redis-helper 0.5.0

Easily store, index, and modify Python dicts in Redis (with flexible searching)

Note: as of redis-helper v0.4.0, version 3.0 of redis-py is in use, which has backwards incompatible changes withe redis-py 2.x. See https://github.com/redis/redis-py/tree/70ef9ec68f9163c86d4cace2941e2f0ae4ce8525#upgrading-from-redis-py-2x-to-30

redis-helper transforms Redis into a human-friendly data exploration and analytics platform that optimizes for cognitive flow, rapid iteration, and interactive data exploration. In the simplest use case, you create an instance of redis_helper.Collection and specify any optional fields to index when data is added to enable quick storage and retrieval of Python dicts in Redis. You can filter through indexed fields with flexible arguments to the find method and take advantage of automatic timestamps for every entry added. There is also change history for data that has been updated and automatic stats relating to access/query patterns. When field validation is needed, regular expressions may be defined via rx_{field} kwargs when creating the collection instance.

At its core, redis-helper solves the mental burden of working with Redis directly by providing a single, powerful abstraction that handles complex operations behind intuitive, string-based interfaces. It’s built for data scientists, analysts, and developers who need to explore data interactively, prototype quickly, and deploy confidently without sacrificing the performance and reliability that Redis provides.

See the request logging demo and urls demo (with unique_field defined). The examples they reference are short and easy to read.

Install

pip install redis-helper

Dependency Incompatibility

Note that when using hiredis v1.1.0, redis-py v5.0.8 (last release on Python 3.7) is not compatible. Either use a newer version of hiredis or redis-py 5.0.7 (on Python 3.7). Newer versions of redis-py (i.e. 5.1.0+ on Python 3.8 - 3.11) are compatible with hiredis v1.1.0.

Configuration

redis-helper uses a settings.ini file for Docker and connection configuration:

[default]
image_version = 6-alpine

[dev]
container_name = redis-helper
port = 6379
rm = False
redis_url = redis://localhost:6379/1

[test]
container_name = redis-helper-test
port = 6380
rm = True
redis_url = redis://localhost:6380/9

On first use, the default settings.ini file is copied to ~/.config/redis-helper/settings.ini

The library automatically starts Redis via Docker if no connection is available, using these settings to configure container behavior, persistence options, and connection parameters for both development and testing environments.

Use the APP_ENV environment variable to specify which section of the settings.ini file your settings will be loaded from. Any settings in the default section can be overwritten if explicity set in another section. If no APP_ENV is explicitly set, dev is assumed.

QuickStart

import redis_helper as rh

# Create a collection for web request logs with validation
ANALYTICS_REQUESTS = rh.Collection(
    'analytics', 'requests',
    unique_field='request_id',
    index_fields='status, method, host, user_id',
    json_fields='headers, response_data',
    rx_status=r'[1-5][0-9][0-9]',         # Validate HTTP status codes
    rx_method=r'(GET|POST|PUT|DELETE)',   # Validate HTTP methods
    insert_ts=True                        # Track creation vs modification time
)

# Add some sample data
ANALYTICS_REQUESTS.add(
    request_id='req_123',
    method='GET',
    status=200,
    host='api.example.com',
    uri='/users/123',
    user_id='user_456',
    response_time=0.045,
    headers={'user-agent': 'curl/7.64.1', 'accept': '*/*'},
    response_data={'id': 123, 'name': 'John Doe', 'active': True}
)

ANALYTICS_REQUESTS.add(
    request_id='req_124',
    method='POST',
    status=400,
    host='api.example.com',
    uri='/users',
    user_id='user_789',
    response_time=0.012
)

ANALYTICS_REQUESTS.add(
    request_id='req_125',
    method='GET',
    status=200,
    host='web.example.com',
    uri='/dashboard',
    user_id='user_456',
    response_time=0.156
)

# Interactive exploration with powerful queries
recent_errors = ANALYTICS_REQUESTS.find('status:400', since='1:hour')
api_requests = ANALYTICS_REQUESTS.find('host:api.example.com, method:GET')

# Multi-temporal analytics in a single query
traffic_by_timeframe = ANALYTICS_REQUESTS.find('status:200', count=True, since='1:hour, 15:min, 5:min')
# Returns: {'1:hour': 1234, '15:min': 345, '5:min': 89}

# Human-readable formatting for reports
print(ANALYTICS_REQUESTS.random(item_format='{method} {uri} -> {status} ({response_time}s) at {_ts}'))
# Output: GET /users/123 -> 200 (0.045s) at 1642262202.123

# Get data with admin timestamp formatting ("%a %m/%d/%Y %I:%M:%S %p")
user_activity = ANALYTICS_REQUESTS.get('req_123', admin_fmt=True)
print(user_activity['_ts'])  # Output: Mon 01/15/2024 02:30:22 PM

# System introspection and monitoring
print(f"Total requests: {ANALYTICS_REQUESTS.size}")
print(f"Index distribution: {ANALYTICS_REQUESTS.index_field_info()}")
print(f"Most accessed endpoints: {ANALYTICS_REQUESTS.get_stats()}")

Running this example gives you immediate access to sophisticated data analytics capabilities with automatic timestamping, flexible querying, built-in statistics, and human-optimized output formatting. The system requires no configuration beyond basic field categorization and automatically handles Redis connection management, key generation, and data serialization.

Concepts

Redis is a fast in-memory data structure server, where each stored object is referenced by a key name. Objects in Redis correspond to one of several basic types, each having their own set of specialized commands to perform operations. The redis Python package provides the StrictRedis class, which contains methods that correspond to all of the Redis server commands, which redis-helper uses under the hood.

Tested for Python 3.5 - 3.13 against Redis 6 docker container.

When initializing Collection objects, you must specify the “namespace” and “name” of the collection (which are used to create the internally used _base_key property). All Redis keys associated with a Collection will have a name pattern that starts with the _base_key.

import redis_helper as rh


request_logs = rh.Collection(
    'log',
    'request',
    index_fields='status, uri, host',
    json_fields='request, response, headers'
)

urls = rh.Collection(
    'web',
    'url',
    unique_field='name',
    index_fields='domain, _type'
)

notes = rh.Collection(
    'input',
    'note',
    index_fields='topic, tag',
    insert_ts=True
)

sample = rh.Collection(
    'ns',
    'sample',
    unique_field='name',
    index_fields='status',
    json_fields='data',
    rx_name='\S{4,6}',
    rx_status='(active|inactive|cancelled)',
    rx_aws='[a-z]+\-[0-9a-f]+',
    insert_ts=True
)

uses_sample = rh.Collection(
    'ns',
    'uses_sample',
    index_fields='z',
    rx_thing='\S{4,6}',
    reference_fields='thing--ns:sample'
)

• a unique_field can be specified on a collection if items in the collection should not contain duplicate values for that particular field

  • the unique_field cannot also be included in json_fields or pickle_fields

  • if you specify a unique_field, that field must exist on each item you add to the collection

• use index_fields to specify which fields you will want to filter on when using the find method

  • the values for data fields being indexed MUST be simple strings or numbers

  • the values for data fields being indexed SHOULD NOT be long strings, as the values themselves are part of the index keys

• use json_fields to specify which fields should be JSON encoded before insertion to Redis

• use rx_{field} to specify a regular expression for any field with strict rules for validation

• use reference_fields to specify fields that reference the unique_field of another collection

  • uses field–basekey combos

• use pickle_fields to specify which fields should be pickled before insertion to Redis

• set insert_ts=True to create an additional index to store insert times

  • only do this if you are storing items that you are likely to update and also likely to want to know the original insert time

    • each time an object is updated, the score associated with the hash_id (at the _ts_zset_key) is updated to the current timestamp

    • the score associated with the hash_id (at the _in_zset_key) is never updated

Essentially, you can store a Python dict in a Redis hash and index some of the fields in Redis sets. The collection’s _ts_zset_key is the Redis key name for the sorted set containing the hash_id of every hash in the collection (with the score being a utc_float corresponding to the UTC time the hash_id was added or modified).

• if insert_ts=True was passed in when initializing the Collection (or sub-class), then the collection will also define self.in_zset_key to be the Redis key name for the sorted set (for hash_id and utc_float of insert time)

request_logs.add(
    method='get',
    status=400,
    host='blah.net',
    uri='/info',
    request={'x': 50, 'y': 100},
    response={'error': 'bad request'},
)

urls.add(
    name='redis-helper github',
    url='https://github.com/kenjyco/redis-helper',
    domain='github.com',
    _type='repo',
)

The get method is a wrapper to hash commands hget, hmget, or hgetall. The actual hash command that gets called is determined by the number of fields requested.

• a Python dict is typically returned from get

• if item_format is specified, a string will be returned matching that format instead

request_logs.get('log:request:1')
request_logs.get('log:request:1', 'host,status')
request_logs.get('log:request:1', item_format='{status} for {host}{uri}')
request_logs.get_by_position(0, item_format='{status} for {host}{uri}')
urls.get_by_position(-1, 'domain,url')
urls.get_by_unique_value('redis-helper github', item_format='{url} points to a {_type}')

• the get_by_position and get_by_unique_value methods are wrappers to get

  • the get_by_unique_value method is only useful if a unique_field was set on the Collection

The find method allows you to return data for items in the collection that match some set of search criteria. Multiple search terms (i.e. index_field:value pairs) maybe be passed in the terms parameter, as long as they are separated by one of , ; |. Any fields specified in the get_fields parameter are passed along to the get method (when the actual fetching takes place).

• when using terms, all terms that include the same field will be treatead like an “or” (union of related sets), then the intersection of different sets will be computed

• see the Redis set commands and sorted set commands

There are many options for specifying time ranges in the find method including:

• since and until when specifying num:unit strings (i.e. 15:seconds, 1.5:weeks, etc)

• start_ts and end_ts when specifying timestamps with a form between YYYY and YYYY-MM-DD HH:MM:SS.f

• start and end when specifying a utc_float

• for since, until, start_ts, and end_ts, multiple values may be passed in the string, as long as they are separated by one of , ; |.

  • when multiple time ranges are specified, the find method will determine all reasonable combinations and return a result-set per combination (instead of returning a list of items, returns a dict of list of items)

If count=True is specified, the number of results matching the search criteria are returned instead of the actual results

• if there are multiple time ranges specified, counts will be returned for each combination

request_logs.find('status:400, host:blah.net', get_fields='uri,error')
request_logs.find(since='1:hr, 30:min', until='15:min, 5:min')
request_logs.find(count=True, since='1:hr, 30:min', until='15:min, 5:min')
urls.find(count=True, since='1:hr, 30:min, 10:min, 5:min, 1:min')
urls.find(start_ts='2017-02-03', end_ts='2017-02-03 7:15:00')
urls.find(start_ts='2017-02-03', item_format='{_ts} -> {_id}')

The update method allows you to change values for some fields (modifying the unique_field, when it is specified, is not allowed).

• every time a field is modified for a particular hash_id, the previous value and score (timestamp) are stored in a Redis hash

• the old_data_for_hash_id or old_data_for_unique_value methods can be used to retrieve the history of all changes for a hash_id

urls.update('web:url:1', _type='fancy', notes='this is a fancy url')
urls.old_data_for_hash_id('web:url:1')
urls.old_data_for_unique_value('redis-helper github')

The load_ref_data option on get, get_by_unique_value, or find methods allow you to load the referenced data object from the other collection (where reference_fields are specified)

In [1]: sample.add(name='hello', aws='ami-0ad5743816d822b81', status='active')
Out[1]: 'ns:sample:1'

In [2]: uses_sample.add(thing='hello', z=500, y=True)
Out[2]: 'ns:uses_sample:1'

In [3]: uses_sample.get('ns:uses_sample:1')
Out[3]: {'thing': 'hello', 'z': 500, 'y': True}

In [4]: uses_sample.get('ns:uses_sample:1', load_ref_data=True)
Out[4]:
{'thing': {'name': 'hello',
  'aws': 'ami-0ad5743816d822b81',
  'status': 'active',
  '_id': 'ns:sample:1',
  '_ts': 20201028210044.875},
 'z': 500,
 'y': True}

In [5]: uses_sample.add(thing='byebye', z=100, y=True)
Out[5]: 'ns:uses_sample:2'

In [6]: uses_sample.get('ns:uses_sample:2', load_ref_data=True)
Out[6]: {'thing': 'byebye', 'z': 100, 'y': True}

Tip

There may be times where you want to use redis-helper (if it’s already installed), but don’t want to make it an explicit requirement of your project. In cases like this you can do the following:

try:
    import redis_helper as rh
    from redis import ConnectionError as RedisConnectionError
except (ImportError, ModuleNotFoundError):
    SomeCollection = None
else:
    try:
        SomeCollection = rh.Collection(
            ...
        )
    except RedisConnectionError:
        SomeCollection = None

Then in whatever function, you can just do:

def some_func():
    if SomeCollection is None:
        return

    # Do stuff with SomeCollection

Console Scripts

The rh-download-examples, rh-download-scripts, rh-notes, and rh-shell scripts are provided.

$ venv/bin/rh-download-examples --help
Usage: rh-download-examples [OPTIONS] [DIRECTORY]

  Download redis-helper example files from github

Options:
  --help  Show this message and exit.

$ venv/bin/rh-download-scripts --help
Usage: rh-download-scripts [OPTIONS] [DIRECTORY]

  Download redis-helper script files from github

Options:
  --help  Show this message and exit.

$ venv/bin/rh-notes --help
Usage: rh-notes [OPTIONS] [TOPIC]

  Prompt user to enter notes (about a topic) until finished; or review notes

Options:
  -c, --ch TEXT  string appended to the topic (default "> ")
  -s, --shell    Start an ipython shell to inspect the notes collection
  --help         Show this message and exit.

$ venv/bin/rh-shell --help
Usage: rh-shell [OPTIONS]

  Interactively select a Collection model and start ipython shell

Options:
  --help  Show this message and exit.

API Overview

Top-Level Functions

• ``zshow(key, start=0, end=-1, desc=True, withscores=True)`` - Wrapper to Redis ZRANGE for debugging

  • key (str): Redis sorted set key to examine

  • start (int): Starting index

  • end (int): Ending index

  • desc (bool): Descending order

  • withscores (bool): Include scores in output

  • Returns: List of items from sorted set

  • Internal calls: None

• ``identity(x)`` - Return input value unmodified (null object pattern)

  • x: Any value to return unchanged

  • Returns: The input value x

  • Internal calls: None

• ``start_docker(exception=False, show=False, force=False)`` - Start Redis Docker container using settings.ini configuration

  • exception (bool): Raise exception if Docker has error response

  • show (bool): Show Docker commands and output

  • force (bool): Stop and remove container before recreating

  • Returns: Boolean indicating success

  • Internal calls: bh.tools.docker_redis_start()

• ``stop_docker(exception=False, show=False)`` - Stop Redis Docker container

  • exception (bool): Raise exception if Docker has error response

  • show (bool): Show Docker commands and output

  • Returns: Boolean indicating success

  • Internal calls: bh.tools.docker_stop()

• ``connect_to_server(url=REDIS_URL, attempt_docker=True, exception=False, show=False)`` - Connect to Redis server and set global REDIS variable

  • url (str): Redis URL (redis://[:password@]host:port/db)

  • attempt_docker (bool): Start Docker if connection fails

  • exception (bool): Raise exception if unable to connect

  • show (bool): Show Docker commands and output

  • Returns: Tuple of (success_boolean, db_size)

  • Internal calls: start_docker()

Collection Creation and Configuration

• ``Collection(namespace, name, unique_field=’’, index_fields=’’, json_fields=’’, pickle_fields=’’, expected_fields=’’, reference_fields=’’, insert_ts=False, list_name=’’, **kwargs)`` - Create and configure a new collection instance

  • namespace (str): Top-level organization category (e.g., ‘analytics’, ‘app’, ‘logs’)

  • name (str): Specific collection identifier within namespace

  • unique_field (str, optional): Field name that enforces uniqueness constraints

  • index_fields (str, optional): Comma/semicolon/pipe-separated fields for fast lookups

  • json_fields (str, optional): Fields that should be automatically JSON serialized/deserialized

  • pickle_fields (str, optional): Fields for complex Python objects requiring pickle serialization

  • expected_fields (str, optional): Fields that are likely to be used (for optimization)

  • reference_fields (str, optional): Fields that reference unique values in other collections

  • insert_ts (bool): Track creation time separately from modification time

  • list_name (str, optional): Optional list name for specialized use cases

  • **kwargs: Additional configuration including rx_{field} regex validation patterns

  • Returns: Collection instance with all Redis keys and configuration established

  • Internal calls: rh.connect_to_server(), ih.make_var_name(), ih.string_to_set(), self.get_model()

Data Manipulation

• ``Collection.add(**data)`` - Add new item with automatic indexing and timestamping

  • **data: Arbitrary keyword arguments representing field-value pairs

  • Returns: String hash ID for the created item

  • Internal calls: self.validate(), self.wait_for_unlock()

• ``Collection.get(hash_ids, fields=’’, include_meta=False, timestamp_formatter=rh.identity, ts_fmt=None, ts_tz=None, admin_fmt=False, item_format=’’, insert_ts=False, load_ref_data=False, update_get_stats=True)`` - Retrieve items with flexible formatting

  • hash_ids (str or list): Single hash ID or list of hash IDs to retrieve

  • fields (str): Comma-separated field names to retrieve (empty = all fields)

  • include_meta (bool): Include system fields like _id and _ts

  • timestamp_formatter: Function to format timestamp values

  • ts_fmt (str): Timestamp format string

  • ts_tz (str): Timezone for timestamp formatting

  • admin_fmt (bool): Use admin formatting from settings

  • item_format (str): Template string for custom output formatting

  • insert_ts (bool): Use insertion time instead of modification time

  • load_ref_data (bool): Resolve reference fields to actual referenced data

  • update_get_stats (bool): Track access statistics for this operation

  • Returns: Dictionary or list of dictionaries with requested data

  • Internal calls: ih.string_to_list(), ih.decode(), ih.string_to_set(), dh.get_timestamp_formatter_from_args(), ih.from_string()

• ``Collection.update(hash_id, change_history=True, **data)`` - Modify existing item with change tracking

  • hash_id (str): Target item identifier

  • change_history (bool): Preserve previous values with timestamps

  • **data: Field-value pairs to update

  • Returns: List of human-readable change descriptions

  • Internal calls: self.validate(), self.wait_for_unlock(), self.get(), ih.from_string()

• ``Collection.delete(hash_id, pipe=None)`` - Remove single item and clean up indexes

  • hash_id (str): Item to remove

  • pipe: Optional Redis pipeline for batching

  • Returns: Result of pipeline execution if pipe used, otherwise None

  • Internal calls: self.wait_for_unlock(), self.get()

• ``Collection.delete_many(*hash_ids)`` - Remove multiple items efficiently

  • *hash_ids: Variable number of hash IDs to delete

  • Returns: Last result from pipeline execution

  • Internal calls: self.wait_for_unlock(), self.delete()

• ``Collection.delete_where(terms=’’, limit=None, desc=False, insert_ts=False)`` - Delete items matching query criteria

  • terms (str): Query string like ‘field1:value1, field2:value2’

  • limit (int): Maximum number of items to delete

  • desc (bool): Process items in descending order

  • insert_ts (bool): Use insertion timestamps for ordering

  • Returns: Result from delete_many operation

  • Internal calls: self.find(), self.delete_many()

• ``Collection.delete_to(score=None, ts=’’, tz=None, insert_ts=False)`` - Delete items up to specified timestamp

  • score (float): Timestamp score for deletion boundary

  • ts (str): Human-readable timestamp (‘2017-01-01’, ‘2017-02-03 7:15:00’)

  • tz (str): Timezone for timestamp interpretation

  • insert_ts (bool): Use insertion timestamps instead of modification timestamps

  • Returns: Result from delete_many operation

  • Internal calls: dh.date_string_to_utc_float_string(), ih.decode(), self.delete_many()

Query Operations

• ``Collection.find(terms=’’, start=None, end=None, limit=20, desc=None, get_fields=’’, all_fields=False, count=False, ts_fmt=None, ts_tz=None, admin_fmt=False, start_ts=’’, end_ts=’’, since=’’, until=’’, include_meta=True, item_format=’’, insert_ts=False, load_ref_data=False, post_fetch_sort_key=’’, sort_key_default_val=’’)`` - Flexible search with temporal filtering

  • terms (str): Query string like ‘field1:value1, field2:value2’ with flexible delimiters

  • start (int): Starting position for result slice

  • end (int): Ending position for result slice

  • limit (int): Maximum results to return

  • desc (bool): Sort order (None for automatic inference, True for recent-first)

  • get_fields (str): Specific fields to retrieve

  • all_fields (bool): Include all fields regardless of configuration

  • count (bool): Return counts instead of data

  • ts_fmt (str): Timestamp format string

  • ts_tz (str): Timezone for timestamp formatting

  • admin_fmt (bool): Use admin formatting from settings

  • start_ts (str): Absolute start timestamp

  • end_ts (str): Absolute end timestamp

  • since (str): Relative time expressions (‘1:hour’, ‘30:minutes’, ‘5:min, 1:min, 30:sec’)

  • until (str): Relative end time expression

  • include_meta (bool): Include system metadata fields

  • item_format (str): Custom output formatting template

  • insert_ts (bool): Use insertion time instead of modification time

  • load_ref_data (bool): Resolve reference fields

  • post_fetch_sort_key (str): Field to sort results by after retrieval

  • sort_key_default_val: Default value for missing sort keys

  • Returns: List of matching items or dictionary of counts by time range

  • Internal calls: dh.get_time_ranges_and_args(), dh.get_timestamp_formatter_from_args(), self.get(), ih.decode()

• ``Collection.random(terms=’’, start=None, end=None, ts_fmt=None, ts_tz=None, admin_fmt=False, start_ts=’’, end_ts=’’, since=’’, until=’’, **get_kwargs)`` - Get random sample with same filtering options as find

  • terms (str): Query string like ‘field1:value1, field2:value2’ with flexible delimiters

  • start (int): Starting position for result slice

  • end (int): Ending position for result slice

  • ts_fmt (str): Timestamp format string

  • ts_tz (str): Timezone for timestamp formatting

  • admin_fmt (bool): Use admin formatting from settings

  • start_ts (str): Absolute start timestamp

  • end_ts (str): Absolute end timestamp

  • since (str): Relative time expressions (‘1:hour’, ‘30:minutes’, ‘5:min, 1:min, 30:sec’)

  • until (str): Relative end time expression

  • **get_kwargs: Additional parameters accepted by the get() method

  • Returns: Single random item matching criteria

  • Internal calls: dh.get_time_ranges_and_args(), dh.get_timestamp_formatter_from_args(), self.get(), self.get_by_position()

Specific Access Methods

• ``Collection.get_by_unique_value(unique_val, fields=’’, include_meta=False, timestamp_formatter=rh.identity, ts_fmt=None, ts_tz=None, admin_fmt=False, item_format=’’, insert_ts=False, load_ref_data=False, update_get_stats=True)`` - Retrieve item by unique field value

  • unique_val: Value to search for in the unique field

  • All other parameters same as get() method

  • Returns: Dictionary with item data or empty dict if not found

  • Internal calls: self.get_hash_id_for_unique_value(), self.get()

• ``Collection.get_by_position(pos, **kwargs)`` - Get item by position (most recent first by default)

  • pos (int): Position index (0 = most recent)

  • **kwargs: All parameters accepted by get() method

  • Returns: Dictionary with item data

  • Internal calls: self.get()

• ``Collection.get_by_slice(start=None, stop=None, **kwargs)`` - Get slice of items by position

  • start (int): Starting position

  • stop (int): Ending position

  • **kwargs: All parameters accepted by get() method

  • Returns: List of dictionaries

  • Internal calls: self.get()

• ``Collection.get_hash_id_for_unique_value(unique_val)`` - Get hash ID for unique field value

  • unique_val: Value to look up

  • Returns: Hash ID string or None if not found

  • Internal calls: None

Collection Management

• ``Collection.get_model(cls, base_key=None, init_args=None)`` (classmethod) - Reconstruct Collection instance from Redis state

  • base_key (str): Redis base key for the collection

  • init_args (str): Initialization arguments string

  • Returns: Collection instance

  • Internal calls: ih.decode()

• ``Collection.select_models(cls, named=False)`` (classmethod) - Interactive collection chooser

  • named (bool): Return dictionary with collection names as keys

  • Returns: Selected Collection instance(s)

  • Internal calls: cls.init_stats(), ih.make_selections(), cls.get_model()

• ``Collection.select_model(cls)`` (classmethod) - Select single collection interactively

  • Returns: Single Collection instance

  • Internal calls: cls.select_models()

• ``Collection.select_and_modify(menu_item_format=’’, action=’update’, prompt=’’, update_fields=’’, **find_kwargs)`` - Interactive bulk operations

  • menu_item_format (str): Template for displaying items in selection menu

  • action (str): Operation type (‘update’ or ‘delete’)

  • prompt (str): Custom prompt for user selection

  • update_fields (str): Fields to modify during update operations

  • **find_kwargs: All parameters accepted by find() method

  • Returns: Results of selected operations

  • Internal calls: ih.string_to_set(), ih.get_keys_in_string(), self.find(), ih.make_selections(), ih.user_input(), self.update(), self.delete()

Validation and Maintenance

• ``Collection.validate(**data)`` - Validate fields against configured regex patterns

  • **data: Field-value pairs to validate

  • Returns: List of validation error tuples (field, value, pattern)

  • Internal calls: None

• ``Collection.reindex()`` - Rebuild all search indexes from current data

  • Returns: None

  • Internal calls: self.wait_for_unlock(), ih.decode(), rh.zshow(), self.get()

• ``Collection.clear_keyspace()`` - Remove all data and indexes for this collection

  • Returns: None

  • Internal calls: None

System Properties and Introspection

• ``Collection.namespace`` (property) - Collection’s namespace

  • Returns: String namespace value

  • Internal calls: None

• ``Collection.name`` (property) - Collection’s name

  • Returns: String name value

  • Internal calls: None

• ``Collection.var_name`` (property) - Variable-safe name for collection

  • Returns: String variable name

  • Internal calls: None

• ``Collection.size`` (property) - Current number of items in collection

  • Returns: Integer count

  • Internal calls: None

• ``Collection.last`` (property) - Most recently modified item

  • Returns: Dictionary with item data

  • Internal calls: self.get_by_position()

• ``Collection.last_admin`` (property) - Most recent item with admin timestamp formatting

  • Returns: Dictionary with formatted timestamps

  • Internal calls: self.get_by_position()

• ``Collection.first`` (property) - Oldest item in collection

  • Returns: Dictionary with item data

  • Internal calls: self.get_by_position()

• ``Collection.first_admin`` (property) - Oldest item with admin timestamp formatting

  • Returns: Dictionary with formatted timestamps

  • Internal calls: self.get_by_position()

• ``Collection.last_update`` (property) - Timestamp of last collection modification

  • Returns: Float timestamp

  • Internal calls: ih.decode()

• ``Collection.last_update_admin`` (property) - Formatted timestamp of last modification

  • Returns: Human-readable timestamp string

  • Internal calls: self.last_update, dh.utc_float_to_pretty()

• ``Collection.now_pretty`` (property) - Current timestamp in admin format

  • Returns: Human-readable current timestamp

  • Internal calls: dh.utc_now_pretty()

• ``Collection.now_utc_float_string`` (property) - Current timestamp as string

  • Returns: Current UTC timestamp as string

  • Internal calls: dh.utc_now_float_string()

• ``Collection.info`` (property) - Complete system state and configuration summary

  • Returns: Formatted string with initialization args, size, last update, keyspace structure, and index statistics

  • Internal calls: self.size, self.last_update_admin, self.keyspace, self.index_field_info(), self.get_stats(), self.get()

• ``Collection.keyspace`` (property) - Redis key structure for debugging and monitoring

  • Returns: Sorted list of (key_name, key_type) tuples showing all Redis keys used by this collection

  • Internal calls: ih.decode()

• ``Collection.is_locked`` (property) - Check if collection is currently locked

  • Returns: Boolean lock status

  • Internal calls: ih.from_string(), ih.decode()

Statistics and Analysis

• ``Collection.get_stats(limit=5)`` - Access pattern analysis for items and fields accessed by get() method

  • limit (int): Number of top items to return in statistics

  • Returns: Dictionary with keys: counts (access frequency), fields (field access patterns), timestamps (access timing)

  • Internal calls: dh.utc_float_to_pretty(), ih.decode()

• ``Collection.find_stats(limit=5)`` - Summary info about temporary sets created during find calls

  • limit (int): Number of top search patterns to return

  • Returns: Dictionary with keys: counts, sizes, timestamps

  • Internal calls: ih.decode(), rh.zshow(), dh.utc_float_to_pretty()

• ``Collection.init_stats(cls, limit=5)`` (classmethod) - Collection creation statistics across all collections

  • limit (int): Number of entries to return

  • Returns: Dictionary with collection initialization patterns

  • Internal calls: dh.utc_float_to_pretty(), ih.decode()

• ``Collection.index_field_info(limit=10)`` - Data distribution analysis for indexed fields

  • limit (int): Number of top values per index to return

  • Returns: List of 2-item tuples with field names and their top values/counts

  • Internal calls: self.size, ih.decode(), rh.zshow()

• ``Collection.top_values_for_index(index_name, limit=10)`` - Most common values for specific index

  • index_name (str): Name of indexed field to analyze

  • limit (int): Number of top values to return

  • Returns: List of (value, count) tuples

  • Internal calls: self.recent_unique_values()

Historical Data Access

• ``Collection.old_data_for_hash_id(hash_id)`` - Change history for specific item

  • hash_id (str): Item to get history for

  • Returns: List of dictionaries with change history including timestamps, fields, and values

  • Internal calls: ih.decode(), dh.utc_float_to_pretty()

• ``Collection.old_data_for_unique_value(unique_val)`` - Change history by unique field value

  • unique_val: Unique field value to get history for

  • Returns: List of change history dictionaries

  • Internal calls: self.get_hash_id_for_unique_value(), self.old_data_for_hash_id()

• ``Collection.recent_unique_values(limit=10)`` - Most recently used unique field values

  • limit (int): Number of values to return

  • Returns: List of unique values ordered by recent use

  • Internal calls: ih.decode()

• ``Collection.all_unique_values()`` - All unique field values in collection

  • Returns: List of all unique field values

  • Internal calls: self.recent_unique_values()

Utility Methods

• ``Collection.wait_for_unlock(sleeptime=0.5)`` - Wait for collection to become unlocked

  • sleeptime (float): Seconds to sleep between lock checks

  • Returns: Total time slept

  • Internal calls: self.is_locked

• ``Collection.clear_find_stats()`` - Reset query statistics

  • Returns: None

  • Internal calls: None

• ``Collection.clear_get_stats()`` - Reset access statistics

  • Returns: None

  • Internal calls: None

• ``Collection.clear_init_stats()`` - Reset initialization statistics

  • Returns: None

  • Internal calls: None

• ``Collection.clear_all_collection_locks(cls)`` (classmethod) - Remove all collection locks (emergency use)

  • Returns: None

  • Internal calls: cls.init_stats()

• ``Collection.report_all(cls)`` (classmethod) - Generate report of all collections

  • Returns: None (prints report)

  • Internal calls: None

Container Protocol Support

The Collection class implements Python’s container protocols for intuitive access:

• collection[0] - Get item by position (most recent first)

• collection['hash_id'] - Get item by direct hash ID

• collection['unique_value'] - Get item by unique field value (falls back to random sample)

• collection[0:10] - Get slice of items

• len(collection) - Get total item count

• for item in collection: - Iterate through all items