Read and write data without further ado.

data, json, yaml, csv, read, write, file
pip install daj==0.1.0


Build Status


Are you terminally annoyed by the number of unaesthetic lines you have to write when the only thing you need is just reading and parsing some fracking data?

Well if this is the case, daj is made for you!

daj's philosophy is to enable you to read and write popular data formats in one simplistic line.

No more of the following nonsense:

import codecs
import json

with codecs.open('path/to/your-fracking-data.json', 'r', encoding='utf-8') as jf:
    data = json.load(jf)

Now, you just write:

from daj import daj

data = daj < 'path/to/your-fracking-data.json'

daj is your quick & dirty scripting companion. No more annoying boilerplate code: you start coding things that matter right now!


With pip

pip install daj

To install the latest dev version

pip install git+https://github.com/Yomguithereal/python-daj.git

Formats supported

  • plain text
  • json
  • yaml
  • csv
  • tsv


Note that if you do not provide a method to daj, this one will try to guess your format by analyzing the file's extension.

So if you have a twisted mind and like to name csv files table.json, well first of all you are a sneaky bastard, second, just use the proper daj method.

# Guessing the format
data = daj < 'file.json'

# Will also work with raw text
data = daj < 'file.txt'

# Using daj methods
data = daj.json < 'file.json'
data = daj.yml < 'file.yml'
data = daj.csv < 'file.csv'
data = daj.tsv < 'file.tsv'

# Needing headers for your neat CSV files?
data = daj.csvh < 'file.csv'
data = daj.tsvh < 'file.tsv'


As for reading, daj will try to guess the correct format for your data based on the extension of the file.

# Writing some data
daj(data) > 'file.json'

# Will also work with raw text
daj(data) > 'file.txt'

# Using daj methods
daj.json(data) > 'file.json'
daj.yml(data) > 'file.yml'

# If you want to ouput a pretty printed json
daj.pjson(data) > 'prettyfile.json'

# For csv, you can give an array of arrays or an array of objects
# If an array of objects is given, daj will output a csv with headers.
daj.csv(data) > 'file.csv'
daj.tsv(data) > 'file.tsv'


daj is clearly orientated toward quick & dirty data processing. This is probably a bad idea to use it in a production context and I would not vouch for that.


Contribution are more than welcome, be sure to add relevant unit tests and pass them all before subitting any code.

# To install dev environment (preferably in a virtualenv)
pip install -r requirements.txt

# To run unit tests