After a comment was made here I was reminded of this question. After a while I was able to solve my issues, I wrote a little tutorial of how to export imagery in my [github page](https://github.com/nicolas-suarez/landsat_8_tutorial), but the most relevant to me was the following:

- Defining my area to be clipped didn't worked after using `bounds`, so I ended up doing the following to convert the patch around the pixel to an `ee.Geometry.Rectangle` object:

```
    region= point.buffer(len/2).bounds().getInfo()['coordinates']
    #defining the rectangle
    coords=np.array(region)
    #taking min and maxs of coordinates to define the rectangle
    coords=[np.min(coords[:,:,0]), np.min(coords[:,:,1]), np.max(coords[:,:,0]), np.max(coords[:,:,1])]
    rectangle=ee.Geometry.Rectangle(coords)
``` 

- The rest of the problems were associated to the arguments used when exporting the function. To clip the image, I used `image.filterBounds(rectangle).mean()`, where image is an `ee.ImageCollection` object, and `rectangle` is the previously defined geometry. Using `mean()` converts this to an `ee.Image` object. 

   With that done, I added the following arguments to either the `ee.batch.Export.image.toDrive`or `ee.batch.Export.image.toCloudStorage` besides the obvious ones (like the image we are exporting or the destination of the file:
   
   * `region=str(region)` to pass the previous list of coordinates of the geometry as a string.
   * `dimensions="33x33"` to pass the number of pixels to be included in the image.

- When the image was exported to either of the sources, I used the `imageio` package, and did something like `np.array(imageio.imread(image_path))` to convert the image from `TIFF` to an `np.array`.