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https://github.com/materialsvirtuallab/flamyngo

Flask frontend for MongoDB
https://github.com/materialsvirtuallab/flamyngo

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Flask frontend for MongoDB

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README 

        
# Flamyngo



Flamyngo is a YAML-powered Flask frontend for MongoDB. The aim is to delegate

most settings to a YAML configuration file, which then allows the  underlying

code to be reused for any conceivable collection. The official web page is at

https://materialsvirtuallab.github.io/flamyngo/.



Complete change log: [link](https://materialsvirtuallab.github.io/flamyngo//CHANGES).



# Usage



Install via pip:



```bash

pip install flamyngo

```



Create your `.flamyngo.yaml`.



```bash

flm --config 

```



If `--config` is not provided, it defaults to `~/.flamyngo.yaml`.



# Configuration



A sample commented configuration yaml file is given below. You can start from

the one below and customize it to suit your needs.



```yaml

# Provide an optional title for your app.

title: "My Flamyngo App"



# Provide some optional help text (html format) for the query.

help: "Supported queries: last name (string)"



# Uncomment the parameter below to provide an optional template folder, which

# will be passed into the Flamyngo app. Path to the template folder should be

# specified relative to localtion where flm is run. If not provided, the

# default provided in the flamyngo.templates will be used. It is highly

# recommended that you start from the default provided and make only stylistic

# changes. It is imperative you do not change the variable names in the Jinja

# templates or Flamyngo will not work.



# template_folder: my_templates



# MongoDB settings

db:

  host: mongo.host.com

  port: 27017

  username: user

  password: password

  database: mydb

# Alternatively, MongoDB settings can just be provided as a connection string.

# dnspython must be installed if you are using the connection string method.

#  connection_string: "mongodb+srv://user:[email protected]/"



# List of collection settings. Note that more than one collection is supported,

# though only one collection can be queried at any one time.

collections:

  -

    name: mycoll



    # These set the special queries as an ordered list of [, , ].

    # If the query string satisfies any of the regex, the Mongo query is set as

    # {: type()}. This allows for much more friendly setups for common

    # queries that do not require a user to type in verbose Mongo criteria. Each

    # regex should be uniquely identifying.

    # Types can be any kind of callable function that takes in a string and return

    # a value without other arguments. E.g., int, str, float, etc. You can support

    # more powerful conversions by writing your own processing function, e.g.,

    # mymodule.convert_degress_to_radians.

    # If none of the regex works, the criteria is interpreted as a Mongo-like dict query.

    query:

      - [last_name, '^[A-Za-z]+$', str]

      - [phone_number, '^[0-9]+$', int]



    # A default list of projection key, processing function to display as a table.

    # Again, processing function can be any callable, and you can define your own.

    # You can also supply any Python formatting string (starts with %) as the processing

    # function. For example, "%.1f" would format that quantity as a float with one

    # decimal.

    summary:

      - [_id, str]

      - [first_name, str]

      - [last_name, str]

      - [phone_number, str]

      - [age, "%d"]



    # Aliases for various fields. These are used to display short names in the summary

    # table. You can also directly perform queries using the short names instead of

    # using the long names.

    aliases:

      phone_number: number



    # Initial sorting for summary. Use asc for ascending and desc for descending.

    # Note that the aliased name (if any) should be used for sorting.

    sort: [last_name, asc]



    # The following defines unique identifiers for each doc. This allows each

    # specific doc to be queried and displayed using this key. If this key is

    # present in the default list of projections, a link will be created to each

    # unique document.

    unique_key: _id

    unique_key_type: bson.objectid.ObjectId



    # The following defines a filter criteria that will be applied to all queries.

    # This allows presenting only a subset of a database.

    filter_criteria:

      "valid": true



    # The following defines keys to exclude from the doc view.

    # This is sometimes useful (or necessary) to reduce the size of the

    # individual documents being viewed (for very large documents).

    # This only affects the doc view.

    doc_exclude:

      - key_to_exclude



# Basic auth can be set up by specifying user and password below. If these are not

# set, then no authentication. Note that this is not the most secure. It is merely

# used for a basic setup. For high security, look into proper implementations.

AUTH_USER: Iam

AUTH_PASSWD: Pink

API_KEY: IamPink

```



# URLs



Assuming that you are running on local host at port 5000, the initial

landing page will be at http://localhost:5000.



Pages for individual docs following the format

http://localhost:5000/[collection_name]/doc/[unique_id].



# REST API



* Getting all unique ids for a collection: http://localhost:5000/[collection_name]/unique_ids

* Getting individual docs as a json response: http://localhost:5000/[collection_name]/doc/[unique_id]/json.

* Getting a field of an individual doc as a plain text response: http://localhost:5000/[collection_name]/doc/[unique_id]/.