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How to jump to a particular line in a huge text file with Python?

Sometimes, we want to jump to a particular line in a huge text file with Python.

In this article, we’ll look at how to jump to a particular line in a huge text file with Python.

How to jump to a particular line in a huge text file with Python?

To jump to a particular line in a huge text file with Python, we’ve to read the file.

For instance, we write

# ...
line_offset = []
offset = 0
for line in file:
    line_offset.append(offset)
    offset += len(line)
file.seek(0)

# ...

file.seek(line_offset[n])

to loop through the file and append the offset to the line_offset list.

Then we add the line‘s length to the offset.

Next, we rewind back to the start of the file with file.seek called with 0.

And then we call file_seek again to jump to the offset with

file.seek(line_offset[n])

Conclusion

To jump to a particular line in a huge text file with Python, we’ve to read the file.

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How to list imported modules with Python?

Sometimes, we want to list imported modules with Python.

In this article, we’ll look at how to list imported modules with Python.

How to list imported modules with Python?

To list imported modules with Python, we can use the modulefinder module.

For instance, we write

from modulefinder import ModuleFinder

finder = ModuleFinder()
finder.run_script("myscript.py")
for name, mod in finder.modules.items():
    print(name)

to create a ModuleFinder object.

Then we call run_script on the object with the path of the script that we want to list the imported modules for.

Then we loop through the dict returned with the module name as the keys with a for loop.

In it, we print the name of the imported module traversed by the loop.

Conclusion

To list imported modules with Python, we can use the modulefinder module.

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How to URL decode UTF-8 in Python?

Sometimes, we want to URL decode UTF-8 in Python

In this article, we’ll look at how to URL decode UTF-8 in Python.

How to URL decode UTF-8 in Python?

To URL decode UTF-8 in Python, we can use the urllib.parse module’s unquote function.

For instance, we write

from urllib.parse import unquote

url = unquote(url)

to call unquote with the url we want to decode to decode the url URL string.

Then returned string is a Unicode string.

Conclusion

To URL decode UTF-8 in Python, we can use the urllib.parse module’s unquote function.

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How to add days to a date in Python?

Sometimes, we want to add days to a date in Python.

In this article, we’ll look at how to add days to a date in Python.

How to add days to a date in Python?

To add days to a date in Python, we can use the datetime.timedelta function.

For instance, we write

import datetime

date_1 = datetime.datetime.strptime(start_date, "%m/%d/%y")
end_date = date_1 + datetime.timedelta(days=10)

to create a date from the start_date date string with strptime.

Then we create a time delta object with timedelta with the days argument set to the number of days we want to add.

Then we add the time delta object to date_1 to return a new date with 10 days added to date_1.

Conclusion

To add days to a date in Python, we can use the datetime.timedelta function.

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How to find row where values for column is maximal in a Python Pandas DataFrame?

Sometimes, we want to find row where values for column is maximal in a Python Pandas DataFrame.

In this article, we’ll look at how to find row where values for column is maximal in a Python Pandas DataFrame.

How to find row where values for column is maximal in a Python Pandas DataFrame?

To find row where values for column is maximal in a Python Pandas DataFrame, we can use the idxmax method.

For instance, we write

import pandas
import numpy as np

df = pandas.DataFrame(np.random.randn(5,3),columns=['A','B','C'])
index_max = df['A'].idxmax()

to create a data frame with some random numbers in columns A, B and C with

df = pandas.DataFrame(np.random.randn(5,3),columns=['A','B','C'])

Then we get the index with the max value of column A with

index_max = df['A'].idxmax()

Conclusion

To find row where values for column is maximal in a Python Pandas DataFrame, we can use the idxmax method.