the following data types: strings, Unicode, floats, boolean, dictionaries, and lists. Decimals and dates are notably missing. Also, binary data will be transferred using Base64 encoding, which will cause of the same characteristics as json, except that it natively supports more data types (in- cluding dates, recursive references, etc.) However, the Python libraries for YAML are a good bit slower than the "10/s"}} 3.2 Configuration Directives 3.2.1 Time and date settings CELERY_ENABLE_UTC If enabled dates and times in messages will be converted to use the UTC timezone. Note that workers running Celery

the following data types: strings, Unicode, floats, boolean, dictionaries, and lists. Decimals and dates are notably missing. Also, binary data will be transferred using Base64 encoding, which will cause of the same characteristics as json, except that it natively supports more data types (including dates, recursive references, etc.) However, the Python libraries for YAML are a good bit slower than the {"rate_limit": "10/s"}} Configuration Directives Time and date settings CELERY_ENABLE_UTC If enabled dates and times in messages will be converted to use the UTC timezone. Note that workers running Celery

read more about the celery command and monitoring in the Monitoring Guide. Timezone All times and dates, internally and in messages uses the UTC timezone. When the worker receives a message, for example the following data types: strings, Unicode, floats, Boolean, dictionaries, and lists. Decimals and dates are notably missing. Binary data will be transferred using Base64 encoding, increasing the size of of the same characteristics as json, except that it natively supports more data types (in- cluding dates, recursive references, etc.). However, the Python libraries for YAML are a good bit slower than the

read more about the celery command and monitoring in the Monitoring Guide. Timezone All times and dates, internally and in messages uses the UTC timezone. When the worker receives a message, for example the following data types: strings, Unicode, floats, Boolean, dictionaries, and lists. Decimals and dates are notably missing. Binary data will be transferred using Base64 encoding, increasing the size of of the same characteristics as json, except that it natively supports more data types (including dates, recursive references, etc.). However, the Python libraries for YAML are a good bit slower than the

read more about the celery command and monitoring in the Monitoring Guide. Timezone All times and dates, internally and in messages uses the UTC timezone. When the worker receives a message, for example the following data types: strings, Unicode, floats, Boolean, dictionaries, and lists. Decimals and dates are notably missing. Binary data will be transferred using Base64 encoding, increasing the size of of the same characteristics as json, except that it natively supports more data types (including dates, recursive references, etc.). However, the Python libraries for YAML are a good bit slower than the

read more about the celery command and monitoring in the Monitoring Guide. Timezone All times and dates, internally and in messages uses the UTC timezone. When the worker receives a message, for example the following data types: strings, Unicode, floats, Boolean, dictionaries, and lists. Decimals and dates are notably missing. Binary data will be transferred using Base64 encoding, increasing the size of of the same characteristics as json, except that it natively supports more data types (in- cluding dates, recursive references, etc.). However, the Python libraries for YAML are a good bit slower than the

read more about the celery command and monitoring in the Monitoring Guide. Timezone All times and dates, internally and in messages uses the UTC timezone. When the worker receives a message, for example the following data types: strings, Unicode, floats, Boolean, dictionaries, and lists. Decimals and dates are notably missing. Binary data will be transferred using Base64 encoding, increasing the size of of the same characteristics as json, except that it natively supports more data types (in- cluding dates, recursive references, etc.). However, the Python libraries for YAML are a good bit slower than the

read more about the celery command and monitoring in the Monitoring Guide. Timezone All times and dates, internally and in messages uses the UTC timezone. When the worker receives a message, for example the following data types: strings, Unicode, floats, Boolean, dictionaries, and lists. Decimals and dates are notably missing. Binary data will be transferred using Base64 encoding, increasing the size of of the same characteristics as json, except that it natively supports more data types (including dates, recursive references, etc.). However, the Python libraries for YAML are a good bit slower than the

read more about the celery command and monitoring in the Monitoring Guide. Timezone All times and dates, internally and in messages uses the UTC timezone. When the worker receives a message, for example the following data types: strings, Unicode, floats, Boolean, dictionaries, and lists. Decimals and dates are notably missing. Binary data will be transferred using Base64 encoding, increasing the size of of the same characteristics as json, except that it natively supports more data types (in- cluding dates, recursive references, etc.). However, the Python libraries for YAML are a good bit slower than the

read more about the celery command and monitoring in the Monitoring Guide. Timezone All times and dates, internally and in messages uses the UTC timezone. When the worker receives a message, for example the following data types: strings, Unicode, floats, Boolean, dictionaries, and lists. Decimals and dates are notably missing. Binary data will be transferred using Base64 encoding, increasing the size of of the same characteristics as json, except that it natively supports more data types (in- cluding dates, recursive references, etc.). However, the Python libraries for YAML are a good bit slower than the