Skip to main content

An easy way to fetch and store data from and store to key-value databases like Redis.

Project description

DB Transfer

PyPI version

An easy way to manipulate data using key-value databases like Redis.
It is designed to support a number of databases, but currently only Redis is supported.

INSTALL (Python 3.x)

pip install DB-Transfer

Design

There are an adapter class for every database.
After instantiating Python Transfer using certain adapter_name, we can manipulate the
data from key-value database just like dictionaries: transfer[key] = value

Keys

Keys are created using prefix, namespace and item.
Example: data:USERS:arrrlo:full_name
(data is prefix, USERS is namespace and arrrlo:full_name is item)

Redis Adapter:

Connect to Redis using environment variables

from db_transfer import Transfer, sent_env

os.environ['REDIS_HOST'] = 'localhost'
os.environ['REDIS_PORT'] = '6379'
os.environ['REDIS_DB'] = '0'

@sent_env('redis', 'HOST', 'REDIS_HOST')
@sent_env('redis', 'PORT', 'REDIS_PORT')
@sent_env('redis', 'DB', 'REDIS_DB')
class RedisTransfer(Transfer):

    def __init__(self, prefix=None, namespace=None):
        super().__init__(prefix=str(prefix), namespace=namespace, adapter_name='redis')

Store data

rt = RedisTransfer()
rt['my_key'] = 'some_string' # redis: "SET" "data:my_key" "some_string"

rt = RedisTransfer(namespace='my_namespace')
rt['my_key'] = 'some_string' # redis: "SET" "data:my_namespace:my_key" "some_string"

rt = RedisTransfer(prefix='my_prefix', namespace='my_namespace')
rt['my_key'] = 'some_string' # redis: "SET" "my_prefix:my_namespace:my_key" "some_string"

Connect to Redis using class parameters

class RedisTransfer(Transfer):

    def __init__(self, prefix, namespace, host, port, db):
        super().__init__(prefix=str(prefix), namespace=namespace, adapter_name='redis')

        self.set_env('HOST', host)
        self.set_env('PORT', port)
        self.set_env('DB', db)

Store data

rt = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)

rt['my_key'] = 'some_string' # redis: "SET" "my_prefix:my_name_space:my_key" "some_string"

Fetch data

rt = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)

my_var = rt['my_key'] # redis: "GET" "my_prefix:my_namespace:my_key"

Delete data

rt = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)

del rt['my_key'] # redis: "DEL" "my_prefix:my_namespace:my_key"

Other data types

rt = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)

rt['my_key_1'] = [1,2,3,4] # redis: "RPUSH" "my_prefix:my_namespace:my_key_1" "1" "2" "3" "4"
rt['my_key_2'] = {'foo', 'bar'} # redis: "SADD" "my_prefix:my_namespace:my_key_2" "foo" "bar"
rt['my_key_3'] = {'foo': 'bar'} # redis: "HMSET" "my_prefix:my_namespace:my_key_3" "foo" "bar"

my_var_1 = list(rt['my_key_1']) # redis: "LRANGE" "my_prefix:my_namespace:my_key_1" "0" "-1"
my_var_2 = set(rt['my_key_2']) # redis: "SMEMBERS" "my_prefix:my_namespace:my_key_2"
my_var_3 = dict(rt['my_key_2']) # redis: "HGETALL" "my_prefix:my_namespace:my_key_3"

Redis hash data type

rt = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)

rt['my_key'] = {'foo': 'bar'} # redis: "HMSET" "my_prefix:my_namespace:my_key" "foo" "bar"

my_var = dict(rt['my_key']) # redis: "HGETALL" "my_prefix:my_namespace:my_key"
my_var = rt['my_key']['foo'] # redis: "HGET" "my_prefix:my_namespace:my_key" "foo"

rt['my_key']['boo'] = 'doo' # redis: "HSET" "my_prefix:my_namespace:my_key" "boo" "bar"

Multiple commands execution with context manager (only for set and delete)

with RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0) as rt:
    rt['my_key_1'] = 'some_string'
    rt['my_key_2'] = [1,2,3,4]
    rt['my_key_3'] = {'foo': 'bar'}

# redis:
#
# "MULTI"
# "SET" "my_prefix:my_namespace:my_key_1" "some_string"
# "RPUSH" "my_prefix:my_namespace:my_key_2" "1" "2" "3" "4"
# "HMSET" "my_prefix:my_namespace:my_key_3" "foo" "bar"
# "EXEC"

Using iterators

rt = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)

for key, value in iter(rt):
    # yields key and value of every key starting with my_prefix:my_namespace:


rt['my_key'] = {...} # saving a hash data (dict)

for key, value in iter(rt['my_key']):
    # yields key and value for every HGET in my_prefix:my_namespace:my_key

Keys

Every key in Redis is stored in set in same Redis.
Example:

rt = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)

rt['key_1'] = 'value'
rt['key_2:key3'] = 'value'
rt['key_2:key4'] = 'value'
rt['key_2:key_5:key_6'] = 'value'
rt['key_2:key_5:key_7'] = 'value'
rt['key_2:key_5:key_8'] = 'value'

So, the keys are "key_1", "key_2:key3", "key_2:key4", "key_2:key5:key_6", "key_2:key5:key_7", "key_2:key5:key_8".
They are not stored in one set, but different keys are stored i different sets:
'my_prefix:my_namespace': set({'key_1', 'key_2:keys'})
'my_prefix:my_namespace:key_2': set({'key_3', 'key_4', 'key_5:keys'})
'my_prefix:my_namespace:key_2:key_5': set({'key_6', 'key_7', 'key_8'})

This is done this way so you can easily access data by keys fom any level recursively:

rt.keys()
# > ['key_1', 'key_2:key3', 'key_2:key4', 'key_2:key_5:key_6', 'key_2:key_5:key_7', 'key_2:key_5:key_8']

rt['key_2'].keys()
# > ['key_3', 'key_4', 'key_5:key_6', 'key_5:key_7', 'key_5:key_8']

rt['key_2:key_5'].keys()
# > ['key_6', 'key_7', 'key_8']

Real life examples

Transfer all data from one Redis database to another:

rt_1 = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)
rt_2 = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='some_host', port=6379, db=0)

for key in rt_1.keys():
    rt_2[key] = rt_1[key]

or if you want to insert data in one batch (read goes one by one):

with rt_2:
    for key in rt_1.keys():
        rt_2[key] = rt_1[key]

Transfer data from one user to another:

rt_1 = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)

for key in rt_1['arrrlo'].keys():
    rt_1['edi:' + key] = rt_1['arrrlo:' + key]

Delete user from database:

rt_1 = RedisTransfer(prefix='my_prefix', namespace='my_namespace', host='localhost', port=6379, db=0)

with rt_1:
    for key in rt_1['arrrlo'].keys():
        del rt_1['arrrlo:' + key]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

DB Transfer-0.3.3.tar.gz (8.0 kB view details)

Uploaded Source

Built Distribution

DB_Transfer-0.3.3-py3-none-any.whl (9.0 kB view details)

Uploaded Python 3

File details

Details for the file DB Transfer-0.3.3.tar.gz.

File metadata

  • Download URL: DB Transfer-0.3.3.tar.gz
  • Upload date:
  • Size: 8.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for DB Transfer-0.3.3.tar.gz
Algorithm Hash digest
SHA256 98c103bb9e63434da5837afbc8b20b87706134c996a69527a80824126f24bfe2
MD5 c51b456d95247950d1b4fb171547b5e9
BLAKE2b-256 4f1cafc3d8b7567575742b67a4c1709612cba00d4fef947e4847229a17a8f3c1

See more details on using hashes here.

File details

Details for the file DB_Transfer-0.3.3-py3-none-any.whl.

File metadata

File hashes

Hashes for DB_Transfer-0.3.3-py3-none-any.whl
Algorithm Hash digest
SHA256 8b019870cbedff293d33f106259552ee3df99a9a55235b9f4068d48e730d2f23
MD5 1f36df8a9ae46869ef3ec00a54935dc7
BLAKE2b-256 04ebac711ad0ad2dc35ed0275ecb3098ced22ccf2193713e8300962cb5ca63b2

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page