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.
pip install redis-helper
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.
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.
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.
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_fieldcan be specified on a collection if items in the collection should not contain duplicate values for that particular field- the
unique_fieldcannot also be included injson_fieldsorpickle_fields - if you specify a
unique_field, that field must exist on each item you add to the collection
- the
- use
index_fieldsto specify which fields you will want to filter on when using thefindmethod- 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_fieldsto 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_fieldsto specify fields that reference theunique_fieldof another collection- uses field–basekey combos
- use
pickle_fieldsto specify which fields should be pickled before insertion to Redis - set
insert_ts=Trueto 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
- each time an object is updated, the score associated with the
- 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
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=Truewas passed in when initializing theCollection(or sub-class), then the collection will also defineself.in_zset_keyto be the Redis key name for the sorted set (forhash_idandutc_floatof 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_formatis 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_positionandget_by_unique_valuemethods are wrappers toget- the
get_by_unique_valuemethod is only useful if aunique_fieldwas set on the Collection
- the
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:
sinceanduntilwhen specifyingnum:unitstrings (i.e. 15:seconds, 1.5:weeks, etc)start_tsandend_tswhen specifying timestamps with a form betweenYYYYandYYYY-MM-DD HH:MM:SS.fstartandendwhen specifying autc_float- for
since,until,start_ts, andend_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
findmethod 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)
- when multiple time ranges are specified, the
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_idorold_data_for_unique_valuemethods can be used to retrieve the history of all changes for ahash_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}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
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.
- ``zshow(key, start=0, end=-1, desc=True, withscores=True)`` -
Wrapper to Redis ZRANGE for debugging
key(str): Redis sorted set key to examinestart(int): Starting indexend(int): Ending indexdesc(bool): Descending orderwithscores(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 responseshow(bool): Show Docker commands and outputforce(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 responseshow(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 failsexception(bool): Raise exception if unable to connectshow(bool): Show Docker commands and output- Returns: Tuple of (success_boolean, db_size)
- Internal calls:
start_docker()
- ``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 namespaceunique_field(str, optional): Field name that enforces uniqueness constraintsindex_fields(str, optional): Comma/semicolon/pipe-separated fields for fast lookupsjson_fields(str, optional): Fields that should be automatically JSON serialized/deserializedpickle_fields(str, optional): Fields for complex Python objects requiring pickle serializationexpected_fields(str, optional): Fields that are likely to be used (for optimization)reference_fields(str, optional): Fields that reference unique values in other collectionsinsert_ts(bool): Track creation time separately from modification timelist_name(str, optional): Optional list name for specialized use cases**kwargs: Additional configuration includingrx_{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()
- ``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 retrievefields(str): Comma-separated field names to retrieve (empty = all fields)include_meta(bool): Include system fields like_idand_tstimestamp_formatter: Function to format timestamp valuests_fmt(str): Timestamp format stringts_tz(str): Timezone for timestamp formattingadmin_fmt(bool): Use admin formatting from settingsitem_format(str): Template string for custom output formattinginsert_ts(bool): Use insertion time instead of modification timeload_ref_data(bool): Resolve reference fields to actual referenced dataupdate_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 identifierchange_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 removepipe: 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 deletedesc(bool): Process items in descending orderinsert_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 boundaryts(str): Human-readable timestamp (‘2017-01-01’, ‘2017-02-03 7:15:00’)tz(str): Timezone for timestamp interpretationinsert_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()
- ``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 delimitersstart(int): Starting position for result sliceend(int): Ending position for result slicelimit(int): Maximum results to returndesc(bool): Sort order (None for automatic inference, True for recent-first)get_fields(str): Specific fields to retrieveall_fields(bool): Include all fields regardless of configurationcount(bool): Return counts instead of datats_fmt(str): Timestamp format stringts_tz(str): Timezone for timestamp formattingadmin_fmt(bool): Use admin formatting from settingsstart_ts(str): Absolute start timestampend_ts(str): Absolute end timestampsince(str): Relative time expressions (‘1:hour’, ‘30:minutes’, ‘5:min, 1:min, 30:sec’)until(str): Relative end time expressioninclude_meta(bool): Include system metadata fieldsitem_format(str): Custom output formatting templateinsert_ts(bool): Use insertion time instead of modification timeload_ref_data(bool): Resolve reference fieldspost_fetch_sort_key(str): Field to sort results by after retrievalsort_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 delimitersstart(int): Starting position for result sliceend(int): Ending position for result slicets_fmt(str): Timestamp format stringts_tz(str): Timezone for timestamp formattingadmin_fmt(bool): Use admin formatting from settingsstart_ts(str): Absolute start timestampend_ts(str): Absolute end timestampsince(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()
- ``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 byget()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 positionstop(int): Ending position**kwargs: All parameters accepted byget()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.get_model(cls, base_key=None, init_args=None)``
(classmethod) - Reconstruct Collection instance from Redis state
base_key(str): Redis base key for the collectioninit_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 menuaction(str): Operation type (‘update’ or ‘delete’)prompt(str): Custom prompt for user selectionupdate_fields(str): Fields to modify during update operations**find_kwargs: All parameters accepted byfind()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()
- ``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
- ``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()
- ``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 analyzelimit(int): Number of top values to return- Returns: List of (value, count) tuples
- Internal calls:
self.recent_unique_values()
- ``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()
- ``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
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 IDcollection['unique_value']- Get item by unique field value (falls back to random sample)collection[0:10]- Get slice of itemslen(collection)- Get total item countfor item in collection:- Iterate through all items