Hash maps suna optimize algorithms ta yaya?

Question

Accepted Answer

A **hash map** (jerin-ƙoƙari) yana ba da **O(1) matsakaita** don neman abubuwa, saka, da gida. Musayar O(n) alaƙa don saurin jiya O(n²) algorithms zuwa O(n) ta hada da sake duba tare da abin da ba ma ji-fi sakamako.

## Tunani

Sai dai neman jerin abubuwa kowane lokaci, ma karbar jerin abubuwa da aka ga cikin hash map da gwaji membership a lokaci mai tsawo.

## Misali: two-sum a O(n)

```python
def two_sum(nums, target):
    seen = {}                          # value -> index
    for i, x in enumerate(nums):
        need = target - x
        if need in seen:               # O(1) lookup
            return (seen[need], i)
        seen[x] = i
    return None

two_sum([2, 7, 11, 15], 9)             # -> (0, 1)
```

Ba tare da taswira ba wannan shine O(n²); tare da shi, jere daya.

## Amfani da gida

- **Cire gida / membership** tare da saitin.
- **Kirgawa frequency** (`Counter`).
- **Gunawa / tsaka** ta maɓalli.
- **Kulli / ainihin tunani** na sakamako.

## Hadaddiyar

- **Matsakaita:** O(1) gida aiki. **Mafi dorewa:** O(n) kan haɗuwa mai nauyi. **Wurin:** O(n).

## Locaci mara kyau

Maɓallan dole ne su kasance **hashable** da rashin canji. Mafi dorewa-sura haɗuwa suna rage aiki. Hash maps ba su da umarnin (yi amfani da umarnin bambanta idan umarnin ya dace).

## Me ya sa yake matukar mahimmanci

Hashing shine saurin gida mafi yawa a kimantawa da'a codewa da ainihin tsari — yana juyar da "neman gida da gida" zuwa "bi da shi sau daya."

Musayar sarari don saurin aiki shine jirgin injin da aka yi maimaitawa.

Kirgawa frequency, kulli, da tsaka duka sun dogara akan wannan tunani daya.