This release is a pre-release and may not be stable for production use.
Mokkari
A python wrapper for the Metron Comic Book Database API.
Installation
pip install mokkari
Authentication
Authenticate with an API token, which you can generate from your metron.cloud account page:
import mokkari
m = mokkari.api(api_token="your-api-token")
Username/password (Basic Auth) was removed in v5.0. If you're upgrading from
4.x, replace mokkari.api(username, password) with a token as shown above.
Example Usage
import mokkari
# Your own config file to keep your credentials secret
from config import api_token
m = mokkari.api(api_token=api_token)
# Get all Marvel comics for the week of 2021-06-07
this_week = m.issues_list(
{
"store_date_range_after": "2021-06-07",
"store_date_range_before": "2021-06-13",
"publisher_name": "marvel",
}
)
# Print the results
for i in this_week:
print(f"{i.id} {i.issue_name}")
# Retrieve the detail for an individual issue
asm_68 = m.issue(31660)
# Print the issue Description
print(asm_68.desc)
Rate Limiting
The API allows at least 20 requests per minute (the server may allow more when
load is low), plus a daily limit that starts at 5,000 requests and is raised for
OpenCollective donors (up to 25,000/day).
Because the daily limit varies per user, mokkari doesn't hardcode it — it reads
the X-RateLimit-* headers Metron returns with every response and pre-empts a
request once those headers show a window is exhausted, avoiding an HTTP call
that would fail anyway. When a rate limit is exceeded, a RateLimitError is
raised.
The most recently observed state is available via session.rate_limit_status:
status = m.rate_limit_status
print(f"Sustained remaining: {status.sustained.remaining}/{status.sustained.limit}")
Handling Rate Limits
The RateLimitError includes a retry_after attribute that tells you exactly
how many seconds to wait before making another request:
import mokkari
from mokkari.exceptions import RateLimitError
import time
m = mokkari.api(api_token=api_token)
try:
issue = m.issue(31660)
except RateLimitError as e:
# Display user-friendly message
print(f"Rate limited: {e}")
# Programmatically wait for the exact time needed
print(f"Waiting {e.retry_after} seconds...")
time.sleep(e.retry_after)
# Retry the request
issue = m.issue(31660)
Thread Safety
A Session can be shared across threads, but the rate-limit check above is
advisory rather than a hard gate: it only blocks once the last known response
headers show a window is exhausted, and that check isn't synchronized with
sending the request. Concurrent threads can therefore each pass the check and
send their requests before either response updates rate_limit_status, letting
a burst of threads momentarily exceed the per-minute limit (Metron's server-side
limit still applies and will reject the excess requests).
If you're calling a shared Session from multiple threads, cap your own
concurrency instead of relying on Session to do it for you, e.g. keep a
ThreadPoolExecutor at or below the burst limit:
from concurrent.futures import ThreadPoolExecutor
m = mokkari.api(api_token=api_token)
# Keep worker count at or below the burst limit (20/min at minimum) to avoid
# racing past the local rate-limit check.
with ThreadPoolExecutor(max_workers=20) as executor:
issues = list(executor.map(m.issue, issue_ids))
Pacing (opt-in)
Passing rate_limiter closes the gap described above: instead of racing past an
advisory check, every HTTP send is dispatched through the rate limiter first,
which can block a caller until capacity actually frees rather than letting it
send anyway. mokkari.rate_limit.HeaderPacedRateLimiter is a ready-to-use
implementation. It sizes the per-minute window from the X-RateLimit-* headers
but paces it from its own monotonic log of send times, so a local clock that has
drifted from Metron's doesn't matter, and it spaces sends evenly across the
window (at the 20/min floor, one every 3 seconds). If Metron still answers with
a 429, it backs every caller off by the Retry-After value the server sent:
from concurrent.futures import ThreadPoolExecutor
import mokkari
from mokkari.rate_limit import HeaderPacedRateLimiter
m = mokkari.api(api_token=api_token, rate_limiter=HeaderPacedRateLimiter())
with ThreadPoolExecutor(max_workers=20) as executor:
issues = list(executor.map(m.issue, issue_ids))
The limiter only blocks for the per-minute window, whose waits are seconds long.
When the daily limit is exhausted it raises RateLimitError instead of blocking
for what could be hours, with retry_after set to the time until the daily
window resets. That leaves it to your application to tell the user and either
wait or quit:
import time
from mokkari.exceptions import RateLimitError
from mokkari.utils import format_time
try:
issue = m.issue(31660)
except RateLimitError as e:
if input(f"Daily limit reached. Wait {format_time(e.retry_after)}? (y/n): ") == "y":
time.sleep(e.retry_after)
issue = m.issue(31660)
Paginated list calls follow the same rules: if a page is rejected with a 429
they retry it through the limiter, which blocks until it's safe to send, and an
exhausted daily limit raises RateLimitError from the list call rather than
being waited out.
A rate limiter object is scoped to the Session it's passed to — construct one
per Session rather than sharing an instance across sessions using different
credentials. Passing your own object works too, as long as it implements the
acquire/on_rate_limited/release methods described in
mokkari.rate_limit.RateLimiter.
Leaving rate_limiter unset (the default) keeps the raise-immediately behavior
described above.
Pacing across processes with Redis
HeaderPacedRateLimiter only sees the requests its own process sends, so
several workers using one account can overrun the per-minute window together
until Metron answers with 429s. mokkari.redis_rate_limit.RedisRateLimiter
paces the same way but keeps its state in Redis, so every process and host using
the same account shares one per-minute window, one daily estimate and one 429
backoff. Install the redis extra and pass it a client:
pip install mokkari[redis]
import redis
import mokkari
from mokkari.redis_rate_limit import RedisRateLimiter
client = redis.Redis(host="localhost", port=6379, socket_connect_timeout=1, socket_timeout=1)
# Any stable name for your Metron account, such as its username. Don't use the
# token itself: it becomes part of key names anyone with Redis access can read.
m = mokkari.api(
api_token=api_token,
rate_limiter=RedisRateLimiter(client, account="your-username"),
)
It raises RateLimitError on an exhausted daily limit just like
HeaderPacedRateLimiter. Times come from the Redis server's clock, and every
key expires on its own, so a worker that crashes mid-request can't leave the
account blocked. If Redis is unreachable, acquire raises the client's
connection error and the request isn't sent. Set socket_connect_timeout and
socket_timeout on the client as above: without them, a Redis host that stops
responding, rather than refusing the connection, makes acquire wait on it
indefinitely. The limiter's own waits happen in the client, not in Redis, so a
short timeout doesn't cut them off.
Caching
Pass a cache to keep responses locally, so repeated requests don't count against your rate limit:
import mokkari
from mokkari.sqlite_cache import SqliteCache
m = mokkari.api(api_token="your-token", cache=SqliteCache("mokkari_cache.db"))
import mokkari no longer loads mokkari.sqlite_cache in v5.0. If you're
upgrading from 4.x and refer to mokkari.sqlite_cache.SqliteCache after only
import mokkari, import the module explicitly as shown above.
Sharing a cache with Redis
SqliteCache keeps its cache on one machine. mokkari.redis_cache.RedisCache
keeps it in Redis instead, so several processes or hosts can share it. It takes
the same default_ttl, ttl and empty_list_ttl options. Install the redis
extra and pass it a client:
import redis
import mokkari
from mokkari.redis_cache import RedisCache
client = redis.Redis(host="localhost", port=6379, socket_connect_timeout=1, socket_timeout=1)
m = mokkari.api(api_token="your-token", cache=RedisCache(client))
Entries expire through Redis's own TTLs, and every key starts with key_prefix
("mokkari:cache" by default), so clear() leaves other data in the database
alone. It needs Redis 7.0 or later on a single server, not a Redis Cluster.
Writes find the entries to drop through per-resource index keys, so if Redis
evicts keys under memory pressure, an evicted index can leave stale entries
until they expire; size Redis so that eviction doesn't happen. If Redis is
unreachable, each request still goes to Metron, but only after the cache lookup
and store have each failed, and both errors are logged. Set
socket_connect_timeout and socket_timeout on the client as above to bound
that delay: without them, a Redis host that stops responding, rather than
refusing the connection, makes every request wait on it indefinitely.
Connection Reuse
A Session keeps its connections to Metron open between requests, so repeated
calls don't pay a new TCP/TLS handshake each time. Cookies are never stored or
sent back. To release the connections deterministically, use the session as a
context manager or call close():
with mokkari.api(api_token="your-token") as m:
issue = m.issue(1)
Closing is optional, and a closed session can still be used; it just opens new
connections. If the server drops an idle connection, the underlying HTTP library
notices and discards it when the next request checks it out, so a request opens
a fresh connection instead. The only failure is a race: if the server closes a
connection in the instant it is reused, that request raises an ApiError. This
is rare, and mokkari doesn't retry it automatically. Don't share a Session
across forked processes; create one per process.
Documentation
Read the project documentation
Bugs/Requests
Please use the GitHub issue tracker to submit bugs or request features.
Metadata
Release files for mokkari 5.0.0a2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
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|---|---|---|---|---|
| mokkari-5.0.0a2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 226.2 kB
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