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        "author": "Dan Kuester, Shane Allman, Paul Blanchard, Yao Ma",
        "author_email": "daniel.kuester@nist.gov",
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        "description": "The `labbench` module provides tools for instrument automation and data management in scripted lab experiments.\n\nA device driver implemented with labbench is a light wrapper around another instrument control library.\nThis means another library (like pyvisa, pyserial, libtelnet, or even a C or .NET DLL) provides low-level routines. The labbench\nabstraction provides several benefits:\n\n* automatic acquisition logging into an SQLite database,\n* automatically-generated jupyter notebook monitoring widgets,\n* interact with settings and data on remote devices with native python data types (instead of strings),\n* python exceptions on invalid device state settings (instead of silent failure),\n* drivers provide consistent style and API conventions for easy scripting (hello, tab completion!),\n* ensure devices disconnect properly when acquisition completes (even on exceptions), and\n* conversion of vector or tabular data to [pandas](pandas.pydata.org) Series or DataFrame objects for rapid exploration of data.\n\nTogether, these features help to minimize the amount of \"copy-and-paste\" code that can make your lab automation scripts error-prone and difficult to maintain.\nThe python code that results can be clear, concise, reusable and maintainable, and\nprovide consistent formatting for stored data.\nThe result helps researchers to meet NIST's\n[open data](https://www.nist.gov/open) obligations, even for complicated, large,\nand heterogeneous datasets.\n\n\n",
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