bojanbabic’s gists

bojanbabic / gruvr2calendar.py

Created May 24, 2010 07:52

	#!/usr/bin/perl
	#author Bojan Babic
	#email:[email protected]

	use Time::HiRes qw /gettimeofday/;
	use LWP::UserAgent;
	use LWP::Simple;
	use HTTP::Request;
	use HTTP::Response;
	use strict;

bojanbabic / all companies

Created July 25, 2016 09:00

bojanbabic / local_paint_nite.json

Created May 9, 2017 23:06

This file has been truncated, but you can view the full file.

bojanbabic / airbnb_ac_result.json

Created March 30, 2020 22:16

	# curl "https://www.airbnb.com/api/v2/autocompletes?country=US&key=d306zoyjsyarp7ifhu67rjxn52tv0t20&language=en&locale=en&num_results=5&user_input=yoga&api_version=1.2.0&vertical_refinement=all&region=1&options=should_show_stays" \| jq '.autocomplete_terms[0] '
	{
	"id": "78f3c2985523dd6742202ebcddcc02604d5af94f5ecd6c44414b86d24d6640c7",
	"explore_search_params": {
	"refinement_paths": [
	"/experiences/KG/Tag:76"
	],
	"reset_filters": false,
	"reset_keys": [],
	"query": "Yoga in San Diego, CA",

bojanbabic / ad_line_item_ids.tsv

Last active May 13, 2023 00:03

We can make this file beautiful and searchable if this error is corrected: No tabs found in this TSV file in line 0.

bojanbabic / gpt_scraper.py

Last active August 20, 2023 22:55

	import openai
	import os
	from bs4 import BeautifulSoup
	from bs4.element import Comment
	from selenium import webdriver
	from selenium.webdriver.chrome.service import Service
	import re

	openai.api_key = os.getenv('OPENAI_API_KEY')

bojanbabic / address_to_hood_id.py

Last active September 22, 2023 16:03

Address to Hood Id

	import pandas as pd
	from nextdoor.i18n import locale_api
	from nextdoor.gql.geo.geo_tag_utils import get_neighborhood_from_lat_lon
	from nextdoor.common.mapbox import mapbox_client
	locale_api.set_locales('en-us')

	csv_file = "/app/CA_ncesdata_642B9065_cleaned.csv"
	output_file = "/app/CA_ncesdata_642B9065_hood_id.csv"
	df = pd.read_csv(csv_file)
	def get_lat_lon(row):

bojanbabic / classification_mlflow_inference.py

Created March 4, 2024 16:50

	import os
	import requests
	import numpy as np
	import pandas as pd
	import json

	def create_tf_serving_json(data):
	return {'inputs': {name: data[name].tolist() for name in data.keys()} if isinstance(data, dict) else data.tolist()}

	def score_model(dataset):