Cacheable Implementation Neutral Data Intermediate

CINDI is a Meta Database Management System which provides a simple way for front-end applications to perform CRUD operations with various back-end stores. CINDI is written in Python 3, and is available in the PyPI Index as a PIP package.

CINDI is a service to translate INDI language statements to either SQL, MongoDB, or Redis. CINDI also caches read queries in memory, so that clients asking for the same thing repetitively do not actually get to hit the backing-stores.

CINDI is intended to be used during the early rapid-prototyping / idea phase, so that developers may focus on the layout, functionality, and usability of a front-end application. Think of CINDI as a temporary substitute, until a proper back-end infrastructure is built. This way, the initial pioneers of a project need only to focus their energy on the front-end(s).

The idea is to forgo the traditional map of API endpoints usually provided by a back-end. Instead, front-end code will submit INDI statements directly to a single endpoint, and receive JSON responses accordingly. The result is, most application logic is shifted into the front-end code, which simplifies the rapid prototyping of applications.

Later, when a minimal-viable-product had been demonstrated to stakeholders, and more developers can be assigned to the project, CINDI would then be replaced with a traditional API back-end.

Users may configure CINDI to use one, some, or all of the currently supported storage systems:

• PostgreSQL
• MySQL
• SQLite3
• MongoDB
• Redis

An easy Implementation Neutral Data Intermediate language is provided in order to abstract-away the underlying chosen store(s). The INDI language is similar to SQL, but re-worded to enforce the CRUD mentality.

Brief INDI Language Tutorial

The INDI language uses four major CRUD keywords: CREATE, READ, UPDATE, and DELETE.

CINDI will cache READ operations in-memory, until it detects those result-sets are stale (due to another CREATE, UPDATE, or DELETE affecting the data).

In order to demonstrate the INDI language, consider the following SQLite3 schema:

 CREATE TABLE nonsense (
 	id INTEGER NOT NULL PRIMARY KEY,
	nonsense_a TEXT,
	nonsense_b TEXT,
	nonsense_c TEXT
	);

The above SQL statement would be prepared (manually, by the user) for CINDI before starting. Then, after loading CINDI, the four CRUD operations may be performed by submitting INDI statements to the system.

For example, here is an INDI CREATE statement:

CREATE IN nonsense FIELDS (nonsense_a, nonsense_b, nonsense_c) VALUES ("hekkin big", "skare", "today and now")

There would be no 'result' to the above query, other than the underlying store(s) being modified to reflect the insertion of new data. Client-side, this is what would be received as a response:

[[]]

Next example, here is an INDI READ statement:

READ IN nonsense id 1 FIELDS nonsense_a

The READ has a result, it would be a JSON array looking like this:

[[['hekkin big']]]

Now for a more comprehensive READ:

READ IN nonsense ALL RECORDS FIELDS (id, nonsense_a, nonsense_b, nonsense_c)

This retrieves all records from the nonsense table, including all columns:

[[[1, 'hekkin big', 'skare', 'today and now']]]

It appears that 'skare' is spelled wrong, so to UPDATE that:

UPDATE IN nonsense nonsense_b skare FIELDS (nonsense_b) VALUES (scare)

The literal result is an empty set:

[[]]

Check to see just that column had been updated:

READ IN nonsense id 1 FIELDS nonsense_b

Result:

[[['scare']]]

Finally, to DELETE the record:

DELETE IN nonsense id 1

A subsequent READ would return an empty set. Note the DELETE may have queried by any field, not just the 'id'!

VALUES quotes are optional, unless the string to be stored contains spaces.

See the doc/demo.txt file for the verbose output from the above demo.

The doc folder also contains schema examples for the other supported systems.

Why ?

The above demonstration may seem trivial, however, consider that CINDI will support managing these INDI statements even if the backing-store is a NoSQL solution, such as MongoDB or Redis. The results are consistent, and if multiple stores are enabled, then any cache-missed READ will query all the stores, and compare the results to ensure consistency across the storage mechanisms.

If clients are submitting the same INDI queries repetitively, then the result from the first time is served from an in-memory Python dictionary. That cached query is discarded when an affecting CREATE, UPDATE, or DELETE occurs.

In the case of the NoSQL solutions, CINDI manages the concept of tables, columns, and primary keys. In particular, the MongoDB setup requires only creating a database, and the Redis setup requires nothing!

CINDI will not automatically initialize SQL / Mongo schemas, this must be done manually prior to runtime. That is why the author has provided a couple Docker demos, read on!

Check cindi_tests.py for more INDI language examples.

Installation, Easiest: cindi-lite Docker Compose Pack

Please go here and follow the instructions in order to have Docker Compose orchestrate the setup of ultasun/cindi-lite, which will consume the least resources. Along the way, you'll learn everything there is to know about configuring the CINDI runtime for a minimalist SQLite3-only backing-store.

Installation, Easier: cindi-plus Docker Compose Pack

Please go here and follow the instructions in order to have Docker Compose orchestrate the complete setup and demonstration of ultasun/cindi, which will, by default, consume significantly more resources than ultasun/cindi-lite. Along the way, you'll learn everything there is to know about configuring the CINDI runtime for a full installation with all five supported backing-stores running simultaneously

Installation, Easy: cindi-lite Docker image (no orchestration)

A Docker image ultasun/cindi-lite is available on Docker Hub, it will use a SQLite3 setup, and provide a similar experience to Installing & Basic Setup on SQLite3.

After start-up, development Flask server will not have SSL enabled.

0. Install the latest version of Docker on your system.
1. Open a terminal, and run the following command for a disposable demo:
   • $ docker run -dp 36963:36963 --rm ultasun/cindi-lite
   • Or, if you'd like to persist logs and data with named-mounts:
   • $ docker run -dp 36963:36963 -v cindi-lite-data:/app/data -v cindi-lite-logs:/app/logs ultasun/cindi-lite
   • Feel free to use bind-mounts for easier access to the produced data.
2. Use Docker Desktop to open a terminal into the running container, or otherwise docker exec -it into the container, and initialize the EXAMPLE data:
   • $ python
   • >>> import cindi
   • >>> cindi.quick_unit_tests()
   • Verify the return value is True, which means all 17 tests passed!
3. Use Postman (or something) to POST some INDI statements to http://localhost:36963/evaluate, such as:
   • READ IN nonsense ALL RECORDS FIELDS (id, nonsense_a, nonsense_b, nonsense_c)
   • Back in the python console, the full list of EXAMPLES may be viewed:
   • >>> cindi.print_2d_list(cindi.EXAMPLE_LIST)
     • These are the EXAMPLES which were ran during cindi.quick_unit_tests()
       • There is no harm in running the DDL or DML statements again!

Hard: Manual Installation & Basic Setup on SQLite3

Installing without Docker

Docker is not necessary to utilize CINDI. This installation demo will show manual installation from PyPI, and configuration using only SQLite3, to keep it brief. Please follow the detailed tutorial on cindi-plus to learn about configuring other backing-store systems.

1. pip install cindi
2. In your current working directory, create a folder called config:
   • $ mkdir config
3. In the config folder, create empty stores.txt and tables.txt files.
   • $ cd config && touch stores.txt && touch tables.txt && cd ..
4. Open stores.txt with a text editor -- the file must contain a python dictionary, here is the basic example using only SQLite3:
   • {'sqlite3': {'db': 'db0', 'sqlite3_file_prefix': ''}}
5. Open tables.txt with a text editor -- the file must contain a python list (or tuple), here is the basic example:
   • ['nonsense']
6. To open the SQLite3 database for intialization, in your terminal, run:
   • $ sqlite3 db0.db
   • You may need to install SQLite3 if the command is not found.
7. In the SQLite3 console, initialize the schema:
   • sqlite> CREATE TABLE nonsense (id INTEGER NOT NULL PRIMARY KEY, nonsense_a TEXT, nonsense_b TEXT, nonsense_c TEXT);
   • Save and quit: sqlite> .quit
8. In your terminal, run:
   • $ python3
9. Finally, try it out! Populate the store(s) with EXAMPLE data:
   • >>> import cindi
   • >>> cindi.quick_unit_tests()
     • The above function returns True if all tests succeed.
   • >>> cindi.quick_cindi(cindi.EXAMPLE5)
     • The above function returns a multi-dimensional list of values.

---

Logging

Since CINDI is in the alpha development stage, every DML statement is logged in the logs/ directory. Whatever data you're submitting, a copy will be saved in that directory.

• This will consume disk space.
• This will expose sensitive data.

There is one INDI DML statement per file. Each filename ends with a nano-seconds-since-epoch timestamp. A filename prefixed with indi is a DML expression. At the time of this writing, there are no other files written to the logs/ directory.

There is no simple way to disable this disk logging without modifying the source code. Just re-define def fprint(w, x='', y='', z=''): to do nothing if you must. CINDI is in the alpha development stage, and it is designed to assist in developing apps which are also in the alpha development stage. SSL on the Flask development server is not even enabled, and the development server is 'not for production use' anyway.

Troubleshooting

CINDI is in the alpha development stage. If you've encountered a problem, then you've probably found a bug in the translation routines, or your backing-stores are not configured correctly.

CINDI will generally exit the Python3 process on most errors ('fail fast'). The logs/ directory is ordred by nanoseconds-since-epoch timestamps, so it should be easy to work-backwards to locate the INDI DML statement which was translated inconsistently across multiple backing-stores. The author can't forsee any other reason for CINDI to crash, besides a backing-store connectivity issue.

When the Python3 process exits, various exit codes are used. This helps frequent users/developers of CINDI quickly identify from the Docker console (or elsewhere) why an exit had occurred.

Here are the exit numbers and error messages which might be produced by CINDI:

• 117: Corrupted store, please file a bug. Check the CINDI README.
  • The chain of INDI DML statements which were submitted to CINDI for execution over time, had managed to cause different inconsistent results to appear in the various backing stores.
  • This will crash the system because, every DQL statement executed verifies consistency across all conneected backing stores ('fail fast'). So CINDI had a translation error during an earlier DML statement.
  • Remedy Options:
    • First, please submit a bug with the full contents of logs/, and santize your data first if possible. This error is really not the fault of the user (you). The VALUES may not be so important, so a simple script to truncate after the VALUES in each file within the logs/ directory if you can't or won't share the VALUES.
      • However, the VALUES would be appreciated, because some parts of the translation code might do the wrong action if a value has too many single-or-double-quotes, it's a your-milage-may-vary scenario (at this time).
        • Regular expressions might be used in the future to mitigate some of the forseen issues regarding single-and-double quotes
      • Because a proper recursive solution might be needed.
    • Second, either:
      • Manually adjust the backing-stores, using their native tools/clients, until the data is consistent.
        • Success will be obvious when DQL statements regarding the 'offending table' no longer cause CINDI to exit.
      • Wipe all backing stores, and reload all the INDI statements from new.
• 5: fprint failed to print to file: ...
  • The log-to-disk mechanism fprint failed to write a file.
  • Remedy Options:
    • Disk space full?
    • Lost directory permissions during runtime?
• 52: !! ERROR: The quantity of fields detected is not euqal to the number of values detected...
  • The submitted INDI DML statement does not have the same quantity of FIELDS and VALUES, or,
  • The submitted INDI DML statement was unable to be parsed properly by the translation routine.
    • Please submit a bug containing the INDI DML statement which caused this.
      • Submitting the full logs/ should not be necessary, because this error would be isolated to parsing a specific INDI DML statement before any writing to a backing-store occured.
  • Remedy Options:
    • Check the INDI syntax
    • Manipulate the single-quotes or double-quotes in the VALUES of the offending statement
      • Many nested single-quotes or double-quotes might confuse the translation routine.
        • Remove the quotes, and please submit a bug.
    • Regular expressions will probably be used in the future to avoid problems like this.
• 29: Redis SET failed.
  • While performing a Redis SET, it failed.
  • Remedy Options:
    • Was CINDI disconnected from Redis in the middle of the transaction?
    • Did CINDI lose write access to the Redis database for some reason?
  • Please submit a bug in any event! Thank you.
• 2: Relating to a configuration 'File Not Found':
  • config/stores.txt not found, please check the CINDI README.
  • config/tables.txt not found, please check the CINDI README.
  • Remedy Options:
    • The config/ directory must be in the same directory . as where the Python3 process was launched. This is an elementary user mistake. Please review this README file carefully, or check one of the published Docker images for a proper example of how the Python3 process needs to be launched.
    • The config/stores.txt or config/tables.txt files are missing or not named properly.
• 61: Relating to a configuration file 'Invalid Syntax':
  • config/stores.txt not a dictionary, check the CINDI README.
    • Remedy Option
      • config/stores.txt must be a Python3 dictionary. Check the syntax of what is in the file, and try again.
  • config/tables.txt must be a list or tuple, check CINDI README.
    • Remedy Option
      • config/tables.txt must be a Python3 list or tuple. Check the syntax of what is in the file, and try again.
  • No stores defined in config/stores.txt! Check CINDI README.
    • Remedy Option
      • The config/stores.txt file has an empty dictionary in it.
        • Review this README file carefully, you must define at least one backing-store for CINDI to use!
• 49: Failed to initialize XXXXX connection.
  • Python3 support for your chosen backing-store mechanism is not installed, or,
  • The connection/credential to the backing store is bad, or, the database you had specified to connect to in config/stores.txt is not available.
  • Remedy Option
    • Verify the Python3 client library for the specified backing-store is installed.
    • Verify the credentials to the backing-store are valid and specified correctly in config/stores.txt
    • Verify the database configured in config/stores.txt exists, permissions are good, and so on.
    • ...sqlite3 connection, file not found?
      • Perhaps the database file was deleted, or access was lost.
        • CINDI will not automatically re-create the SQLite3 database in this event.
    • Either reconstruct the SQLite3 database manually, or,
    • Wipe out all backing-stores, and start again from new.
  • Submit a bug if continuing to have difficulty connecting to a store, perhaps something changed in an underlying connectivity library!
• 131: High level error: ...
  • Some error, likely in a driver, occured.
  • Remedy Option: If the solution is not obvious, then you should submit a bug.
    • Especially if the problem is an OperationalError, complaining the SQL syntax is invalid.
• 22: Low level error: ...
  • Some error, unforseen by the author, occured.
  • Remedy Option: If the solution is not obvious, then you should submit a bug.

Cache Duality Caveat

If you have multiple CINDI instances running against the same backing-stores, then a cache in one instance will not have a way to know if a DML CREATE/UPDATE/DELETE occured in another instance. Please do not allow multiple clones of CINDI to interact with the same backing-stores concurrently.

• A simple solution to this in a future release will be to have a /cache-clear endpoint in Flask, or
• A file on the file system is monitored, if it is changed, then other instances know to clear the cache.

Credits

Please read the LICENSE. This software was written by a single individual. This is alpha-quality software, you are likely to find bugs! Please submit feedback! Thank you for evaluating CINDI!