validate.rs

static USAGE: &str = r#"
Validates CSV data using two modes:

JSON SCHEMA VALIDATION MODE:
This mode is invoked if a JSON Schema file is provided.

The CSV data is validated against the JSON Schema. If the CSV data is valid, no output
files are created and the command returns an exit code of 0.

If invalid records are found, they are put into an "invalid" file, with the rest of the
records put into a "valid"" file.

A "validation-errors.tsv" report is also created with the following columns:

  * row_number: the row number of the invalid record
  * field: the field name of the invalid field
  * error: a validation error message detailing why the field is invalid

It uses the JSON Schema Validation Specification (draft 2020-12) to validate the CSV.
It validates not only the structure of the file, but the data types and domain/range of the
fields as well. See https://json-schema.org/draft/2020-12/json-schema-validation.html

You can create a JSON Schema file from a reference CSV file using the `qsv schema` command.
Once the schema is created, you can fine-tune it to your needs and use it to validate other CSV
files that have the same structure.

Be sure to select a “training” CSV file that is representative of the data you want to validate
when creating a schema. The data types, domain/range and regular expressions inferred from the
reference CSV file should be appropriate for the data you want to validate. 

Typically, after creating a schema, you should edit it to fine-tune each field's inferred
validation rules.

For example, if we created a JSON schema file called "reference.schema.json" using the `schema` command.
And want to validate "mydata.csv" which we know has validation errors, the output files from running
`qsv validate mydata.csv reference.schema.json` are: 

  * mydata.csv.valid
  * mydata.csv.invalid
  * mydata.csv.validation-errors.tsv

With an exit code of 1 to indicate a validation error.

If we validate another CSV file, "mydata2.csv", which we know is valid, there are no output files,
and the exit code is 0.

If piped from stdin, the filenames will use `stdin.csv` as the base filename. For example:
`cat mydata.csv | qsv validate reference.schema.json`

   * stdin.csv.valid
   * stdin.csv.invalid
   * stdin.csv.validation-errors.tsv

RFC 4180 VALIDATION MODE:
If run without a JSON Schema file, the CSV is validated if it complies with qsv's interpretation of
the RFC 4180 CSV standard (see https://github.com/jqnatividad/qsv#rfc-4180-csv-standard).

It also confirms if the CSV is UTF-8 encoded.

For both modes, returns exit code 0 when the CSV file is valid, exitcode > 0 otherwise.
If all records are valid, no output files are produced.

For examples, see https://github.com/jqnatividad/qsv/blob/master/tests/test_validate.rs.

Usage:
    qsv validate [options] [<input>] [<json-schema>]
    qsv validate --help

Validate arguments:
    <input>                    Input CSV file to validate. If not provided, will read from stdin.
    <json-schema>              JSON Schema file to validate against. If not provided, `validate`
                               will run in RFC 4180 validation mode.
                               The file can be a local file or a URL.

Validate options:
    --fail-fast                Stops on first error.
    --valid <suffix>           Valid record output file suffix. [default: valid]
    --invalid <suffix>         Invalid record output file suffix. [default: invalid]
    --json                     When validating without a schema, return the RFC 4180 check
                               as a JSON file instead of a message.
    --pretty-json              Same as --json, but pretty printed.
    -j, --jobs <arg>           The number of jobs to run in parallel.
                               When not set, the number of jobs is set to the
                               number of CPUs detected.
    -b, --batch <size>         The number of rows per batch to load into memory,
                               before running in parallel.
                               [default: 50000]
    --timeout <seconds>        Timeout for downloading json-schemas.
                               [default: 30]

Common options:
    -h, --help                 Display this message
    -n, --no-headers           When set, the first row will not be interpreted
                               as headers. Namely, it will be sorted with the rest
                               of the rows. Otherwise, the first row will always
                               appear as the header row in the output.
    -d, --delimiter <arg>      The field delimiter for reading CSV data.
                               Must be a single character. [default: ,]
    -p, --progressbar          Show progress bars. Not valid for stdin.
"#;

use std::{
    env,
    fs::File,
    io::{BufReader, BufWriter, Read, Write},
    str,
    sync::{
        atomic::{AtomicU16, Ordering},
        OnceLock,
    },
};

use csv::ByteRecord;
use indicatif::HumanCount;
#[cfg(any(feature = "feature_capable", feature = "lite"))]
use indicatif::{ProgressBar, ProgressDrawTarget};
use itertools::Itertools;
use jsonschema::{output::BasicOutput, paths::PathChunk, JSONSchema};
use log::{debug, info, log_enabled};
use rayon::{
    iter::{IndexedParallelIterator, ParallelIterator},
    prelude::IntoParallelRefIterator,
};
use serde::{Deserialize, Serialize};
use serde_json::{json, value::Number, Map, Value};
use simdutf8::basic::from_utf8;

use crate::{
    config::{Config, Delimiter, DEFAULT_WTR_BUFFER_CAPACITY},
    util, CliResult,
};

// to save on repeated init/allocs
static NULL_TYPE: OnceLock<Value> = OnceLock::new();

static TIMEOUT_SECS: AtomicU16 = AtomicU16::new(15);

#[derive(Deserialize)]
#[allow(dead_code)]
struct Args {
    flag_fail_fast:   bool,
    flag_valid:       Option<String>,
    flag_invalid:     Option<String>,
    flag_json:        bool,
    flag_pretty_json: bool,
    flag_jobs:        Option<usize>,
    flag_batch:       u32,
    flag_no_headers:  bool,
    flag_delimiter:   Option<Delimiter>,
    flag_progressbar: bool,
    arg_input:        Option<String>,
    arg_json_schema:  Option<String>,
    flag_timeout:     u16,
}

#[derive(Serialize, Deserialize)]
struct RFC4180Struct {
    delimiter_char: char,
    header_row:     bool,
    quote_char:     char,
    num_records:    u64,
    num_fields:     u64,
    fields:         Vec<String>,
}

pub fn run(argv: &[&str]) -> CliResult<()> {
    let args: Args = util::get_args(USAGE, argv)?;

    TIMEOUT_SECS.store(
        util::timeout_secs(args.flag_timeout)? as u16,
        Ordering::Relaxed,
    );

    #[cfg(any(feature = "feature_capable", feature = "lite"))]
    let mut rconfig = Config::new(&args.arg_input)
        .delimiter(args.flag_delimiter)
        .no_headers(args.flag_no_headers);
    #[cfg(feature = "datapusher_plus")]
    let rconfig = Config::new(&args.arg_input)
        .delimiter(args.flag_delimiter)
        .no_headers(args.flag_no_headers);

    let mut rdr = rconfig.reader()?;

    // prep progress bar
    #[cfg(any(feature = "feature_capable", feature = "lite"))]
    let progress = ProgressBar::with_draw_target(None, ProgressDrawTarget::stderr_with_hz(5));

    #[cfg(any(feature = "feature_capable", feature = "lite"))]
    let show_progress =
        (args.flag_progressbar || util::get_envvar_flag("QSV_PROGRESSBAR")) && !rconfig.is_stdin();

    #[cfg(any(feature = "feature_capable", feature = "lite"))]
    if show_progress {
        // for full row count, prevent CSV reader from aborting on inconsistent column count
        rconfig = rconfig.flexible(true);
        let record_count = util::count_rows(&rconfig)?;
        rconfig = rconfig.flexible(false);
        util::prep_progress(&progress, record_count);
    } else {
        progress.set_draw_target(ProgressDrawTarget::hidden());
    }

    // if no JSON Schema supplied, only let csv reader RFC4180-validate csv file
    if args.arg_json_schema.is_none() {
        // just read csv file and let csv reader report problems
        // since we're using csv::StringRecord, this will also detect non-utf8 sequences

        // first, let's validate the header row
        let mut header_msg = String::new();
        let mut header_len: u64 = 0;
        let mut field_vec: Vec<String> = Vec::with_capacity(20);
        if !args.flag_no_headers {
            let fields_result = rdr.headers();
            match fields_result {
                Ok(fields) => {
                    header_len = fields.len() as u64;
                    for field in fields {
                        field_vec.push(field.to_string());
                    }
                    let field_list = field_vec.join(r#"", ""#);
                    header_msg =
                        format!("{} columns (\"{field_list}\") and ", HumanCount(header_len));
                },
                Err(e) => {
                    // we're returning a JSON error for the header,
                    // so we have more machine-friendly details
                    if args.flag_json || args.flag_pretty_json {
                        // there's a UTF-8 error, so we report utf8 error metadata
                        if let csv::ErrorKind::Utf8 { pos, err } = e.kind() {
                            let header_error = json!({
                                "errors": [{
                                    "title" : "Header UTF-8 validation error",
                                    "detail" : format!("{e}"),
                                    "meta": {
                                        "record_position": format!("{pos:?}"),
                                        "record_error": format!("{err}"),
                                    }
                                }]
                            });
                            let json_error = if args.flag_pretty_json {
                                serde_json::to_string_pretty(&header_error).unwrap()
                            } else {
                                header_error.to_string()
                            };

                            return fail_encoding_clierror!("{json_error}");
                        }
                        // it's not a UTF-8 error, so we report a generic
                        // header validation error
                        let header_error = json!({
                            "errors": [{
                                "title" : "Header Validation error",
                                "detail" : format!("{e}"),
                            }]
                        });
                        let json_error = if args.flag_pretty_json {
                            serde_json::to_string_pretty(&header_error).unwrap()
                        } else {
                            header_error.to_string()
                        };
                        return fail_encoding_clierror!("{json_error}");
                    }
                    // we're not returning a JSON error, so we can use
                    // a user-friendly error message with suggestions
                    if let csv::ErrorKind::Utf8 { pos, err } = e.kind() {
                        return fail_encoding_clierror!(
                            "non-utf8 sequence detected in header, position {pos:?}.\n{err}\nUse \
                             `qsv input` to fix formatting and to handle non-utf8 sequences.\n
                             You may also want to transcode your data to UTF-8 first using `iconv` \
                             or `recode`."
                        );
                    }
                    // its not a UTF-8 error, report a generic header validation error
                    return fail_clierror!("Header Validation error: {e}.");
                },
            }
        }

        // now, let's validate the rest of the records
        let mut record_idx: u64 = 0;
        for result in rdr.records() {
            #[cfg(any(feature = "feature_capable", feature = "lite"))]
            if show_progress {
                progress.inc(1);
            }

            if let Err(e) = result {
                if args.flag_json || args.flag_pretty_json {
                    // we're returning a JSON error, so we have more machine-friendly details
                    // using the JSON API error format
                    if let csv::ErrorKind::Utf8 { pos, err } = e.kind() {
                        // it's a UTF-8 error, so we report utf8 error metadata
                        let validation_error = json!({
                            "errors": [{
                                "title" : "UTF-8 validation error",
                                "detail" : format!("{e}"),
                                "meta": {
                                    "last_valid_record": format!("{record_idx}"),
                                    "record_position": format!("{pos:?}"),
                                    "record_error": format!("{err}"),
                                }
                            }]
                        });

                        let json_error = if args.flag_pretty_json {
                            serde_json::to_string_pretty(&validation_error).unwrap()
                        } else {
                            validation_error.to_string()
                        };
                        return fail_encoding_clierror!("{json_error}");
                    }
                    // it's not a UTF-8 error, so we report generic validation error
                    let validation_error = json!({
                        "errors": [{
                            "title" : "Validation error",
                            "detail" : format!("{e}"),
                            "meta": {
                                "last_valid_record": format!("{record_idx}"),
                            }
                        }]
                    });

                    let json_error = if args.flag_pretty_json {
                        serde_json::to_string_pretty(&validation_error).unwrap()
                    } else {
                        validation_error.to_string()
                    };

                    return fail!(json_error);
                }

                // we're not returning a JSON error, so we can use
                // a user-friendly error message with suggestions
                match e.kind() {
                    csv::ErrorKind::UnequalLengths {
                        expected_len: _,
                        len: _,
                        pos: _,
                    } => {
                        return fail_clierror!(
                            "Validation error: {e}.\nUse `qsv fixlengths` to fix record length \
                             issues."
                        );
                    },
                    csv::ErrorKind::Utf8 { pos, err } => {
                        return fail_encoding_clierror!(
                            "non-utf8 sequence at record {record_idx} position \
                             {pos:?}.\n{err}\nUse `qsv input` to fix formatting and to handle \
                             non-utf8 sequences.\nYou may also want to transcode your data to \
                             UTF-8 first using `iconv` or `recode`."
                        );
                    },
                    _ => {
                        return fail_clierror!(
                            "Validation error: {e}.\nLast valid record: {record_idx}"
                        );
                    },
                }
            }
            record_idx += 1;
        }

        #[cfg(any(feature = "feature_capable", feature = "lite"))]
        if show_progress {
            progress.set_message(format!(
                " validated {} records.",
                HumanCount(progress.length().unwrap())
            ));
            util::finish_progress(&progress);
        }

        let msg = if args.flag_json || args.flag_pretty_json {
            let rfc4180 = RFC4180Struct {
                delimiter_char: rconfig.get_delimiter() as char,
                header_row:     !rconfig.no_headers,
                quote_char:     rconfig.quote as char,
                num_records:    record_idx,
                num_fields:     header_len,
                fields:         field_vec,
            };

            if args.flag_pretty_json {
                serde_json::to_string_pretty(&rfc4180).unwrap()
            } else {
                serde_json::to_string(&rfc4180).unwrap()
            }
        } else {
            format!(
                "Valid: {header_msg}{} records detected.",
                HumanCount(record_idx)
            )
        };
        woutinfo!("{msg}");

        return Ok(());
    }

    let headers = rdr.byte_headers()?.clone();
    let headers_len = headers.len();

    // parse and compile supplied JSON Schema
    let (schema_json, schema_compiled): (Value, JSONSchema) =
        match load_json(&args.arg_json_schema.unwrap()) {
            Ok(s) => {
                // parse JSON string
                match serde_json::from_str(&s) {
                    Ok(json) => {
                        // compile JSON Schema
                        match JSONSchema::options().compile(&json) {
                            Ok(schema) => (json, schema),
                            Err(e) => {
                                return fail_clierror!("Cannot compile schema json. error: {e}");
                            },
                        }
                    },
                    Err(e) => {
                        return fail_clierror!("Unable to parse schema json. error: {e}");
                    },
                }
            },
            Err(e) => {
                return fail_clierror!("Unable to retrieve json. error: {e}");
            },
        };

    debug!("compiled schema: {:?}", &schema_compiled);

    // how many rows read and processed as batches
    let mut row_number: u64 = 0;
    // how many invalid rows found
    let mut invalid_count: u64 = 0;

    // amortize memory allocation by reusing record
    let mut record = csv::ByteRecord::new();
    // reuse batch buffer
    let batch_size = args.flag_batch as usize;
    let mut batch = Vec::with_capacity(batch_size);
    let mut validation_results = Vec::with_capacity(batch_size);
    let mut valid_flags: Vec<bool> = Vec::with_capacity(batch_size);
    let mut validation_error_messages: Vec<String> = Vec::with_capacity(50);

    // set RAYON_NUM_THREADS
    util::njobs(args.flag_jobs);

    // set this once, as this is used repeatedly in a hot loop
    NULL_TYPE.set(Value::String("null".to_string())).unwrap();

    // main loop to read CSV and construct batches for parallel processing.
    // each batch is processed via Rayon parallel iterator.
    // loop exits when batch is empty.
    'batch_loop: loop {
        for _ in 0..batch_size {
            match rdr.read_byte_record(&mut record) {
                Ok(has_data) => {
                    if has_data {
                        row_number += 1;
                        let mut buffer = itoa::Buffer::new();
                        record.push_field(buffer.format(row_number).as_bytes());

                        // non-allocating trimming in place is much faster on the record level
                        // with our csv fork than doing per field std::str::trim which is allocating
                        record.trim();
                        batch.push(record.clone());
                    } else {
                        // nothing else to add to batch
                        break;
                    }
                },
                Err(e) => {
                    return fail_clierror!("Error reading row: {row_number}: {e}");
                },
            }
        }

        if batch.is_empty() {
            // break out of infinite loop when at EOF
            break 'batch_loop;
        }

        // do actual validation via Rayon parallel iterator
        // validation_results vector should have same row count and in same order as input CSV
        batch
            .par_iter()
            .map(|record| {
                do_json_validation(
                    &headers,
                    headers_len,
                    record,
                    &schema_json,
                    &schema_compiled,
                )
            })
            .collect_into_vec(&mut validation_results);

        // write to validation error report, but keep Vec<bool> to gen valid/invalid files later
        // because Rayon collect() guarantees original order, we can sequentially append results
        // to vector with each batch
        for result in &validation_results {
            if let Some(validation_error_msg) = result {
                invalid_count += 1;
                valid_flags.push(false);

                validation_error_messages.push(validation_error_msg.to_string());
            } else {
                valid_flags.push(true);
            }
        }

        #[cfg(any(feature = "feature_capable", feature = "lite"))]
        if show_progress {
            progress.inc(batch.len() as u64);
        }
        batch.clear();

        // for fail-fast, exit loop if batch has any error
        if args.flag_fail_fast && invalid_count > 0 {
            break 'batch_loop;
        }
    } // end batch loop

    #[cfg(any(feature = "feature_capable", feature = "lite"))]
    if show_progress {
        progress.set_message(format!(
            " validated {} records.",
            HumanCount(progress.length().unwrap())
        ));
        util::finish_progress(&progress);
    }

    // only write out invalid/valid/errors output files if there are actually invalid records.
    // if 100% invalid, valid file is not needed, but this is rare so OK with creating empty file.
    if invalid_count > 0 {
        let msg = "Writing invalid/valid/error files...";
        woutinfo!("{msg}");

        let input_path = args
            .arg_input
            .clone()
            .unwrap_or_else(|| "stdin.csv".to_string());

        write_error_report(&input_path, validation_error_messages)?;

        let valid_suffix = args.flag_valid.unwrap_or_else(|| "valid".to_string());
        let invalid_suffix = args.flag_invalid.unwrap_or_else(|| "invalid".to_string());

        split_invalid_records(
            &rconfig,
            &valid_flags[..],
            &headers,
            &input_path,
            &valid_suffix,
            &invalid_suffix,
        )?;

        // done with validation; print output
        let fail_fast_msg = if args.flag_fail_fast {
            format!(
                "fail-fast enabled. stopped after row {}.\n",
                HumanCount(row_number)
            )
        } else {
            String::new()
        };

        return fail_clierror!(
            "{fail_fast_msg}{} out of {} records invalid.",
            HumanCount(invalid_count),
            HumanCount(row_number)
        );
    }

    winfo!("All {} records valid.", HumanCount(row_number));
    Ok(())
}

fn split_invalid_records(
    rconfig: &Config,
    valid_flags: &[bool],
    headers: &ByteRecord,
    input_path: &str,
    valid_suffix: &str,
    invalid_suffix: &str,
) -> CliResult<()> {
    // track how many rows read for splitting into valid/invalid
    // should not exceed row_number when aborted early due to fail-fast
    let mut split_row_num: usize = 0;

    // prepare output writers
    let mut valid_wtr = Config::new(&Some(input_path.to_owned() + "." + valid_suffix)).writer()?;
    valid_wtr.write_byte_record(headers)?;

    let mut invalid_wtr =
        Config::new(&Some(input_path.to_owned() + "." + invalid_suffix)).writer()?;
    invalid_wtr.write_byte_record(headers)?;

    let mut rdr = rconfig.reader()?;

    let mut record = csv::ByteRecord::new();
    while rdr.read_byte_record(&mut record)? {
        split_row_num += 1;

        // length of valid_flags is max number of rows we can split
        if split_row_num > valid_flags.len() {
            break;
        }

        // vector is 0-based, row_num is 1-based
        let is_valid = valid_flags[split_row_num - 1];

        if is_valid {
            valid_wtr.write_byte_record(&record)?;
        } else {
            invalid_wtr.write_byte_record(&record)?;
        }
    }

    valid_wtr.flush()?;
    invalid_wtr.flush()?;

    Ok(())
}

fn write_error_report(input_path: &str, validation_error_messages: Vec<String>) -> CliResult<()> {
    let wtr_capacitys = env::var("QSV_WTR_BUFFER_CAPACITY")
        .unwrap_or_else(|_| DEFAULT_WTR_BUFFER_CAPACITY.to_string());
    let wtr_buffer_size: usize = wtr_capacitys.parse().unwrap_or(DEFAULT_WTR_BUFFER_CAPACITY);

    let output_file = File::create(input_path.to_owned() + ".validation-errors.tsv")?;

    let mut output_writer = BufWriter::with_capacity(wtr_buffer_size, output_file);

    output_writer.write_all(b"row_number\tfield\terror\n")?;

    // write out error report
    for error_msg in validation_error_messages {
        output_writer.write_all(error_msg.as_bytes())?;
        // since writer is buffered, it's more efficient to do additional write than append Newline
        // to message
        output_writer.write_all(&[b'\n'])?;
    }

    // flush error report; file gets closed automagically when out-of-scope
    output_writer.flush()?;

    Ok(())
}

/// if given record is valid, return None, otherwise, error file entry string
fn do_json_validation(
    headers: &ByteRecord,
    headers_len: usize,
    record: &ByteRecord,
    schema_json: &Value,
    schema_compiled: &JSONSchema,
) -> Option<String> {
    // row number was added as last column. We use can do unwrap safely since we know its there
    let row_number_string = from_utf8(record.get(headers_len).unwrap()).unwrap();

    // debug!("instance[{row_number}]: {instance:?}");
    validate_json_instance(
        &(match to_json_instance(headers, headers_len, record, schema_json) {
            Ok(obj) => obj,
            Err(e) => {
                return Some(format!("{row_number_string}\t<RECORD>\t{e}"));
            },
        }),
        schema_compiled,
    )
    .map(|validation_errors| {
        // squash multiple errors into one long String with linebreaks
        let combined_errors: String = validation_errors
            .iter()
            .map(|tuple| {
                // validation error file format: row_number, field, error
                format!("{row_number_string}\t{}\t{}", tuple.0, tuple.1)
            })
            .join("\n");

        combined_errors
    })
}

/// convert CSV Record into JSON instance by referencing Type from Schema
#[inline]
fn to_json_instance(
    headers: &ByteRecord,
    headers_len: usize,
    record: &ByteRecord,
    schema: &Value,
) -> CliResult<Value> {
    // make sure schema has expected structure
    let Some(schema_properties) = schema.get("properties") else {
        return fail_clierror!("JSON Schema missing 'properties' object");
    };

    // map holds individual CSV fields converted as serde_json::Value
    // we use with_capacity to minimize allocs
    let mut json_object_map: Map<String, Value> = Map::with_capacity(headers_len);

    // safety: we set NULL_TYPE in main() and it's never changed
    let null_type = NULL_TYPE.get().unwrap();

    let mut key_string: String;
    let mut value_string: String;
    let mut field_def: &Value;
    let mut field_type_def: &Value;
    let mut json_type: u8;

    // iterate over each CSV field and convert to JSON type
    for (i, header) in headers.iter().enumerate() {
        // convert csv header to string. It's the key in the JSON object
        key_string = if let Ok(s) = from_utf8(header) {
            s.to_owned()
        } else {
            let s = String::from_utf8_lossy(header);
            return fail_encoding_clierror!("CSV header is not valid UTF-8: {s}");
        };

        // convert csv value to string; no trimming reqd as it's done on the record level beforehand
        let Some(value) = record.get(i) else {
            return fail_clierror!(
                "CSV record is missing value for header '{key_string}' at index {i}"
            );
        };
        value_string = if let Ok(s) = from_utf8(value) {
            s.to_owned()
        } else {
            let s = String::from_utf8_lossy(value);
            return fail_encoding_clierror!("CSV value is not valid UTF-8: {s}");
        };

        // if value_string is empty, then just put an empty JSON String
        if value_string.is_empty() {
            json_object_map.insert(key_string, Value::Null);
            continue;
        }

        // get json type from schema; defaults to STRING if not specified
        field_def = schema_properties.get(&key_string).unwrap_or(&Value::Null);

        field_type_def = field_def.get("type").unwrap_or(&Value::Null);

        // we do json_type as a u8 so match will be a tad faster below
        json_type = match field_type_def {
            Value::String(s) => s.as_bytes()[0],
            Value::Array(vec) => {
                // if can't find usable type info, defaults to "string"
                let mut return_val = b's';

                // grab the first entry that's not a "null", since it just means value is optional
                for val in vec {
                    if *val == *null_type {
                        // keep looking
                        continue;
                    }
                    return_val = if let Some(s) = val.as_str() {
                        s.as_bytes()[0]
                    } else {
                        return fail_clierror!("type info should be a JSON string");
                    };
                }

                return_val
            },
            _ => {
                // default to JSON String
                b's'
            },
        };

        // dbg!(i, &header_string, &value_string, &json_type);

        // matching against a u8, rather than an str should be a tad faster
        match json_type {
            b's' => {
                // string
                json_object_map.insert(key_string, Value::String(value_string));
            },
            b'n' => {
                // number
                if let Ok(float) = fast_float::parse(&value_string) {
                    json_object_map.insert(
                        key_string,
                        // safety: we know it's a valid f64 from the fast_float::parse() above
                        Value::Number(Number::from_f64(float).unwrap()),
                    );
                } else {
                    return fail_clierror!(
                        "Can't cast into Float. key: {key_string}, value: {value_string}, json \
                         type: number"
                    );
                }
            },
            b'i' => {
                // integer
                if let Ok(int) = value_string.parse::<i64>() {
                    json_object_map.insert(key_string, Value::Number(Number::from(int)));
                } else {
                    return fail_clierror!(
                        "Can't cast into Integer. key: {key_string}, value: {value_string}, json \
                         type: integer"
                    );
                }
            },
            b'b' => {
                // boolean
                if let Ok(boolean) = value_string.parse::<bool>() {
                    json_object_map.insert(key_string, Value::Bool(boolean));
                } else {
                    return fail_clierror!(
                        "Can't cast into Boolean. key: {key_string}, value: {value_string}, json \
                         type: boolean"
                    );
                }
            },
            _ => {
                unreachable!("we should never get an unknown json type");
            },
        }
    }

    // dbg!(&json_object_map);

    Ok(Value::Object(json_object_map))
}

#[cfg(test)]
mod tests_for_csv_to_json_conversion {

    use serde_json::json;

    use super::*;

    /// get schema used for unit tests
    fn schema_json() -> Value {
        // from https://json-schema.org/learn/miscellaneous-examples.html
        serde_json::json!({
            "$id": "https://example.com/test.schema.json",
            "$schema": "https://json-schema.org/draft/2020-12/schema",
            "title": "test",
            "type": "object",
            "properties": {
                "A": {
                    "type": "string",
                },
                "B": {
                    "type": "number",
                },
                "C": {
                    "type": "integer",
                },
                "D": {
                    "type": "boolean",
                },
                "E": {
                    "type": ["string", "null"],
                },
                "F": {
                    "type": ["number", "null"],
                },
                "G": {
                    "type": ["integer", "null"],
                },
                "H": {
                    "type": ["boolean", "null"],
                },
                "I": {
                    "type": ["string", "null"],
                },
                "J": {
                    "type": ["number", "null"],
                },
                "K": {
                    "type": ["null", "integer"],
                },
                "L": {
                    "type": ["boolean", "null"],
                },
            }
        })
    }

    #[test]
    #[allow(clippy::approx_constant)]
    fn test_to_json_instance() {
        let _ = NULL_TYPE.get_or_init(|| Value::String("null".to_string()));
        let csv = "A,B,C,D,E,F,G,H,I,J,K,L
        hello,3.1415,300000000,true,,,,,hello,3.1415,300000000,true";

        let mut rdr = csv::Reader::from_reader(csv.as_bytes());
        let headers = rdr.byte_headers().unwrap().clone();
        let mut record = rdr.byte_records().next().unwrap().unwrap();
        record.trim();

        assert_eq!(
            to_json_instance(&headers, headers.len(), &record, &schema_json())
                .expect("can't convert csv to json instance"),
            json!({
                "A": "hello",
                "B": 3.1415,
                "C": 300_000_000,
                "D": true,
                "E": null,
                "F": null,
                "G": null,
                "H": null,
                "I": "hello",
                "J": 3.1415,
                "K": 300_000_000,
                "L": true,
            })
        );
    }

    #[test]
    fn test_to_json_instance_cast_integer_error() {
        let _ = NULL_TYPE.get_or_init(|| Value::String("null".to_string()));
        let csv = "A,B,C,D,E,F,G,H
        hello,3.1415,3.0e8,true,,,,";

        let mut rdr = csv::Reader::from_reader(csv.as_bytes());
        let headers = rdr.byte_headers().unwrap().clone();

        let result = to_json_instance(
            &headers,
            headers.len(),
            &rdr.byte_records().next().unwrap().unwrap(),
            &schema_json(),
        );
        assert!(&result.is_err());
        let error = result.err().unwrap().to_string();
        assert_eq!(
            "Can't cast into Integer. key: C, value: 3.0e8, json type: integer",
            error
        );
    }
}

/// Validate JSON instance against compiled JSON Schema
/// If invalid, returns Some(Vec<(String,String)>) holding the error messages
#[inline]
fn validate_json_instance(
    instance: &Value,
    schema_compiled: &JSONSchema,
) -> Option<Vec<(String, String)>> {
    let validation_output = schema_compiled.apply(instance);

    // If validation output is Invalid, then grab field names and errors
    if validation_output.flag() {
        None
    } else {
        // get validation errors as String
        let validation_errors: Vec<(String, String)> = match validation_output.basic() {
            BasicOutput::Invalid(errors) => errors
                .iter()
                .map(|e| {
                    if let Some(PathChunk::Property(box_str)) = e.instance_location().last() {
                        (box_str.to_string(), e.error_description().to_string())
                    } else {
                        (
                            e.instance_location().to_string(),
                            e.error_description().to_string(),
                        )
                    }
                })
                .collect(),
            BasicOutput::Valid(_annotations) => {
                // shouldn't happen
                unreachable!("Unexpected error.");
            },
        };

        Some(validation_errors)
    }
}

#[cfg(test)]
mod tests_for_schema_validation {
    use super::*;

    fn schema_json() -> Value {
        // from https://json-schema.org/learn/miscellaneous-examples.html
        serde_json::json!({
            "$id": "https://example.com/person.schema.json",
            "$schema": "https://json-schema.org/draft/2020-12/schema",
            "title": "Person",
            "type": "object",
            "properties": {
                "title": {
                    "type": "string",
                    "description": "The person's title.",
                    "minLength": 2
                },
                "name": {
                    "type": "string",
                    "description": "The person's name.",
                    "minLength": 2
                },
                "age": {
                    "description": "Age in years which must be equal to or greater than 18.",
                    "type": "integer",
                    "minimum": 18
                }
            }
        })
    }

    fn compiled_schema() -> JSONSchema {
        JSONSchema::options()
            .compile(&schema_json())
            .expect("Invalid schema")
    }

    #[test]
    fn test_validate_with_no_errors() {
        let _ = NULL_TYPE.get_or_init(|| Value::String("null".to_string()));
        let csv = "title,name,age
        Professor,Xaviers,60";

        let mut rdr = csv::Reader::from_reader(csv.as_bytes());
        let headers = rdr.byte_headers().unwrap().clone();

        let record = &rdr.byte_records().next().unwrap().unwrap();

        let instance = to_json_instance(&headers, headers.len(), record, &schema_json()).unwrap();

        let result = validate_json_instance(&instance, &compiled_schema());

        assert!(result.is_none());
    }

    #[test]
    fn test_validate_with_error() {
        let _ = NULL_TYPE.get_or_init(|| Value::String("null".to_string()));
        let csv = "title,name,age
        Professor,X,60";

        let mut rdr = csv::Reader::from_reader(csv.as_bytes());
        let headers = rdr.byte_headers().unwrap().clone();

        let record = &rdr.byte_records().next().unwrap().unwrap();

        let instance = to_json_instance(&headers, headers.len(), record, &schema_json()).unwrap();

        let result = validate_json_instance(&instance, &compiled_schema());

        assert!(result.is_some());

        assert_eq!(
            vec![(
                "name".to_string(),
                "\"X\" is shorter than 2 characters".to_string()
            )],
            result.unwrap()
        );
    }
}

fn load_json(uri: &str) -> Result<String, String> {
    let json_string = match uri {
        url if url.to_lowercase().starts_with("http") => {
            use reqwest::blocking::Client;

            let client_timeout =
                std::time::Duration::from_secs(TIMEOUT_SECS.load(Ordering::Relaxed) as u64);

            let client = match Client::builder()
                // safety: we're using a validated QSV_USER_AGENT or if it's not set,
                // the default user agent
                .user_agent(util::set_user_agent(None).unwrap())
                .brotli(true)
                .gzip(true)
                .deflate(true)
                .use_rustls_tls()
                .http2_adaptive_window(true)
                .connection_verbose(
                    log_enabled!(log::Level::Debug) || log_enabled!(log::Level::Trace),
                )
                .timeout(client_timeout)
                .build()
            {
                Ok(c) => c,
                Err(e) => {
                    return fail_format!("Cannot build reqwest client: {e}.");
                },
            };

            match client.get(url).send() {
                Ok(response) => response.text().unwrap_or_default(),
                Err(e) => return fail_format!("Cannot read JSON at url {url}: {e}."),
            }
        },
        path => {
            let mut buffer = String::new();
            match File::open(path) {
                Ok(p) => {
                    BufReader::new(p)
                        .read_to_string(&mut buffer)
                        .unwrap_or_default();
                },
                Err(e) => return fail_format!("Cannot read JSON file {path}: {e}."),
            }
            buffer
        },
    };

    Ok(json_string)
}

#[test]
fn test_load_json_via_url() {
    let json_string_result = load_json("https://geojson.org/schema/FeatureCollection.json");
    assert!(&json_string_result.is_ok());

    let json_result: Result<Value, serde_json::Error> =
        serde_json::from_str(&json_string_result.unwrap());
    assert!(&json_result.is_ok());
}