This is an alternative to using next(), about 2%-5% faster:

values = list(range(1, 10000000))

def first_value(items):
    for item in items:
        if item > 9999999:  # Your condition
            return item
    return None  # Default value

value = first_value(values)

This is the benchmark.

The following are 3 alternatives, with benchmarks.

Using next()

The one-liner:

values = list(range(1, 10000000))

value = next((x for x in values if x > 9999999), None)

Using a function

This is an alternative to using next() using a function, it's about 2%-5% faster:

values = list(range(1, 10000000))

def first(items):
    for item in items:
        if item > 9999999:  # Your condition
            return item
    return None  # Default value

value = first(values)

Using lambda

This is a function that can be used for replacing next() in all cases. Performance are about 300% slower:

values = list(range(1, 10000000))

def first(items, condition, default = None):
    for item in items:
        if condition(item):
            return item
    return default

value = first(values, lambda x: x > 9999999, None)

Benchmarks

• Function: 1x
• Next: 1.02x-1.05x
• Lambda: > 3x

Memory consumption is on par.

This is the benchmark.

This is an alternative to using next(), about 2%-5% faster:

values = list(range(1, 10000000))

def first_value(items):
    for item in items:
        if item > 9999999: # Your condition
            return item

value = first_value(values)

This is the benchmark.

This is an alternative to using next(), about 2%-5% faster:

values = list(range(1, 10000000))

def first_value(items):
    for item in items:
        if item > 9999999:  # Your condition
            return item
    return None  # Default value

value = first_value(values)

This is the benchmark.