Coding topics to refresh

Python

Be comfortable with:

from collections import Counter

counts = Counter(items)

for index, item in enumerate(items):
    ...

for name, score in zip(names, scores):
    ...

users.sort(key=lambda user: user.created_at)

users = sorted(users, key=lambda user: user.name)

descending:

sorted(users, key=lambda user: user.score, reverse=True)

if any(user.active for user in users):
    ...

if all(user.valid for user in records):
    ...

highest = max(records, key=lambda r: r.score)

Remember the distinction:

values = [expensive(x) for x in items]

creates the entire list.

Whereas:

values = (expensive(x) for x in items)

is lazy.

For a large dataset:

for item in read_records():
    process(item)

can be much better than loading everything into memory.

Also remember:

yield

for generator functions.

This could easily come up if they give you data-processing work.

You may see:

async def fetch():
    result = await client.get(...)
    return result

Remember:

Don't use async just because it's available.

A useful interview line:

“This workload is I/O-bound, so async could help if we're making many independent external calls.”

And if you have several independent calls:

results = await asyncio.gather(
    fetch_a(),
    fetch_b(),
    fetch_c(),
)

Know what that means, but don't worry about advanced asyncio.

Know how to: