machbase-neo
HTTP API
Client in Python

Client in Python

Query

GET CSV 

import requests
params = {"q":"select * from example", "format":"csv", "heading":"false"} 
response = requests.get("http://127.0.0.1:5654/db/query", params)
print(response.text)

Write

POST CSV 

import requests
csvdata = """temperature,1677033057000000000,21.1
humidity,1677033057000000000,0.53
"""
response = requests.post(
    "http://127.0.0.1:5654/db/write/example?heading=false", 
    data=csvdata, 
    headers={'Content-Type': 'text/csv'})
print(response.json())

Example - matplotlib

📌
To write test data, use the command below from the Write waves by shell.
sh gen_wave.sh | machbase-neo shell import --timeformat=s EXAMPLE

Python code

import requests
import json
import datetime
import matplotlib.pyplot as plt
import numpy as np

url = "http://127.0.0.1:5654/db/query"
querystring = {"q":"select * from example order by time limit 200"} 
response = requests.request("GET", url, params=querystring)
data = json.loads(response.text)

sinTs, sinSeries, cosTs, cosSeries = [], [], [], []
for row in data["data"]["rows"]:
    ts = datetime.datetime.fromtimestamp(row[1]/1000000000)
    if row[0] == 'wave.cos':
        cosTs.append(ts)
        cosSeries.append(row[2])
    else:
        sinTs.append(ts)
        sinSeries.append(row[2])

plt.plot(sinTs, sinSeries, label="sin")
plt.plot(cosTs, cosSeries, label="cos")
plt.title("Tutorial Waves")
plt.legend()
plt.show()

Example - pandas

📌
To write test data, use the command below from the Write waves by shell.
sh gen_wave.sh | machbase-neo shell import --timeformat=s EXAMPLE

This example shows how to load data into pandas dataframe via machbase-neo HTTP API.

from urllib import parse
import pandas as pd

query_param = parse.urlencode({
    "q": "select * from example order by time limit 500",
    "format": "csv",
    "timeformat": "s",
})
df = pd.read_csv(f"http://127.0.0.1:5654/db/query?{query_param}")
df

Load CSV

Import pandas and urllib.

from urllib import parse
import pandas as pd

Make query url for "format": "csv" option, then call read_csv. Use timeformat to specify the precision of time data. s, ms, us and ns(default) are available.

query_param = parse.urlencode({
    "q":"select * from example order by time limit 500",
    "format": "csv",
    "timeformat": "s",
})
df = pd.read_csv(f"http://127.0.0.1:5654/db/query?{query_param}")
df

Load compressed CSV

Read gzip’ed CSV from HTTP API.

from urllib import parse
import pandas as pd
import requests
import io
query_param = parse.urlencode({
    "q":"select * from example order by time desc limit 1000",
    "format": "csv",
    "timeformat": "s",
    "compress": "gzip",
})
response = requests.get(f"http://127.0.0.1:5654/db/query?{query_param}", timeout=30, stream=True)
df = pd.read_csv(io.BytesIO(response.content))
df
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