title: Progress bar (using tqdm) prints in a new line everytime the update is called on the tqdm object (VSCode terminal)
body: <p>I am trying to print the status of the progress of an optimization algorithm using the tqdm module available in Python, however, every time I try to update it, it prints the progress in a new line, is there a way I could only update the original tqdm bar which is being instantiated at the beginning? My code is as follows which is based out of backtrader backtesting library:</p>
  <pre><code>def optimizer_callbacks(cb):
      pbar.update()
  
  def strategy_optim(**kwargs):
  
      total = np.prod([len(value) for key,value in kwargs.items()])
  
      csv_file = FDaxCSVData(---data---)
      cerebro = bt.Cerebro()
      cerebro.adddata(csv_file)    
      cerebro.broker.setcash(500000.0)
      cerebro.broker.setcommission(commission=2.0)
  
      strats = cerebro.optstrategy(strategy_name, printlog = False, **kwargs)
  
      global pbar
      pbar = tqdm.tqdm(smoothing=0.05, desc='Optimization Runs', total=total)
      cerebro.optcallback(optimizer_callbacks)
  
      runnings = cerebro.run(optreturn=False, maxcpus=2)  
  
  if __name__==&quot;__main__&quot;:
      strategy_optim(periods = [100, 200, 300],  abs_margin= [25, 50, 75], trail_stop=[10, 20, 30, 40])
  </code></pre>
  <p>Output:</p>
  <pre><code>Optimization Runs:   0%|                                                    | 0/12 [00:00&lt;?, ?it/s]
  Optimization Runs:   8%|██████▉                                             | 1/12 [00:18&lt;03:21, 18.29s/it]
  Optimization Runs:  17%|█████████████▊                                      | 2/12 [00:19&lt;01:35,  9.59s/it]
  Optimization Runs:  25%|████████████████████▊                               | 3/12 [00:40&lt;02:19, 15.55s/it]
  </code></pre>
  <p>I did check out the other posts on stackoverflow regarding similar issues(most of them are concentrated on jupyter notebook interface) and they didn't solve my error. Also, this is a multitreading process and the <strong>cerebro.optcallback</strong> calls the optimizer_callbacks function after each iteration of a unique set of values of the params</p>