Let's apply this technique to a more transparent question.
CLAIM: $0.333\ldots < 1/3$
Proof: We induct on the number of decimal digits. Clearly, $0.3 < 1/3$. Now, by induction, if $n$ digits of $0.333\ldots 3 < 1/3$, than in particular $3 \cdot 0.333\ldots3 = 0.999\ldots900 < 1$, and so $0.999\ldots 990$ (i.e. with one more $9$ digit) $<1$, and thus it holds for $n+1$ as well. So by induction, the claim is proven.
What's wrong with this? Induction is a proof for all natural numbers, not for $\infty$. It's clear that $0.333\ldots = 1/3$. But any finite decimal representation is less than $1/3$. And the induction only shows that any finite decimal representation is, in fact, less than $1/3$.
This is the same flaw at the heart of the $\pi$ rational argument.
I think this calculation would have been doable in 1873, as follows:
(1) Compute $\log \pi$ to $60$ digits. For this, we begin with the expansion
$$\log \pi = \log \left(\frac{\pi}{22/7}\right)+\log 2 + \log 11-\log 7$$
and take full advantage of the fact that the logarithm tables of small integers were known to great precision. As for the logarithm of $\pi/(22/7) \approx 1.00041$, the Taylor series for the logarithm spits out $60$ digits after only $17$ terms. (Surprisingly, this exact analysis has been done on MSE before.)
(2) Compute $(\pi+1)\log \pi$ to $60$ digits. This is no big deal, given our value for $\log \pi$ from (1), since $\pi$ was known (to Gauss, no less!) to at least $100$ digits back in 1844. For reference, this value is
$$ \approx 4.7410048855785583722294291029994190930164741026691888020108672.$$
(The multiplication will of course be a pain, as it requires around $1800$ flops. Nevertheless, this computation would likely be delegated to a lesser mathematician. The Wikipedia article on Zacharias Dase (a temporary assistant to Gauss) puts these computations into perspective:
At age 15 [Zacharias Dase] began to travel extensively, giving exhibitions in Germany, Austria and England. Among his most impressive feats, he multiplied 79532853 × 93758479 in 54 seconds. He multiplied two 20-digit numbers in 6 minutes; two 40-digit numbers in 40 minutes; and two 100-digit numbers in 8 hours 45 minutes. The famous mathematician Carl Friedrich Gauss commented that someone skilled in calculation could have done the 100-digit calculation in about half that time with pencil and paper.
(3) Exponentiate the product, again to $60$ places. Using just the series
$$e^z = \sum_{k=0}^\infty \frac{z^k}{k!}$$
such a calculation would require $77$ terms. For this reason, we instead calculate
$$e^{4.741} \approx 114.54869311801681310751748724665811195370661075419665168411647;$$
$$e^{0.0000048\cdots} \approx 1.0000048855904928305900123833767696556988185632721564706179420.$$
The latter approximation requires a mere $10$ terms of the exponential Taylor series to achieve $60$ digits, a commitment of around 18000 flops. By Gauss's metric, we might expect a skilled mathematician to complete this task in just over seven hours.
The prior calculation could be done in one of two ways: directly, at a cost of another $18000$ flops (e.g. $77$ consecutive multiplications of a $4$-digit and a $60$-digit number); or by calculating $\mathrm{exp}(4)$ and $\mathrm{exp}(.741)$ independently (a slight time savings, I believe, even after the final multiplication). Of course, now it just takes another $1800$ flops to multiply these numbers to $60$ places.
Note: In hindsight, it appears that calculating the triple product
$$e^4 e^{3/4}e^{-9/1000}$$
may expedite this most recent step.
In case you've lost track, we now know the value of
$$e^{(\pi +1)\log \pi}=\pi^{\pi+1}$$
to $60$ digits, all within a day or two of starting our calculations.
(4) Multiply $\log \pi$ and $\pi^{\pi+1}$ to $60$ digits. This step is easy, given steps (1) and (3). This value is
$$\approx 131.12795303153615589452803943707399841542170349230159549341360.$$
Of course, this value is also the logarithm of $(\pi^\pi)^{\pi^\pi}$, so it remains to:
(5) Exponentiate the term from (4). Since it worked out so well in (3), we'll again split our exponential into a product of simpler terms. Here, we luck out - since the binary expansion of $131.127953\ldots$ begins as
$$10000011.001000001100000\cdots_2,$$
the partial approximation $131+1/8$ is surprisingly accurate: to within $\approx 0.002953$. The exponential of this remainder can be made accurate to over $60$ digits with a mere $18$ terms (i.e. $32000$ flops).
Secondly, we compute $e^{131}$ to $60$ digits, using iterated multiplication and an approximation of $e$ to $62$ digits ($205$ digits were known to William Shanks in 1871). Since it suffices here to successively compute
$$e^2,e^4,e^8,e^{16},e^{32},e^{64},e^{128},$$
this step can be done in less than $15000$ flops. Thirdly, we compute $e^{1/8}$ to $60$ digits using three applications of Newton's method for the square root (another $6000$ flops). We find a value of
$$ \approx 887455172183124295874631455225434602688412866765466125005\color{red}{.16},$$
a non-integer.
All said and done, I would be surprised if this calculation took much longer than a week. At the same time, I stress that this problem would have been barely doable in that era. If twice the number of digits were required, for example, this work may very well have taken the better part of a year.
Best Answer
That number has 666262452970848504 decimal places, so to determine if it's an integer you'd have to compute it with that precision. But this would take 270,000 TB, and we don't have many hard drives that large.