CREATE FAKE DATA HOW TO
CREATE FAKE DATA CODE
CREATE FAKE DATA OFFLINE
CREATE FAKE DATA ZIP

In most situations, importing a single locale is preferable for performance because some testing frameworks reload imports for every test file, which causes startup latencies to add up quickly.

CREATE FAKE DATA HOW TO

The first import indicates how one can import the entirety of Faker, which includes every locale, while the commented-out import showcases how to import only a single locale. The point of interest is the import statements at the top.

CREATE FAKE DATA CODE

The above code indicates a basic usage of Faker. Please do not send any of your messages/calls to them from your test setup. The generated names, addresses, emails, phone numbers, and/or other data might be coincidentally valid information. Note: Faker tries to generate realistic data and not obvious fake data.

🔢 Numbers - Of course, we can also generate random numbers and strings.

CREATE FAKE DATA OFFLINE

🧍 Names - Generate virtual humans with a complete online and offline identity.

👾 Hacker Jargon - “Try to reboot the SQL bus, maybe it will bypass the virtual application!”.

👠 Products - Generate Prices, Product Names, Adjectives, and Descriptions.

💸 Finance - Create stubbed out Account Details, Transactions, and Crypto Addresses.

🌏 Localization - Set a locale to generate realistic looking Names, Addresses, and Phone Numbers.

⏰ Time-based Data - Past, present, future, recent, soon.

CREATE FAKE DATA ZIP

💌 Locations - Generate valid looking Addresses, Zip Codes, Street Names, States, and Countries!.Please proceed to the Getting Started Guide for the stable release of Faker.įor detailed API documentation, please select the version of the documentation you are looking for. Open in StackBlitz 📙 API Documentation ⚠️ You are reading the docs for the next branch ⚠️ It's usually ok to just remove or alter double quotes to single.Generate massive amounts of fake (but realistic) data for testing and development. With embedded quotes, those will not parse well and it's hard to escape them. Now I'm just slapping a whole event into _raw so that I can test a regular expression on it. Note that the gettime macro is included with the ITSI app and not core Splunk. By adding 81 (as random() is zero-indexed), the random values will range from 80-120. In this example, the field resp_time can be used in ITSI as a threshold field. To generate more than 2 values, you'll need to use case(): | makeresults count=10Įrror = case( num = 10 AND num = 13, 200 ),Įrror_msg = case(error = 404, 'Not found', error = 500, 'Internal Server Error', error = 200, 'OK') These are good to pass to a stats function (and then visualiations) like this: | makeresults count=100 | eval poll=if((random()%5) = 1, 'Option A', 'Option B') | stats count by poll | makeresults count=100 | eval poll=if((random()%5) = 1, 'Option A', 'Option B') I'm using a higher count of 100 to give the results more entropy. To 1, this means that the first option will appear in approximately 25% of the events. Remainder will be 0.divisor (which is 5 here). Because we are using random() and modulo again, we know the This will create events containing one of the two 'answers' as supplied This will create numbers between 1.10: | makeresults count=10 | eval int=random() % 10 + 1įields containing random values from a set | makeresults count=10 | eval int=random() % 10Īnd if you want to modify the range, you could add to it.

Note that all events generated this way will have the same _time. 'wraps around', you know that the remainder will alwys be less than yourĭivisor, in this case, 10. WeĬan make it fit a desired range with the modulo operator. Unfortunately, this commandĭoes not have a range parameter, so it spits out a random 32-bit integer. This uses random() function to the eval command. Make event containing a string and numeric field | makeresults | eval msg='hello', seq=1 Note that when using these techniques, you are not going through the indexingĪnd parsing pipelines, so you can't test everything. Reason, here are some searches that have helped me out. Maybe you are helping someone with a hairy regex,Īnd you don't want to index data just to test it on your instance. Might be during developmentĪnd you don't feel like writing a real search, but you really need a number for aĭashboard panel to look right. Sometimes, you need to fake something in Splunk. How to make fake data in Splunk using SPL

Create fake data