Handle Date and Time in YAML Files Using Python

This tutorial will guide you through handling dates and times in YAML files using Python.

You’ll learn how to read, write, and manipulate them.

 

 

Format Dates for YAML

Formatting dates correctly ensures they are correctly interpreted when loading and dumping YAML files.

Custom Date Formats with strftime()

You can format dates using custom formats with strftime().

from datetime import datetime
now = datetime.now()
custom_format = now.strftime('%Y-%m-%d %H:%M:%S')
print(custom_format)

Output:

2024-10-12 14:45:30

This formats the date and time without microseconds, which might be preferable for readability.

Handling Timezone Information

To include timezone information, use the pytz library.

from datetime import datetime
import pytz
now_utc = datetime.now(pytz.utc)
print(now_utc.isoformat())

Output:

2024-10-12T14:45:30.123456+00:00

The output includes the timezone offset, ensuring the timestamp is unambiguous globally.

Represent Date-Only vs. Date-Time Values

To distinguish between dates and datetimes, ensure that date-only values do not include time.

start_date: 2024-10-12
start_datetime: 2024-10-12T14:45:30Z

This makes it clear which values include time information.

Work with YAML Tag !!timestamp

You can explicitly tag a YAML value as a timestamp.

deployment_time: !!timestamp '2024-10-12T14:45:30Z'

This tells the YAML parser to treat the value as a timestamp.

 

Store Dates in YAML Files

Represent Dates as Scalars

In Python, you can store dates as scalar values in a dictionary.

data = {
    'name': 'Ahmed',
    'birth_date': '1990-05-15'
}

Using YAML Tags (!!timestamp)

When dumping YAML, you can use tags to specify data types.

import yaml
from datetime import datetime
data = {
    'event': 'Conference',
    'date': datetime(2024, 10, 12, 14, 45, 30)
}
yaml_str = yaml.dump(data, default_flow_style=False)
print(yaml_str)

Output:

date: 2024-10-12 14:45:30
event: Conference

The datetime object is automatically converted to a YAML timestamp.

Structuring Date and Time Components

You can store date and time components separately.

meeting:
  year: 2024
  month: 10
  day: 12
  hour: 14
  minute: 45
  second: 30

This method allows for more flexibility when parsing the date and time components individually.

Preserve Microseconds in YAML Output

You can include microseconds in your timestamps:

import yaml
from datetime import datetime
data = {
    'timestamp': datetime.now()
}
yaml_str = yaml.dump(data)
print(yaml_str)

Output:

timestamp: 2024-10-12 14:45:30.123456

 

Read Dates from YAML Files

Reading dates from YAML files requires proper parsing to get the correct data types.

Using PyYAML

You can load YAML files and parse dates using PyYAML.

import yaml
yaml_str = """
start_date: 2024-10-12
start_datetime: 2023-10-12T14:45:30Z
"""
data = yaml.safe_load(yaml_str)
print(data)

Output:

{'start_date': datetime.date(2024, 10, 12), 'start_datetime': datetime.datetime(2024, 10, 12, 14, 45, 30, tzinfo=datetime.timezone.utc)}

PyYAML automatically converts date and datetime strings to appropriate Python objects.

Deal with Ambiguous Date Representations

If dates are in non-standard formats, you need to handle them manually.

import yaml
from datetime import datetime
yaml_str = """
custom_date: '12/10/2024'
"""
data = yaml.safe_load(yaml_str)
date_str = data['custom_date']
parsed_date = datetime.strptime(date_str, '%d/%m/%Y')
print(parsed_date)

Output:

2024-10-12 00:00:00

You parse the custom date format using datetime.strptime().

 

Handle Timedeltas

Timedeltas represent the difference between two dates or times.

from datetime import datetime, timedelta
start_time = datetime(2024, 10, 12, 14, 45, 30)
end_time = datetime(2024, 10, 12, 16, 15, 45)
duration = end_time - start_time
print(duration)

Output:

1:30:15

The duration between the two times is computed as a timedelta object.

You can store this duration in YAML by converting it to a string.

duration: '1:30:15'

When loading, you can parse it back to a timedelta.

from datetime import datetime, timedelta
duration_str = '1:30:15'
h, m, s = map(int, duration_str.split(':'))
duration = timedelta(hours=h, minutes=m, seconds=s)
print(duration)

Output:

1:30:15

The string is converted back to a timedelta object representing the duration.