Unfamiliar Notation in Sakurai

This is notation from Distribution Theory in Functional Analysis. The theory of distributions is meant to make things like the Dirac Delta rigorous.

In this context, just to give you one overview, a distribution is a functional on the space of test functions. We define the space of test functions over $\mathbb{R}$ as $\mathcal{D}(\mathbb{R})$ being the space of smooth functions with compact support (that is, the set where they are not zero is bounded and closed).

In that case, the space of distributions is the space of continuous linear functionals over $\mathcal{D}(\mathbb{R})$ and is denoted as $\mathcal{D}'(\mathbb{R})$. If $\eta\in \mathcal{D}'(\mathbb{R})$ and $\phi\in \mathcal{D}(\mathbb{R})$ we usually denote $\eta(\phi)$ by $(\eta,\phi)$. Since distributions are just linear functionals, we say that two distributions $\eta,\zeta$ are equal if $(\eta,\phi)=(\zeta,\phi)$ for all $\phi\in \mathcal{D}(\mathbb{R})$.

The Dirac Delta, for instance, is defined as $\delta\in \mathcal{D}'(\mathbb{R})$ whose action on $\phi\in \mathcal{D}(\mathbb{R})$ is $(\delta,\phi)=\phi(0)$. Now, given $\phi\in\mathcal{D}(\mathbb{R})$ one can always build a distribution associated with it:

$$(\phi,\psi)=\int_{-\infty}^{\infty}\phi(x)\psi(x)dx, \qquad \forall \ \psi\in \mathcal{D}(\mathbb{R}).$$

There are other ways, though, to make one usual function into a distribution, even if the function is not a test function. One of them is the principal value. Consider $f(x) = \frac{1}{x}$. This obviously doesn't have compact support, so $f\notin \mathcal{D}(\mathbb{R})$. We can make $f$ into a distribution, though, by considering the principal value:

$$\left(\operatorname{Pv}\frac{1}{x},\phi\right)=\lim_{\epsilon\to 0^+}\left(\int_{-\infty}^{-\epsilon}\dfrac{\phi(x)}{x}dx+\int_\epsilon^\infty \dfrac{\phi(x)}{x}dx\right).$$

This is what the book means by $\operatorname{Pr}$.

Now, the formula you state is the Sokhotski–Plemelj formula. It should be read in the distributional sense. Saying that:

$$\lim_{\epsilon\to 0}\frac{1}{x+i\epsilon}=\operatorname{Pr}\frac1x -i\pi\delta(x).$$

Really means that for all $\phi\in \mathcal{D}(\mathbb{R})$ we have

$$\lim_{\epsilon\to 0}\left(\frac{1}{x+i\epsilon},\phi\right)=\left(\operatorname{Pr}\frac1x,\phi\right) -i\pi\left(\delta(x),\phi\right),$$

where

$$\left(\frac{1}{x+i\epsilon},\phi\right)=\int_{-\infty}^{\infty}\dfrac{\phi(x)}{x+i\epsilon}dx.$$

This is not a peculiar physicist notation oddly enough. The notation allows one to interpret $1/x$ as a distribution (which makes sense since it's being added to the delta distribution on the right hand side of the equation). For a suitable test function $\varphi$, one defines this distribution as $$ \mathrm{pv}(1/x)(\varphi) = \lim_{\epsilon\to 0+}\int_{\mathbb R\setminus [-\epsilon, \epsilon]} \frac{\varphi(x)}{x}\, dx $$ As noted by user anon0909, this distribution is called the principal value of $1/x$. Given this definition, the equation that appears in Sakurai should be interpreted as $$ \lim_{\epsilon\to 0^+} \int_{-\infty}^{\infty} \frac{\varphi(x)}{x + i\epsilon} = \lim_{\epsilon\to 0+}\int_{\mathbb R\setminus [-\epsilon, \epsilon]} \frac{\varphi(x)}{x}\, dx - i\pi\varphi(0) $$