Carnets vs Pyremto

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. You can chose between Jupyter notebooks and the more advance Jupyterlab using Settings. Numpy, Sympy, Matplotlib, Pandas, lxml, bokeh, nbextensions (including ipywidgets) and many other packages are pre-installed. 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. If you need scipy, seaborn or scikit-learn, please use our other App, "Carnets - Jupyter (with scipy)". 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, cryptography, cvxopt, Fiona, geopandas, geopy, lxml, matplotlib, numpy, openCV, pandas, pillow, pyFFTW, pyproj, rasterio, regex, shapely, sympy, wordcloud.

Use the Pypy package "pyremto" to log values to your smartphone, send inputs back to the Python script, and receive downtime alerts if your script stops running. The following use cases are supported: - Downtime Alert: Setup a downtime alert and get notified when your python script stops working / is not executed in the desired frequency. Either receive a push notification or check the status of your script in the app. - Log to your smartphone: Log values from your python script directly to the pyremto app. You can also log datapoints, which are displayed as a graph. - Remote Control: Let your python script ask for inputs after logging some values. Enter your commands in the pyremto app and send them back to your python script. - Job Scheduling: Create a list of jobs, which should be executed on your servers / multiple computers. The job scheduling is done automatically on a job-to-job basis. This maximizes the resource usage without planning the job distribution ahead. See the job progress in the pyremto app. More info at https://www.pyremto.com/ - you can find code examples at https://github.com/MatthiasKi/pyremto