iparq

After reading this blog, I began to wonder which Parquet version and compression methods the everyday tools we rely on actually use, only to find that there's no straightforward way to determine this. That curiosity and the difficulty of quickly discovering such details motivated me to create iparq (Information Parquet). My goal with iparq is to help users easily identify the specifics of the Parquet files generated by different engines, making it clear which features—like newer encodings or certain compression algorithms—the creator of the parquet is using.

Features

• Bloom filters: Detects real Bloom-filter metadata and reports its size. Read more in this great article.
• Encodings and types: Shows physical and logical types plus encodings such as RLE_DICTIONARY, DELTA_BINARY_PACKED, and BYTE_STREAM_SPLIT.
• Indexes and dictionary pages: Reports dictionary pages, column indexes, and offset indexes.
• Statistics: Displays min/max values and available null and distinct counts.
• Row groups and sort order: Shows row-group sizes, row counts, and declared sorting columns.
• Page locations: Reports column-chunk, dictionary-page, data-page, and Bloom-filter offsets.
• Schema details: Includes legacy converted types, decimal precision/scale, nesting levels, and GeoParquet statistics availability.
• Compression: Shows codecs with optional column sizes and compression ratios.
• Machine-readable output: Emits JSON for scripts and agent workflows.

iParq requires Python 3.10 or later.

Installation

Zero installation - Recommended

1. Make sure to have Astral's UV installed by following the steps here:

   https://docs.astral.sh/uv/getting-started/installation/

2. Execute the following command:

   uvx --refresh iparq inspect yourparquet.parquet
   

Using pip

1. Install the package using pip:

   pip install iparq
   

2. Verify the installation by running:

   iparq --help
   

Using uv

1. Make sure to have Astral's UV installed by following the steps here:

   https://docs.astral.sh/uv/getting-started/installation/

2. Execute the following command:

   uv pip install iparq
   

3. Verify the installation by running:

   iparq --help
   

Using Homebrew in a MAC

1. Run the following:

   brew tap MiguelElGallo/tap https://github.com/MiguelElGallo//homebrew-iparq.git
   brew install MiguelElGallo/tap/iparq
   iparq --help
   

Usage

iparq supports inspecting single files, multiple files, and glob patterns:

iparq inspect <filename(s)> [OPTIONS]

Options include:

• --format, -f: Output format, either rich (default) or json
• --metadata-only, -m: Show only file metadata without column details
• --column, -c: Filter results to show only a specific column
• --sizes, -s: Show column sizes and compression ratios
• --details, -d: Show row groups, sort order, encodings, types, indexes, page locations, Bloom-filter size, and detailed statistics

Single File Examples:

# Basic inspection .
iparq inspect yourfile.parquet

# Output in JSON format
iparq inspect yourfile.parquet --format json

# Show only metadata
iparq inspect yourfile.parquet --metadata-only

# Filter to show only a specific column
iparq inspect yourfile.parquet --column column_name

# Show column sizes and compression ratios
iparq inspect yourfile.parquet --sizes

# Show storage-level details
iparq inspect yourfile.parquet --details

Multiple Files and Glob Patterns:

# Inspect multiple specific files
iparq inspect file1.parquet file2.parquet file3.parquet

# Use glob patterns to inspect all parquet files
iparq inspect *.parquet

# Use specific patterns
iparq inspect yellow*.parquet data_*.parquet

# Combine patterns and specific files
iparq inspect important.parquet temp_*.parquet

When inspecting multiple files, each file's results are displayed with a header showing the filename. The utility will read the metadata of each file and print the compression codecs used in the parquet files.

For scripts and agents, add --format json. A single file produces one JSON object; multiple files produce one JSON array whose entries include file. Diagnostics are written to stderr, and any unreadable input makes the command exit non-zero without corrupting successful JSON output.

Agent discovery

iParq publishes CLI and Agent Skill documentation, an Agentic Resource Discovery (ARD) catalog, an agent-readable documentation index, and a portable Parquet inspection skill. The catalog advertises the existing read-only CLI and its JSON output; it does not add a network service or change how iParq accesses files.

Projects that declare iParq as a dependency can install the version-matched skill bundled in the Python package:

uv add iparq
uvx library-skills install --skill iparq-parquet-inspector --yes

This creates a project-local .agents/skills/iparq-parquet-inspector symlink to the skill in the installed iParq package. It is separate from ephemeral CLI execution with uvx iparq, which does not add iParq to the project environment.

Example output

ParquetMetaModel(
    created_by='parquet-cpp-arrow version 14.0.2',
    num_columns=3,
    num_rows=3,
    num_row_groups=1,
    format_version='2.6',
    serialized_size=2223,
    key_value_metadata_keys=['ARROW:schema', 'pandas']
)
                                     Parquet Column Information                                      
┏━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━┓
┃ Row Group ┃ Column Name ┃ Index ┃ Compression ┃ Bloom ┃ Min Value ┃ Max Value ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━┩
│     0     │ one         │   0   │ SNAPPY      │  ❌   │ -1.0      │ 2.5       │
│     0     │ two         │   1   │ SNAPPY      │  ❌   │ bar       │ foo       │
│     0     │ three       │   2   │ SNAPPY      │  ❌   │ False     │ True      │
└───────────┴─────────────┴───────┴─────────────┴───────┴───────────┴───────────┘
Compression codecs: {'SNAPPY'}

With --sizes flag

iparq inspect yourfile.parquet --sizes

                                         Parquet Column Information                                         
┏━━━━━━━━┳━━━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━┓
┃  Row   ┃ Column  ┃       ┃        ┃       ┃           ┃           ┃        ┃        ┃       ┃
┃ Group  ┃ Name    ┃ Index ┃ Compr… ┃ Bloom ┃ Min Value ┃ Max Value ┃ Values ┃ Compr… ┃ Ratio ┃
┡━━━━━━━━╇━━━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━┩
│   0    │ one     │   0   │ SNAPPY │  ❌   │ -1.0      │ 2.5       │      3 │ 104.0B │  1.0x │
│   0    │ two     │   1   │ SNAPPY │  ❌   │ bar       │ foo       │      3 │  80.0B │  0.9x │
│   0    │ three   │   2   │ SNAPPY │  ❌   │ False     │ True      │      3 │  42.0B │  1.0x │
└────────┴─────────┴───────┴────────┴───────┴───────────┴───────────┴────────┴────────┴───────┘