Allows to temporarily modify the power management settings on a MacOS to run processes uninterruptedly.
espressomaker is a Python 3 module that provides a context manager, among other functionalities, to modify the power management settings on a MacOS X system so that lengthy tasks (e.g. a machine learning training algorithm) can run uninterruptedly — without your Mac going to sleep.
espressomaker is a wrapper of
caffeinate, a shell command in MacOS X distributions that allows users to alter the system's sleep behavior. In this sense,
caffeinate subprocesses from the Python 3 interpreter or the IPython kernel from where it was imported and allows to control your Mac's sleep settings through a simple and intuitive set of Python commands.
- 1. Quick Start
- 2. Purpose
- 3. Installation
- 4. User guide
1. Quick Start
espressomaker, run the following on your Terminal:
$ pip install espressomaker
espressomaker as a context manager for a block of code, run on a Python 3 interpreter or an IPython kernel:
from espressomaker import Espresso with Espresso.shot(): function_1() function_2() ...
The indented code will be run using the context manager of
Espresso.shot(). While this code is running, your Mac won't go to sleep.
espressomaker provides a Python 3 module that prevents your Mac from sleep when you are running lengthy tasks — blocks of code that take a long time to finish.
Many applications that run on Python may take hours to finish, like machine learning training algorithms. If a task is actively running on a Python 3 interpreter — e.g. a Python script — or an iPython kernel — e.g. a Jupyter notebook — and the system goes to sleep, the running processes will be interrupted and all the progress related to that block of code will be lost.
To avoid that,
espressomaker provides a handful of functionalities, including a useful context manager to run blocks of code. The context manager functionality, provided in
Espresso — a module of
espressomaker —, will allow you to temporarily change the power management settings of your Mac while the indented block of code is running. Once the task is done, the settings will return to its default state.
espressomakeris a package that intends to facilitate dealing with lengthy Python tasks such that the user can, in a single line of code, forget about dealing with interrupted processes.
espressomaker, run on your terminal:
$ pip install espressomaker
You can find the package's PyPI link here.
The installation process using
pip should be uneventful. After the installation, the package should be located at:
/Users/<your_username>/.local/lib/pythonX.Y/site-packages/, if you use
pipas the default package manager; or,
/Users/<your_username>/anaconda3/lib/pythonX.Y/site-packages/, if you use
condaas a package manager;
where X.Y is your current Python version (root environment). You can check if these directories are considered by Python's system's path by running:
import sys sys.path
However, if when importing a
ModuleNotFoundError occurs, it could be possible that your current interpreter/kernel is not including the directory where
espressomaker is installed at. Although this is unlikely, you can find the current location of the package by running on your Terminal:
$ find /Users/ -type d -name 'espressomaker' 2>/dev/null | grep ".*python.*"
The previous command will search for a folder called
espressomaker in the
Users/ directory and only print the matches that belong to a
python subdirectory. If the directory found is not on
sys.path, you can manually add it to Python's path using:
4. User guide
4.1 Working principle
Espresso module from
espressomaker allows you to run
caffeinate subprocesses — child processes of your current Python interpreter or IPython kernel.
caffeinate is a shell command available on MacOS distributions that allows to modify the power management settings of your system by creating assertions. In this context,
caffeinate is used to prevent your MacOS system from sleeping while a task is being computed.
Espresso module offers two ways to run
- As a context manager for a task — a block of code —, using the
- As a manual method call, using the
closetab()methods (i.e. the user defines when to start running the subprocess and when to finish it).
In either way, your Mac will not sleep until the task is completed — when using the context manager mode — or until you manually close the tab.
4.2 Importing the module
To import the functionalities of
espressomaker to Python, run:
from espressomaker import Espresso
4.3 Default settings
Espresso module has two class-level settings:
verbose parameter enables messages related to the status of the module when using the
shot() context manager. The
display_on parameter determines whether the display of your Mac will remain on (if
display_on = True) or if it will turn off (
display_on = False) as per the current settings of your Mac.
The default class-level settings can be retrieved using
>>> Espresso.config() Espresso(verbose = True, display_on = False)
To change these class-level settings — to set new default settings —, just pass in the parameters you want to change into
>>> Espresso.config(display_on = True) Espresso(verbose = True, display_on = True)
For safety reasons,
espressomaker only works when your Mac is connected to AC power — it will not work if you are using battery power.
4.4 Using the context manager —
One of the main advantages of the
Espresso module is that it allows to run a task — a block of code — using a context manager. The context manager enables the
caffeinate functionality — instantiates the subprocess — for the code inside it and then closes the process — kills the subprocess.
To use it, run:
>>> with Espresso.shot(display_on = True): ... function_1() ... function_2() ...
As shown above, you can always override the
display_on default settings by passing in a new value for that argument, which will only work for that instance call.
4.5 Manually opening and closing tabs —
Espresso also provides a manual way to instantiate a "caffeinate" subprocess in the current interpreter or kernel. The
closetab() methods allow you to instantiate and kill the
caffeinate subprocess, respectively.
>>> Espresso.opentab() [espressomaker] Espresso tab opened on Mon, 23/Sep/2019 10:38:46 (display_on = False). # Your work >>> Espresso.closetab() [espressomaker] Espresso tab closed.
Espresso module will prevent you from opening more than one
caffeinate subprocess for the same parent process — e.g. the Python interpreter, the IPython kernel from which you are running
espressomaker. Moreover, you can always run
espressomaker in multiple interpreters and kernels and check which
caffeinate subprocess belongs to your current interpreter or kernel by running
While opening more than one
caffeinate subprocess from a single parent process using
espressomaker is not possible, if it occurs you might not be able to use
closetab() to close all the running subprocesses. When you kill the parent process — e.g. close the Jupyter notebook, restart the kernel — all the child processes are killed along with it. If for some reason you suspect a
caffeinate process is still running, you can try to pinpoint it using
Espresso.check(), or you can kill all the
caffeinate processes in your Mac running
4.6 Checking the tabs —
Espresso.check() allows you to retrieve a list of all the running
caffeinate processes in your Mac. If you have one running in your current interpreter or kernel, it will be explicitly indicated:
>>> Espresso.check() [espressomaker] The following "caffeinate" processes were found: USER PID COMMAND <your_username> 62900 caffeinate -is -w 5531 (This kernel)
4.7 Killing all
caffeinate processes —
killall() method will kill all
caffeinate processes running in the system. Before running it, be sure that you don't have other
caffeinate active processes that you might need.
Formatting (GitHub flavor) passed and completed.
Basic skeleton of the package ready for shipping to TestPyPI.
- Automated file exporting from .ipynb to .py and standardized the formatting.
- Automated file exporting from .ipynb to .md and standardized the formatting.
- Improved variable handling on instance methods.
- Added a message for the user to recognize the current kernel when using opentabs().
- Added debugging tracers for all private methods.
- Finished class- and static- methods docstrings.
- Updated setup.py.
- Improved HISTORY.md title formatting.
- Updated "classifiers" of setup.py.
- Changed opentabs() classmethod to check() in espresso.py.
- Successfully ran manual tests in all APIs.
- Added PyPI version and GitHub issues badges to README.md.
- Ran installation test using
$ pip install espressomaker.
- Added config() classmethod to allow user modify Espresso class-level settings. Returns current settings.
- Added parameters to shot() and opentab() to allow user override "display_on" class-level setting.
- Repositioned status retrieval in closetab() classmethod.
- Added return message for killall() staticmethod.
- Added atexit.register call to closetab() (to be used when using opentab() in a .py script and not using closetab() at the end; however, killing the parent process should kill the "caffeinate" subprocess anyway).
- Finished User Guide in README.md.
- Corrected numbering and hrefs on README.md to work correctly on GitHub.
- Finish unittest.
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