Installation¶
All you need to get started with picoDAQ is a single Python library. There are no hardware drivers to install.
The latest version of the library is always available through the Python package archive and may be installed as follows.
Command line¶
A simple
pip install picodaq
should get you the latest. Most versions of Python allow you to
install picodaq globally or in a virtual environment. On Windows, you may
find that pip only works from a VSCode terminal, not from the
PowerShell.
IDEs¶
Many Python IDEs provide convenient front ends for pip. For
instance, in PyCharm, in Settings -> Project -> Python Interpreter,
you can click the “+” icon to show a list of available packages, which
includes picodaq. In VSCode, one of the easiest methods is to type
!pip install picodaq
in an Interactive session. Be sure to first create a virtual environment, unless you want to install picodaq system-wide.
Jupyter¶
Picodaq can be used in a local Jupyter notebook. This is very convenient for immediate analysis of acquired data. Use
!pip install picodaq
to install the library. While picodaq can be installed in Google Colab or other cloud-based notebooks, this is not very useful because the virtual machine will not have access to your hardware.
Verifying software installation¶
Open your favorite Python IDE or Notebook. Type
import picodaq
print(picodaq.version)
and run that code. You should be greeted with a version number, like
"0.1.4"
If, instead, you receive a ModuleNotFoundError exception, make sure
that the environment used by your IDE includes the place where you
installed the picodaq library. It may be helpful to
import sys
print(sys.path)
Troubleshooting strategies for this situation vary by IDE. Fortunately, advice is broadly available on the internet.
Next steps¶
Now that you have installed picoDAQ, the next step is to see if it works.