Mojo Date and Time
Working with dates and times appears in logging, scheduling, performance measurement, data analysis, and report generation. Mojo provides the time module for precise performance timing, and Python's datetime module is available through interop for calendar date and time operations.
Two Distinct Needs
Performance timing (Mojo's time module):
"How many nanoseconds did this function take?"
Use: PerfCounter, time.now()
Calendar date/time (Python's datetime module):
"What day is today? How many days until the deadline?"
Use: datetime.date, datetime.datetime, timedelta
Measuring Elapsed Time with PerfCounter
from time import perf_counter_ns
fn slow_function(n: Int) -> Int:
var total = 0
for i in range(n):
total += i
return total
fn main():
var start = perf_counter_ns()
var result = slow_function(10_000_000)
var end = perf_counter_ns()
var elapsed_ns = end - start
var elapsed_ms = Float64(elapsed_ns) / 1_000_000.0
print("Result:", result)
print("Time:", elapsed_ms, "ms")
perf_counter_ns() returns an integer nanosecond timestamp.
1 second = 1,000 ms = 1,000,000 µs = 1,000,000,000 ns
Elapsed = end - start
Convert: ns ÷ 1,000,000 = ms
ns ÷ 1,000 = µs
Timing Multiple Sections
from time import perf_counter_ns
fn main():
# Time section 1
var t0 = perf_counter_ns()
var a = 0
for i in range(1_000_000):
a += i
var t1 = perf_counter_ns()
# Time section 2
var b = 1
for i in range(1, 21):
b *= i
var t2 = perf_counter_ns()
print("Sum loop: ", (t1 - t0) // 1000, "µs")
print("Factorial: ", (t2 - t1) // 1000, "µs")
print("Total: ", (t2 - t0) // 1000, "µs")
Multi-section timing diagram: t0 ──── section 1 ──── t1 ──── section 2 ──── t2 │ │ │ └── duration1 = t1-t0 └── duration2 = t2-t1 │ └──────── total = t2 - t0 ─────────────────────┘
Sleeping / Pausing Execution
from time import sleep
fn main():
print("Starting...")
sleep(1) # pause for 1 second (Float64 in seconds)
print("1 second passed")
sleep(0.5) # pause for 500 ms
print("Another 500ms passed")
Getting the Current Date and Time
from python import Python
fn main() raises:
var dt = Python.import_module("datetime")
var now = dt.datetime.now()
print(now) # 2025-03-15 14:23:07.123456
print(now.year) # 2025
print(now.month) # 3
print(now.day) # 15
print(now.hour) # 14
print(now.minute) # 23
print(now.second) # 7
var today = dt.date.today()
print(today) # 2025-03-15
Formatting Dates as Strings
from python import Python
fn main() raises:
var dt = Python.import_module("datetime")
var now = dt.datetime.now()
# strftime format codes:
print(now.strftime("%Y-%m-%d")) # 2025-03-15
print(now.strftime("%d/%m/%Y")) # 15/03/2025
print(now.strftime("%B %d, %Y")) # March 15, 2025
print(now.strftime("%H:%M:%S")) # 14:23:07
print(now.strftime("%I:%M %p")) # 02:23 PM
print(now.strftime("%A, %B %d %Y")) # Saturday, March 15 2025
strftime format codes: %Y → 4-digit year 2025 %m → 2-digit month 03 %d → 2-digit day 15 %H → hour (24h) 14 %I → hour (12h) 02 %M → minutes 23 %S → seconds 07 %p → AM/PM PM %A → full weekday Saturday %B → full month name March %a → short weekday Sat %b → short month Mar
Parsing Strings into Dates
from python import Python
fn main() raises:
var dt = Python.import_module("datetime")
# Parse a date string
var d = dt.datetime.strptime("2025-12-31", "%Y-%m-%d")
print(d.year, d.month, d.day) # 2025 12 31
var d2 = dt.datetime.strptime("15/03/2025 14:30", "%d/%m/%Y %H:%M")
print(d2) # 2025-03-15 14:30:00
Date Arithmetic with timedelta
from python import Python
fn main() raises:
var dt = Python.import_module("datetime")
var today = dt.date.today()
var one_week = dt.timedelta(days=7)
var next_week = today + one_week
print("Today: ", today)
print("Next week: ", next_week)
# Days between two dates
var start = dt.date(2025, 1, 1)
var end = dt.date(2025, 12, 31)
var delta = end - start
print("Days in 2025:", int(delta.days)) # 364
Date arithmetic diagram:
today: 2025-03-15
+ timedelta(days=7)
result: 2025-03-22
end - start = timedelta object
timedelta.days gives the integer count
Timestamps for Logging
from python import Python
from time import perf_counter_ns
fn log(level: String, message: String) raises:
var dt = Python.import_module("datetime")
var now = dt.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
print("[" + str(now) + "] [" + level + "] " + message)
fn main() raises:
log("INFO", "Application started")
log("DEBUG", "Loading config file")
log("WARN", "High memory usage detected")
log("ERROR", "Failed to connect to database")
Output:
[2025-03-15 14:23:07] [INFO] Application started [2025-03-15 14:23:07] [DEBUG] Loading config file [2025-03-15 14:23:07] [WARN] High memory usage detected [2025-03-15 14:23:07] [ERROR] Failed to connect to database
UTC and Timezone Awareness
from python import Python
fn main() raises:
var dt = Python.import_module("datetime")
var utc = dt.timezone.utc
# UTC-aware timestamp
var now_utc = dt.datetime.now(utc)
print(now_utc) # 2025-03-15 09:23:07+00:00
# Convert to ISO 8601 format (used in APIs)
print(now_utc.isoformat()) # 2025-03-15T09:23:07+00:00
Key Takeaways
Use Mojo's perf_counter_ns() for high-precision performance timing in nanoseconds. Use sleep(seconds) to pause execution. For calendar dates and times, use Python's datetime module through interop. Format dates with strftime() using format codes like %Y-%m-%d. Parse date strings back to objects with strptime(). Add and subtract durations with timedelta. Use UTC-aware timestamps in APIs and logs to avoid timezone confusion. Combine datetime.now().strftime() with your log messages to create timestamped records.