csv2numbers 1.1.1

Automator scripts

Converter for CSV to Apple Numbers

csv2numbers is a command-line utility to convert CSV files to Apple Numbers spreadsheets.

Installation

python3 -m pip install csv2numbers

A pre-requisite for this package is python-snappy which will be installed by Python automatically, but python-snappy also requires that the binary libraries for snappy compression are present.

The most straightforward way to install the binary dependencies is to use Homebrew and source Python from Homebrew rather than from macOS as described in the python-snappy github:

For Intel Macs:

brew install snappy python3
CPPFLAGS="-I/usr/local/include -L/usr/local/lib" python3 -m pip install python-snappy

For Apple Silicon Macs:

brew install snappy python3
CPPFLAGS="-I/opt/homebrew/include -L/opt/homebrew/lib" python3 -m pip install python-snappy

For Linux (your package manager may be different):

sudo apt-get -y install libsnappy-dev

On Windows, you will need to either arrange for snappy to be found for VSC++ or you can install python binary libraries compiled by Christoph Gohlke. You must select the correct python version for your installation. For example for python 3.11:

C:\Users\Jon>pip install C:\Users\Jon\Downloads\python_snappy-0.6.1-cp311-cp311-win_amd64.whl

Usage

Use csv2numbers to print command-line usage. You must provide at least one CSV file on the command-line and can provide multiple files, which will then all be converted using the same parameters. Output files can optionally be provided, but is none are provided, the output is created by replacing the input's files suffix with .numbers. For example:

csv2numbers file1.csv file2.csv -o file1.numbers file2.numbers

CSV files are read using the Excel dialect.

The following options affecting the output of the entire file. The default for each is always false.

• --whitespace: strip whitespace from beginning and end of strings and collapse other whitespace into single space
• --reverse: reverse the order of the data rows
• --no-header: CSV file has no header row
• --day-first: dates are represented day first in the CSV file

csv2numbers can also perform column manipulation. Columns can be identified using their name if the CSV file has a header or using a column index. Columns are zero-indexed and names and indices can be used together on the same command-line. When multiple columns are required, you can specify them using comma-separated values. The format for these arguments, like for the CSV file itself, the Excel dialect.

Deleting columns

Delete columns using --delete. The names or indices of the columns to delete are specified as comma-separated values:

csv2numbers file1.csv --delete=Account,3

Renaming columns

Rename columns using --rename. The current column name and new column name are separated by a : and each renaming is specified as comma-separated values:

csv2numbers file1.csv --rename=2:Account,"Paid In":Amount

Date columns

The --date option identifies a comma-separated list of columns that should be parsed as dates. Use --day-first where the day and month is ambiguous anf the day comes first rather than the month.

Transforming columns

Columns can be merged and new columns created using simple functions. The --transform option takes a comma-seperated list of transformations of the form NEW:FUNC=OLD. Supported functions are:

Function	Arguments	Description
MERGE	dest=MERGE:source	The dest column is writen with values from one or more columns indicated by source. For multiple columns, which are separated by ;, the first empty value is chosen.
NEG	dest=NEG:source	The dest column contains absolute values of any column that is negative. This is useful for isolating debits from account exports.
POS	dest=NEG:source	The dest column contains values of any column that is positive. This is useful for isolating credits from account exports.
LOOKUP	dest=LOOKUP:source;filename	A lookup map is read from filename which must be an Apple Numbers file containing a single table of two columns. The table is used to match agsinst source, searching the first column for matches and writing the corresponding value from the second column to dest. Values are chosen based on the longest matching substring.

Examples:

csv2numbers --transform="Paid In"=POS:Amount,Withdrawn=NEG:Amount file1.csv
csv2numbers --transform='Category=LOOKUP:Transaction;mapping.numbers' file1.csv

License

All code in this repository is licensed under the MIT License