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_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 injson_fields
orpickle_fields
- if you specify a
unique_field
, that field must exist on each item you add to the collection
- the
- use
index_fields
to specify which fields you will want to filter on when using thefind
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 theunique_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
- 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=True
was passed in when initializing theCollection
(or sub-class), then the collection will also defineself.in_zset_key
to be the Redis key name for the sorted set (forhash_id
andutc_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
andget_by_unique_value
methods are wrappers toget
- the
get_by_unique_value
method is only useful if aunique_field
was 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:
since
anduntil
when specifyingnum:unit
strings (i.e. 15:seconds, 1.5:weeks, etc)start_ts
andend_ts
when specifying timestamps with a form betweenYYYY
andYYYY-MM-DD HH:MM:SS.f
start
andend
when 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
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)
- 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_id
orold_data_for_unique_value
methods 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 debuggingkey
(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 configurationexception
(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 containerexception
(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 variableurl
(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 instancenamespace
(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 formattinghash_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_id
and_ts
timestamp_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 trackinghash_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 indexeshash_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 criteriaterms
(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 timestampscore
(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 filteringterms
(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 findterms
(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 valueunique_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 positionstart
(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 valueunique_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 statebase_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 choosernamed
(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 operationsmenu_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() methodlimit
(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 callslimit
(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 collectionslimit
(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 fieldslimit
(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 indexindex_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 itemhash_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 valueunique_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 valueslimit
(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 unlockedsleeptime
(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