Provided by: python3-clevercsv_0.7.4+ds-2_amd64 bug

NAME

       clevercsv-standardize - Convert a CSV file to one that conforms to RFC-4180

SYNOPSIS

       clevercsv standardize [-e ENCODING | --encoding=ENCODING] [-i | --in-place]
                             [-n NUM_CHARS | --num-chars=NUM_CHARS]
                             [-o OUTPUT | --output=OUTPUT] [-t | --transpose]
                             <path [path ...]>

DESCRIPTION

       The standardize command can be used to convert a non-standard CSV file to the standard
       RFC-4180 format [1]. When using the --in-place option, the return code of CleverCSV can be
       used to check whether a file was altered or not. The return code will be 2 when the file
       was altered and 0 otherwise.

       [1]: https://tools.ietf.org/html/rfc4180

OPTIONS

       -h, --help
           show this help message and exit

       -e, --encoding
           The file encoding of the given CSV file is automatically detected using chardet. While
           chardet is incredibly accurate, it is not perfect. In the rare cases that it makes a
           mistake in detecting the file encoding, you can override the encoding by providing it
           through this flag. For this command, the provided encoding will also be used for the
           output file(s). When only one encoding is given, it will be used for all files given
           on the command line. When multiple encodings are given, the number must correspond to
           the number of files provided as input.

       -i, --in-place
           Standardize and overwrite the input file(s)

       -n, --num-chars
           On large CSV files, dialect detection can sometimes be a bit slow due to the large
           number of possible dialects to consider. To alleviate this, you can limit the number
           of characters to use for detection.

           One aspect to keep in mind is that CleverCSV may need to read a specific number of
           characters to be able to correctly infer the dialect. For example, in the ``imdb.csv``
           file in the GitHub repository, the correct dialect can only be found after at least 66
           lines of the file are read. Therefore, if there is availability to run CleverCSV on
           the entire file, that is generally recommended.

       -o, --output
           The output files to write the standardized input files to. The order of the input
           files and the order of the output files should match if this option is used with more
           than one input file.

       -t, --transpose
           Transpose the columns of the input file(s) before writing

       <path>
           Path to one or more CSV file(s)

CLEVERCSV

       Part of the CleverCSV suite