Parser for function arguments
Project description
Function Argument Pre-Processor
This is a abstract library that need to be extended before put actual use.
The primary use case is to extend it as a Flask Extenstion
but is open to use with any other environment/framework that needs to deal with http endpoints eg: AWS Lambda
Implementations
Installation
$ pip install funcargpreprocessor
or download the code and run
$ python3 setup.py install
What it does?
- Extraction and transformation of function argument and raise appropriate exceptions
Example
- Please refer testimplementation.py and fieldtest.py for examples
Explanation
The following explanantion uses the example from test
folder
{
"pageNo": { #Key name expected from the HTTP endpoint
"data_type": int # Data type expected, accepts 1, '1', 1.0 all of these values will be type casted to 1 before passing to the function
, "min_val": 0 # Min validation for the key
, "max_val": 20 # Max validation for the key
, 'alias': 'page_no' # Key for the function argument, to the function the argument will be 'page_no'
# Need? most of the time the http request are expected json and the keys will be in camelCase
}
, "start_date": {
"data_type": DateArg('%Y-%m-%d') # Expects a date argument in <str>'YYYY-MM-DD' format or datetime.date object accepts '2020-01-10', datetime.date(2020, 1, 10) converts,in case of a string argument, to datetime.date(2020, 1, 10) and passes it to the function
, "min_val": date(2020, 1, 1)
, "required": True # This key is required to be there in the input
}
, "id_list": {
"data_type": list # Expects list of value
, "nested": int # The values in the list should be int same rule as `date_type`
, "value_list": [0, 1, 2, 3] # Accepted values ex: [1,2], [1], [2,3,0]
# Need? Multiselect options/ENUMS
}
, 'reg_time': {"data_type": DateTimeArg('%Y-%m-%d %H:%M:%S')}
, "location": {"data_type": list
, "nested": { # Custom definition for objects in the list
"address_line_1": {"data_type": str, "required": True}
, "address_line_2": {"data_type": str}
, "pincode": {"data_type": int, "required": True}
, "contact_person": {
"data_type": dict
, "nested": {
"first_name": {"data_type": str, "required": True}
, "last_name": {"data_type": str}
, "phone_number": {
"data_type": str
, "required": True
, "regex": r"[0-9]{10,12}" # Regular expression validation
, "regex_error_message": "<some message>" # Message when the RegEx validation fails
}
}
}
}
}
}
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