<jupyter_start><jupyter_text><jupyter_code>from datetime import datetime

# current date and time
now = datetime.now()
start_time = datetime.timestamp(now)
print("start_time =", start_time)

transition_o1_d1_prev = start_time

now = datetime.now()
transition_o1_d1 = datetime.timestamp(now)
print("transition_o1_d1 time,1,", transition_o1_d1 - transition_o1_d1_prev)
transition_o1_d1_prev = transition_o1_d1

now = datetime.now()
transition_o1_d1 = datetime.timestamp(now)
print("transition_o1_d1 time,2,", transition_o1_d1 - transition_o1_d1_prev)
transition_o1_d1_prev = transition_o1_d1

now = datetime.now()
transition_o1_d1 = datetime.timestamp(now)
print("transition_o1_d1 time,3,", transition_o1_d1 - transition_o1_d1_prev)
transition_o1_d1_prev = transition_o1_d1<jupyter_output>start_time = 1608197445.884393
transition_o1_d1 time,1, 0.00019812583923339844
transition_o1_d1 time,2, 0.00014090538024902344
transition_o1_d1 time,3, 0.0001609325408935547
{'fraction_non_alphanumeric': 0.08757637474541752, 'fraction_numerical': 0.13034623217922606, 'mean_word_length': 7.474137931034483, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '344452', 'license': 'MIT', 'n_tokens_mistral': 445, 'n_tokens_neox': 398, 'n_words': 56, 'path': 'CTMC_Transition_Timestamps.ipynb', 'repo_name': 'hpi-sam/MarkovModels_Lecture', 'size': '982'}