PERF: json_normalize, for basic use case
- [X] closes #15621
- [X] tests passed
- [X] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them

Proposed speed up for very simple use cases using the `pd.json_normalize` function. E.g. `pd.json_normalize(data)`

The speed up can be seen in this example:
```
import datetime
import pandas as pd

# example json data
data = {"hello": ["thisisatest", 999898, datetime.date.today()],
        "nest1": {"nest2": {"nest3": "nest3_value", "nest3_int": 3445}},
        "nest1_list": {"nest2": ["blah", 32423, 546456.876, 92030234]},
        "hello2": "string"}

hundred_thousand_rows = [data for i in range(100000)]

s = time()
pd.json_normalize(hundred_thousand_rows)
pandas_json_normalize_time_taken = time() - s
print(f"\npandas time taken for a 100,000 rows: {pandas_json_normalize_time_taken} seconds")
```

With output from Pandas 1.2.2: `pandas time taken for a 100,000 rows: 3.0518009662628174 seconds`
From this branch: `pandas time taken for a 100,000 rows: 0.632451057434082 seconds`

To show tests pass for the appropriate file, ran `pytest pandas/tests/io/json/test_normalize.py -v` [test_normalize.py_pytest.log](https://github.com/pandas-dev/pandas/files/6039361/test_normalize.py_pytest.log)

To show pre-commit passed on file, ran `pre-commit run --files pandas/io/json/_normalize.py` [_normalize.py_pre-commit.log](https://github.com/pandas-dev/pandas/files/6039363/_normalize.py_pre-commit.log)

There was one code check that was caught, running `./ci/code_checks.sh` [code_checks.log](https://github.com/pandas-dev/pandas/files/6039360/code_checks.log)

```
pandas/io/json/_normalize.py:208: error: Incompatible types in assignment (expression has type "List[Union[List[Dict[Any, Any]], Dict[Any, Any]]]", variable has type "Dict[Any, Any]")  [assignment]
```
As it a type hint issue, decided to still make pull request. Can you advice on how to fix, I'm fairly new to type hints?

Kind regards,
Sam