import sqlalchemy as sa
import sqlite3
# Show plots in Jupyter notebooks
%matplotlib inline
# Reload modules whenever they change
# (for development purposes)
%load_ext autoreload
%autoreload 2
import pandas as pd
# Make clusterking package available even without installation
import sys
sys.path = ["../../"] + sys.path
import json
import clusterking as ck
%time d = ck.Data("/home/kilian/tmp/scan/flavio_q2_10spoints_10bins.sql")
df = pd.read_csv("/home/kilian/tmp/scan/flavio_q2_10spoints_10bins_data.csv")
df.set_index("index", inplace=True)
d.df = df
with open("/home/kilian/tmp/scan/flavio_q2_10spoints_10bins_metadata.json") as mdfile:
md = json.load(mdfile)
d.md = md
d.write("/home/kilian/tmp/scan/flavio_q2_10spoints_10bins.sql")
d.load("/home/kilian/Documents/19/git_sync/clusterking/clusterking/data/test/data/test.sql")
d.df
d.df = pd.DataFrame({"1": [3, 4], "abc": [5, 6]})
d.df
d.load("test.sql")
d.md["test"]["abc"]
d.md["test"]["abc"] = 5
engine = sa.create_engine('sqlite:///' + "test.sql")
engine.create_table(
"md",
sa.Column("md", sa.PickleType())
)
import pickle
nd = {1: {2: 3}}
ndpick = pickle.dumps(nd)
conn = engine.connect()
conn.execute("insert into table md values (data)", sqlite3.Binary(ndpick))