Frequently we need a table that a user can scroll through to present data for users. This is very easy with Field Engine and can be done with a few simple steps.
We need to include the Field Engine files:
<link href="FieldEngine.css" rel="stylesheet" />
<link href="FieldEngine-Defaults.css" rel="stylesheet" />
<script src="fe-browser.js"></script>
Then we need to specify the CSS for the hex grid, we're going to make our borders black and our hexes white:
.field-hex .field_view_inner {
background-color: black;
}
.field-hex .field_location {
background-color: white;
color: black;
}
Then we specify the scrollable table with a table and the class field-table
<table class="field-table" columns="3" rows="3">
<tr><th>Col A</th><th>Col B</th></tr>
<tr><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td></tr>
<tr><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td></tr>
<tr><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td></tr>
<tr><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td></tr>
<tr><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td></tr>
<tr><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td></tr>
<tr><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td></tr>
<tr><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td></tr>
<tr><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td><td>123</td><td>456</td></tr>
<tr><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td><td>789</td><td>012</td></tr>
</table>
And like that you have a scrollable table. Note that columns and rows specify the size of the view of the data.
from sdtk import com_sdtk_api_GitAPI def printer(data, reader): print(reader.toArrayOfNativeMaps(None)) com_sdtk_api_GitAPI.reposAPI().retrieveData({"owner": "Vis-LLC"}, printer)To retrieve all branches a repo has using Simple Data Toolkit, we can do the following:
from sdtk import com_sdtk_api_GitAPI def printer(data, reader): print(reader.toArrayOfNativeMaps(None)) com_sdtk_api_GitAPI.branchesAPI().retrieveData({"owner": "Vis-LLC", "repo": "Simple-Data-Toolkit"}, printer)To retrieve all the files in a branch using Simple Data Toolkit, we can do the following:
from sdtk import com_sdtk_api_GitAPI def printer(data, reader): print(reader.toArrayOfNativeMaps(None)) com_sdtk_api_GitAPI.filesAPI().retrieveData({"owner": "Vis-LLC", "repo": "Simple-Data-Toolkit", "branch": "main"}, printer)To retrieve the data in a file using Simple Data Toolkit, we can do the following:
from sdtk import com_sdtk_api_GitAPI def printerData(data, reader): print(data) com_sdtk_api_GitAPI.retrieveAPI().retrieveData({"owner": "Vis-LLC", "repo": "Simple-Data-Toolkit-UI", "branch": "main", "path": "index.html"}, printerData)We can also login using a personal access token (https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens)
from sdtk import com_sdtk_api_GitAPI def printerData(data, reader): print(data) com_sdtk_api_GitAPI.instance().setKey("Personal Access Token Here").retrieveAPI().retrieveData({"owner": "Vis-LLC", "repo": "Simple-Data-Toolkit-UI", "branch": "main", "path": "index.html"}, printerData)Simple Data Toolkit - Tutorial - Windows - Scheduled TaskLet's suppose you want to create a task that loads a Pipe Delimited File into a database on a daily basis. The task is to run on Windows and you are using Snowflake for the database. You can do it with SDTK as follows: 1) Download SDTK. For this tutorial, we're going to use the latest version of the Windows Shell Script version as of this writing (0.1.2) which is here: https://sourceforge.net/projects/simple-data-toolkit/files/0.1.3/stc-wsh.js/download 2) Create a new text file called ConvertPSV.cmd 3) Open the file with a text editor (like Notepad or Visual Studio Code) Enter the following text: cscript stc-wsh.js clients.psv clients.sql createorreplace clients (For more info on STC and SDTK see the following URL: https://www.vis-software.com/#sdtk) (For more info on cscript see the following URL: https://docs.microsoft.com/en-us/windows-server/administration/windows-commands/cscript) SET SNOWSQL_PWD=password snowsql -a myorganization-myaccount -u jsmith -f clients.sql -d database -s public -o quiet=true -o friendly=false (For more info on snowsql see the following URL: https://docs.snowflake.com/en/user-guide/snowsql-use.html) 4) Go to the Start Menu. 5) Search for Task Scheduler. (For more info on Task Scheduler see the following URL: https://docs.microsoft.com/en-us/windows/win32/taskschd/about-the-task-scheduler) 6) Open Task Scheduler. 7) Click Create Task. 8) For name enter: Convert PSV to SQL 9) Click Triggers Tab 10) Click New button 11) Select Daily 12) Start start time to 8:00 AM. 13) Click the OK button. 14) Click Actions tab. 15) Click New button 16) For Program/script click Browse. 17) Find the ConvertPSV.cmd script. 18) Click Open. 19) Set Start in to the directory that the ConvertPSV.cmd script is in. 20) Click the OK button. 21) Click the OK button. 22) To test, right click Convert PSV to SQL. 23) Select Run.Simple Data Toolkit - Tutorial - Ortingo API - PythonAt the time of this writing, Ortingo does not have an official API. Fortunately, Simple Data Toolkit provides an unofficial API for reading posts (at the time of this writing, the release of this is pending for complete support, but it is coming soon) To retrieve all posts for a given user in Python, using Simple Data Toolkit, we can do the following:
from sdtk import com_sdtk_api_OrtingoAPI def printer(data, reader): print(reader.toArrayOfNativeMaps(None)) com_sdtk_api_OrtingoAPI.postsAPI().retrieveData({"owner": "60CQ59FN46SVQFXJ"}, printer)Let's suppose we want only a list of titles for a given user, we can do this instead:
from sdtk import com_sdtk_api_OrtingoAPI def printer(data, reader): print(reader.filterColumnsOnly(["title"]).toArrayOfNativeMaps(None)) com_sdtk_api_OrtingoAPI.postsAPI().retrieveData({"owner": "60CQ59FN46SVQFXJ"}, printer)We can also pull suggested content from Ortingo with the following, where the topics we are searching on are provided with the query parameter (in this case it's value is data):
from sdtk import com_sdtk_api_OrtingoAPI def printerUrls(data, reader): print(reader.filterColumnsOnly(["url"]).toArrayOfNativeMaps(None)) com_sdtk_api_OrtingoAPI.suggestionsAPI().retrieveData({"query": "data"}, printerUrls)And finally, we can also pull comments attached to a post in Ortingo with the following, where the user is myself and the post is a test post I created:
from sdtk import com_sdtk_api_OrtingoAPI def printerComments(data, reader): print(reader.filterColumnsOnly(["commentDate", "post"]).toArrayOfNativeMaps(None)) com_sdtk_api_OrtingoAPI.commentsAPI().retrieveData({"owner": "60CQ59FN46SVQFXJ", "id": "test"}, printerComments)The columns supported at the time of this writing are: - id - owner - title - subtitle - post - url For comments the following columns are supported: - id - owner - commentDate - replyTo - postSimple Data Toolkit - Tutorial - Mac OS - Scheduled TaskLet's suppose you want to create a task that loads a Pipe Delimited File into a database on a daily basis. The task is to run on Mac OS and you are using Snowflake for the database. You can do it with SDTK as follows: 1) Download SDTK. For this tutorial, we're going to use the latest version of the Python version as of this writing (0.1.2) which is here: https://sourceforge.net/projects/simple-data-toolkit/files/0.1.3/stc.py/download 2) Create a new text file called ConvertPSV.sh 3) Open the file with a text editor (like Text Edit) Enter the following text: #!/bin/sh python stc.py clients.psv clients.sql createorreplace clients (For more info on STC and SDTK see the following URL: https://www.vis-software.com/#sdtk) export SNOWSQL_PWD=password snowsql -a myorganization-myaccount -u jsmith -f clients.sql -d database -s public -o quiet=true -o friendly=false (For more info on snowsql see the following URL: https://docs.snowflake.com/en/user-guide/snowsql-use.html) 4) Go to the Terminal. 5) Edit the list of cron jobs with the following command: nano crontab -e 6) Add the following to a new line: 0 8 * * * cd ~ && ConvertPSV.sh 7) Press CTRL+O and CTRL+X to save and exit nano.Simple Data Toolkit - Tutorial - Linux - Scheduled TaskLet's suppose you want to create a task that loads a Pipe Delimited File into a database on a daily basis. The task is to run on Linux and you are using Snowflake for the database. You can do it with SDTK as follows: 1) Download SDTK. For this tutorial, we're going to use the latest version of the Python version as of this writing (0.1.2) which is here: https://sourceforge.net/projects/simple-data-toolkit/files/0.1.3/stc.py/download 2) Create a new text file called ConvertPSV.sh 3) Open the file with a text editor (like Text Edit) Enter the following text: #!/bin/sh python stc.py clients.psv clients.sql createorreplace clients (For more info on STC and SDTK see the following URL: https://www.vis-software.com/#sdtk) export SNOWSQL_PWD=password snowsql -a myorganization-myaccount -u jsmith -f clients.sql -d database -s public -o quiet=true -o friendly=false (For more info on snowsql see the following URL: https://docs.snowflake.com/en/user-guide/snowsql-use.html) 4) Go to the Terminal. 5) Edit the list of cron jobs with the following command: nano crontab -e 6) Add the following to a new line: 0 8 * * * cd ~ && ConvertPSV.sh 7) Press CTRL+O and CTRL+X to save and exit nano.Simple Data Toolkit - Tutorial - Ethereum via Etherscan - PythonSimple Data Toolkit provides an unofficial API for reading Ethereum transactions from the Etherscan API. (At the time of this writing, the release of this is pending for complete support, but it is coming soon) To retrieve all Ethereum transactions for a particular address we can do the following:
from sdtk import com_sdtk_api_EtherscanAPI def printer(data, reader): print(reader.toArrayOfNativeMaps(None)) com_sdtk_api_EtherscanAPI.transactionsAPI().retrieveData({"address": "0xAddress"}, printer)Replace 0xAddress with the address you wish to search on. Additionally, we can convert the transactions to our standard internal event interface like so:
from sdtk import com_sdtk_api_EtherscanAPI,com_sdtk_calendar_EtherscanFormat def printerEvents(data, reader): etherScan = com_sdtk_calendar_EtherscanFormat.instance() for event in reader.toArrayOfNativeMaps(None): ci = etherScan.read(event) print(ci.start.toString()) com_sdtk_api_EtherscanAPI.transactionsAPI().retrieveData({"address": "0xAddress"}, printerEvents)Replace 0xAddress with the address you wish to search on.
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