Perform queries across multiple MongoDB databases and collections, where the field names and the field content structure in each database may vary.

Suppose you've got two database collections, "leak1" and "leak2"

In leak1, the schema looks like this:

FIRST_NAME: "JOHN"
LAST_NAME: "DOE"

and in leak2, the schema looks like this:

FName: "John"
LName: "Doe"

A simple program to iterate through all your collections and perform queries wouldn't work, because:

• the field names are different. Notice that in leak1, the first name field is FIRST_NAME, while in leak2, the first name field is named FName.
• the field values might be structured differently. In leak1, everything is captialized. In leak2, it's all title-case.

This program lets you write a configuration for each collection, specifying, in JSON, how to query each field.

It's a work in progress, but so far, it works pretty well. It'll probably be easier to understand if you take a look at the config files under ./collections/. Each JSON file under ./collections/ should be an array of objects. The program automatically processes all JSON files under that directory.

Some more info for how the configurations work can be found in the wiki.

Find all records of a guy named John Doe.

python3 -m dev --firstname John --lastname Doe

Each database will be searched, and results will be put into a new file under ./results/

Find all records for someone with an address of "1234 NW Long St" python3 -m dev --address "1234 NW long st"

Adding a zipcode to the end, or a state/province might speed up the query (depending on how you index your databases)

(information redacted for this person's privacy)

Configured fields will print to the console, while all the other fields in a result will be saved under ./results/.