Though you already have an accepted answer, I figured I'd add this for anyone else interested in a different solution-

• The csv module's DictReader object has a public attribute called fieldnames (as of Python 2.6 and above). https://docs.python.org/3.4/library/csv.html#csv.csvreader.fieldnames

An implementation could be as follows:

import csv

with open('C:/mypath/to/csvfile.csv', 'r') as f:
    dict_reader = csv.DictReader(f)

    #get header fieldnames from DictReader and store in list
    headers = dict_reader.fieldnames

    #sample file reading logic
    for line in dict_reader:
        print(line[headers[0]])
        

In the above, dict_reader.fieldnames returns a list of your headers (assuming the headers are in the top row). Which allows...

>>> print(headers)
['MyColumn1', 'MyColumn2', 'MyColumn3']

If your headers are in, say the 2nd row (with the very top row being row 1), you could do as follows:

import csv

with open('C:/mypath/to/csvfile.csv', 'r') as f:
    #you can eat the first line before creating DictReader.
    #if no "fieldnames" param is passed into
    #DictReader object upon creation, DictReader
    #will read the upper-most line as the headers
    f.readline()
    
    dict_reader = csv.DictReader(f)
    headers = dict_reader.fieldnames

    #sample file reading logic
    for line in dict_reader:
        print(line[headers[0]])

The easiest way is to just set:

reader.fieldnames = "email", "name", "id",  "phone"

You can save the old fieldnames if you want too.

You are looking for DictReader

with open('info.csv') as f:
    reader = csv.DictReader(f, delimiter=';')
    for row in reader:
        name = row['name']
        blah = row['blah']

to quote from the link:

Create an object which operates like a regular reader but maps the information read into a dict whose keys are given by the optional fieldnames parameter. ... If the fieldnames parameter is omitted, the values in the first row of the csvfile will be used as the fieldnames.

I'd say your best bet is to do a simple assert that heading is not None:

try:
    with open("inpu.csv", newline="") as f:
        reader = csv.DictReader(f, skipinitialspace=True)
        headings = reader.fieldnames
        assert headings is not None
        assert len(headings) == 3

        menu: list[list[str]] = []
        for row in reader:
            menu.append([row[headings[0]], row[headings[1]], row[headings[2]]])
except IOError as e:
    print(f"couldn't open CSV: {e}")
except AssertionError:
    print(
        f"couldn't get fieldnames, check CSV and ensure first line is a properly encoded row"
    )
else:
    print(menu)

If it fails, you'll know to look at the CSV file for any kind of issues.

• Before the assert, VSCode shows that headings could be Sequence[str] | None.
• After the assert, the type checker realizes that it cannot have been None, so headings must be Sequence[str].

Also, look at Barmar's and Mark Tolonen's comments, you can do what you much more simply by just reading the CSV as a list of strings:

reader = csv.reader(f)
menu = list(reader)[1:]

print(menu)

[
    ["foo", "1", "a"],
    ["bar", "2", "b"],
    ["baz", "3", "c"],
]

The DictReader stores the fields (dict keys) in an property called fieldnames:

fields = dictreader.fieldnames
print(fields)
# ['Attributes', 'Description', 'Dial-Up']

So to print the row values in this order:

print(','.join(fields))
for row in dictreader:
    print(','.join(row[field] for field in fields))

yields

Attributes,Description,Dial-Up
4,2,0.2
3,1,0.4

Or, using @JonClements' idea:

import operator
fields = dictreader.fieldnames
getfields = operator.itemgetter(*fields)
for row in dictreader:
    print(','.join(getfields(row)))

The motivation for using operator.itemgetter would be that it is faster than using a list comprehension:

In [70]: %timeit getfields(row)
10000000 loops, best of 3: 174 ns per loop

In [71]: %timeit [row[field] for field in fields]
1000000 loops, best of 3: 272 ns per loop