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lukasmartinelli/pgfutter: Import CSV and JSON into PostgreSQL the easy way

Import CSV and line delimited JSON into PostgreSQL the easy way. This small tool abstract all the hassles and swearing you normally have to deal with when you just want to dump some data into the database.

Features:

• Generated import tables (pgfutter csv <file> and you're done)
• Good performance using the COPY streaming protocol
• Easy deployment
• Dealing with import errors
• Import over the network
• Only supports UTF8 encoding

Check out pgclimb for exporting data from PostgreSQL into different data formats.

You can download a single binary for Linux, OSX or Windows.

OSX

wget -O pgfutter https://github.com/lukasmartinelli/pgfutter/releases/download/v1.2/pgfutter_darwin_amd64
chmod +x pgfutter

./pgfutter --help

Linux

wget -O pgfutter https://github.com/lukasmartinelli/pgfutter/releases/download/v1.2/pgfutter_linux_amd64
chmod +x pgfutter

./pgfutter --help

Install from source

go get github.com/lukasmartinelli/pgfutter

If you are using Windows or 32-bit architectures you need to download the appropriate binary yourself.

pgfutter will deal with CSV files conforming to RFC 4180.

Create friends.csv.

name,age,friends
Jacob,26,"Anthony"
Anthony,25,""
Emma,28,"Jacob,Anthony"

Import the CSV file.

Because header rows are already provided pgfutter will create the appropriate table and copy the rows.

pgfutter will only help you to get the data into the database. After that SQL is a great language to sanitize and normalize the data according to your desired database schema.

CREATE TABLE public.person (
    name VARCHAR(200) PRIMARY KEY,
    age INTEGER
)

CREATE TABLE public.friendship (
    person VARCHAR(200) REFERENCES public.person(name),
    friend VARCHAR(200) REFERENCES public.person(name)
)

INSERT INTO public.person
SELECT name, age::int
FROM import.friends

WITH friends AS
    (SELECT name as person, regexp_split_to_table(friends, E'\\,') AS friend
    FROM import.friends)
INSERT INTO public.friendship
SELECT * FROM
friends WHERE friend <> ''

A lot of event logs contain JSON objects nowadays (e.g. GitHub Archive). pgfutter expects each line to have a valid JSON object. Importing JSON is only supported for Postgres 9.3 and Postgres 9.4 due to the JSON type.

Create friends.json.

{"name": "Jacob", "age": 26, "friends": ["Anthony"]}
{"name": "Anthony", "age": 25, "friends": []}
{"name": "Emma", "age": 28, "friends": ["Jacob", "Anthony"]}

Import the JSON file.

pgfutter json friends.json

Your JSON objects will be stored in a single JSON column called data.

PostgreSQL has excellent JSON support which means you can then start normalizing your data.

CREATE TABLE public.person (
    name VARCHAR(200) PRIMARY KEY,
    age INTEGER
)

CREATE TABLE public.friendship (
    person VARCHAR(200) REFERENCES public.person(name),
    friend VARCHAR(200) REFERENCES public.person(name)
)

INSERT INTO public.person
SELECT data->>'name' as name, (data->>'age')::int as age
FROM import.friends

INSERT INTO public.friendship
SELECT data->>'name' as person, json_array_elements_text(data->'friends')
FROM import.friends

Database connection details can be provided via environment variables or as separate flags.

Quite often you want to specify a custom delimiter (default: ,).

pgfutter csv -d "\t" traffic_violations.csv

You have to use " as a quoting character and \ as escape character. You might omit the quoting character if it is not necessary.

If you want to use tab as delimiter you need to pass $'\t' as delimiter to ensure your shell does not swallow the correct delimiter.

pgfutter csv -d $'\t' traffic_violations.csv

If you want to specify the field names explicitly you can skip the header row and pass a comma separated field name list.

pgfutter csv --skip-header --fields "name,state,year" traffic_violations.csv

If you don't have a header row in a document you should specify the field names as well.

pgfutter csv --fields "name,state,year" traffic_violations.csv

All CSV files need to be utf-8 encoded. No other encoding is supported. Encoding is a nasty topic and you should deal with it before it enters the database.

A lot of CSV files don't confirm to proper CSV standards. If you want to ignore errors you can pass the --ignore-errors flag which will commit the transaction even if some rows cannot be imported. The failed rows will be written to stdout so you can clean them up with other tools.

pgfutter --ignore-errors csv traffic_violations.csv 2> traffic_violations_errors.csv

This works the same for invalid JSON objects.

pgfutter will take the sanitized filename as the table name. If you want to specify a custom table name or import into your predefined table schema you can specify the table explicitly.

pgfutter --table violations csv traffic_violations.csv

For more sophisticated needs you should take a look at pgloader.

The program is tested with open data sets from around the world.

Download all samples into the folder samples.

Run import regression tests against the samples.

We use gox to create distributable binaries for Windows, OSX and Linux.

docker run --rm -v "$(pwd)":/usr/src/pgfutter -w /usr/src/pgfutter tcnksm/gox:1.9

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