static USAGE: &str = r#" Partitions the given CSV data into chunks based on the value of a column. See `split` command to split a CSV data by row count, by number of chunks or by kb-size. The files are written to the output directory with filenames based on the values in the partition column and the `--filename` flag. EXAMPLE: Partition nyc311.csv file into separate files based on the value of the "Borough" column in the current directory: $ qsv partition Borough . --filename "nyc311-{}.csv" nyc311.csv will create the following files, each containing the data for each borough: nyc311-Bronx.csv nyc311-Brooklyn.csv nyc311-Manhattan.csv nyc311-Queens.csv nyc311-Staten_Island.csv For more examples, see https://github.com/jqnatividad/qsv/blob/master/tests/test_partition.rs. Usage: qsv partition [options] [] qsv partition --help partition arguments: The column to use as a key for partitioning. You can use the `--select` option to select the column by name or index, but only one column can be used for partitioning. See `select` command for more details. The directory to write the output files to. The CSV file to read from. If not specified, then the input will be read from stdin. partition options: --filename A filename template to use when constructing the names of the output files. The string '{}' will be replaced by a value based on the partition column, but sanitized for shell safety. [default: {}.csv] -p, --prefix-length Truncate the partition column after the specified number of bytes when creating the output file. --drop Drop the partition column from results. Common options: -h, --help Display this message -n, --no-headers When set, the first row will NOT be interpreted as column names. Otherwise, the first row will appear in all chunks as the header row. -d, --delimiter The field delimiter for reading CSV data. Must be a single character. (default: ,) "#; use std::{ collections::{hash_map::Entry, HashSet}, fs, io, path::Path, }; use ahash::AHashMap; use regex::Regex; use serde::Deserialize; use crate::{ config::{Config, Delimiter}, select::SelectColumns, util::{self, FilenameTemplate}, CliResult, }; #[derive(Clone, Deserialize)] struct Args { arg_column: SelectColumns, arg_input: Option, arg_outdir: String, flag_filename: FilenameTemplate, flag_prefix_length: Option, flag_drop: bool, flag_no_headers: bool, flag_delimiter: Option, } pub fn run(argv: &[&str]) -> CliResult<()> { let args: Args = util::get_args(USAGE, argv)?; fs::create_dir_all(&args.arg_outdir)?; // It would be nice to support efficient parallel partitions, but doing // so would involve more complicated inter-thread communication, with // multiple readers and writers, and some way of passing buffers // between them. args.sequential_partition() } impl Args { /// Configuration for our reader. fn rconfig(&self) -> Config { Config::new(&self.arg_input) .delimiter(self.flag_delimiter) .no_headers(self.flag_no_headers) .select(self.arg_column.clone()) } /// Get the column to use as a key. #[allow(clippy::unused_self)] fn key_column(&self, rconfig: &Config, headers: &csv::ByteRecord) -> CliResult { let select_cols = rconfig.selection(headers)?; if select_cols.len() == 1 { Ok(select_cols[0]) } else { fail!("can only partition on one column") } } /// A basic sequential partition. fn sequential_partition(&self) -> CliResult<()> { let rconfig = self.rconfig(); let mut rdr = rconfig.reader()?; let headers = rdr.byte_headers()?.clone(); let key_col = self.key_column(&rconfig, &headers)?; let mut gen = WriterGenerator::new(self.flag_filename.clone()); let mut writers: AHashMap, BoxedWriter> = AHashMap::new(); let mut row = csv::ByteRecord::new(); while rdr.read_byte_record(&mut row)? { // Decide what file to put this in. let column = &row[key_col]; let key = match self.flag_prefix_length { // We exceed --prefix-length, so ignore the extra bytes. Some(len) if len < column.len() => &column[0..len], _ => column, }; let mut entry = writers.entry(key.to_vec()); let wtr = match entry { Entry::Occupied(ref mut occupied) => occupied.get_mut(), Entry::Vacant(vacant) => { // We have a new key, so make a new writer. let mut wtr = gen.writer(&*self.arg_outdir, key)?; if !rconfig.no_headers { if self.flag_drop { wtr.write_record(headers.iter().enumerate().filter_map( |(i, e)| if i == key_col { None } else { Some(e) }, ))?; } else { wtr.write_record(&headers)?; } } vacant.insert(wtr) }, }; if self.flag_drop { wtr.write_record(row.iter().enumerate().filter_map(|(i, e)| { if i == key_col { None } else { Some(e) } }))?; } else { wtr.write_byte_record(&row)?; } wtr.flush()?; } Ok(()) } } type BoxedWriter = csv::Writer>; /// Generates unique filenames based on CSV values. struct WriterGenerator { template: FilenameTemplate, counter: usize, used: HashSet, non_word_char: Regex, } impl WriterGenerator { fn new(template: FilenameTemplate) -> WriterGenerator { WriterGenerator { template, counter: 1, used: HashSet::new(), non_word_char: Regex::new(r"\W").unwrap(), } } /// Create a CSV writer for `key`. Does not add headers. fn writer

(&mut self, path: P, key: &[u8]) -> io::Result where P: AsRef, { let unique_value = self.unique_value(key); self.template.writer(path.as_ref(), &unique_value) } /// Generate a unique value for `key`, suitable for use in a /// "shell-safe" filename. If you pass `key` twice, you'll get two /// different values. fn unique_value(&mut self, key: &[u8]) -> String { // Sanitize our key. let utf8 = String::from_utf8_lossy(key); let safe = self.non_word_char.replace_all(&utf8, "").into_owned(); let base = if safe.is_empty() { "empty".to_owned() } else { safe }; // Now check for collisions. if self.used.contains(&base) { loop { let candidate = format!("{}_{}", &base, self.counter); self.counter = self.counter.checked_add(1).unwrap_or_else(|| { // We'll run out of other things long before we ever // reach this, but we'll check just for correctness and // completeness. panic!("Cannot generate unique value") }); if !self.used.contains(&candidate) { self.used.insert(candidate.clone()); return candidate; } } } else { self.used.insert(base.clone()); base } } }