This MongoDB Query lesson is for a beginner. Read the short notes, run each example, then change one name or number and run it again.
A query document names the fields that must match. {"track": "Python"} keeps documents whose track is Python.
Comparison operators use names such as $gt and $lt inside the field.
Example 1: Start here
The MongoDB filter for that test is {"score": {"$gt": 80}}.
collection = [{"name": "Meera", "score": 82}, {"name": "Arun", "score": 74}] # a list; the values stay in this order
print([doc for doc in collection if doc["score"] > 80]) # keep the items that pass the test
Example 2: Filter the rows
MongoDB Query is easier to see as a list of records. The filter keeps every row whose seats value is at least 10.
rows = [{"topic": "MongoDB Query", "seats": 30}, {"topic": "SQL", "seats": 12}] # a list; the values stay in this order
print([row["topic"] for row in rows if row["seats"] >= 10]) # keep the items that pass the test
Example 3: Update one field
An update changes one field and leaves the rest of the record alone. On a database you would run an UPDATE or an update_one for the same change.
row = {"topic": "MongoDB Query", "seats": 30} # a dictionary; each key has one value
row["seats"] = row["seats"] + 1 # change this one field
print(row)
Example 4: Count the matches
Counting matches is the idea behind COUNT(*). Here the number 30 appears twice.
rows = [30, 4, 30] # a list; the values stay in this order
print(sum(1 for value in rows if value == 30)) # keep the items that pass the test
The MongoDB filter for that test is {"score": {"$gt": 80}}.
