fundamentals.renderer.list_of_dictionaries

Render a python list of dictionaries in various list and markup formats

Author

David Young

Module Contents

Classes

list_of_dictionaries

The dataset object is a list of python dictionaries. Using this class, the data can be rendered as various list and markup formats

API

class fundamentals.renderer.list_of_dictionaries.list_of_dictionaries(log, listOfDictionaries, reDatetime=False)

Bases: object

The dataset object is a list of python dictionaries. Using this class, the data can be rendered as various list and markup formats

Key Arguments

• log – logger

• listOfDictionaries – the list of dictionaries to render

• reDatetime – a pre-compiled datetime regex. Default Falsefss

Usage

To initialise the dataset object:

dataList = [
    {
        "owner": "daisy",
        "pet": "dog",
        "address": "belfast, uk"
    },
    {
        "owner": "john",
        "pet": "snake",
        "address": "the moon"
    },
    {
        "owner": "susan",
        "pet": "crocodile",
        "address": "larne"
    }

]

from fundamentals.renderer import list_of_dictionaries
dataSet = list_of_dictionaries(
    log=log,
    listOfDictionaries=dataList
)

Initialization

csv(filepath=None)

Render the data in CSV format

Key Arguments

• filepath – path to the file to write the csv content to. Default None

Return

• renderedData – the data rendered in csv format

Usage

To render the data set as csv:

print(dataSet.csv())

owner,pet,address
daisy,dog,"belfast, uk"
john,snake,the moon
susan,crocodile,larne

and to save the csv rendering to file:

dataSet.csv("/path/to/myfile.csv")

json(filepath=None)

Render the data in json format

Key Arguments

• filepath – path to the file to write the json content to. Default None

Return

• renderedData – the data rendered as json

Usage

To render the data set as json:

print(dataSet.json())

[
    {
        "address": "belfast, uk",
        "owner": "daisy",
        "pet": "dog"
    },
    {
        "address": "the moon",
        "owner": "john",
        "pet": "snake"
    },
    {
        "address": "larne",
        "owner": "susan",
        "pet": "crocodile"
    }
]

and to save the json rendering to file:

dataSet.json("/path/to/myfile.json")

property list

Returns the original list of dictionaries

Usage

dataSet.list

markdown(filepath=None)

Render the data as a markdown table

Key Arguments

• filepath – path to the file to write the markdown to. Default None

Return

• renderedData – the data rendered as a markdown table

Usage

To render the data set as a markdown table:

print(dataSet.markdown())

| owner  | pet        | address      |
|:-------|:-----------|:-------------|
| daisy  | dog        | belfast, uk  |
| john   | snake      | the moon     |
| susan  | crocodile  | larne        |

and to save the markdown table rendering to file:

dataSet.table("/path/to/myfile.md")

mysql(tableName, filepath=None, createStatement=None)

Render the dataset as a series of mysql insert statements

Key Arguments

• tableName – the name of the mysql db table to assign the insert statements to.

• filepath – path to the file to write the mysql inserts content to. Default None createStatement

Return

• renderedData – the data rendered mysql insert statements (string format)

Usage

print(dataSet.mysql("testing_table"))

this output the following:

INSERT INTO `testing_table` (address,dateCreated,owner,pet) VALUES ("belfast, uk" ,"2016-09-14T16:21:36" ,"daisy" ,"dog")  ON DUPLICATE KEY UPDATE  address="belfast, uk", dateCreated="2016-09-14T16:21:36", owner="daisy", pet="dog" ;
INSERT INTO `testing_table` (address,dateCreated,owner,pet) VALUES ("the moon" ,"2016-09-14T16:21:36" ,"john" ,"snake")  ON DUPLICATE KEY UPDATE  address="the moon", dateCreated="2016-09-14T16:21:36", owner="john", pet="snake" ;
INSERT INTO `testing_table` (address,dateCreated,owner,pet) VALUES ("larne" ,"2016-09-14T16:21:36" ,"susan" ,"crocodile")  ON DUPLICATE KEY UPDATE  address="larne", dateCreated="2016-09-14T16:21:36", owner="susan", pet="crocodile" ;

To save this rendering to file use:

dataSet.mysql("testing_table", "/path/to/myfile.sql")

reST(filepath=None)

Render the data as a resturcturedText table

Key Arguments

• filepath – path to the file to write the table to. Default None

Return

• renderedData – the data rendered as a resturcturedText table

Usage

To render the data set as a resturcturedText table:

print(dataSet.reST())

+--------+------------+--------------+
| owner  | pet        | address      |
+========+============+==============+
| daisy  | dog        | belfast, uk  |
+--------+------------+--------------+
| john   | snake      | the moon     |
+--------+------------+--------------+
| susan  | crocodile  | larne        |
+--------+------------+--------------+

and to save the table rendering to file:

dataSet.reST("/path/to/myfile.rst")

table(filepath=None)

Render the data as a plain text table

Key Arguments

• filepath – path to the file to write the table to. Default None

Return

• renderedData – the data rendered as a plain text table

Usage

To render the data set as a plain text table:

print(dataSet.table())

+--------+------------+--------------+
| owner  | pet        | address      |
+========+============+==============+
| daisy  | dog        | belfast, uk  |
| john   | snake      | the moon     |
| susan  | crocodile  | larne        |
+--------+------------+--------------+

and to save the table rendering to file:

dataSet.table("/path/to/myfile.ascii")

yaml(filepath=None)

Render the data in yaml format

Key Arguments

• filepath – path to the file to write the yaml content to. Default None

Return

• renderedData – the data rendered as yaml

Usage

To render the data set as yaml:

print(dataSet.yaml())

- address: belfast, uk
  owner: daisy
  pet: dog
- address: the moon
  owner: john
  pet: snake
- address: larne
  owner: susan
  pet: crocodile

and to save the yaml rendering to file:

dataSet.json("/path/to/myfile.yaml")