#Generate fake data python how to

Output.Python Tutorial Python Features Python History Python Applications Python Install Python Example Python Variables Python Data Types Python Keywords Python Literals Python Operators Python Comments Python If else Python Loops Python For Loop Python While Loop Python Break Python Continue Python Pass Python Strings Python Lists Python Tuples Python List Vs Tuple Python Sets Python Dictionary Python Functions Python Built-in Functions Python Lambda Functions Python Files I/O Python Modules Python Exceptions Python Date Python Regex Python Sending Email Read CSV File Write CSV File Read Excel File Write Excel File Python Assert Python List Comprehension Python Collection Module Python Math Module Python OS Module Python Random Module Python Statistics Module Python Sys Module Python IDEs Python Arrays Command Line Arguments Python Magic Method Python Stack & Queue PySpark MLlib Python Decorator Python Generators Web Scraping Using Python Python JSON Python Itertools Python Multiprocessing How to Calculate Distance between Two Points using GEOPY Gmail API in Python How to Plot the Google Map using folium package in Python Grid Search in Python Python High Order Function nsetools in Python Python program to find the nth Fibonacci Number Python OpenCV object detection Python SimpleImputer module Second Largest Number in Python with open('%s.json' % filename, 'w') as output: We also want to enclose our dates in strings to avoid getting a json serialization error this is done by setting the parameters of output.write() to default=str. Once we run our script, we’ll want to save and serialize the OrderedDict in a json file.

dictionaries / json object ( collections.OrderedDict).

integers ( fake.random_int()) you can randomize within a range of integers.

strings ( ntence(), fake.word(), fake.pystr()) you can sample from list of words created above.

There are variations in the values, including: Most of the fields are typical key-value pairs. Everything is pushed into an collections.OrderedDict and in some cases, we have nested data. This next section is where we create a number of json objects, specified by length. Without these keywords, we’ll need to rely on random words/sentences that comes with the Faker library and that may not always be appropriate for our context. As we create mock json objects, for certain fields, we’ll want to populate from a sample of keywords that’s important for our project. This next section save a list of words that pertinent to our project in lists. We’ll save the file that we eventually write as testing_bounty and keep it a short length (5), while we’re still testing.įinally, we initialize the Faker library by calling the Faker function and setting to fake. Since we’ll be creating mock json data, the json built-in library is imported (specifically dumps), the Faker library is the main tool and we’ll also be using OrderedDict from collections to create document objects.ĭatabase is set to an empty array which will store the json object ( OrderedDict). Output.write(dumps(database, indent=4, sort_keys=False, default=str)) # turns date_between into string, circumvent json serialization

With open('%s.json' % filename, 'w') as output: ('skillsRequired', [fake.word(ext_word_list=skills), ('bountyHash', fake.md5(raw_output=False)), ('status', fake.word(ext_word_list=bounty_status)), ('bountyStatus', [collections.OrderedDict([ ('bountySubmissionLink', '# list of dictionaries ('bountySubmittedBy', fake.word(ext_word_list=random_guilds)), ('bount圜laimedAt', fake.date_between(start_date='today', end_date='+4m')), ('bount圜laimedBy', collections.OrderedDict([ ('bountyDueAt', fake.date_between(start_date='today', end_date='+1y')), ('bount圜reatedAt', fake.date_between(start_date='today', end_date='+3m')), ('discordHandle', fake.word(ext_word_list=discord_handle)), ('guildName', fake.word(ext_word_list=random_guilds)), ('bount圜reatedBy', collections.OrderedDict([ ('applicableGuilds', [collections.OrderedDict( ('currency', fake.word(ext_word_list=random_currencies)), ('bountyReward', collections.OrderedDict([ 'Developer's Guild', 'Analytics Guild', 'Writer's Guild']ĭiscord_handle = ['Open', 'Draft', 'In-Progress',ĭatabase.append(collections.OrderedDict([

Random_guilds = ['Marketing Guild', 'Treasury Guild', I’ve created a basic document (json) and now need to replicate multiple documents to simulate data once it’s populated with data from the frontend (or a Bot for this project specifically). Project context: Utilizing MongoDB as our NoSQL database.

#Generate fake data python full

The full code for a recent project is below, with breakdown of each section to follow. If you need to simulate mock data, the Faker library is a great resource. Creating mock data in Python with the Faker library