## Overview
Sometimes our direct dependency declares outdated intermediate dependency or is too tight to solve with other direct dependencies. In this case, we can override the intermediate dependency in our `pyproject.toml`or `pixi.toml` file.
> [!Note] This option is not recommended unless you know what you are doing, as uv will ignore all the version constraints of the dependency and use the version you specified.
## Example
### Override a dependency version
```toml
# pyproject.toml
[tool.pixi.pypi-options.dependency-overrides]
numpy = ">=2.0.0"
```
or in `pixi.toml`:
```toml
# pixi.toml
[pypi-options.dependency-overrides]
numpy = ">=2.0.0"
```
This will override the version of `numpy` used by all dependencies to be at least `2.0.0`, regardless of what the dependencies specify.
This is useful if you need a specific version of a library that is not compatible with the versions specified by your dependencies.
### Override a dependency version in a specific feature
it can also be specified in feature level,
```toml
[features.dev.pypi-options.dependency-overrides]
numpy = ">=2.0.0"
```
This will override the version of `numpy` used by all dependencies in the `dev` feature to be at least `2.0.0`, regardless of what the dependencies specify when the `dev` feature is enabled.
### Interact with other overrides
For a specific environment, all the `dependency-overrides` defined in different features will be combined in the order they were defined.
If the same dependency is overridden multiple times, we'll use the override from the **prior** feature in that environment.
Also, the default feature will always come, and come last in the list of all overrides.
```toml
# pixi.toml
[pypi-options]
dependency-overrides = { numpy = ">=2.1.0" }
[pypi-dependencies]
numpy = ">=1.25.0"
[feature.dev.pypi-options.dependency-overrides]
numpy = "==2.0.0"
[feature.outdated.pypi-options.dependency-overrides]
numpy = "==1.21.0"
[environments]
dev = ["dev"]
outdated = ["outdated"]
conflict_a=["outdated", "dev"]
conflict_b=["dev","outdated"]
```
the following constrains are merged out:
default: `numpy >= 2.1.0`
dev: `numpy == 2.0.0`
outdated: `numpy == 1.21.0`
conflict_a: `numpy == 1.21.0` (from `outdated`)
conflict_b: `numpy == 2.0.0` (from `dev`)
This may contrast with the intuition that all overrides are applied and combined to a result. It
is done this way to avoid conflicts and confusion: Since users are granted fully control over the
overrides, it is up to them to choose the right overrides for an environment.
