Google Earth Engine export

I am exporting a single image and a collection of Landsat raw images from Google Earth Engine using Python, but all my images are in black and white. Should they be like that? Isn’t there a way of getting coloured Landsat images. I am very new.
Below is my code:

# Import libraries.
import ee
import webbrowser

# Trigger the authentication flow.
# ee.Authenticate()

# Initialize the library.
ee.Initialize()

# Access a collection
collection = 'LANDSAT/LC08/C01/T1' #Landsat 8 Collection

#Landsat_composite in Nithi area
area_nithi = list([(37.288, 0.172), (38.333, 0.172), (38.333, -0.568), (37.288, -0.568), (37.288, 0.172)])
area_nithi = ee.Geometry.Polygon(area_nithi)
time_range_nithi = ['2017-01-01', '2017-12-31']

collection_nithi = ('LANDSAT/LC08/C01/T1')
print(type(area_nithi))

#Methods from climada.util.earth_engine module
def obtain_image_landsat_composite(collection, time_range, area):
    """ Selection of Landsat cloud-free composites in the Earth Engine library
    See also: https://developers.google.com/earth-engine/landsat

    Parameters:
        collection (): name of the collection
        time_range (['YYYY-MT-DY','YYYY-MT-DY']): must be inside the available data
        area (ee.geometry.Geometry): area of interest

    Returns:
        image_composite (ee.image.Image)
     """
    collection = ee.ImageCollection(collection)

    ## Filter by time range and location
    collection_time = collection.filterDate(time_range[0], time_range[1])
    image_area = collection_time.filterBounds(area)
    image_composite = ee.Algorithms.Landsat.simpleComposite(image_area, 75, 3)
    return image_composite

#Application to examples
composite_nithi = obtain_image_landsat_composite(collection_nithi, time_range_nithi, area_nithi)


#Selection of specific bands from an image
nithi_band = composite_nithi.select(['B4', 'B3', 'B2'])

nithi_bandVis = {
  min: 0.0,
  max: 30000.0,
}
print(composite_nithi.getInfo())

print(type(nithi_band))

print(type(nithi_bandVis))

def get_region(geom):
    """Get the region of a given geometry, needed for exporting tasks.

    Parameters:
        geom (ee.Geometry, ee.Feature, ee.Image): region of interest

    Returns:
        region (list)
    """
    if isinstance(geom, ee.Geometry):
        region = geom.getInfo()["coordinates"]
    elif isinstance(geom, ee.Feature, ee.Image):
        region = geom.geometry().getInfo()["coordinates"]
    elif isinstance(geom, list):
        condition = all([isinstance(item) == list for item in geom])
        if condition:
            region = geom
    return region


region_nithi = get_region(area_nithi)

def get_url(name, image, imageVis, scale, region):
    """It will open and download automatically a zip folder containing Geotiff data of 'image'.
    If additional parameters are needed, see also:
    https://github.com/google/earthengine-api/blob/master/python/ee/image.py

    Parameters:
        name (str): name of the created folder
        image (ee.image.Image): image to export
        scale (int): resolution of export in meters (e.g: 30 for Landsat)
        region (list): region of interest

    Returns:
        path (str)
     """
    path = image.getDownloadURL({
        'name':(name),
        'scale': scale,
        'region':(region)
        })

    webbrowser.open_new_tab(path)
    return path



#url_nithi = get_url('nithi', median_swiss, 900, region_swiss)
url_nithi = get_url('nithi0.1', composite_nithi, 900, region_nithi)
#url_landcover = get_url('landcover_swiss', landCover_layer, 100, region_swiss)

#For the example of nithi, due to size, it doesn't work on Jupyter Notebook but it works on Python
url_nithi2 = get_url('nithi0.2', nithi_band, nithi_bandVis, 1000, region_nithi)


print(url_nithi)
print(url_nithi2)