Day 65: Data from unconventional json files in Python

Unconventional files

python json files

There are .json files that comes in all shapes and sizes.

And the structure differs from the classic scheme.

Sample .json structure

Let’s analyze the schema below.

We can see that we have 3 root keys: e, ok and data.

e –> Did you guess what it means? yes, Endpoint !

ok –> The data was returned to us. This is like an acknowledgement.

data –> A list of the data we requested.

See, if we wanted to refer to a particular pair, we just can’t refer to it by name.

So, we’ll have to find another way of referring to the items.

  "e": "tickers",
  "ok": "ok",
  "data": [
      "timestamp": "1615031084",
      "pair": "BTC:USD",
      "low": "47000",
      "high": "49514.4",
      "last": "48251",
      "volume": "89.36530799",
      "volume30d": "6651.52124769",
      "priceChange": "861.2",
      "priceChangePercentage": "1.82",
      "bid": 48119.7,
      "ask": 48250.3
      "timestamp": "1615031084",
      "pair": "ETH:USD",
      "low": "1455",
      "high": "1594.99",
      "last": "1559.3",
      "volume": "1937.83401000",
      "volume30d": "87819.24143600",
      "priceChange": "83.97",
      "priceChangePercentage": "5.69",
      "bid": 1557.33,
      "ask": 1563.47
      "timestamp": "1615031084",
      "pair": "BCH:USD",
      "low": "478.57",
      "high": "504.99",
      "last": "491.37",
      "volume": "79.93941602",
      "volume30d": "16639.56261792",
      "priceChange": "3.35",
      "priceChangePercentage": "0.69",
      "bid": 491.37,
      "ask": 496.19
      "timestamp": "1615031084",
      "pair": "DASH:USD",
      "low": "202.681",
      "high": "212.62",
      "last": "205.55",
      "volume": "296.77032892",
      "volume30d": "21556.63940289",
      "priceChange": "-1.205",
      "priceChangePercentage": "-0.58",
      "bid": 205.55,
      "ask": 208.134

The code

import json

#Our source filename, this is a downloaded file
filename = 'tickers_form.json'

#We start by opening our local .json
with open (filename) as json_file:
    data = json.load(json_file) #We load it as a python dictionary

#At this moment, it's important to know the size of the data key.
#This will help us know exactly how many items are there.
maxlen = len(data['data'])

#Output the size of the dictionary
print ('{}:{}'.format("Size is",maxlen))

#Here I input the pair that I am interested in.(my search)
looking_for = 'FUN:USD'

#We loop from 0(array start) to maxlen, which is the max size of the dictionary.
for i in range(0,maxlen):

    #Declare variables for all the data I am interested in
    market = data['data'][i]['pair']
    price = data['data'][i]['last']
    low = data['data'][i]['low']
    high = data['data'][i]['high']
    bid = data['data'][i]['bid']
    ask = data['data'][i]['bid']
    if (market == looking_for): #If the pair, matches our search, we print the results
        print ('{} {}:{}'.format(market, 'found! at position', i))
        print ('{}:{}'.format('Price',price))
        print ('{} {}'.format('Low', low))
        print ('{} {}'.format('High', high))
        print ('{} {}'.format('Bid', bid))
        print ('{} {}'.format('Ask', ask))


Size is:50
FUN:USD found! at position:47
Low 0.02936
High 0.0325
Bid 0.03144
Ask 0.03144

#Searching for BTT:USD

Size is:50
BTT:USD found! at position:10
Low 0.0011805
High 0.00125
Bid 0.0012331
Ask 0.0012331

All the explanation is in the comments.

In essence, instead of using keys to reference items, we are using indexes of each item to reference to it.

I hope you enjoyed this little article.

And have fun json’ing under python !!! :)

\ Codarren /

Written on March 6, 2021