Studying notes about Gamma function, I came across the following problem that I was unable to solve.
Let's be $\phi = \frac{d}{dx}(\log(F(x))),$ where $F(x) = \int_{0}^{+\infty} t^{x}e^{-t}dt$,
Forgetting for a second that we defined $\phi$ in the way above,
We were able with a lot of calculation to find that $\displaystyle\phi = \sum_{k=1}^{+\infty}\left[\frac{1}{k}-\frac{1}{k+t}\right]$ (which is convergent by comparison)
But we also found a function $\Phi$, $\displaystyle\Phi = \sum_{k=1}^{+\infty}\left[\frac{x}{k}-\log\left(1+\frac{x}{k}\right)\right]$ such that $\Phi'=\phi$.
The problem is that I'd like to solve is to show without any bigger theorem, just with calculations, that $$\sum_{k=1}^{+\infty}\left[\frac{1}{k}-\frac{1}{k+t}\right]$$converges uniformly under the uniform norm, on every $[a,b] \subseteq ]-1,+\infty[$, or equivalently that $\left\lVert \phi - \phi_{m}\right\rVert_{\infty,[a,b]} \underset{m\to \infty}{\longmapsto} 0$, where $\phi_{m}$ is the sum up to $m$.
In this way I think I could justify the following:
\begin{align} \int_{0}^{x}\phi(t)dt &= \int_{0}^{x}\sum_{k=1}^{+\infty}\left[\frac{1}{k}-\frac{1}{k+t}\right]dt \\&= \sum_{k=1}^{+\infty}\int_{0}^{x} \left[\frac{1}{k}-\frac{1}{k+t}\right]dt \\&= \sum_{k=1}^{+\infty}\left[\frac{x}{k}-\log\left(1+\frac{x}{k}\right)\right] \\&= \Phi(x) \end{align}
In other words that $$\int_{0}^{x}\phi(t)dt = \int_{0}^{x}\Phi'(t)dt = \Phi(x)-\Phi(0)=\Phi(x).$$
Is there a relatively simple way to do it?
Your $k$th summand equals $\dfrac{t}{k(k+t)}.$ We can thus write the series as
$$\sum_{k=1}^{\infty}\frac{t}{k(k+t)}.$$
This series converges uniformly on $[a,b]\subset (-1,\infty)$ iff the sum from $k=2$ to $\infty$ converges uniformly on $[a,b].$ For this range of $k,$ we can use Weierstrass M: Fix $-1<a<b.$ Then for $k\ge 2$ and $t\in [a,b]$ we have
$$\left |\frac{t}{k(k+t)}\right| \le \frac{|t|}{k(k-1)} \le \frac{|a|+|b|}{(k-1)^2}.$$
Since
$$\sum_{k=2}^{\infty}\frac{|a|+|b|}{(k-1)^2} = \frac{(|a|+|b|)\pi^2}{6} <\infty,$$
we have uniform convergence on $[a,b]$ by Weierstrass M.