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fix: docs indentation #2448

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16 changes: 8 additions & 8 deletions docs/usage/settings.md
Expand Up @@ -22,19 +22,19 @@ _(This script is complete, it should run "as is")_
The following rules are used to determine which environment variable(s) are read for a given field:

* By default, the environment variable name is built by concatenating the prefix and field name.
* For example, to override `special_function` above, you could use:
* For example, to override `special_function` above, you could use:

export my_prefix_special_function='foo.bar'
export my_prefix_special_function='foo.bar'

* Note 1: The default prefix is an empty string.
* Note 2: Field aliases are ignored when building the environment variable name.
* Note 1: The default prefix is an empty string.
* Note 2: Field aliases are ignored when building the environment variable name.

* Custom environment variable names can be set in two ways:
* `Config.fields['field_name']['env']` (see `auth_key` and `redis_dsn` above)
* `Field(..., env=...)` (see `api_key` above)
* `Config.fields['field_name']['env']` (see `auth_key` and `redis_dsn` above)
* `Field(..., env=...)` (see `api_key` above)
* When specifying custom environment variable names, either a string or a list of strings may be provided.
* When specifying a list of strings, order matters: the first detected value is used.
* For example, for `redis_dsn` above, `service_redis_dsn` would take precedence over `redis_url`.
* When specifying a list of strings, order matters: the first detected value is used.
* For example, for `redis_dsn` above, `service_redis_dsn` would take precedence over `redis_url`.

!!! warning
Since **v1.0** *pydantic* does not consider field aliases when finding environment variables to populate settings
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36 changes: 18 additions & 18 deletions docs/usage/types.md
Expand Up @@ -279,37 +279,37 @@ types:

* `datetime` fields can be:

* `datetime`, existing `datetime` object
* `int` or `float`, assumed as Unix time, i.e. seconds (if >= `-2e10` or <= `2e10`) or milliseconds (if < `-2e10`or > `2e10`) since 1 January 1970
* `str`, following formats work:
* `datetime`, existing `datetime` object
* `int` or `float`, assumed as Unix time, i.e. seconds (if >= `-2e10` or <= `2e10`) or milliseconds (if < `-2e10`or > `2e10`) since 1 January 1970
* `str`, following formats work:

* `YYYY-MM-DD[T]HH:MM[:SS[.ffffff]][Z or [±]HH[:]MM]]]`
* `int` or `float` as a string (assumed as Unix time)
* `YYYY-MM-DD[T]HH:MM[:SS[.ffffff]][Z or [±]HH[:]MM]]]`
* `int` or `float` as a string (assumed as Unix time)

* `date` fields can be:

* `date`, existing `date` object
* `int` or `float`, see `datetime`
* `str`, following formats work:
* `date`, existing `date` object
* `int` or `float`, see `datetime`
* `str`, following formats work:

* `YYYY-MM-DD`
* `int` or `float`, see `datetime`
* `YYYY-MM-DD`
* `int` or `float`, see `datetime`

* `time` fields can be:

* `time`, existing `time` object
* `str`, following formats work:
* `time`, existing `time` object
* `str`, following formats work:

* `HH:MM[:SS[.ffffff]][Z or [±]HH[:]MM]]]`
* `HH:MM[:SS[.ffffff]][Z or [±]HH[:]MM]]]`

* `timedelta` fields can be:

* `timedelta`, existing `timedelta` object
* `int` or `float`, assumed as seconds
* `str`, following formats work:
* `timedelta`, existing `timedelta` object
* `int` or `float`, assumed as seconds
* `str`, following formats work:

* `[-][DD ][HH:MM]SS[.ffffff]`
* `[±]P[DD]DT[HH]H[MM]M[SS]S` (ISO 8601 format for timedelta)
* `[-][DD ][HH:MM]SS[.ffffff]`
* `[±]P[DD]DT[HH]H[MM]M[SS]S` (ISO 8601 format for timedelta)

```py
{!.tmp_examples/types_dt.py!}
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20 changes: 10 additions & 10 deletions docs/usage/validators.md
Expand Up @@ -11,10 +11,10 @@ A few things to note on validators:
of `UserModel`.
* the second argument is always the field value to validate; it can be named as you please
* you can also add any subset of the following arguments to the signature (the names **must** match):
* `values`: a dict containing the name-to-value mapping of any previously-validated fields
* `config`: the model config
* `field`: the field being validated. Type of object is `pydantic.fields.ModelField`.
* `**kwargs`: if provided, this will include the arguments above not explicitly listed in the signature
* `values`: a dict containing the name-to-value mapping of any previously-validated fields
* `config`: the model config
* `field`: the field being validated. Type of object is `pydantic.fields.ModelField`.
* `**kwargs`: if provided, this will include the arguments above not explicitly listed in the signature
* validators should either return the parsed value or raise a `ValueError`, `TypeError`, or `AssertionError`
(``assert`` statements may be used).

Expand All @@ -25,13 +25,13 @@ A few things to note on validators:

* where validators rely on other values, you should be aware that:

- Validation is done in the order fields are defined.
E.g. in the example above, `password2` has access to `password1` (and `name`),
but `password1` does not have access to `password2`. See [Field Ordering](models.md#field-ordering)
for more information on how fields are ordered
* Validation is done in the order fields are defined.
E.g. in the example above, `password2` has access to `password1` (and `name`),
but `password1` does not have access to `password2`. See [Field Ordering](models.md#field-ordering)
for more information on how fields are ordered

- If validation fails on another field (or that field is missing) it will not be included in `values`, hence
`if 'password1' in values and ...` in this example.
* If validation fails on another field (or that field is missing) it will not be included in `values`, hence
`if 'password1' in values and ...` in this example.

## Pre and per-item validators

Expand Down