Obtaining a confidence interval for the prediction of a linear regression
You can estimate the standard deviation of your prediction: 

stdev = np.sqrt(sum((linreg.predict(X_train) - y_train)**2) / (len(y_train) - 2))

Then, for any significance level you want, you should check correspondent Gaussian critical value (for example, for significance level 95% it is 1.96). 

Finally, confidence intervals are (prediction - 1.96*stdev, prediction + 1.96*stdev) (or similarly for any other confidence level).

Another approach is to use statsmodels package.