# persidict
Simple persistent dictionaries for Python.
## What Is It?
`persidict` offers a simple persistent key-value store for Python.
It saves the content of the dictionary in a folder on a disk
or in an S3 bucket on AWS. Each value is stored as a separate file / S3 object.
Only text strings, or sequences of strings, are allowed as keys.
Unlike other persistent dictionaries (e.g. Python's native `shelve`),
`persidict` is suitable for work in highly **distributed environments**,
where multiple instances of a program run in parallel on
a large number of different machines.
## Usage
Class 'FileDirDict' is a persistent dictionary that stores its content
in a folder on a disk.
from persidict import FileDirDict
my_dictionary = FileDirDict(dir_name="my_folder")
Once created, it can be used as a regular Python dictionary:
my_dictionary["Eliza"] = "MIT Eliza was a mock psychotherapist."
my_dictionary["Eliza","year"] = 1965
my_dictionary["Eliza","authors"] = ["Joseph Weizenbaum"]
my_dictionary["Shoebox"] = "IBM Shoebox performed arithmetic operations"
my_dictionary["Shoebox"] += " on voice commands."
my_dictionary["Shoebox", "year"] = 1961
my_dictionary["Shoebox", "authors"] = ["W.C. Dersch", "E.A. Quade"]
for k in my_dictionary:
print(list(k), "==>", my_dictionary[k])
if not "Eliza" in my_dictionary:
print("Something is wrong")
If you run the code above, it will produce the following output:
>>> ['Eliza'] ==> MIT Eliza was a mock psychotherapist.
>>> ['Shoebox'] ==> IBM Shoebox performed arithmetic operations on voice commands.
>>> ['Shoebox', 'authors'] ==> ['W.C. Dersch', 'E.A. Quade']
>>> ['Shoebox', 'year'] ==> 1961
>>> ['Eliza', 'authors'] ==> ['Joseph Weizenbaum']
>>> ['Eliza', 'year'] ==> 1965
Behind the scenes, the dictionary will create a folder named "my_folder"
on a local disk. Each key-value pair will be stored as a separate file
in this folder.
If the key is a string, the string will be used to create
a filename for the object. If the key is a sequence of strings,
all but the last strings in the sequence will be used to create a name
for a sub-folder in the main folder;
the last string will be used to create a filename for the object
which will be placed in the sub-folder.
Persistent dictionaries only accept sequences
of strings as keys. Any pickleable Python object can be used as a value.
Unlike regular Python dictionaries, insertion order is not preserved.
del my_dictionary
new_dict = FileDirDict(dir_name="my_folder")
print("len(new_dict) == ",len(new_dict))
The code above will create a new object named new_dict and then will
print its length:
>>> len(new_dict) == 6
The length is 6, because the dictionary was already stored on a disk
in the "my_folder" directory, which contained 6 pickle files.
Technically, `FileDirDict` saves its content in a folder on a local disk.
But you can share this folder with other machines
(for example, using Dropbox or NFS), and work with the same dictionary
simultaneously from multiple computers (from multiple instances of your program).
This approach would allow you to use a persistent dictionary in
a system that is distributed over dozens or hundreds of computers.
If you need to run your program on thousands (or more) computers,
class `S3Dict` is a better choice: it's a persistent dictionary that
stores its content in an AWS S3 bucket.
from persidict import S3Dict
my_cloud_dictionary = S3Dict(bucket_name="my_bucket")
Once created, it can be used as a regular Python dictionary.
## Key Classes
* `SafeStrTuple` - an immutable sequence of URL/filename-safe non-empty strings.
* `PersiDict` - an abstract base class for persistent dictionaries.
* `FileDirDict` - a persistent dictionary that stores its content
in a folder on a disk.
* `S3Dict` - a persistent dictionary that stores its content
in an AWS S3 bucket.
## Key Similarities With Python Built-in Dictionaries
`PersiDict` and its subclasses can be used as regular Python dictionaries.
* You can use square brackets to get, set, or delete values.
* You can iterate over keys, values, or items.
* You can check if a key is in the dictionary.
* You can check whether two dicts are equal
(meaning they contain the same key-value pairs).
* You can get the length of the dictionary.
* Methods `keys()`, `values()`, `items()`, `get()`, `clear()`
, `setdefault()`, `update()` etc. work as expected.
## Key Differences From Python Built-in Dictionaries
`PersiDict` and its subclasses persist values between program executions,
as well as make it possible to concurrently run programs
that simultaneously work with the same instance of a dictionary.
* Keys must be sequences of URL/filename-safe non-empty strings.
* Values must be pickleable Python objects.
* You can constrain values to be an instance of a specific class.
* Insertion order is not preserved.
* You can not assign initial key-value pairs to a dictionary in its constructor.
* `PersiDict` API has additional methods `delete_if_exists()`, `mtimestamp()`,
`get_subdict()`, random_keys(), and `subdicts()` , which are
not available in Python dicts.
## Fine Tuning
`PersiDict` subclasses have a number of parameters that can be used
to impact behaviour of a dictionary.
* `base_class_for_values` - A base class for values stored in a dictionary.
If specified, it will be used to check types of values in the dictionary.
If not specified (if set to `None`), no type checking will be performed
and all types will be allowed.
* `file_type` - a string that specifies the type of files used to store objects.
If `file_type` has one of two values: "pkl" or "json", it defines
which file format will be used by the dictionary to store values.
For all other values of `file_type`, the file format will always be plain
text. "pkl" or "json" allow to store arbitrary Python objects,
while all other file_type-s only work with str objects;
it means `base_class_for_values` must be explicitly set to `str`
if `file_type` is not set to "pkl" or "json".
* `immutable_items` - a boolean that specifies whether items in a dictionary
can be modified/deleted. It enables various distributed cache optimizations
for remote storage. True means an append-only dictionary.
False means normal dict-like behaviour. The default value is False.
* `digest_len` - a length of a hash signature suffix which `PersiDict`
automatically adds to each string in a key while mapping the key to
the address of a value in a persistent storage backend
(e.g. a filename or an S3 objectname). It is needed to ensure correct work
of persistent dictionaries with case-insensitive (even if case-preserving)
filesystems, such as MacOS HFS. The default value is 8.
## How To Get It?
The source code is hosted on GitHub at:
[https://github.com/vladlpavlov/persidict](https://github.com/vladlpavlov/persidict)
Binary installers for the latest released version are available at the Python package index at:
[https://pypi.org/project/persidict](https://pypi.org/project/persidict)
pip install persidict
## Dependencies
* [jsonpickle](https://jsonpickle.github.io)
* [joblib](https://joblib.readthedocs.io)
* [lz4](https://python-lz4.readthedocs.io)
* [pandas](https://pandas.pydata.org)
* [numpy](https://numpy.org)
* [boto3](https://boto3.readthedocs.io)
* [pytest](https://pytest.org)
* [moto](http://getmoto.org)
## Key Contacts
* [Vlad (Volodymyr) Pavlov](https://www.linkedin.com/in/vlpavlov/)
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"description": "# persidict\n\nSimple persistent dictionaries for Python.\n\n## What Is It?\n\n`persidict` offers a simple persistent key-value store for Python. \nIt saves the content of the dictionary in a folder on a disk \nor in an S3 bucket on AWS. Each value is stored as a separate file / S3 object.\nOnly text strings, or sequences of strings, are allowed as keys.\n\nUnlike other persistent dictionaries (e.g. Python's native `shelve`), \n`persidict` is suitable for work in highly **distributed environments**, \nwhere multiple instances of a program run in parallel on \na large number of different machines.\n\n## Usage\nClass 'FileDirDict' is a persistent dictionary that stores its content \nin a folder on a disk.\n\n from persidict import FileDirDict \n my_dictionary = FileDirDict(dir_name=\"my_folder\")\n\nOnce created, it can be used as a regular Python dictionary:\n\n my_dictionary[\"Eliza\"] = \"MIT Eliza was a mock psychotherapist.\"\n my_dictionary[\"Eliza\",\"year\"] = 1965\n my_dictionary[\"Eliza\",\"authors\"] = [\"Joseph Weizenbaum\"]\n \n my_dictionary[\"Shoebox\"] = \"IBM Shoebox performed arithmetic operations\"\n my_dictionary[\"Shoebox\"] += \" on voice commands.\"\n my_dictionary[\"Shoebox\", \"year\"] = 1961\n my_dictionary[\"Shoebox\", \"authors\"] = [\"W.C. Dersch\", \"E.A. Quade\"]\n\n for k in my_dictionary:\n print(list(k), \"==>\", my_dictionary[k])\n\n if not \"Eliza\" in my_dictionary:\n print(\"Something is wrong\")\n\nIf you run the code above, it will produce the following output:\n\n >>> ['Eliza'] ==> MIT Eliza was a mock psychotherapist.\n >>> ['Shoebox'] ==> IBM Shoebox performed arithmetic operations on voice commands.\n >>> ['Shoebox', 'authors'] ==> ['W.C. Dersch', 'E.A. Quade']\n >>> ['Shoebox', 'year'] ==> 1961\n >>> ['Eliza', 'authors'] ==> ['Joseph Weizenbaum']\n >>> ['Eliza', 'year'] ==> 1965\n\nBehind the scenes, the dictionary will create a folder named \"my_folder\" \non a local disk. Each key-value pair will be stored as a separate file \nin this folder. \n\nIf the key is a string, the string will be used to create \na filename for the object. If the key is a sequence of strings, \nall but the last strings in the sequence will be used to create a name \nfor a sub-folder in the main folder; \nthe last string will be used to create a filename for the object \nwhich will be placed in the sub-folder.\n\nPersistent dictionaries only accept sequences \nof strings as keys. Any pickleable Python object can be used as a value. \nUnlike regular Python dictionaries, insertion order is not preserved.\n\n del my_dictionary\n new_dict = FileDirDict(dir_name=\"my_folder\")\n print(\"len(new_dict) == \",len(new_dict))\n\nThe code above will create a new object named new_dict and then will\nprint its length: \n\n >>> len(new_dict) == 6\n\nThe length is 6, because the dictionary was already stored on a disk \nin the \"my_folder\" directory, which contained 6 pickle files.\n\nTechnically, `FileDirDict` saves its content in a folder on a local disk. \nBut you can share this folder with other machines \n(for example, using Dropbox or NFS), and work with the same dictionary \nsimultaneously from multiple computers (from multiple instances of your program). \nThis approach would allow you to use a persistent dictionary in \na system that is distributed over dozens or hundreds of computers.\n\nIf you need to run your program on thousands (or more) computers, \nclass `S3Dict` is a better choice: it's a persistent dictionary that \nstores its content in an AWS S3 bucket.\n\n from persidict import S3Dict\n my_cloud_dictionary = S3Dict(bucket_name=\"my_bucket\")\n\nOnce created, it can be used as a regular Python dictionary.\n\n## Key Classes\n\n* `SafeStrTuple` - an immutable sequence of URL/filename-safe non-empty strings.\n* `PersiDict` - an abstract base class for persistent dictionaries. \n* `FileDirDict` - a persistent dictionary that stores its content \nin a folder on a disk.\n* `S3Dict` - a persistent dictionary that stores its content \nin an AWS S3 bucket.\n\n## Key Similarities With Python Built-in Dictionaries\n\n`PersiDict` and its subclasses can be used as regular Python dictionaries. \n\n* You can use square brackets to get, set, or delete values. \n* You can iterate over keys, values, or items. \n* You can check if a key is in the dictionary. \n* You can check whether two dicts are equal\n(meaning they contain the same key-value pairs).\n* You can get the length of the dictionary.\n* Methods `keys()`, `values()`, `items()`, `get()`, `clear()`\n, `setdefault()`, `update()` etc. work as expected.\n\n## Key Differences From Python Built-in Dictionaries\n\n`PersiDict` and its subclasses persist values between program executions, \nas well as make it possible to concurrently run programs \nthat simultaneously work with the same instance of a dictionary.\n\n* Keys must be sequences of URL/filename-safe non-empty strings.\n* Values must be pickleable Python objects.\n* You can constrain values to be an instance of a specific class.\n* Insertion order is not preserved.\n* You can not assign initial key-value pairs to a dictionary in its constructor.\n* `PersiDict` API has additional methods `delete_if_exists()`, `mtimestamp()`,\n`get_subdict()`, random_keys(), and `subdicts()` , which are \nnot available in Python dicts.\n\n## Fine Tuning\n\n`PersiDict` subclasses have a number of parameters that can be used \nto impact behaviour of a dictionary. \n\n* `base_class_for_values` - A base class for values stored in a dictionary. \nIf specified, it will be used to check types of values in the dictionary. \nIf not specified (if set to `None`), no type checking will be performed \nand all types will be allowed.\n* `file_type` - a string that specifies the type of files used to store objects.\nIf `file_type` has one of two values: \"pkl\" or \"json\", it defines \nwhich file format will be used by the dictionary to store values. \nFor all other values of `file_type`, the file format will always be plain\ntext. \"pkl\" or \"json\" allow to store arbitrary Python objects,\nwhile all other file_type-s only work with str objects; \nit means `base_class_for_values` must be explicitly set to `str` \nif `file_type` is not set to \"pkl\" or \"json\".\n* `immutable_items` - a boolean that specifies whether items in a dictionary \ncan be modified/deleted. It enables various distributed cache optimizations \nfor remote storage. True means an append-only dictionary. \nFalse means normal dict-like behaviour. The default value is False. \n* `digest_len` - a length of a hash signature suffix which `PersiDict` \nautomatically adds to each string in a key while mapping the key to \nthe address of a value in a persistent storage backend \n(e.g. a filename or an S3 objectname). It is needed to ensure correct work\nof persistent dictionaries with case-insensitive (even if case-preserving) \nfilesystems, such as MacOS HFS. The default value is 8. \n\n\n## How To Get It?\n\nThe source code is hosted on GitHub at:\n[https://github.com/vladlpavlov/persidict](https://github.com/vladlpavlov/persidict) \n\nBinary installers for the latest released version are available at the Python package index at:\n[https://pypi.org/project/persidict](https://pypi.org/project/persidict)\n\n pip install persidict\n\n## Dependencies\n\n* [jsonpickle](https://jsonpickle.github.io)\n* [joblib](https://joblib.readthedocs.io)\n* [lz4](https://python-lz4.readthedocs.io)\n* [pandas](https://pandas.pydata.org)\n* [numpy](https://numpy.org)\n* [boto3](https://boto3.readthedocs.io)\n* [pytest](https://pytest.org)\n* [moto](http://getmoto.org)\n\n## Key Contacts\n\n* [Vlad (Volodymyr) Pavlov](https://www.linkedin.com/in/vlpavlov/)\n",
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