old_contents: import time
  import numpy as np
  import logging
  import subprocess
  import signal
  import sys
  import time
  import os
  import json
  
  FORMAT = '%(asctime)-15s %(message)s'
  logging.basicConfig(format=FORMAT,level=logging.DEBUG)
  logger = logging.getLogger('imgserver')
  
  def camera_active():
      # is the camera running?
      cmd = "ps aux |grep raspistill -n -w"
      lines = subprocess.check_output(cmd,shell=True)
      for line in lines.decode("utf-8").split('\n'):
          if '-awb off' in line:
              return True
      return False
  
  
  def single_image_raspistill(filename='test.jpg', exp=20000000):
      if camera_active():
          return False
      annot = "%Y-%m-%d  %H:%M:%S"
      cmd = f"raspistill -n -w 1012 -h 760 -ISO 800 -ss {exp} -awb off -a 8 -a '{annot}' -o {filename}"
      proc = subprocess.Popen(cmd.split(), shell=False)
      for n in range(0,100):
          if proc.poll() is None:
              time.sleep(0.5)
              proc.send_signal(signal.SIGUSR1)
      if proc.returncode == 0:
          sys.stdout.write(f'Image {filename} Captured')
      else:
          sys.stderr.write(f'Problem with camera')
          sys.stderr.write(f"{proc.stderr}")
      return proc.pid
  
  def check_image_status(pid):
      """ Check For the existence of a unix pid. """
      try:
          os.kill(pid, 0)
      except OSError:
          return json.dumps({'status':'complete'})
      else:
          return json.dumps({'status':'runnning'})
  
  def scale_data(data):
      '''
      Scale image
      - Find the 99.5% value
      - Make all values above 99.5% value white
      '''
      data[data<0.]=0.
      median = np.median(data)
      data-= median
      data[data<0.]=0.
      sc_data= data #np.arcsinh(data)
      max_val = np.percentile(sc_data,99.5)
      logging.warning('99.5 =%s' % max_val)
      scaled = sc_data*255./(max_val)
      scaled[scaled>255]=255
      logging.warning('Median of scaled=%s' % np.median(scaled))
      logging.warning('Min scaled=%s' % scaled.min())
      return scaled
  
  
  if __name__ == '__main__':
      single_image_raspistill()
  
new_contents: import time
  import numpy as np
  import logging
  import subprocess
  import signal
  import sys
  import time
  import os
  import json
  
  FORMAT = '%(asctime)-15s %(message)s'
  logging.basicConfig(format=FORMAT,level=logging.DEBUG)
  logger = logging.getLogger('imgserver')
  
  def camera_active():
      # is the camera running?
      cmd = "ps aux |grep raspistill -n -w"
      lines = subprocess.check_output(cmd,shell=True)
      for line in lines.decode("utf-8").split('\n'):
          if '-awb off' in line:
              return True
      return False
  
  
  def single_image_raspistill(filename='test.jpg', exp=20000000):
      if camera_active():
          return False
      annot = "%Y-%m-%dT%H:%M:%S"
      cmd = f"raspistill -n -w 1012 -h 760 -ISO 800 -ss {exp} -awb off -a 8 -a '{annot}' -o {filename}"
      proc = subprocess.Popen(cmd.split(), shell=False)
      for n in range(0,100):
          if proc.poll() is None:
              time.sleep(0.5)
              proc.send_signal(signal.SIGUSR1)
      if proc.returncode == 0:
          sys.stdout.write(f'Image {filename} Captured')
      else:
          sys.stderr.write(f'Problem with camera')
          sys.stderr.write(f"{proc.stderr}")
      return proc.pid
  
  def check_image_status(pid):
      """ Check For the existence of a unix pid. """
      try:
          os.kill(pid, 0)
      except OSError:
          return json.dumps({'status':'complete'})
      else:
          return json.dumps({'status':'runnning'})
  
  def scale_data(data):
      '''
      Scale image
      - Find the 99.5% value
      - Make all values above 99.5% value white
      '''
      data[data<0.]=0.
      median = np.median(data)
      data-= median
      data[data<0.]=0.
      sc_data= data #np.arcsinh(data)
      max_val = np.percentile(sc_data,99.5)
      logging.warning('99.5 =%s' % max_val)
      scaled = sc_data*255./(max_val)
      scaled[scaled>255]=255
      logging.warning('Median of scaled=%s' % np.median(scaled))
      logging.warning('Min scaled=%s' % scaled.min())
      return scaled
  
  
  if __name__ == '__main__':
      single_image_raspistill()
  
subject: Add 't' to timestamp