Metadata-Version: 2.1
Name: saqc
Version: 1.3.0
Summary: Data quality checking and processing tool/framework
Home-page: https://git.ufz.de/rdm-software/saqc
Author: Bert Palm, David Schaefer, Peter Luenenschloss, Lennard Schmidt
Author-email: david.schaefer@ufz.de
License: GPLv3
Description: # System for automated Quality Control (SaQC)
        
        Quality Control of numerical data requires a significant amount of
        domain knowledge and practical experience. Finding a robust setup of
        quality tests that identifies as many suspicious values as possible, without
        removing valid data, is usually a time-consuming and iterative endeavor,
        even for experts.
        
        SaQC is both, a Python framework and a command line application, that
        addresses the exploratory nature of quality control by offering a
        continuously growing number of quality check routines through a flexible
        and simple configuration system.
        
        Below its user interface, SaQC is highly customizable and extensible.
        A modular structure and well-defined interfaces make it easy to extend
        the system with custom quality checks and even core components, like
        the flagging scheme, are exchangeable.
        
        ![SaQC Workflow](ressources/images/readme_image.png "SaQC Workflow")
        
        ## Why?
        During the implementation of data workflows in environmental sciences,
        our experience shows a significant knowledge gap between the people
        collecting data and those responsible for the processing and the
        quality-control of these datasets.
        While the former usually have a solid understanding of the underlying
        physical properties, measurement principles and the resulting errors,
        the latter are mostly software developers with expertise in
        data processing.
        
        The main objective of SaQC is to bridge this gap by allowing both
        parties to focus on their strengths: The data collector/owner should be
        able to express his/her ideas in an easy and succinct way, while the actual
        implementation of the algorithms is left to the respective developers.
        
        
        ## How?
        The most import aspect of SaQC, the [general configuration](docs/ConfigurationFiles.md)
        of the system, is text-based. All the magic takes place in a semicolon-separated
        table file listing the variables within the dataset and the routines to inspect,
        quality control and/or modify them.
        
        ```
        varname    ; test                                ; plot
        #----------;-------------------------------------;------
        SM2        ; harm_shift2Grid(freq="15Min")       ; False
        SM2        ; flagMissing(nodata=NAN)             ; False
        'SM(1|2)+' ; flagRange(min=10, max=60)           ; False
        SM2        ; spikes_flagMad(window="30d", z=3.5) ; True
        ```
        
        While a good (but still growing) number of predefined and highly configurable
        [functions](docs/FunctionIndex.md) are included and ready to use, SaQC
        additionally ships with a python based for quality control but also general
        purpose data processing
        [extension language](docs/GenericFunctions.md).
        
        For a more specific round trip to some of SaQC's possibilities, please refer to
        our [GettingStarted](docs/GettingStarted.md).
        
        
        ## Installation
        
        ### Python Package Index
        SaQC is available on the Python Package Index ([PyPI](https://pypi.org/)) and
        can be installed using [pip](https://pip.pypa.io/en/stable/):
        ```sh
        python -m pip install saqc
        ```
        
        ### Anaconda
        Currently we don't provide pre-build conda packages but the installing of `SaQC`
        using the [conda package manager](https://docs.conda.io/en/latest/) is
        straightforward:
        1. Create an anaconda environment including all the necessary dependencies with:
           ```sh
           conda env create -f environment.yml
           ```
        2. Load the freshly created environment with:
           ```sh
           conda activate saqc
           ```
        
        ### Manual installation
        
        The latest development version is directly available from the
        [gitlab](https://git.ufz.de/rdm-software/saqc) server of the
        [Helmholtz Center for Environmental Research](https://www.ufz.de/index.php?en=33573).
        More details on how to setup an respective environment are available
        [here](CONTRIBUTING.md#development-environment)
        
        ### Python version
        The minimum Python version required is 3.6.
        
        
        ## Usage
        ### Command line interface (CLI)
        SaQC provides a basic CLI to get you started. As soon as the basic inputs,
        a dataset and the [configuration file](saqc/docs/ConfigurationFiles.md) are
        prepared, running SaQC is as simple as:
        ```sh
        saqc \
            --config path_to_configuration.txt \
            --data path_to_data.csv \
            --outfile path_to_output.csv
        ```
        
        
        ### Integration into larger workflows
        The main function is [exposed](saqc/core/core.py#L79) and can be used in within
        your own programs.
        
        
        ## License
        Copyright(c) 2019,
        Helmholtz Centre for Environmental Research - UFZ.
        All rights reserved.
        
        The "System for Automated Quality Control" is free software. You can
        redistribute it and/or modify it under the terms of the GNU General
        Public License as published by the free Software Foundation either
        version 3 of the License, or (at your option) any later version. See the
        [license](LICENSE.txt) for details.
        
        This program is distributed in the hope that it will be useful, but
        WITHOUT ANY WARRANTY; without even the implied warranty of
        MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
        See the GNU General Public License for more details.
        
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