Lernen Automating Time Tracking | Automating Freelance Workflow

As a freelancer, keeping accurate records of the time you spend on various projects is crucial for both billing and productivity analysis. Manual time tracking can be tedious and prone to errors, but Python offers a way to automate this process, saving you time and ensuring accuracy. By automating time tracking, you can focus more on your work and less on administrative tasks, while also gaining valuable insights into how your time is allocated across different projects.


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import datetime

# Dictionary to store time logs for each project
time_logs = {}

def start_timer(project_name):
    start_time = datetime.datetime.now()
    if project_name not in time_logs:
        time_logs[project_name] = []
    # Add a new entry with start time and placeholder for end time
    time_logs[project_name].append({'start': start_time, 'end': None})
    print(f"Started tracking '{project_name}' at {start_time.strftime('%H:%M:%S')}")

def stop_timer(project_name):
    end_time = datetime.datetime.now()
    if project_name in time_logs and time_logs[project_name]:
        # Find the last entry without an end time
        for entry in reversed(time_logs[project_name]):
            if entry['end'] is None:
                entry['end'] = end_time
                print(f"Stopped tracking '{project_name}' at {end_time.strftime('%H:%M:%S')}")
                break
        else:
            print(f"No active timer found for '{project_name}'.")
    else:
        print(f"No time log found for '{project_name}'.")

def log_entries():
    for project, entries in time_logs.items():
        print(f"\nProject: {project}")
        for i, entry in enumerate(entries, 1):
            start = entry['start'].strftime('%Y-%m-%d %H:%M:%S')
            end = entry['end'].strftime('%Y-%m-%d %H:%M:%S') if entry['end'] else "In Progress"
            print(f"  Entry {i}: Start: {start}, End: {end}")

# Example usage:
start_timer("Website Redesign")
# Simulate some work with a short pause
import time
time.sleep(2)
stop_timer("Website Redesign")
log_entries()

This script introduces a simple way to track time for multiple freelance projects. It uses a dictionary called time_logs where each key is a project name and each value is a list of time entry dictionaries. Each time entry records a start and an end time. The start_timer function adds a new entry with the current time as the start, while stop_timer updates the most recent entry for that project with the current time as the end. The log_entries function prints all the recorded time entries for each project, showing both start and end times, or indicating if a timer is still running. By associating project names with lists of time entries, you can easily manage multiple projects and sessions.


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def summarize_time_per_project(time_logs):
    summary = {}
    for project, entries in time_logs.items():
        total_seconds = 0
        for entry in entries:
            if entry['end'] and entry['start']:
                duration = (entry['end'] - entry['start']).total_seconds()
                total_seconds += duration
        summary[project] = total_seconds / 60  # convert to minutes
    for project, minutes in summary.items():
        print(f"Total time spent on '{project}': {minutes:.2f} minutes")

# Example usage with existing time_logs:
summarize_time_per_project(time_logs)

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Abschnitt 1. Kapitel 1

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Suggested prompts:

How can I add more projects to track time for?

Can I export the time logs to a file?

How do I reset or clear the time logs?

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import datetime

# Dictionary to store time logs for each project
time_logs = {}

def start_timer(project_name):
    start_time = datetime.datetime.now()
    if project_name not in time_logs:
        time_logs[project_name] = []
    # Add a new entry with start time and placeholder for end time
    time_logs[project_name].append({'start': start_time, 'end': None})
    print(f"Started tracking '{project_name}' at {start_time.strftime('%H:%M:%S')}")

def stop_timer(project_name):
    end_time = datetime.datetime.now()
    if project_name in time_logs and time_logs[project_name]:
        # Find the last entry without an end time
        for entry in reversed(time_logs[project_name]):
            if entry['end'] is None:
                entry['end'] = end_time
                print(f"Stopped tracking '{project_name}' at {end_time.strftime('%H:%M:%S')}")
                break
        else:
            print(f"No active timer found for '{project_name}'.")
    else:
        print(f"No time log found for '{project_name}'.")

def log_entries():
    for project, entries in time_logs.items():
        print(f"\nProject: {project}")
        for i, entry in enumerate(entries, 1):
            start = entry['start'].strftime('%Y-%m-%d %H:%M:%S')
            end = entry['end'].strftime('%Y-%m-%d %H:%M:%S') if entry['end'] else "In Progress"
            print(f"  Entry {i}: Start: {start}, End: {end}")

# Example usage:
start_timer("Website Redesign")
# Simulate some work with a short pause
import time
time.sleep(2)
stop_timer("Website Redesign")
log_entries()


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def summarize_time_per_project(time_logs):
    summary = {}
    for project, entries in time_logs.items():
        total_seconds = 0
        for entry in entries:
            if entry['end'] and entry['start']:
                duration = (entry['end'] - entry['start']).total_seconds()
                total_seconds += duration
        summary[project] = total_seconds / 60  # convert to minutes
    for project, minutes in summary.items():
        print(f"Total time spent on '{project}': {minutes:.2f} minutes")

# Example usage with existing time_logs:
summarize_time_per_project(time_logs)

War alles klar?

Danke für Ihr Feedback!

Abschnitt 1. Kapitel 1

Automating Time Tracking

1. What is the main benefit of automating time tracking for freelancers?

2. Which Python data structure is most suitable for storing time logs for multiple projects?

3. Why is it important to record both start and stop times in a time tracking system?

Automating Time Tracking

1. What is the main benefit of automating time tracking for freelancers?

2. Which Python data structure is most suitable for storing time logs for multiple projects?

3. Why is it important to record both start and stop times in a time tracking system?