Pattern Matching: Finding Keys

The File Search Analogy

When you search for files on your computer, you can use wildcards:

*.txt finds all text files
photo_?.jpg finds photo_1.jpg, photo_2.jpg, etc.
report_[abc].pdf finds report_a.pdf, report_b.pdf, report_c.pdf

PyKV uses the same glob patterns to search through your keys!

Wildcard Reference

Pattern	Meaning	Example
`*`	Match anything (zero or more characters)	`user:*` matches `user:alice`, `user:bob`
`?`	Match exactly one character	`log?` matches `log1`, `logA`, not `log10`
`[abc]`	Match one of the listed characters	`item_[12]` matches `item_1`, `item_2`

Finding Keys

from pykv import BasicStore, match_keys

store = BasicStore()
store.set("user:alice", "admin")
store.set("user:bob", "member")
store.set("post:1", "Hello!")
store.set("post:2", "World!")

# Find all user keys
match_keys(store, "user:*")    # ["user:alice", "user:bob"]

# Find all post keys
match_keys(store, "post:*")    # ["post:1", "post:2"]

# Find everything
match_keys(store, "*")         # ["post:1", "post:2", "user:alice", "user:bob"]

Finding Keys AND Values

from pykv import match_items

match_items(store, "user:*")
# {"user:alice": "admin", "user:bob": "member"}

Counting Matches

from pykv import count_matches

count_matches(store, "user:*")  # 2
count_matches(store, "post:*")  # 2
count_matches(store, "nope:*")  # 0

Combining with Namespaces

Pattern matching works great alongside namespaces for powerful data organization:

from pykv import BasicStore, Namespace, match_keys

store = BasicStore()
pages = Namespace(store, "cache:page")   # a folder inside "cache"
api = Namespace(store, "cache:api")
pages.set("home", "<html>...")
pages.set("about", "<html>...")
api.set("users", "[...]")

# Find all cached pages
match_keys(store, "cache:page:*")  # ["cache:page:about", "cache:page:home"]