babel, bokeh, cartopy, cryptography, cvxopt, Fiona, geopandas, geopy, gym, inequality, libpysal, lxml, mapclassify, matplotlib, networkx, nltk, numpy, openCV, pandas, parso, pillow, pyFFTW, pyproj, qutip, rasterio, regex, Rtree, scikit-learn, scipy, seaborn, segregation, shapely, soupsieve, spopt, statsmodels, sympy, wordcloud.

An everyday Python reference, from strings and collections to threading and design patterns. Every example comes with an explanation, and most of them run. The construct is on the tip of your tongue, but the exact syntax slips away: • How do you sort a dictionary by value? • How do you serialize a class to JSON and read it back? • How do you start a thread and wait for the result? The app answers with a working example; all that is left is to fit it to your task. • 22 sections: basic types, arrays and collections, classes, files, serialization, functions and lambdas, exceptions, regular expressions, threading, databases, algorithms, design patterns. • Run in the app: the example actually runs and the output appears under the code. Needs an internet connection; the daily limit is 30 runs. • What changed in new versions: 8 sections from Python 3.0 to 3.13, with the old and the new code side by side. • Keyword and function reference: over 200 articles, browsable as a list or searchable by word. • SQL alongside: over 200 queries against a live practice database (JOIN, GROUP BY, subqueries, data types). Queries have their own daily limit. • Edit examples and add your own; they stay in the app and are always at hand. • Search looks inside the code itself, not just the titles: remember a fragment and you will find the example. • Everything except running works offline: examples, search, favorites. • Comfortable to read: light and dark themes, your own font and size, line numbers, and long lines wrap instead of spilling off the screen. Examples are drawn from professional sources and verified by running them. Built by a developer for developers. In active development since 2015.