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## python_resources.md

      
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                mwebler
                / python_resources.md
            
            
              Created
              January 21, 2014 15:27
                — forked from jookyboi/python_resources.md
            
              
                Python-related modules and guides.
              
          
    Packages


lxml - Pythonic binding for the C libraries libxml2 and libxslt.
boto - Python interface to Amazon Web Services
Django - Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.
Fabric - Library and command-line tool for streamlining the use of SSH for application deployment or systems administration task.
PyMongo - Tools for working with MongoDB, and is the recommended way to work with MongoDB from Python.
Celery - Task queue to distribute work across threads or machines.
pytz - pytz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.4 or higher.

Guides


## index.html
<!doctype html>

<html lang="en">
<head>
  <meta charset="utf-8">

  <title>HTML Init</title>
  <meta name="description" content="HTML scaffold">
  <meta name="author" content="HTML Init">
</head>

## index.js
const yeoman = require('yeoman-environment');
const env = yeoman.createEnv();

env.lookup(() => {
  env.run('generator', {'skip-install': true, 'force':true}, err => {
    console.log('done');
    env.run('generator', {'skip-install': true, 'force':true}, err => {
        console.log('done');
    });
  });

## CloudSQLSource.py
import threading

import mysql.connector

import apache_beam as beam

class CloudSQLSource(beam.io.iobase.BoundedSource):

    def __init__(self, node):
        sql = mysql.connector.connect(user='', password='',

## GoogleDatastoreCount.py
# Imports the Google Cloud client library
from google.cloud import datastore

# Instantiates a client
client = datastore.Client(project='PROJECT')
query = client.query(kind='KIND')
query_iter = query.fetch()
total = sum(1 for _ in query_iter)

## json_file_source.py
import apache_beam as beam
import re
import json


class JsonFileSource(beam.io.filebasedsource.FileBasedSource):
    """A Beam source for JSON that emits all top-level json objects.

    Note that the beginning of a top-level json object is assumed to begin on a
    new line with no leading spaces, possibly preceded by a square bracket ([)

## firebase-functions-debug.md

      
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                mwebler
                / firebase-functions-debug.md
            
            
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              May 17, 2018 03:14
            
              
                Debug firebase http functions v1.0 locally with VS Code
              
          
    You will need to have google cloud functions emulator modules installed:
npm install -g @google-cloud/functions-emulator

Then you will need to get your firebase project configuration.
For that, you need to go to your firebase functions project folder, log in to your project and run the setup:web command:
firebase login
firebase setup:we


## query_by_kind.py
import apache_beam as beam

from apache_beam.io.gcp.datastore.v1.datastoreio import ReadFromDatastore
from google.cloud.proto.datastore.v1 import query_pb2


p = beam.Pipeline(options=pipeline_options)

# Create a query and filter by kind
query = query_pb2.Query()

## query_by_property.py
import apache_beam as beam

from apache_beam.io.gcp.datastore.v1.datastoreio import ReadFromDatastore
from google.cloud.proto.datastore.v1 import query_pb2

from googledatastore import helper as datastore_helper
from googledatastore import PropertyFilter


p = beam.Pipeline(options=pipeline_options)
	<!doctype html>

	<html lang="en">
	<head>
	<meta charset="utf-8">

	<title>HTML Init</title>
	<meta name="description" content="HTML scaffold">
	<meta name="author" content="HTML Init">
	</head>
	const yeoman = require('yeoman-environment');
	const env = yeoman.createEnv();

	env.lookup(() => {
	env.run('generator', {'skip-install': true, 'force':true}, err => {
	console.log('done');
	env.run('generator', {'skip-install': true, 'force':true}, err => {
	console.log('done');
	});
	});
	import threading

	import mysql.connector

	import apache_beam as beam

	class CloudSQLSource(beam.io.iobase.BoundedSource):

	def __init__(self, node):
	sql = mysql.connector.connect(user='', password='',
	# Imports the Google Cloud client library
	from google.cloud import datastore

	# Instantiates a client
	client = datastore.Client(project='PROJECT')
	query = client.query(kind='KIND')
	query_iter = query.fetch()
	total = sum(1 for _ in query_iter)
	import apache_beam as beam
	import re
	import json


	class JsonFileSource(beam.io.filebasedsource.FileBasedSource):
	"""A Beam source for JSON that emits all top-level json objects.

	Note that the beginning of a top-level json object is assumed to begin on a
	new line with no leading spaces, possibly preceded by a square bracket ([)
	import apache_beam as beam

	from apache_beam.io.gcp.datastore.v1.datastoreio import ReadFromDatastore
	from google.cloud.proto.datastore.v1 import query_pb2


	p = beam.Pipeline(options=pipeline_options)

	# Create a query and filter by kind
	query = query_pb2.Query()