TabPro — Table Data Processor

TabPro is a command-line toolkit for reshaping tabular data, built for a specific situation: data that people produced by hand. Spreadsheets come back with columns renamed or added on a whim, rows that do not follow the spec, and values typed in the wrong format. TabPro is designed to detect those anomalies, separate them from the rest, transform what is left, and deliver it as JSON or JSON Lines.

If your input is already clean and machine-generated, tools like Miller, csvkit or DuckDB will serve you better and faster. TabPro does not try to compete with them on throughput or on breadth of features.

Installation

pip install tabpro

Requires Python 3.10 or later.

Supported formats

Format	Extension	Read	Write
CSV	`.csv`	✓	✓
TSV	`.tsv`	✓	✓
Excel	`.xlsx`	✓	✓
JSON	`.json`	✓	✓
JSON Lines	`.jsonl`	✓	✓

The format is chosen from the file extension, so conversion is just a matter of naming the output file:

tabpro convert annotations.xlsx --output delivery.jsonl

Excel cells are read as text so that dates and long numbers are not silently reinterpreted. Nested JSON values are flattened to dot-separated columns when written to CSV/TSV/Excel (user.name), and rebuilt into nested objects when written back to JSON/JSON Lines.

The staging area

This is the one concept worth reading before anything else, because it explains why an action may appear to do nothing.

Every row carries a hidden namespace called __staging__. Actions write their results into staging rather than into the row itself, and staging is discarded just before the row is written out.

So this command produces output identical to its input:

# The cast happens, but its result is discarded with the staging area.
tabpro convert input.csv --do 'cast:score=score:as=int' --output out.jsonl

You promote staged values into the output with --pick, which also declares the output schema and its column order:

tabpro convert input.csv \
  --do 'cast:score=score:as=int' \
  --pick id score \
  --output out.jsonl

{"id": "1", "score": 10}

The point is that intermediate values never pollute what you deliver. You can build up as many working values as a transformation needs and then state exactly which of them are part of the result.

--pick can also rename columns, with the new name on the left:

tabpro convert input.csv --pick 'user_id=id' 'display_name=name' --output out.jsonl

When an action looks up a field, it searches three places in order:

__staging__.<name> — a value produced by an earlier action
<name> — a column of the row itself
__staging__.__input__.<name> — the original input value, before any action

That ordering is what lets actions be chained: each one sees what the previous one produced.

To see the staging area instead of discarding it, pass --output-debug.

Commands

Every command is available both as a subcommand and as a standalone executable (tabpro convert = tabpro-convert = convert-tables). All of them accept --help, --verbose / -v and --version / -V.

convert — transform and change format

tabpro convert [options] <input_file>... --output <output_file>

Option	Description
`--output-file`, `--output`, `-O`	Output file path
`--output-file-filtered-out`, `-f`	Write rows removed by filters here, instead of dropping them
`--config`, `-c`	YAML configuration file
`--do-actions`, `--actions`, `--do`	Actions to apply (see below)
`--pick-columns`, `--pick`	Columns to emit, optionally renamed as `new=old`
`--action-delimiter`	Separator inside action strings (default `:`)
`--ignore-file-rows`, `--ignore`	Skip specific rows, given as `file:index`
`--no-header`	Treat CSV/TSV input as having no header row; columns become `0`, `1`, …
`--output-debug`	Keep the staging area in the output

Multiple input files are concatenated. --output-file-filtered-out is the one to reach for when triaging bad data: the rows a filter rejects are written to a separate file for inspection rather than quietly disappearing.

merge — apply hand-made corrections to a base table

tabpro merge --previous <base>... --new <corrections>... --keys <key>... [options]

Rows are matched on --keys. Every field present in a correction file overwrites the corresponding field of the matching base row.

Option	Description
`--previous-files`, `--previous`, `--old`, `-P`	Base files
`--modification-files`, `--new`, `-M`	Files holding the corrections
`--keys`, `-K`	Primary key columns
`--merge-fields`	Limit the merge to these fields (default: every field of the correction file)
`--output-base-data-file`, `--output-base`	All base rows, with corrections applied
`--output-modified-data-file`, `--output-modified`	Only the rows that were corrected
`--output-remaining-data-file`, `--output-remaining`	Only the rows that were not corrected
`--ignore-not-found`	Skip correction rows whose key is absent from the base, instead of failing
`--allow-duplicate-conventional-keys`	Permit duplicate keys in the base files
`--allow-duplicate-modification-keys`	Permit duplicate keys in the correction files
`--merge-staging`, `--use-staging`	Carry the staging area across the merge

--output-remaining-data-file is what tells you which rows are still waiting for someone to look at them.

aggregate — profile a table before trusting it

tabpro aggregate [options] <input_file>... --output <report.json>

Reports, per column: how many distinct values there are, which types appeared, the minimum and maximum length, and a value/count breakdown. Useful as a first pass over a batch of submissions, to see which columns hold something unexpected.

Option	Description
`--output-file`, `--output`, `-O`	Report path (`.json`), printed to the terminal when omitted
`--keys-to-show-duplicates`	List every duplicated value for these columns
`--keys-to-show-all-count`	List all value counts for these columns, not just the top ones
`--keys-to-expand`, `--expand`	Also aggregate array elements individually, by index
`--show-count-threshold`, `-C`	Above this many distinct values, show only a summary (default 50)
`--show-count-max-length`, `-L`	Truncate displayed values to this length (default 100)

sort

tabpro sort [options] <input_file>... --sort-keys <key>... --output <output_file>

Option	Description
`--sort-keys`, `--sort-key`, `-K`	Columns to sort by
`--output-file`, `--output`, `-O`	Output file path
`--reverse`, `-R`	Descending order

Values are compared as they are read, so numeric columns coming from CSV sort as strings. Use convert with cast first if that matters.

compare

tabpro compare [options] <file1> <file2> --query <key>... --output <diff_file>

Reports rows present in only one of the files, and per-field differences for rows present in both. Removed values are prefixed with -, added ones with +.

Option	Description
`--query-keys`, `--query`, `-Q`	Columns identifying a row (required)
`--compare-keys`, `--compare`, `-C`	Columns to compare (default: all)
`--output-path`, `--output`, `-O`	Output file path

Actions

Actions are given to convert via --do, one string per action:

<action-name>:<fields>[:<options>]

<fields> is a comma-separated list of target=source pairs — a bare name means target and source are the same. <options> is a comma-separated list of key=value pairs or bare flags. Remember that results land in staging, so --pick decides what actually reaches the output.

Action	Form	Options	Description
`assign`	`assign:t=s`	`default`, `required`, `ignore-empty`	Copy a value
`assign-constant`	`assign-constant:t=value`	`type` (`str`/`int`/`float`/`bool`)	Set a fixed value
`assign-format`	`assign-format:t={a}-{b}`	—	Build a string from other fields
`assign-id`	`assign-id:t=s`	`context`, `reverse`	Assign sequential integer ids per distinct value
`assign-length`	`assign-length:t=s`	—	Length of the value
`cast`	`cast:t=s`	`as` (`bool`/`int`/`float`/`str`), `required`, `default`	Convert the type
`filter`	`filter:field==value`	—	Keep matching rows (`==`, `!=`, `=~`)
`filter-empty`	`filter-empty:field`	—	Keep rows where the field is empty or absent
`filter-not-empty`	`filter-not-empty:field`	—	Keep rows where the field has a value
`join`	`join:t=s`	`delimiter` (default `;`)	Join an array into a string
`omit`	`omit:field`	`purge`	Remove a column; `purge` discards it instead of staging it
`parse`	`parse:t=s`	`as` (`bool`/`json`/`literal`), `required`, `default`	Parse a string into a value
`parse-json`	`parse-json:t=s`	`required`	Shorthand for `parse` with `as=json`
`push`	`push:t=s`	`condition`	Append a value to an array
`replace`	`replace:t=s`	`old`, `new`, `count`, `recursive`	Replace a substring
`split`	`split:t=s`	`delimiter`	Split a string into an array

Rows rejected by a filter are dropped unless --output-file-filtered-out is given.

# Separate rows whose id does not look like a 4-digit number,
# rather than losing them.
tabpro convert submissions.xlsx \
  --do 'filter:id=~^[0-9]{4}$' \
  --output valid.jsonl \
  --output-filtered-out rejected.jsonl

Configuration file

Anything repeated often belongs in a YAML file passed with --config. Command-line --do and --pick are applied in addition to it.

# Columns to emit, in this order.
# Use a list to keep the names as they are...
pick:
  - id
  - name

# ...or a mapping to rename them, with the new name as the key.
# (a list and a mapping cannot be mixed in one `pick` block)
#
# pick:
#   id: id
#   score: raw_score

process:
  # Fixed values
  assign_constants:
    source_batch: 2026-04

  # Strings built from other fields
  assign_formats:
    label: '{name} ({id})'

  # Length of a field
  assign_length:
    name_length: name

  # Sequential ids per distinct value.
  # A list uses several columns as the key; `context` numbers
  # independently within each group.
  assign_ids:
    speaker_id: speaker_name
    utterance_id:
      primary: [speaker_name, utterance]
      context: [document_id]

  # Collect several fields into an array
  assign_array:
    choices:
      - choice_a
      - field: choice_b
        optional: true

  # Keep only matching rows.
  # operator: == != =~ not-in empty not-empty
  filter:
    - field: status
      operator: '=='
      value: done

  # Append to an array, optionally only when another field is truthy
  push:
    - target: notes
      source: comment
      condition: has_comment

  # Split a string into an array
  split:
    tags:
      field: raw_tags
      delimiter: ';'

Known limitations

Memory. The whole input is held in memory; a 30 MB JSON Lines file needs roughly 500 MB. Fine for spreadsheets, not for very large exports.
Almost no stdout. Only aggregate writes its report to standard output when --output is omitted. The other commands write to the file named by --output and cannot be used in the middle of a shell pipeline.
Action options cannot contain a comma, because options are themselves comma-separated. split:t=s:delimiter=, does not work.
sort compares values as they are read, so CSV columns sort as text.

License

MIT. See LICENSE.

Metadata

Release files for tabpro 0.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for tabpro 0.6.0
File	Size	Uploaded	Provenance
tabpro-0.6.0.tar.gz	38.1 kB	Sep 18, 2026	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for tabpro 0.6.0
File	Interpreter	ABI	Platform	Reset
tabpro-0.6.0-py3-none-any.whl 54.5 kB Sep 18, 2026 Without provenance	Python 3	none	any	Details

Total release size: 92.6 kB

Release files / tabpro-0.6.0.tar.gz

Download URL	tabpro-0.6.0.tar.gz
Size	38.1 kB
Tags	Source
SHA-256 checksum How to use checksums	`bf5ad84222cc0f67e9358e917ab4c419e342277f9206df33aef99cbfe81396e7`
BLAKE2b-256 checksum How to use checksums	`8e47bf6d1a4088b4648c1bf428e165e3fd57f91a8f0d39d1c7ad9085e59c4a78`
Upload date	Sep 18, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/2.4.3 CPython/3.13.11 Linux/6.18.33.2-microsoft-standard-WSL2`

Release files / tabpro-0.6.0-py3-none-any.whl

Download URL	tabpro-0.6.0-py3-none-any.whl
Size	54.5 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`143000226c44371dfda29c8a0fcf3ab8f3cde138c90a05d93e90046b8dde2ce3`
BLAKE2b-256 checksum How to use checksums	`324885a8b1d3514cb8213e47c29d6b9dfaed03ccc46a55417601ced8c10628a6`
Upload date	Sep 18, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/2.4.3 CPython/3.13.11 Linux/6.18.33.2-microsoft-standard-WSL2`

Security for tabpro 0.6.0

Report project as malware

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.