Getting Satellite date based on stac

requirements.txt

GDAL==3.4.3
odc-stac==0.3.8
pystac-client==0.7.5
rasterio==1.3.9
numpy==1.26.3

satellie_stac.py

from pystac_client import Client
from odc.stac import load
import odc.geo
from datetime import date, timedelta
from osgeo import gdal
import rasterio as rio
from rasterio import mask as msk

today =  date.today() # get today's date
today_string = today.strftime("%Y-%m-%d")  # convert in string 
collection = "sentinel-2-l2a" # Satellite name  -> Checkout other available satellite IDs at https://earth-search.aws.element84.com/v1/collections 
feature_geometry = {
        "coordinates": [
          [
            [
              73.05683851936746,
              19.33321254579718
            ],
            [
              73.05664412469514,
              19.33253384375915
            ],
            [
              73.05713011137598,
              19.33198354273874
            ],
            [
              73.05714955084323,
              19.3329832548836
            ],
            [
              73.05683851936746,
              19.33321254579718
            ]
          ]
        ],
        "type": "Polygon"
      } # GeoJSON feature geometry

client = Client.open("https://earth-search.aws.element84.com/v1") # Pystac client init
try:
    search = client.search(collections=[collection], intersects=feature_geometry ,datetime=today_string) # Find all data for today's date
    data = load(search.items() ,geopolygon=feature_geometry, groupby="solar_day", chunks={}) # group collection based on day
    data["ndvi"] = (data.nir - data.red ) / (data.red + data.nir) # calculate ndvi
    odc.geo.xr.write_cog(data['ndvi'],fname=f"ndvi_old.tiff",  overwrite=True) # write ndvi to tiff in original CRS
    # Path to your input GeoTIFF file
    input_file = f"ndvi_old.tiff"
    # Path to save the reprojected GeoTIFF file
    output_file = f"ndvi_reprojected.tiff"
    # Define the target CRS (EPSG:4326)
    dst_crs = 'EPSG:4326'
    input_raster = gdal.Open(input_file)
    output_raster = output_file
    warp = gdal.Warp(output_raster, input_raster, dstSRS=dst_crs) # Convert tiff to EPSG:4326

    raster = rio.open(output_file)
    with raster as src:
        out_image, out_transform = msk.mask(
            src, [feature_geometry], crop=True
        )         # clip the tiff as per geometry
        out_meta = src.meta.copy()
        out_meta.update(
            {
                "driver": "GTiff",
                "height": out_image.shape[1],
                "width": out_image.shape[2],
                "transform": out_transform,
                "nodata": 0,
            }
        )
    farmpath = (f"ndvi.tiff")
    with rio.open(farmpath, "w", **out_meta) as dest:
        dest.write(out_image)
        dest.close() # write clipped tiff to ndvi.tiff
except:
    print('no data found for the date')