lenolib

# Related graphql-js issue: https://github.com/graphql/graphql-js/issues/2262
const rewire = require('rewire');

const rewiredExecuteModule = rewire('graphql/execution/execute');

const completeValue = rewiredExecuteModule.__get__('completeValue');
const handleFieldError = rewiredExecuteModule.__get__('handleFieldError');

const { GraphQLError } = require('graphql');
const { addPath, pathToArray } = require('graphql/jsutils/Path');

lenolib

ALTER TABLE my_table ADD COLUMN tsdoc tsvector;
CREATE INDEX my_table_tsvec_idx ON my_table USING GIN (customer_id, tsdoc);

-- Full text search for datafield specs
CREATE FUNCTION my_table_tsvec_trigger() RETURNS trigger AS $$  
BEGIN
  NEW.tsdoc :=
    setweight(to_tsvector('simple', coalesce(NEW.name,'')), 'A') ||
    setweight(to_tsvector('simple', coalesce(NEW.description,'')), 'B');
  return NEW;

lenolib

import re
from notion.client import NotionClient


def enumerate_notion_items(
    view_url, id_col, created_at_col="created_time", token=None, client=None
):
    """
    Given that a property with name e.g. "Item ID" exists for a notion dataset,
    and that at least one item has a value for that property, this function

lenolib

# Find python imports in current directory that are not part of the python standard library
function non-stdlib-imports () {
    # Requires isort to be pip-installed
    stdlib_mods=`python -c "import isort, sys; sys.stdout.write('|'.join(isort.settings.default['known_standard_library']))"`
    non_stdlib_used_mods=`grep "import " $(find . -name "*.py") | cut -f2 -d ' ' | cut -f1 -d'.' | sort | uniq | grep -v -E $stdlib_mods`
    grep -nRE "$non_stdlib_used_mods" | grep -e "import.* " -e "from.* "
}

lenolib

def archive_to_bytes(archive):
    def to_seconds(s):
        SECONDS_IN_A = {
            's': 1,
            'm': 1 * 60,
            'h': 1 * 60 * 60,
            'd': 1 * 60 * 60 * 24,
            'y': 1 * 60 * 60 * 24 * 365,
        }

lenolib

from IPython.core.history import HistoryAccessor
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
hist_access = HistoryAccessor()
start_times, n_cmds = zip(*list(hist_access.db.execute('select start, num_cmds from sessions')))
num_cmds = pd.Series(n_cmds, index=start_times)
cmds_hod = num_cmds.groupby(num_cmds.index.hour).agg(sum)

starts = pd.Series(np.ones(len(start_times)), index=start_times)

lenolib

from __future__ import print_function
from collections import Iterable, Sized

def deprint(obj, depth=5, indent=0, size_limit=10, index=""):
    if not depth:
        print("".join([" "*indent,"[reached depth limit]"]))
        return
    type_str = type(obj).__name__
    if type(obj).__module__ != '__builtin__':
        type_str = ".".join([type(obj).__module__, type_str])