Memory leak with pyplot

When I create matplotlib.pyplot plots, the memory keeps increasing and is not released by the garbage collector. The following is the case I'm interested in (with subplots) and bellow I include a more basic MWE.

Example with subplots

```julia
using PyCall
plt = pyimport("matplotlib.pyplot")

function test_pyplot()
for i in 1:10000
@info i
z = rand(4, 50)
ẑ = rand(4, 50)
fig, axs = plot_pyplot(z, ẑ)
end
end

function plot_pyplot(z, ẑ)
# plt = pyimport("matplotlib.pyplot")
N = Int(size(z, 1)/2)
fig, axs = plt.subplots(2, N)
for i in 1:N
axs[1,i].plot(z[i,:], label = "true")
axs[1,i].plot(ẑ[i,:], label = "model")

axs[2,i].plot(z[i+N,:], label = "true")
axs[2,i].plot(ẑ[i+N,:], label = "predicted")

axs[2,i].set_xlabel("time steps")
axs[i].grid(true)
axs[i+N].grid(true)

axs[i+N].label_outer()
axs[i].label_outer()
end
# plt.close()
return fig, axs
end

test_pyplot()
```

I tried defining `plt` and closing it inside the `plot_pyplot` function (commented lines) but it doesn't solve the memory leak.

Here you have a simpler MWE:
```julia
using PyCall
plt = pyimport("matplotlib.pyplot")

plot_pyplot(z) = plt.plot(z)

function test_pyplot()
for i in 1:1000000
@info i
z = rand(50)
fig = plot_pyplot(z)
end
end
```

Version info and status

```julia
julia> versioninfo()
Julia Version 1.8.2
Commit 36034abf260 (2022-09-29 15:21 UTC)
Platform Info:
OS: macOS (arm64-apple-darwin21.3.0)
CPU: 8 × Apple M1 Pro
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-13.0.1 (ORCJIT, apple-m1)
Threads: 1 on 6 virtual cores
```

```julia
(memory_leak) pkg> st
Status `~/Documents/issues/memory_leak/Project.toml`
[438e738f] PyCall v1.94.1
```

I need to use pyplot directly from PyCall.jl and not through PyPlot.jl because I need to pass the fig object to Wandb.jl. Actually, maybe I could get that object from PyPlot.jl, I didn't try that yet. But since I found the bug here, I think it can be helpful to report it anyway.

Start with the supplied Julia MWE and the PyCall calls to pyplot, comparing memory use with and without plot creation and garbage collection. Trace the returned fig and plot objects through PyCall; done means identifying and fixing the retained references so repeated plotting no longer causes unbounded memory growth.

Scritto dal modello di indicizzazione a partire dal testo della issue.