typedtsv 0.6.0

A simple format for typed TSVs with an implementation in Python

typedtsv

Typed TSV: A simple format for typing TSVs with an implementation in Python 3.

Why?

JSON, YAML, TOML and other simple formats aren't built for list/table like sets of data.

YAML is particularly slow due to its expansive featureset and JSON, being that is for single objects and not collections, is not chunkable. I once stored all PyPI package info in a YAML file and reading it back out was going to take half a day. Using a dead-simple newline-delimited JSON format made parsing take seconds.

Newline-delimited JSON is convenient with little chance of making mistakes in parsing and good performance. The downsides are the types supported are a bit too limited (no int vs float), and it is also not easily human readable or editable.

TOML is particularly targeted towards configuration files and similarly parses results in a single dictionary object rather than a collection.

CSV/TSV formats have too much ambiguity resulting in repetitive custom parsing logic contained outside the file itself. CSV quote escaping can also lead to poor parsing performance.

Goals

• Be simple
• Be fast
• Be easily parallelized
• Be a better alternative to CSV/TSV/JSON and simple uses of YAML
• Push information about a dataset into the data file itself for future reproducibility

Use Cases in Mind

• Database-agnostic, program-agnostic simple file format for open data
• A quick go-to serialization format for sharing reproducible data science datasets
• Easily-created, easily-editable, easily-understood database fixtures for tests

Non-Goals

• Unlimited extensibility a la YAML
• Config files. Focus is on lists of objects/tabular data

Format

Format is a normal TSV except the header rows uses a colon format to annotate the type:

<col_name>:<col_type>\t<col_name2>:<coL_type2>...

For example:

# I'm a comment and will be ignored
url:str    n_times:int   score:float
https://www.example.com 5   1.6
https://archive.org 99  9.9

Initial pass centered around Python's basic types plus JSON. Current valid types are:

Type	Notes
int
float
bool	Valid values: true, false, t, f, yes, no, y, n, 1, 0
str	Newlines, tabs, , and # must be escaped
datetime	'2011-01-01 00:00:00' Without timezone assumes UTC
json
null	All types are nullable with value 'null'. To get literal string 'null', use '\null'

Comments are supported, just prefix with #. Escape actual # in a string with a single backslash '\#'.

Row separators use '\n' only. Windows line breaks, '\r\n' are not valid.

Gotcha: In Python, you need to be careful about opening files that may contain Windows newlines:

infile = open('data.ttsv', 'r', newline='\n')   # must set newline='\n' because default for newline is '\n' or '\r' or '\r\n'

We'll never allow quoted '\n' because this would make the file difficult to chunk and thus make it difficult to parallelize reading.

TODO:

• Add a boolean type
• Add nulls
• Add a datetime/date/time type: need to avoid ambiguity yet support common uses
• Maybe: extend format to support column comments / unit annotation / other common metadata
• Maybe: support array and map types for compatibility with Postgres
• Maybe: Support date, time, and/or timeinterval types

Developing

Make sure you have Poetry installed: https://github.com/sdispater/poetry

git clone [e-mail]:jimmybot/typedtsv.git
cd typedtsv
poetry install
poetry shell
pytest