dataprof 0.8.1

High-performance data profiler with ISO 8000/25012 quality metrics for CSV, JSON/JSONL, and Parquet files
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131

use std::time::Duration;

use dataprof::{
    ChunkSize, CsvParserConfig, DataSource, DataType, EngineType, FileFormat, JsonFormat,
    JsonParserConfig, MetricPack, OutputFormat, Profiler, ProfilerConfig, ProgressSink,
    QualityDimension, SamplingStrategy, StopCondition, analyze_column_fast,
    calculate_numeric_stats, calculate_text_stats, detect_patterns, infer_type,
};

#[test]
fn stable_facade_builder_surface_compiles() {
    let _profiler = Profiler::with_config(ProfilerConfig::default())
        .engine(EngineType::Auto)
        .chunk_size(ChunkSize::Fixed(128))
        .sampling(SamplingStrategy::None)
        .memory_limit_mb(32)
        .stop_when(StopCondition::MaxRows(1_000))
        .format(FileFormat::Csv)
        .csv_delimiter(b';')
        .csv_flexible(true)
        .quality_dimensions(vec![QualityDimension::Completeness])
        .metric_packs(vec![MetricPack::Schema, MetricPack::Quality])
        .locale("IT")
        .progress_interval(Duration::from_millis(25))
        .progress_sink(ProgressSink::None);

    let source = DataSource::File {
        path: "sample.csv".to_string(),
        format: FileFormat::Csv,
        size_bytes: 42,
        modified_at: None,
        parquet_metadata: None,
    };

    assert!(source.is_file());
    assert_eq!(FileFormat::Csv.to_string(), "csv");
    assert!(matches!(OutputFormat::Json, OutputFormat::Json));
}

#[test]
fn parser_and_metrics_reexports_compile() {
    let numeric_values = vec!["1".to_string(), "2".to_string(), "3".to_string()];
    let text_values = vec![
        "alice@example.com".to_string(),
        "bob@example.com".to_string(),
    ];

    assert_eq!(infer_type(&numeric_values), DataType::Integer);
    assert_eq!(analyze_column_fast("n", &numeric_values).name, "n");
    let _numeric_stats = calculate_numeric_stats(&numeric_values);
    let _text_stats = calculate_text_stats(&text_values);
    let _patterns = detect_patterns(&text_values, Some("US"));

    let csv_config = CsvParserConfig::strict()
        .with_delimiter(b';')
        .has_header(true)
        .max_rows(Some(10));
    assert_eq!(csv_config.delimiter, Some(b';'));

    let jsonl_config = JsonParserConfig::jsonl().with_max_rows(10);
    assert_eq!(jsonl_config.format, Some(JsonFormat::Jsonl));
    assert_eq!(
        JsonParserConfig::json_array().format,
        Some(JsonFormat::JsonArray)
    );
}

#[cfg(feature = "parquet")]
#[test]
fn parquet_facade_reexports_compile() {
    use dataprof::ParquetConfig;

    let config = ParquetConfig::batch_size(1_024);
    assert_eq!(config.batch_size, 1_024);
    assert_eq!(ParquetConfig::adaptive_batch_size(0), 1_024);
}

#[cfg(feature = "database")]
#[test]
fn database_facade_reexports_compile() {
    use dataprof::{DataProfilerError, DatabaseConfig, DatabaseConnector, create_connector};

    let _config = DatabaseConfig {
        connection_string: "sqlite::memory:".to_string(),
        load_credentials_from_env: false,
        ..Default::default()
    };

    let _factory: fn(DatabaseConfig) -> Result<Box<dyn DatabaseConnector>, DataProfilerError> =
        create_connector;
}

/// Regression: `Profiler::format()` must override extension-based detection,
/// even on the auto engine path that previously short-circuited to Parquet
/// based on the `.parquet` file extension.
#[test]
fn format_override_beats_extension() {
    use std::io::Write;

    let mut tmp = tempfile::Builder::new()
        .suffix(".parquet")
        .tempfile()
        .expect("tmpfile");
    writeln!(tmp, "city,population").unwrap();
    writeln!(tmp, "Rome,2873").unwrap();
    writeln!(tmp, "Milan,1352").unwrap();
    tmp.flush().unwrap();

    let report = Profiler::new()
        .format(FileFormat::Csv)
        .analyze_file(tmp.path())
        .expect("forced CSV parse of .parquet-named file should succeed");

    assert_eq!(report.execution.columns_detected, 2);
}

#[cfg(feature = "async-streaming")]
#[test]
fn async_streaming_facade_reexports_compile() {
    use dataprof::{AsyncSourceInfo, AsyncStreamingProfiler, BytesSource};
    use dataprof_engines::streaming::{IncrementalProfiler, MemoryMappedCsvReader};

    let info = AsyncSourceInfo::new("inline", FileFormat::Csv).size_hint(Some(4));
    let _source = BytesSource::new(bytes::Bytes::from_static(b"a\n1\n"), info);
    let _profiler = AsyncStreamingProfiler::new();
    let _incremental = IncrementalProfiler::new()
        .chunk_size(ChunkSize::Fixed(256))
        .sampling(SamplingStrategy::None)
        .stop_condition(StopCondition::Never);
    let _reader_type_size = std::mem::size_of::<MemoryMappedCsvReader>();
}