JmailClient - Jmail Data API

Constructor

JmailClient(cache=True)

Create a new client instance.

Parameters

bool

default:"True"

Enable local ETag-based file caching at ~/.cache/jmail/. Set to False to always download fresh data.

Example

from jmail import JmailClient

# Default: caching enabled
client = JmailClient()

# No caching
client = JmailClient(cache=False)

Methods

Method	Returns	Description
`manifest()`	`dict`	API manifest with dataset metadata
`emails(slim)`	`DataFrame`	Email archive
`documents(include_text)`	`DataFrame`	Document metadata/text
`photos()`	`DataFrame`	Photo metadata
`people()`	`DataFrame`	Identified people
`photo_faces()`	`DataFrame`	Face bounding boxes
`imessage_conversations()`	`DataFrame`	iMessage conversations
`imessage_messages()`	`DataFrame`	iMessage messages
`star_counts()`	`DataFrame`	Crowd-sourced stars
`release_batches()`	`DataFrame`	Release batch info
`url(dataset, fmt)`	`str`	Raw dataset URL

`manifest()`

Fetch the API manifest with dataset metadata and checksums.

manifest = client.manifest()
print(manifest)

Returns: dict — parsed JSON from data.jmail.world/v1/manifest.json

`url(dataset, fmt="parquet")`

Get the raw URL for a dataset file. Useful for passing directly to DuckDB, Polars, or any tool that reads Parquet over HTTP.

url = client.url("emails-slim")
# "https://data.jmail.world/v1/emails-slim.parquet"

url = client.url("documents", fmt="ndjson.gz")
# "https://data.jmail.world/v1/documents.ndjson.gz"

str

required

Dataset name. One of: emails, emails-slim, documents, photos, people, photo_faces, imessage_conversations, imessage_messages, star_counts, release_batches.

str

default:"parquet"

File format. Either parquet or ndjson.gz.

Returns: str — full URL

​Constructor

​Parameters

​Example

​Methods

​manifest()

​url(dataset, fmt="parquet")