  Roughly speaking, a near-best (abbr. NB) quasi-interpolant (abbr. QI) is an
approximation operator of the form $Q_af=\sum_{\alpha\in A} \Lambda_\alpha (f)
B_\alpha$ where the $B_\alpha$'s are B-splines and the $\Lambda_\alpha (f)$'s
are linear discrete or integral forms acting on the given function $f$. These
forms depend on a finite number of coefficients which are the components of
vectors $a_\alpha$ for $\alpha\in A$. The index $a$ refers to this sequence of
vectors. In order that $Q_a p=p$ for all polynomials $p$ belonging to some
subspace included in the space of splines generated by the $B_\alpha$'s, each
vector $a_\alpha$ must lie in an affine subspace $V_\alpha$, i.e. satisfy some
linear constraints. However there remain some degrees of freedom which are used
to minimize $\Vert a_\alpha \Vert_1$ for each $\alpha\in A$. It is easy to
prove that $\max \{\Vert a_\alpha \Vert_1 ; \alpha\in A\}$ is an upper bound of
$\Vert Q_a \Vert_{\infty}$: thus, instead of minimizing the infinite norm of
$Q_a$, which is a difficult problem, we minimize an upper bound of this norm,
which is much easier to do. Moreover, the latter problem has always at least
one solution, which is associated with a NB QI. In the first part of the paper,
we give a survey on NB univariate or bivariate spline QIs defined on uniform or
non-uniform partitions and already studied by the author and coworkers. In the
second part, we give some new results, mainly on univariate and bivariate
integral QIs on {\sl non-uniform} partitions: in that case, NB QIs are more
difficult to characterize and the optimal properties strongly depend on the
geometry of the partition. Therefore we have restricted our study to QIs having
interesting shape properties and/or infinite norms uniformly bounded
independently of the partition.
