How can I easily implement vectorized numba, numpy to this code

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Python3.6

Here is the code:

<pre>import concurrent.futures as cf
from cryptotools.BTC.HD import check, WORDS

N_THREADS = 192
result = []

def doWork(data):
    for line in data:
        stripped_line = line.strip()
        for word in WORDS:
            mnemonic = stripped_line.format(x=word)
            if check(mnemonic):
               result.append(mnemonic)

m_input = open("input.txt", "r")
lines = [line for line in m_input]
#the data for the threads will be here
#as a list of rows for each thread
m_data= { i: [] for i in range(0, N_THREADS)} 
for l, n in zip(lines, range(0, len(lines))):
    m_data[n%N_THREADS].append(l)
'''
If you have to trim the number of threads uncomment these lines
m_data= { k:v for k, v in m_data.items() if len(v) != 0}
N_THREADS = N_THREADS if len(m_data) > N_THREADS else len(m_data)
if(N_THREADS == 0): 
    exit()
'''
with cf.ThreadPoolExecutor(max_workers=N_THREADS) as tp:
    for d in m_data.keys():
        tp.submit(doWork,m_data[d])
    
#work done
output = open("print.txt", "w")
for item in result:
    output.write(f"{item}\n")
output.close()

The text file being processed looks something likes but with 100k-300k lines
gloom document {x} stomach uncover peasant sock minor decide special roast rural
happy seven {x} gown rally tennis yard patrol confirm actress pledge luggage
tattoo time {x} other horn motor symbol dice update outer fiction sign
govern wire {x} pill valid matter tomato scheme girl garbage action pulp

What I have tried:

The code above is fast just need it to work faster, but have no idea how to implement numba and numpy ove the functions