Reads a Wakatime export, and prints the hours spent on ActivityWatch projects, by project and by date.

analyze_wakatime.py

"""
Reads a Wakatime export, and prints the hours spent on ActivityWatch projects, by project and by date.

Original author: @brayo-pip
Modifications by: @ErikBjare
"""

import csv
import json
import sys
from collections import Counter

from tabulate import tabulate

if len(sys.argv) == 2:
    path = sys.argv[1]
else:
    print("Usage: python analyze.py <path to JSON file>")
    sys.exit(1)

file = open(path, "r")

data = json.load(file)
# store the last 50 days of data
data["days"] = data["days"][-50:]

hours_by_date: Counter[str] = Counter()
hours_by_project: Counter[str] = Counter()

for day in data["days"]:
    date = day["date"]
    for project in day["projects"]:
        # Match ActivityWatch projects
        name = project["name"].lower()
        if name.startswith("activitywatch") or name.startswith("aw"):
            for entity in project["entities"]:
                hours_by_date[date] += entity["total_seconds"] / 60 / 60
                hours_by_project[name] += entity["total_seconds"] / 60 / 60

# Compute total, filter out projects with less than 2 hours
hours_total = sum(v for v in hours_by_project.values() if v > 2)

header = ["Date", "Hours"]

print(tabulate(hours_by_date.items(), headers=header))
print()
print(tabulate(hours_by_project.most_common(10), headers=header))
print()
print(f"total hours spent on aw: {hours_total} hours")

with open("output.csv", "w", newline="") as file:
    writer = csv.writer(file)

    # Write the header
    writer.writerow(header)

    # Write the data
    for date, hours in hours_by_date.items():
        writer.writerow([date, hours])

print()
print("Data written to output.csv")