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Triptych for data exchange and persistence

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Pyrustic Shared

Data exchange and persistence

This project is part of the Pyrustic Open Ecosystem.

Installation . Latest . Modules

Table of contents

Overview

Shared is a Python package created to be the programmer's companion when it comes to storing application data, managing configuration files, caching data, and exchanging data with other programs.

Although a lightweight package, Shared smoothly handles collections (dict, list, set), binary data, and SQL queries.

Designed as a triptych

Shared's intuitive application programming interface is designed as a triptych. Thus, three classes with similar interfaces are created to cover the needs of data exchange and persistence: Document, Dossier, and Database.

Class Relevance
Document For individual access to Jesth and JSON files that are likely to be manually edited by a human.
Dossier To store collections and binary data in a dossier without worrying about how they are actually saved.
Database For an intuitive interaction with SQLite databases.

Note: The Document class is not intended to be used directly. Instead, depending on the requirement, one will use the JsonDoc or JesthDoc class which subclasses the Document class.

Some characteristics

Since all three classes share similar interfaces, some handy functionality has been replicated in all of them with a few exceptions.

Initialization

All three classes emphasize initialization:

  • Document and Dossier give the possibility to define default data.
  • Database allows the definition of an initialization SQL script which is only executed to create a new database.

Data access

All three classes provide an optional read-only access to data and also allow the creation of temporary data which is automatically deleted when the user closes the application.

Document and Dossier provide Autosave functionality, while Database automatically closes the underlying database connection when the user closes the application.

Command-line interface

Among the three classes, Dossier is the class of which a single instance can handle multiple underlying files. The Dossier class has its own protocol for organizing data. For this reason, Dossier offers a simple yet powerful command-line interface that allows other programs or a human to read and write the contents of a dossier.


Let's explore the Document, Dossier, and Database classes in the next sections !

Document

The Document class represents an interface for reading and writing an underlying file whose format is either Jesth or JSON.

As stated previously in the Overview section, the Document class is not intended to be used directly. Instead, depending on the requirement, one will use the JsonDoc or JesthDoc class which subclasses the Document class.

Since JSON is very popular, we will focus on the JsonDoc class in the following examples.

Accessing a document or creating a new one is as simple as this:

from shared import JsonDoc

# Create a new document instance which will be linked to the 'my-data.json' file.
# If this file doesn't exist yet, it will be automatically created
document = JsonDoc("my-data.json")

# From now, we can use 'document' to read and write the contents of 'my-data.json' !
# ...

The string my-data.json is the base name of a file that will be created if it does not yet exist. This string is called Target and can be an absolute path or an instance of pathlib.Path. The Document class exposes the read and write methods, respectively, to read and write the underlying document.

Initialization

A document can be initialized with a conditional statement or by defining default data. By default, the Document class will assign a dict to the null parameter default_data.

Use a conditional statement

It's as simple as testing a boolean to check if the underlying document file is newly created or not:

from shared import JsonDoc

# access 'my-data.json'
document = JsonDoc("my-data.json")

# let's initialize the content of 'my-data.json'
if document.new:
    data = {"name": "alex", "job": "evangelist"}
    document.write(data)  # persisted !

Set default data

The most elegant, less verbose and recommended way to initialize a document is to set some default data to the default parameter:

from shared import JsonDoc

# default data to init the file 'my-data.json'
DEFAULT_DATA = {"name": "alex", "job": "evangelist"}

# access 'my-data.json'
document = JsonDoc("my-data.json", default=DEFAULT_DATA)

# From now, thanks to the initialization functionality, the underlying
# document contains the default data, assuming that 'my-data.json'
# did not exist before the `Document` class was instantiated

Data location

The only mandatory argument to be supplied to the Document class constructor is the target. For convenience, the target is either the absolute path or the base name of a file. Its data type is either a string or an instance of pathlib.Path.

The optional directory parameter exists to supplement the target value when that value is not an absolute path.

Default directory

By default, document files are saved in $HOME/PyrusticHome/shared. You can change the location according to your needs:

from shared import JsonDoc

DIRECTORY = "/home/alex/private"

# access 'my-data.json'
document = JsonDoc("my-data.json", directory=DIRECTORY)

# From now, you can access these properties:
#   document.name == "my-data.json"
#   document.directory == "/home/alex/private"
#   document.target == "my-data.json"

Absolute pathname

You can set an absolute path as the target. In this case, the Document class ignores the directory parameter.

from shared import JsonDoc

pathname = "/home/alex/private/my-data.json"

# access 'my-data.json'
document = JsonDoc(pathname)

# From now, you can access these properties:
#   document.name == "my-data.json"
#   document.directory == "/home/alex/private"
#   document.target == "/home/alex/private/my-data.json"

Temporary data

Setting the temporary boolean can enable temporary mode, so a document can only be created and used while the application is running, and then safely deleted when the application closes:

from shared import JsonDoc

# access 'my-data.json'
document = JsonDoc("my-data.json", temporary=True)

# This document will be created in a temporary directory
# then it will be safely deleted when the application closes
# or when the developer explicitly calls the 'close' or 'delete' method

The Document class uses tempfile.TemporaryDirectory to implement this functionality.

Autosave

Thanks to atexit module, Document can autosave content when the application is closed:

import sys
from shared import JsonDoc

# access 'my-config.json' with `autosave` mode enabled
document = JsonDoc("my-config.json", autosave=True, default=[])
# load the data
data = document.read()

# few lines of code later...

data.append("batman")  # data modified

sys.exit()  # data automatically saved !

Along with atexit module, the Document class also uses a caching mechanism to implement the autosave functionality.

Caching

By default, caching mode is enabled, so the user can access cached data through the cache property of an instance of the Document class:

from shared import JsonDoc

DEFAULT_DATA = {"name": "alex", "job": "evangelist"}

# access 'my-config.json'
document = JsonDoc("my-config.json", caching=True, default=DEFAULT_DATA)

data = document.read()

if data is document.cache:
    print("Same same !")

Readonly

Setting the readonly parameter to True prevents the running application from accidentally modifying the content of a document:

from shared import JsonDoc

# access 'my-data.json'
document = JsonDoc("my-data.json", readonly=True)

# when you set readonly to True, you can no longer edit the content !
# shared.ReadonlyError will be raised if you try to mess with a readonly document

Clear data

You can delete the underlying file of a document (assuming the file isn't in readonly mode):

from shared import JsonDoc

# access 'my-data.json'
document = JsonDoc("my-data.json")

# delete 'my-data.json'
document.delete()

if document.deleted:
    print("Successfully deleted !")

Convenience functions

Four convenience functions are available for the JsonDoc class (also for the JesthDoc class):

from shared import json_create, json_readonly, json_write, json_autosave

# quickly create a document
DEFAULT = ["red", "violet"]
json_create("my-data.json", default=DEFAULT)

# quickly open a document in readonly mode
data = json_readonly("my-data.json")

# quickly change the content of a document
data = ["red", "green"]
json_write("my-data.json", data)

# quickly read the content of a document in autosave mode
data = json_autosave("my-data.json")
data.append("blue")  # data will be automatically saved on exit

Recapitulation

For individual access to Jesth and JSON files that are likely to be manually edited by a human, the Document class is the recommended interface.

For more technical details about this class and the subclasses JesthDoc and JsonDoc, read the reference documentation.

Dossier

The Dossier class stores collections (list, dict, set) and binary data with a unified interface inside a dossier. Shared allows to read and write a dossier not only programmatically but also from the command line.

This class shares a similar interface with the Document class. Thus, the Dossier class constructor has target, directory, autosave, readonly and temporary as parameters. These parameters are already covered in the Document class section.

Under the hood, Dossier uses files and JSON to store data.

Example

Let's create a dossier with script_1.py:

# script_1.py
from shared import Dossier

# data
people = {"Jack": "male", "Jane": "female"}  # dict
planets = ["Mars", "Venus", "Jupiter"]  # list
colors = {"red", "green", "blue"}  # set

# let's persist the data in 'my-dossier'
dossier = Dossier("my-dossier")
dossier.set("people", people)  # set the 'people' entry
dossier.set("planets", planets)  # set the 'planets' entry
dossier.set("colors", colors)  # set the 'colors' entry

# Done ! The data is persisted !

From script_2.py, let's access the dossier created with script_1.py:

# script_2.py
from shared import Dossier

# let's access the shared dossier
dossier = Dossier("my-dossier")

# get data from the shared dossier
people = dossier.get("people") # get the 'people' entry
planets = dossier.get("planets") # get the 'planets' entry'
colors = dossier.get("colors") # get the 'colors' entry

print(people)
# output: {'Jack': 'male', 'Jane': 'female'}

print(planets)
# output: ['Mars', 'Venus', 'Jupiter']

print(set(colors)) # there is nothing called 'set' in JSON [1]
# output: {'red', 'green', 'blue'}


# [1] the value of 'colors' is this dictionary:
# {'red': None, 'green': None, 'blue': None}

Binary data

You can store binary data with the same unified interface:

# script_1.py
from shared import Dossier

dossier = Dossier("my-dossier")

with open("/home/alex/selfie.png", "rb") as file:
    data = file.read()
    dossier.set("selfie", data)  # set the 'selfie' entry

# the 'set' method returns the path to the binary file that stores the binary entry

The above code can also be expressed like this:

# script_1.py
import pathlib
from shared import Dossier

dossier = Dossier("my-dossier")

path = pathlib.Path("/home/alex/selfie.png")
dossier.set("selfie", path)  # set the 'selfie' entry

# the 'set' method returns the path to the binary file that stores the binary entry

You can retrieve your binary data from another script:

# script_2.py
from shared import Dossier
from shutil import copyfile

dossier = Dossier("my-dossier")
source_path = dossier.get("selfie")  # get the filename of the 'selfie' bin entry
destination_path = "/home/alex/new.png"

# copy the content from source to destination
copyfile(source_path, destination_path)

Check

Use the check method to check the contents of a dossier or a specific entry:

from shared import Dossier

dossier = Dossier("my-dossier")

# check a specific entry
info = dossier.check("entry")
if info:
    # info is a 3-tuple (name, container, filename).
    # The name is simply the entry name.
    # The container is a string that represents the type of the entry.
    # containers: "dict", "list", "set", and "bin"
    # The filename is either the path to a JSON file or a binary file
    name, container, filename = info

# check the contents of the dossier
dossier_info = dossier.check()  # returns a dict, keys are entries and values are 3-tuples

for entry, info in dossier_info.items():
    print("Entry:", info.name) # the entry name
    print("Container:", info.container)  # 'dict', 'set', 'list', or 'bin'
    print("Filename:", info.filename) # the underlying file in which the data is stored
    print()

Clear data

You can decide to delete a specific entry, a group of entries, or the dossier:

from shared import Dossier

dossier = Dossier("my-dossier")

# delete a specific entry
dossier.delete("entry_1")

# delete a group of entries
dossier.delete("entry_2", "entry_3")

# delete the dossier
dossier.delete()  # collections, binary data, and meta data are gone

Recapitulation

To store collections and binary data in a dossier without worrying about how they are actually saved, the Dossier class is the interface to use.

For more technical details about this class, read its documentation.

Database

Intuitive interaction with SQLite databases.

Example

The following example shows how nice it is to work with the Database class:

from shared import Database

# Initialization script
# This SQL script will create two tables: friends and projects
INIT_SCRIPT = """\
CREATE TABLE friends (name TEXT PRIMARY KEY,
                      age INTEGER NOT NULL);

CREATE TABLE projects (name TEXT PRIMARY KEY,
                       language TEXT NOT NULL);
"""

# If this database doesn't exist yet,
# it will be created with the initialization script
database = Database("my-database", init_script=INIT_SCRIPT)

# This will only be executed once !
# So you can safely restart this script again and again...
if database.new:
    # Populate this database
    sql = """INSERT INTO friends VALUES ("Jack", 20)"""
    database.edit(sql)

    # few lines of code later...

    # Populate this database
    sql = """INSERT INTO friends VALUES (?, ?)"""
    parameters = ("Jane", 21)
    database.edit(sql, param=parameters)

# Read data
sql = "SELECT * FROM friends"
columns, data = database.query(sql)  # returns a shared.dto.QueryResult namedtuple

print(columns)
# output: ['name', 'age']

print(data)
# output: [('Jack', 20), ('Jane', 21)]

For more technical details about this class, read its documentation.

Command line interface

Shared comes with an intuitive command line interface for the Dossier class. Type help in the command line interface to display a short manual.

For the following subsections, assume we have a pre-populated dossier named my-dossier and located in /home/alex/dossiers.

Check the content

Check the contents of my-dossier or a specific entry:

$ cd /home/alex/dossiers/my-dossier

$ shared check
- 'colors' set 56B
- 'people' dict 44B
- 'planets' list 42B

$ shared check people
'people' dict 44B

$ shared check colors
'colors' set 56B

Read the content of a specific entry

$ cd /home/alex/dossiers/my-dossier

$ shared get people
{
    "Jack": "male",
    "Jane": "female"
}

$ shared get planets
[
    "Mars",
    "Venus",
    "Jupiter"
]

shared get colors
{
    "red": null,
    "blue": null,
    "green": null
}

The output text is the exact JSON representation as stored in a file. So the output can be consumed as is by another program and deserialized with a JSON library. Note that the colors entry is a set but represented as a dict in JSON.

Store binary data

$ shared set selfie bin: '/home/alex/selfie.png'
Entry successfully updated !

You can copy a binary entry into an arbitrary file from the command line:

$ shared get selfie > '/home/alex/selfie-copy.png'

Store a collection

$ shared set countries list: '/home/alex/countries.json'
Entry successfully updated !

$ shared set my_config dict: '/home/alex/app_config.json'
Entry successfully updated !

Delete an entry

$ shared del "selfie"
Entry successfully deleted !

$ shared check selfie
This entry doesn't exist.

Delete a dossier

Right-click on the folder with your mouse, then send it safely to the trash... ;)

Miscellaneous

In June 2022, Shared entered the top 5000 most downloaded Python packages on PyPI over 30 days for the first time.

Installation

Shared is cross platform and versions under 1.0.0 will be considered Beta at best. It should work on Python 3.5 or newer.

For the first time

$ pip install shared

Upgrade

$ pip install shared --upgrade --upgrade-strategy eager

Show information

$ pip show shared



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