Python filter data from given string

Question

I have below data:

data = """
item: apple
store name: USA_1
store id: 1000
total: 200

item: apple
store name: USA_2
store id: 1001
total: 230

item: apple
store name: USA_3
store id: 1002
total: 330

item: apple
store name: UK1
store id: 2000
total: 20

item: apple
store name: UK_2
store id: 1021
total: 230
"""

I have to get store dict format like below:

{' USA_1': ' 1000', ' USA_2': ' 1001', ' USA_3': ' 1002', ' UK1': ' 2000', ' UK_2': ' 1021'}

I have written below code which will obtain above output:

STORE_NAME_GATHERED = []
STORE_IDS_GATHERED = []
STORE_info = {}
for line in data.split("\n"):
    line = line.strip()
    if line.startswith("store name:"):
        name = line.split(":")[1]
        if not name in  STORE_NAME_GATHERED:
            STORE_NAME_GATHERED.append(name)
    elif line.startswith("store id:"):
        id = line.split(":")[1]
        if not id in STORE_IDS_GATHERED:
            STORE_IDS_GATHERED.append(id)
            STORE_info[name] = id
print(STORE_info)

I am getting expected results from above code, However it is not a best code to achieve above output and not reliable, Can some one help me with right code to achieve same results with reliable manner

what do you mean reliable?

Nikos M.
– Nikos M.

2019-05-13 12:05:09 +00:00
Commented May 13, 2019 at 12:05 — Nikos M.
– Nikos M., Commented May 13, 2019 at 12:05

Rakesh · Accepted Answer · 2019-05-13 12:05:27Z

5

Using regex

Ex:

import re


data = """
item: apple
store name: USA_1
store id: 1000
total: 200

item: apple
store name: USA_2
store id: 1001
total: 230

item: apple
store name: USA_3
store id: 1002
total: 330

item: apple
store name: UK1
store id: 2000
total: 20

item: apple
store name: UK_2
store id: 1021
total: 230
"""

name = re.findall(r"store name: (.*)", data)   #Get Store Name
store = re.findall(r"store id: (.*)", data)    #Get Store ID

print(dict(zip(name, store)))

Output:

{'UK1': '2000',
 'UK_2': '1021',
 'USA_1': '1000',
 'USA_2': '1001',
 'USA_3': '1002'}

answered May 13, 2019 at 12:05

Rakesh

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