A package for encoding and decoding time series in JSON files into embedded base 16, 64, or 91 encodings.
Project description
A class for encoding timeseries data in JSON into an embedded base 16, base 64 or base 91 encoding.
Installation
pip install timeseriesencoder
Use
To use pass any json into TimeSeriesEncoder.encode_json(data, ts_key, ts_value) where ts_key and ts_value are the timestamp key and the value key in the json.
from timeseriesencoder import *
encoded = TimeSeriesEncoder.encode_json(myJson, ts_key='UTC', ts_value='Value')
To decode you can apply the reverse:
decoded = TimeSeriesEncoder.decode_json(encoded)
The encoder will encode all time series it finds in the json. Each will get their own encoding that is optimal for the data sparsity and values. Sorting the data before encoding can improve compression. If you'd like the encoder to sort for you, you can include sort_values = True on the encode_json call. This will sort each time series by the timeseries key before encoding. This allows smaller compression if the data is regular by avoiding directly encoding the timeoffsets, and instead only encodes the data.
Tests
To run tests call pytests on the tests folder from the base package folder.
pytest ./tests/ -v -s
Examples
Example of encoding a json file, with the inputs/outputs below.
Note: The numpyencoder module is not required, but is used in the example to read/write the json to a file easily.
from timeseriesencoder import *
import json
from numpyencoder import NumpyEncoder
with open('sample.json', 'r') as rfile:
data = json.load(rfile)
data['Response'][0]['ForecastWeather'] = data['Response'][0]['ForecastWeather'][:3]
with open('data.json', 'w') as rfile:
json.dump(data, rfile, cls=NumpyEncoder)
encoded = TimeSeriesEncoder.encode_json(data, ts_key='UTC', ts_value='Value', sort_values=True)
with open('encoded.json', 'w') as rfile:
json.dump(encoded, rfile, cls=NumpyEncoder)
Size
Size before and after encoding. Encoding reduced package size by 10x.
In 0.1.2 the optional gzip parameter was added to encode_json and decode_json. This allows the final package to be smaller, which allows for lower data size for sending across networks, or storing in a cache system like Redis.
The raw sample.json had a size of 281KB. The encoded json that is output from the program that is sorted and is using base64 style encoding is 27KB. The raw zipped sample.json is 26KB The programs gzipped, encoded file is just 11KB. This is nearly 1/3rd the size of the regular zip file, and just 1/25th of the original data size.
Data Output
{
"Request": {
"locations": [
"XXX"
],
"attributes": null,
"aggregate": true,
"startDate": "2021-04-12T01:46:08.8622635Z"
},
"Response": [
{
"LocationName": "XXX",
"EntityType": "WIND_TURBINE",
"DisplayName": "XXX",
"Latitude": -1,
"Longitude": -1,
"Timezone": "Europe/Brussels",
"DataSource": "ECMWF-IFS",
"AsOfDateUTC": "2021-04-08T00:00:00Z",
"ForecastWeather": [
{
"AttributeName": "fresh_snow_6h:cm",
"AttributeUnitOfMeasure": "cm",
"AttributeDescription": "fresh snow of previous 6h [cm]",
"AttributeDataType": "Numeric",
"Values": {
"encoder": "TimeSeriesEncoder",
"start": 1618192800.0,
"ts_key": "UTC",
"ts_value": "Value",
"interval": 3600.0,
"static_value": 0.0,
"static_count": 143
}
},
{
"AttributeName": "precip_1h:mm",
"AttributeUnitOfMeasure": "mm",
"AttributeDescription": "amount of precipitation in the previous 1h [mm]",
"AttributeDataType": "Numeric",
"Values": {
"encoder": "TimeSeriesEncoder",
"start": 1618192800.0,
"ts_key": "UTC",
"ts_value": "Value",
"encoding_size": 64,
"data": "00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000KKKKKK888888TTTTTT888888000000",
"interval": 3600.0,
"encoding_depth": 1,
"float_precision": 2,
"signed": false
}
},
{
"AttributeName": "relative_humidity_100m:p",
"AttributeUnitOfMeasure": "%",
"AttributeDescription": "relative humidity at 100m [%]",
"AttributeDataType": "Numeric",
"Values": {
"encoder": "TimeSeriesEncoder",
"start": 1618192800.0,
"ts_key": "UTC",
"ts_value": "Value",
"encoding_size": 64,
"data": "BkBUBJB7AyAA9Q8i887b726d6B5m6P747m808H8Y8F7x7c7u8B8U9LAAA-AzAyAy9u8r7q7t7w7z8V939e9h9l9o9Y9I918y8u8p8l8g8c8K837o7Y7J74797F7K7Q7W7c7p818E8S8g8u8t8t8t8t8t8s8h8W8K897-7p828I8X8m909G9kADAiBBBgCACGCMCSCYCeCjC4BSAqAE9e939H9W9l9zACARB6BnCTD9DrEXEgEpExF4FCFKEtEQDzDWD4CdCBBmBKAuATA1ADAQAcAoA-BA",
"interval": 3600.0,
"encoding_depth": 2,
"float_precision": 1,
"signed": false
}
}
]
}
]
}
Input
{
"Request": {
"locations": [
"XXX"
],
"attributes": null,
"aggregate": true,
"startDate": "2021-04-12T01:46:08.8622635Z"
},
"Response": [
{
"LocationName": "XXX",
"EntityType": "XXX",
"DisplayName": "BEZ_E01",
"Latitude": -1,
"Longitude": -1,
"Timezone": "Europe/Brussels",
"DataSource": "ECMWF-IFS",
"AsOfDateUTC": "2021-04-08T00:00:00Z",
"ForecastWeather": [
{
"AttributeName": "fresh_snow_6h:cm",
"AttributeUnitOfMeasure": "cm",
"AttributeDescription": "fresh snow of previous 6h [cm]",
"AttributeDataType": "Numeric",
"Values": [
{
"UTC": "2021-04-12T02:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-12T03:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-12T04:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T03:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T04:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T05:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T06:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T07:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T08:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T09:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T10:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T11:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T12:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T13:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T14:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T15:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T16:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T17:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T18:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T19:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T20:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T21:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T22:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T23:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-14T00:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-12T05:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T06:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T07:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T08:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T09:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T10:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T11:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-12T12:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-12T13:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T14:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T15:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T16:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T17:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T18:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-12T19:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T20:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T21:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T22:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-12T23:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-13T00:00:00Z",
"Value": 0.0
},
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"UTC": "2021-04-13T01:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-13T02:00:00Z",
"Value": 0.0
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"Value": 0.0
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"Value": 0.0
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"Value": 0.0
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"Value": 0.0
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"UTC": "2021-04-14T05:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-14T06:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-14T07:00:00Z",
"Value": 0.0
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"UTC": "2021-04-14T08:00:00Z",
"Value": 0.0
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"UTC": "2021-04-14T09:00:00Z",
"Value": 0.0
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"UTC": "2021-04-14T10:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-14T11:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-14T12:00:00Z",
"Value": 0.0
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{
"UTC": "2021-04-14T13:00:00Z",
"Value": 0.0
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"Value": 0.0
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"UTC": "2021-04-14T15:00:00Z",
"Value": 0.0
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"UTC": "2021-04-14T16:00:00Z",
"Value": 0.0
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"UTC": "2021-04-14T17:00:00Z",
"Value": 0.0
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"Value": 0.0
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"UTC": "2021-04-14T22:00:00Z",
"Value": 0.0
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"UTC": "2021-04-14T23:00:00Z",
"Value": 0.0
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"Value": 0.0
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"Value": 0.0
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"Value": 0.0
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{
"UTC": "2021-04-15T07:00:00Z",
"Value": 0.0
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"Value": 0.0
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"Value": 0.0
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{
"UTC": "2021-04-15T14:00:00Z",
"Value": 0.0
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{
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"Value": 0.0
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{
"UTC": "2021-04-18T00:00:00Z",
"Value": 0.0
}
]
},
{
"AttributeName": "precip_1h:mm",
"AttributeUnitOfMeasure": "mm",
"AttributeDescription": "amount of precipitation in the previous 1h [mm]",
"AttributeDataType": "Numeric",
"Values": [
{
"UTC": "2021-04-12T02:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-12T03:00:00Z",
"Value": 0.0
},
{
"UTC": "2021-04-12T04:00:00Z",
"Value": 0.0
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"Value": 0.0
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{
"UTC": "2021-04-13T07:00:00Z",
"Value": 0.0
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"Value": 0.0
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{
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"Value": 0.0
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{
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"Value": 0.0
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"Value": 0.0
},
{
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"Value": 0.0
},
{
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"Value": 0.0
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"Value": 0.0
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"Value": 0.0
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"Value": 0.0
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"Value": 0.0
},
{
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"Value": 0.0
},
{
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"Value": 0.0
},
{
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"Value": 0.0
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"Value": 0.0
},
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"Value": 0.0
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"Value": 0.0
},
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"Value": 0.0
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{
"UTC": "2021-04-18T00:00:00Z",
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}
]
}
]
}
]
}
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