Best Practices

Hear from Anaplan experts on the best ways to use the platform.
A guide to integrating Anaplan with IOS shortcuts and allowing you to automate from time, location, or even voice commands to Siri.
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The purpose of this Transactional API Tutor Script based on Python is to facilitate the learning process of Transactional API Calls using the Anaplan Platform.
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In this article, we describe how to easily extract Anaplan data with QlikView and use it in your analytics dashboards.
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Following announcements on the global strategic partnership between Anaplan and Google Cloud, we are pleased to unveil a new connector.
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I recently posted a Python library for version 1.3 of our API. With the GA announcement of API 2.0, I'm sharing a new library that works with these endpoints. Like the previous library, this supports certificate authentication as well. Both the public certificate and private key must be in PEM format. Additionally, this library supports the use of Java keystore. Edit: A recent update to the M2Crypto library caused it to become incompatible on certain systems. As a result, I have migrated to the Cryptography package to handle certificate authentication. Many thanks to @christophe_keom  for your assistance with the migration to Cryptography! Note:   While all of these scripts have been tested and found to be fully functional, due to the vast amount of potential use cases, Anaplan does not explicitly support custom scripts built by our customers. This article is for information only and does not suggest any future product direction. This library is a work in progress and will be updated with new features once they have been tested. Getting Started The attached Python library serves as a wrapper for interacting with the Anaplan API. This article will explain how you can use the library to automate many of the requests that are available in our Apiary, which can be found at   https://anaplanbulkapi20.docs.apiary.io/#. This article assumes you have the requests and M2Crypto modules installed as well as the Python 3.7. Please make sure you are installing these modules with Python 3, and not for an older version of Python. For more information on these modules, please see their respective websites: Python   (If you are using a Python version older or newer than 3.7 we cannot guarantee the validity of the article)   Requests   Cryptography Note:   Please read the comments at the top of every script before use, as they more thoroughly detail the assumptions that each script makes. Gathering the Necessary Information In order to use this library, the following information is required: Anaplan model ID Anaplan workspace ID Anaplan action ID CA certificate key-pair (private key and public certificate), or username and password There are two ways to obtain the model and workspace IDs: While the model is open, go Help>About:  Select the workspace and model IDs from the URL:  Authentication Every API request is required to supply valid authentication. There are two (2) ways to authenticate: Certificate Authentication Basic Authentication For full details about CA certificates, please refer to our Anapedia article. Basic authentication uses your Anaplan username and password. To create a connection with this library, define the authentication type and details, and the Anaplan workspace and model IDs: Certificate Files: conn = AnaplanConnection(anaplan.generate_authorization("Certificate","<path to private key>", "<path to public certificate>"), "<workspace ID>", "<model ID>") Basic: conn = AnaplanConnection(anaplan.generate_authorization("Basic","<Anaplan username>", "<Anaplan password>"), "<workspace ID>", "<model ID>")   Java Keystore: from anaplan_auth import get_keystore_pair key_pair=get_keystore_pair('/Users/jessewilson/Documents/Certificates/my_keystore.jks', '<passphrase>', '<key alias>', '<key passphrase>') privKey=key_pair[0] pubCert=key_pair[1] #Instantiate AnaplanConnection without workspace or model IDs conn = AnaplanConnection(anaplan.generate_authorization("Certificate", privKey, pubCert), "", "") Note: In the above code, you must import the get_keystore_pair method from the anaplan_auth module in order to pull the private key and public certificate details from the keystore. Getting Anaplan Resource Information You can use this library to get the necessary file or action IDs. This library builds a Python key-value dictionary, which you can search to obtain the desired information: Example: list_of_files = anaplan.get_list(conn, "files") files_dict = anaplan_resource_dictionary.build_id_dict(list_of_files) This code will build a dictionary, with the file name as the key. The following code will return the ID of the file: users_file_id = anaplan_resource_dictionary.get_id(files_dict, "file name") print(users_file_id) To build a dictionary of other resources, replace "files" with the desired resource: actions, exports, imports, processes.  You can use this functionality to easily refer to objects (workspace, model, action, file) by name, rather than ID. Example: #Fetch the name of the process to run process=input("Enter name of process to run: ") start = datetime.utcnow() with open('/Users/jessewilson/Desktop/Test results.txt', 'w+') as file: file.write(anaplan.execute_action(conn, str(ard.get_id(ard.build_id_dict(anaplan.get_list(conn, "processes"), "processes"), process)), 1)) file.close() end = datetime.utcnow() The code above prompts for a process name, queries the Anaplan model for a list of processes, builds a key-value dictionary based on the resource name, then searches that dictionary for the user-provided name, and executes the action, and writes the results to a local file. Uploads You can upload a file of any size and define a chunk size up to 50mb. The library loops through the file or memory buffer, reading chunks of the specified size and uploads to the Anaplan model. Flat file:  upload = anaplan.file_upload(conn, "<file ID>", <chunkSize (1-50)>, "<path to file>") "Streamed" file: with open('/Users/jessewilson/Documents/countries.csv', "rt") as f: buf=f.read() f.close() print(anaplan.stream_upload(conn, "113000000000", buf)) print(anaplan.stream_upload(conn, "113000000000", "", complete=True)) The above code reads a flat file and saves the data to a buffer (this can be replaced with any data source, it does not necessarily need to read from a file). This data is then passed to the "streaming" upload method. This method does not accept the chunk size input. Instead, it simply ensures that the data in the buffer is less than 50mb before uploading. You are responsible for ensuring that the data you've extracted is appropriately split. Once you've finished uploading the data, you must make one final call to mark the file as complete and ready for use by Anaplan actions. Executing Actions You can run any Anaplan action with this script and define a number of times to retry the request if there's a problem. In order to execute an Anaplan action, the ID is required. To execute, all that is required is the following: run_job = execute_action(conn, "<action ID>", "<retryCount>") print(run_job) This will run the desired action, loop until complete, then print the results to the screen. If failure dump(s) exits, this will also be returned. Example output: Process action 112000000082 completed. Failure: True Process action 112000000079 completed. Failure: True Details: hierarchyName Worker Report successRowCount 0 successCreateCount 0 successUpdateCount 0 warningsRowCount 435 warningsCreateCount 0 warningsUpdateCount 435 failedCount 4 ignoredCount 0 totalRowCount 439 totalCreateCount 0 totalUpdateCount 435 invalidCount 4 updatedCount 435 renamedCount 435 createdCount 0 lineItemName Code rowCount 0 ignoredCount 435 Failure dump(s): Error dump for 112000000082 "_Status_","Employees","Parent","Code","Prop1","Prop2","_Line_","_Error_1_" "E","Test User 2","All employees","","101.1a","1.0","2","Error parsing key for this row; no values" "W","Jesse Wilson","All employees","a004100000HnINpAAN","","0.0","3","Invalid parent" "W","Alec","All employees","a004100000HnINzAAN","","0.0","4","Invalid parent" "E","Alec 2","All employees","","","0.0","5","Error parsing key for this row; no values" "W","Test 2","All employees","a004100000HnIO9AAN","","0.0","6","Invalid parent" "E","Jesse Wilson - To Delete","All employees","","","0.0","7","Error parsing key for this row; no values" "W","#1725","All employees","69001","","0.0","8","Invalid parent" [...] "W","#2156","All employees","21001","","0.0","439","Invalid parent" "E","All employees","","","","","440","Error parsing key for this row; no values" Error dump for 112000000079 "Worker Report","Code","Value 1","_Line_","_Error_1_" "Jesse Wilson","a004100000HnINpAAN","0","434","Item not located in Worker Report list: Jesse Wilson" "Alec","a004100000HnINzAAN","0","435","Item not located in Worker Report list: Alec" "Test 2","a004100000HnIO9AAN","0","436","Item not located in Worker Report list: Test 2 Downloading a File If the above code is used to execute an export action, the fill will not be downloaded automatically. To get this file, use the following: download = get_file(conn, "<file ID>", "<path to local file>") print(download) This will save the file to the desired location on the local machine (or mounted network share folder) and alert you once the download is complete, or warn you if there is an error. Get Available Workspaces and Models API 2.0 introduced a new means of fetching the workspaces and models available to a given user. You can use this library to build a key-value dictionary (as above) for these resources. #Instantiate AnaplanConnection without workspace or model IDs conn = AnaplanConnection(anaplan.generate_authorization("Certificate", privKey, pubCert), "", "") #Setting session variables uid = anaplan.get_user_id(conn) #Fetch models and workspaces the account may access workspaces = ard.build_id_dict(anaplan.get_workspaces(conn, uid), "workspaces") models = ard.build_id_dict(anaplan.get_models(conn, uid), "models") #Select workspace and model to use while True: workspace_name=input("Enter workspace name to use (Enter ? to list available workspaces): ") if workspace_name == '?': for key in workspaces: print(key) else: break while True: model_name=input("Enter model name to use (Enter ? to list available models): ") if model_name == '?': for key in models: print(key) else: break #Extract workspace and model IDs from dictionaries workspace_id = ard.get_id(workspaces, workspace_name) model_id = ard.get_id(models, model_name) #Updating AnaplanConnection object conn.modelGuid=model_id conn.workspaceGuid=workspace_id The above code will create an AnaplanConnection instance with only the user authentication defined. It queries the API to return the ID of the user in question, then queries for the available workspaces and models and builds a dictionary with these results. You can then enter the name of the workspace and model you wish to use (or print to screen all available), then finally update the AnaplanConnection instance to be used in all future requests.
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This article provides a detailed approach of how to invoke Anaplan Rest API using Java Spring Boot Framework.
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One important thing to consider about data is the format of the time that the source system has. This article explains the formats Anaplan can accept in an import and those which it cannot.
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The native DocuSign integration with Anaplan makes it simple to share information. Learn how a script can help simplify the process even more. 
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Power BI is a popular reporting tool, and this article will describe how to implement it with Anaplan Rest API version 2.0.
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Anaplan API: Communication failure <SSL peer unverified:  peer not authenticated> This is a common error if a Customer Server is behind a proxy or firewall. The solution is to have the customer whitelist '*.anaplan.com' for firewall blocks.  If behind a proxy, use the '-via" or 'viauser" commands in Anaplan Connect. The other very common cause for this error is that the security certificate isn’t synced up with java. If the whitelist or via command solutions don’t apply or don’t resolve the error, uninstalling and reinstalling Java usually does the trick. Here are the commands available: -via -v Proxy URL Use specified proxy -viauser -vu username:pa Pass credentials to
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Overview Imports are blocking operations: To maintain a consistent view of the data, the model is locked during the import, and concurrent imports run by end-users will need to run one after the other and will block the model for everyone else. Exports are blocking for data entry while the export data is retrieved, and then the model is released. During the blocking phase, users can still navigate within the model. Rule #1  Carefully Decide If You Let End-Users Import (And Export) During Business Hours Imports executed by end-users should be carefully considered, and if possible, executed once or twice a day. Customers more easily accept model updates at scheduled hours for a predefined time—even if it takes 10+ minutes—and are frustrated when these imports are run randomly during business hours. Your first optimization is to adjust the process and run these imports by an administrator at a scheduled time, and then let the user based know about the schedule. Rule #2 Use a Saved View The first part of any import (or export) is retrieving the data. The time it takes to open the view directly affects the time of the import or export. Always import from a saved view—NEVER from the default view. And use the naming convention for easy maintenance. Ensure the view is using optimized filters with a single Boolean value per axis. Hide the line items that are not needed for import; do not bring extra columns that are not needed. If you have done all of the above, and the view is still taking time to complete, consider using the Tabular Multi Column export and filter "in the way out." This has been proven to improve some sluggish exports.  Rule #3 Mapping Objective = Zero Errors or Warning Make sure your import executes with no errors or warnings as every error takes processing time. The time to import into a medium-to-large list (>50k) is significantly reduced if no errors are to be processed. In the import definition, always map all displayed line items (source→target) or use the "ignore" setting. Don't leave any line item unmapped. Rule #4 Watch the Formulas Recalculated During the Import If your end-users encounter poor performance when clicking a button that triggers an import or a process, it is likely due to the recalculations that are triggered by the import, especially if the action creates or moves items within a hierarchy. You will likely need the help of the Anaplan Model Optimization team to identify what formulas are triggered after the import is done and to get a performance check on these formulas to identify which one takes most of the time. Usually, those fetching many cells such as SUM, LOOUKP, ANY, or FINDITEM are likely to be responsible for the performance impact. Speak to your Business Partner for more details on the Model Optimization services available to you. To solve such situations, you will need to challenge the need for recalculating the formula identified each time a user calls the action. Often, for actions such as creations, moves, assignments done in WFP or Territory Planning, many calculations used for reporting are triggered in real-time after the hierarchy is modified by the import, and are not necessarily needed by users until later in the process. The recommendation is to challenge your customer and see if these formulas can be calculated only once a day, instead of each time a user runs the action. If this is acceptable, you'll need to rearchitect your modules and/or formulas so that these heavy formulas get to run through a different process run daily by an administrator and not by each end-users. If not, you will need to look at the formulas more closely to see what improvements can be made. Remember, breaking formulas up often helps performance. Rule #5 Don't Import List Properties Importing list properties takes more time than importing these as a module line item. Review your model list impacted by imports, and look to replace list properties with module line items when possible. Use a system module to hold these for the key hierarchies, as per D.I.S.C.O. Rule #6 Get Your Data Hub Hub and spoke: Setup a data hub model, which will feed the other production models used by stakeholders. Performance benefits: It will prevent production models to be blocked by a large import from an external data source. But since data hub to production model imports will still be blocking operations, carefully filter what you import, and use the best practices rules listed above. All import, mapping/transformation modules required to prepare the data to be loaded into planning modules can now be located in a dedicated data hub model and not in the planning model. This model will then be smaller and will work more efficiently. Try and keep the transaction data history in the data hub with a specific analysis dashboard made available for end users; often, the detail is not needed for planning purposes, and holding this data in the planning model has a negative impact on size, model opening times, and performance. As a reminder of the other benefits of a data hub not linked to performance: Better structure, easier maintenance: data hub helps keep all the data organized in a central location. Better governance: Whenever possible put this Data Hub on a different workspace. That will ease the separation of duties between production models and meta-data management, at least on actual data and production lists. IT departments will love the idea to own the data hub and have no one else be an administrator in the workspace. Lower implementation costs: A data hub is a way to reduce the implementation time of new projects. Assuming IT can load the data needed by the new project in the data hub, then business users do not have to integrate with complex source systems but with the Anaplan data hub instead. Rule #7 Incremental Import/Export This can be the magic bullet in some cases. If you export on a frequent basis (daily or more) from an Anaplan model into a reporting system, or write back to the source system, or simply transfer data from one Anaplan model to another, you have ways to only import/export the data that have changed since the last export. Use a Boolean line item to identify records that have changed and only import those.
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You can interact with the data in your models using Anaplan's RESTful API. This enables you to securely import and export data, as well as run actions through any programmatic way you desire. The API can be leveraged in any custom integration, allowing for a wide range of integration solutions to be implemented. Completing an integration using the Anaplan API is a technical process that will require significant action by an individual with programming experience. Visit the links below to learn more: API Documentation Anaplan API Guide You can also view demonstration videos to understand how to implement APIs in your custom Integration client. The below videos show step-by-step guides of sequencing API calls and exporting data from Anaplan, importing data into Anaplan, and running delete actions and Anaplan processes. API sequence for uploading a file to Anaplan and running an import action is as follows: API sequence for running an export action and downloading a file from Anaplan is as follows: API sequence for running an Anaplan process and a delete action is as follows:
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Summary Anaplan Connect is a command-line client to the Anaplan cloud-based planning environment and is a java-based utility that is able to perform a variety of commands, such as uploading and downloading data files, executing JDBC SQL queries (for importing & exporting data from Anaplan), and running Anaplan actions and processes. To enhance the deployment of Anaplan Connect, it is important to be able to integrate the trapping of error conditions, enable the ability to retry the Anaplan Connect operation, and integrate email notifications. This article provides best practices on how to incorporate these capabilities. This article leverages the standard Windows command line batch script and documents the various components and syntax of the script. In summary, the script has the following main components: Set variable values such as exit codes, Anaplan Connect login parameters, and operations and email parameters Run commands prior to running Anaplan Connect commands Main loop block for multiple retries Establish a log file based upon the current date and loop number Run the native Anaplan Connect commands Search for string criteria to trap error conditions Branching logic based upon the discovery of any trapped error conditions Send email success or failure notification of Anaplan Connect run status Logic to determine if a retry is required End main loop block Run commands post to running Anaplan Connect commands Exit the script Section #1: Setting Script Variables The following section of the script establishes and sets variables that are used in the script. The first three lines perform the following actions: Clears the screen Sets the default to echo all commands Indicates to the operating system that variable values are strictly local to the the script The variables used in the script are as follows: ERRNO   – Sets the exit code to 0 unless set to 1 after multiple failed reties COUNT   – Counter variable used for looping multiple retries RETRY_COUNT   – Counter variable to store the max retry count (note: the /a switch indicates indicates a numeric value) AnaplanUser   – Anaplan login credentials in the format as indicated in the example WorkspaceId   – Anaplan numerical or named Workspace ID ModelId   – Anaplan numerical or named Model ID Operation   – A combination of Anaplan Connect commands. It should be noted that a ^ can be used to enhance readability by indicating that the current command continues on the next line Domain   – Email base domain. Typically, in the format of company.com Smtp   – Email SMTP server User   – Email SMTP server User ID Pass   – Email SMTP server password To   – Target email address(es). To increase the email distribution, simply add additional -t and the email addresses as in the example. From   – From email address Subject   – Email subject line. Note that this is dynamically set later in the script. cls echo on setlocal enableextensions REM **** SECTION #1 - SET VARIABLE VALUES **** set /a ERRNO=0 set /a COUNT=0 set /a RETRY_COUNT=2 REM Set Anaplan Connect Variables set AnaplanUser="<<Anaplan UserID>>:<<Anaplan UserPW>>" set WorkspaceId="<<put your WS ID here>>" set ModelId="<<put your Model ID here>>" set Operation=-import "My File" -execute ^ -output ".\My Errors.txt" REM Set Email variables set Domain="spg-demo.com" set Smtp="spg-demo" set User="fpmadmin@spg-demo.com" set Pass="1Rapidfpm" set To=-t "fpmadmin@spg-demo.com" -t "gburns@spg-demo.com" set From="fpmadmin@spg-demo.com" set Subject="Anaplan Connect Status" REM Set other types of variables such as file path names to be used in the Anaplan Connect "Operation" command Section #2: Pre Custom Batch Commands The following section allows custom batch commands to be added, such as running various batch operations like copy and renaming files or running stored procedures via a relational database command line interface. REM **** SECTION #2 - PRE ANAPLAN CONNECT COMMANDS *** REM Use this section to perform standard batch commands or operations prior to running Anaplan Connect Section #3: Start of Main Loop Block / Anaplan Connect Commands The following section of the script is the start of the main loop block as indicated by the :START. The individual components breakdown as follows: Dynamically set the name of the log file in the following date format and indicates the current loop number:   2016-16-06-ANAPLAN-LOG-RUN-0.TXT Delete prior log and error files Native out-of-the-box Anaplan Connect script with the addition of outputting the Anaplan Connect run session to the dynamic log file as highlighted here: cmd /C %Command% > .\%LogFile% REM **** SECTION #3 - ANAPLAN CONNECT COMMANDS *** :START REM Dynamically set logfile name based upon current date and retry count. set LogFile="%date:~-4%-%date:~7,2%-%date:~4,2%-ANAPLAN-LOG-RUN-%COUNT%.TXT" REM Delete prior log and error files del .\BAT_STAT.TXT del .\AC_API.ERR REM Out-of-the-box Anaplan Connect code with the exception of sending output to a log file setlocal enableextensions enabledelayedexpansion || exit /b 1 REM Change the directory to the batch file's drive, then change to its folder cd %~dp0 if not %AnaplanUser% == "" set Credentials=-user %AnaplanUser% set Command=.\AnaplanClient.bat %Credentials% -workspace %WorkspaceId% -model %ModelId% %Operation% @echo %Command% cmd /C %Command% > .\%LogFile% Section #4: Set Search Criteria The following section of the script enables trapping of error conditions that may occur with running the Anaplan Connect script. The methodology relies upon searching for certain strings in the log file after the AC commands execute. The batch command findstr can search for certain string patterns based upon literal or regular expressions and echo any matched records to the file AC_API.ERR. The existence of this file is then used to trap if an error has been caught. In the example below, two different patterns are searched in the log file. The output file AC_API.ERR is always produced even if there is no matching string. When there is no matching string, the file size will be an empty 0K file. Since the existence of the file determines if an error condition was trapped, it is imperative that any 0K files are removed, which is the function of the final line in the example below. REM **** SECTION #4 - SET SEARCH CRITERIA - REPEAT @FINDSTR COMMAND AS MANY TIMES AS NEEDED *** @findstr /c:"The file" .\%LogFile% > .\AC_API.ERR @findstr /c:"Anaplan API" .\%LogFile% >> .\AC_API.ERR REM Remove any 0K files produced by previous findstr commands @for /r %%f in (*) do if %%~zf==0 del "%%f" Section #5: Trap Error Conditions In the next section, logic is incorporated into the script to trap errors that might have occurred when executing the Anaplan Connect commands. The branching logic relies upon the existence of the AC_API.ERR file. If it exists, then the contents of the AC_API.ERR file are redirected to a secondary file called BAT_STAT.TXT and the email subject line is updated to indicate that an error occurred. If the file AC_API.ERR does not exist, then the contents of the Anaplan Connect log file is redirected to BAT_STAT.TXT and the email subject line is updated to indicate a successful run. Later in the script, the file BAT_STAT.TXT becomes the body of the email alert.  REM **** SECTION #5 - TRAP ERROR CONDITIONS *** REM If the file AC_API.ERR exists then echo errors to the primary BAT_STAT log file REM Else echo the log file to the primary BAT_STAT log file @if exist .\AC_API.ERR ( @echo . >> .\BAT_STAT.TXT @echo *** ANAPLAN CONNECT ERROR OCCURED *** >> .\BAT_STAT.TXT @echo -------------------------------------------------------------- >> .\BAT_STAT.TXT type .\AC_API.ERR >> .\BAT_STAT.TXT @echo -------------------------------------------------------------- >> .\BAT_STAT.TXT set Subject="ANAPLAN CONNECT ERROR OCCURED" ) else ( @echo . >> .\BAT_STAT.TXT @echo *** ALL OPERATIONS COMPLETED SUCCESSFULLY *** >> .\BAT_STAT.TXT @echo -------------------------------------------------------------- >> .\BAT_STAT.TXT type .\%LogFile% >> .\BAT_STAT.TXT @echo -------------------------------------------------------------- >> .\BAT_STAT.TXT set Subject="ANAPLAN LOADED SUCCESSFULLY" ) Section #6: Send Email In this section of the script, a success or failure email notification email will be sent. The parameters for sending are all set in the variable section of the script.  REM **** SECTION #6 - SEND EMAIL VIA MAILSEND *** @mailsend -domain %Domain% ^ -smtp %Smtp% ^ -auth -user %User% ^ -pass %Pass% ^ %To% ^ -f %From% ^ -sub %Subject% ^ -msg-body .\BAT_STAT.TXT Note: Sending email via SMTP requires the use of a free and simple Windows program known as MailSend. The latest release is available here:   https://github.com/muquit/mailsend/releases/ . Once downloaded, unpack the .zip file, rename the file to mailsend.exe and place the executable in the same directory where the Anaplan Connect batch script is located.  Section #7: Determine if a Retry is Required This is one of the final sections of the script that will determine if the Anaplan Connect commands need to be retried. Nested IF statements are typically frowned upon but are required here given the limited capabilities of the Windows batch language. The first IF test determines if the file AC_API.ERR exists. If this file does exist, then the logic drops in and tests if the current value of COUNT   is less than   the RETRY_COUNT. If the condition is true, then the COUNT gets incremented and the batch returns to the :START location (Section #3) to repeat the Anaplan Connect commands. If the condition of the nested IF is false, then the batch goes to the end of the script to exit with an exit code of 1.  REM **** SECTION #7 - DETERMINE IF A RETRY IS REQUIRED *** @if exist .\AC_API.ERR ( @if %COUNT% lss %RETRY_COUNT% ( @set /a COUNT+=1 @goto :START ) else ( set /a ERRNO=1 @goto :END ) ) else ( set /a ERRNO=0 Section #8: Post Custom Batch Commands The following section allows custom batch commands to be added, such as running various batch operations like copy and renaming files, or running stored procedures via a relational database command line interface. Additionally, this would be the location to add functionality to bulk insert flat file data exported from Anaplan into a relational target via tools such as Oracle SQL Loader (SQLLDR) or Microsoft SQL Server Bulk Copy (BCP).  REM **** SECTION #8 - POST ANAPLAN CONNECT COMMANDS *** REM Use this section to perform standard batch commands or operations after running Anaplan Connect commands :END exit /b %ERRNO% Sample Email Notifications The following are sample emails sent by the batch script, which are based upon the sample script in this document. Note how the needed content from the log files is piped directly into the body of the email.  Success Mail: Error Mail:
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As described in the Authentication API documentation, an authentication token is needed to issue requests with API 2.0.  The request for a token is made to: https://auth.anaplan.com/token/authenticate API 2.0 supports both Basic Authentication and CA Certificates.  Basic Authentication is achieved in the same manner it was for API 1.3. The only difference is that it is used with the authentication request to get the token, not on each individual request. CA Certificate authentication requires that the public key and private key be used in the request to obtain an authentication token. The following steps are needed to create the request using a CA Certificate.   Add the contents of the public key to the authorization header Authorization: CACertificate {your_CA_certificate} {you_CA_certificate} should be replaced by the contents of the public key.  This should include the contents between the "--- BEGIN CERTIFICATE ---" and "--- END CERTIFICATE ---" lines and not including them.  The Content-Type header should be "application/json". The body of the request should have the following json string. { "encodedData" : "{encodedString}", "encodedSignedData" : "{signedString}" } The {encodedString} value should be a randomly generated base-64 encoded string of at least 100 bytes. The {signedString} value is the {encodedString} value that has been signed by the private key and then base-64 encoded.   Ideally, each time an application needs to connect to Anaplan it should generate a new random string and signed string. If this is not possible, then it can be generated once and used each time. Examples: The documentation has some sample Java code that can be added to an existing API implementation.  A full python library has been published in community. This can be used as needed to develop an authentication process. Below is a simple chunk of python code based on the library above that will output the strings needed as well. In this code, the path to the public key and private key files will need to be entered into the certfile and keyfile variables respectively.  This code requires the following: Python 3. Request. pyOpenSSL.   from base64 import b64encode import os import requests from OpenSSL import crypto import random import string certfile = "{path_to_public_key_file}" keyfile = "{path_to_private_key_file}" """ docstring """ st_cert=open(certfile, 'rt').read() cert=crypto.load_certificate(crypto.FILETYPE_PEM, st_cert) st_key=open(keyfile, 'rt').read() key=crypto.load_privatekey(crypto.FILETYPE_PEM, st_key) pem = crypto.dump_certificate(crypto.FILETYPE_TEXT, cert) print (type(pem)) random_str = os.urandom(100) signed_str = crypto.sign(key, random_str, "sha512") auth_headers = "'authorization': 'CACertificate %s'" % (st_cert.replace("\n", "").replace("-----BEGIN CERTIFICATE-----", "").replace("-----END CERTIFICATE-----", "")) print(auth_headers, '\n') encodedstr = b64encode(random_str) signedstr = b64encode(signed_str) print("{") print(" 'encodedData': %s " %encodedstr.decode("utf-8") ) print(" 'encodedSignedData': %s" % signedstr.decode("utf-8") ) print("}")   This code returns the header needed, as well as the json body needed for the authentication request.  Authentication Header: json Body:
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This article covers the necessary steps to update the iPaaS connectors for HyperConnect/Informatica Cloud, Dell Boomi, Mulesoft and SnapLogic. See the article A Guide to CA Certificates in Anaplan Integrations - Anaplan Community for the steps to process a certificate once it has been procured. HyperConnect/Informatica Cloud Authentication within HyperConnect/Informatica Cloud is handled at the connection level. There should be a connection for each model that is used within the integrations. HyperConnect/Informatica Cloud supports basic authentication and certificate authentication.  The steps to use Certificate Authority (CA) certificates with HyperConnect/Informatica are listed below: Each connection must be using the "Anaplan V2" connector.  A java keystore containing both the public and private keys needs to be created and placed where the secure agent can access it. In each connection: Set the Auth Type to "Cert Auth". Clear the "Certificate Path Location" field. Update the API Major Version. Set it to 2. Update the API Minor Version. Set it to 0. Enter the full path to the java keystore in the "KeyStore Path Location". Enter the alias used when the java keystore was created in the "KeyStore Alias" field. Enter the password for the java keystore in the "KeyStore Password" field. Note the password is masked. Test for connectivity. Dell Boomi Authentication within Dell Boomi is handled at the connection level. There should be a connection for each workspace that is used within the integrations. Dell Boomi supports basic authentication and certificate authentication.  The steps to use CA certificates with Dell Boomi are listed below: Each connection must be using the "Anaplan" version of the connector. The "Anaplan V2" and "Anaplan (legacy)" versions are not current and do not support CA certificate authentication. A P12 bundle of both the public and private keys needs to be created. The file received from the CA provider is sometimes in the P12 bundle format. To test this: Use the java keytool to run the following command. keytool -v list -storetype pkcs12 -keystore %path to keystore% Within the output of the command, there should be an "Alias name" property. This value will be used in the connection. If the certificate does not contain the alias, a P12 bundle can be created using OpenSSL. See Creating a Java Keystore for the steps to create a P12 bundle. Once the bundle is created, the remaining steps in the article are not needed. In Dell Boomi: Create a new object.  Type: Certificate. Certificate Type: X.509. The name and location of the certificate are up to you. Click "Create". Import the P12 bundle file. Edit the connection. Ensure the URL is pointed to "https://api.anaplan.com/2/0". Set the Authentication Type to "Client Certificate". Select the certificate created above from the "Certificate" dropdown. Enter the alias used in the P12 bundle into the "Private Key Alias" field. Enter the password for the P12 bundle in the "Password" field. MuleSoft Authentication within MuleSoft is handled at the c onnection level. Typically only a single connection is needed. MuleSoft supports basic authentication and certificate authentication.  The steps to use CA Certificates with MuleSoft are listed below: A java keystore containing both the public and private keys needs to be created. Enter the full path to the java keystore in the "Key store path". Enter the alias used when the java keystore was created in the "KeyStore Alias" field. Enter the password for the java keystore in the "KeyStore Password" field. Note the password is masked. SnapLogic Authentication within SnapLogic is handled at the c onnection level. Typically only a single connection is needed. SnapLogic supports basic authentication and certificate authentication.  The steps to use CA Certificates with SnapLogic are listed below: Public Key Open the public key file in a text editor. Copy everything from "--- BEGIN CERTIFICATE ---" through "---END CERTIFICATE ---". Paste the contents into the "External certificate contents". Private Key The private key cannot be encrypted for use in SnapLogic. Open the private key file in a text editor. If the key information begins with "--- BEGIN RSA PRIVATE KEY ---" then the key is not encrypted. Continue with step iii below. If the key information begins with "--- BEGIN ENCRYPTED PRIVATE KEY ---" then the key needs to be un-encrypted prior to use. Issue the following OpenSSL command to create a new private key file from the original. openssl rsa -in private_key.pem -out unencrypted_private_key.pem Copy everything from "--- BEGIN RSA PRIVATE KEY ---" through "---END RSA PRIVATE KEY ---" Paste the contents into the "External private key" field.
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This article covers the necessary steps for you to migrate your Anaplan Connect (AC) 1.3.x.x script to Anaplan Connect 1.4.x. For additional details and examples, refer to the  latest Anaplan Connect User Guide. The changes are: New connectivity parameters. Replace reference to Anaplan Certificate with Certificate Authority (CA) certificates using new parameters. Optional Chunksize & Retry parameters. Changes to JDBC configuration. New Connectivity Parameters Add the following parameters to your Anaplan Connect 1.4.x integration scripts. These parameters provide connectivity to Anaplan and Anaplan authentication services. Note: Both of the urls listed below need to be whitelisted with your network team. -service "https://api.anaplan.com/" -auth "https://auth.anaplan.com" Certificate Changes As noted in our   Anaplan-Generated Certificates to Expire at the End of 2019 blog post, new and updated Anaplan integration options support Certificate Authority (CA) certificates for authentication. Basic Authentication is still available in Anaplan Connect 1.4.x, however, the use of certificates has changed. In Anaplan Connect 1.3.x.x, the script references the full path to the Anaplan certificate file. For example: -certificate "/Users/username/Documents/AnaplanConnect1.3/certificate.pem" In Anaplan Connect 1.4.x the CA certificate can be referenced via two different options. Examples of both options are included at the end of this article as well as in the Anaplan Connect 1.4.x download. Option 1: Direct Use of the Private Key with Anaplan Connect Use your Private Key with Anaplan Connect by providing to certificate, private key and optional private key passphrase.  For example: If your private key has been encrypted use the following: CertPath="FullPathToThePublicCertificate" PrivateKey="FullPathToThePrivateKey:Passphrase" If your private key has not been encrypted then the passphrase can be omitted, however the colon is still needed in the path of the private key. CertPath="FullPathToThePublicCertificate" PrivateKey="FullPathToThePrivateKey:" To pass these values to Anaplan Connect 1.4.x, use these command line parameters: -certificate {path to the certificate file} -privatekey {path to the private key file:}{passphrase} These parameters should be passed as part of the credentials in the script: Credentials="-certificate ${CertPath} -privatekey ${PrivateKey}" Option 2: Create a Java Keystore A Java Keystore (JKS) is a repository of security certificates and their private keys.  Refer to   this video   for a walkthrough of the process of getting the CA certificate into the key store. You can also refer to   Anaplan Connect User Guide   for steps to create the Java key store. Once you have imported the key into the JKS,   make note of this information : Path to the JKS (directory path on server where JKS is saved) The Password to the JKS The alias of the certificate within the JKS. For example: KeyStorePath ="/Users/username/Documents/AnaplanConnect1.4/my_keystore.jks" KeyStorePass ="your_password" KeyStoreAlias ="keyalias" To pass these values to Anaplan Connect 1.4.x, use these command line parameters: -keystore {KeystorePath} -keystorealias {KeystoreAlias} -keystorepass {KeystorePass} These parameters should be passed as part of the credentials in the script: Credentials="-keystore ${KeyStorePath} -keystorepass ${KeyStorePass} -keystorealias ${KeyStoreAlias}" Chunksize Anaplan Connect 1.4.x allows for custom chunk sizes on files being imported. The -chunksize parameter can be included in the call with the value being the size of the chunks in megabytes. The chunksize can be any whole number between 1 and 50. -chunksize {SizeInMBs} Retry Anaplan Connect 1.4.x allows for the client to retry requests to the server in the event that the server is busy. The -maxretrycount parameter defines the number of times the process retries the action before exiting. The -retrytimeout parameter is the time in seconds that the process waits before the next retry. -maxretrycount {MaxNumberOfRetries} -retrytimeout {TimeoutInSeconds} Changes to JDBC Configuration With Anaplan Connect 1.3.x.x the parameters and query for using JDBC are stored within the Anaplan Connect script itself. For example: Operation="-file Sample.csv' -jdbcurl 'jdbc:mysql://localhost:3306/mysql?useSSL=false' -jdbcuser 'root:Welcome1' -jdbcquery 'SELECT * FROM py_sales' -import 'Sample.csv' -execute" With Anaplan Connect 1.4.x. the parameters and query for using JDBC have been moved to a separate file. The name of that file is then added to the AnaplanClient call using the   -jdbcproperties   parameter. For example:  Operation="-auth 'https://auth.anaplan.com' -file 'Sample.csv'  -jdbcproperties 'jdbc_query.properties' -import 'Sample.csv' -execute " To run multiple JDBC calls in the same operation, a separate jdbcpropeties file will be needed for each query. Each set of calls in the operation should include then following parameters: -file, -jdbcproperties, -import, and -execute. In the code sample below each call is underlined separately.  For example: Operation="-auth 'https://auth.anaplan.com' -file 'SampleA.csv' -jdbcproperties 'SampleA.properties' -import 'SampleA Load' -execute -file 'SampleB.csv' -jdbcproperties 'SampleB.properties' -import 'SampleB Load' -execute" JDBC Properties File Below is an example of the JDBCProperties file. Refer to the   Anaplan Connect User Guide   for more details on the properties shown below. If the query statement is long, the statement can be broken up on multiple lines by using the \ character at the end of each line. No \ is needed on the last line of the statement. The \ must be at the end of the line and nothing can follow it. jdbc.connect.url=jdbc:mysql://localhost:3306/mysql?useSSL=false jdbc.username=root jdbc.password=Welcome1 jdbc.fetch.size=5 jdbc.isStoredProcedure=false jdbc.query=select * \ from mysql.py_sales \ where year = ? and month !=?; jdbc.params=2018,04 CA Certificate Examples Direct Use of the Private Key Anaplan Connect Windows BAT Script Example (with direct use of the private key) '@echo of rem This example lists files in a model set CertPath="C:\CertFile.pem" set PrivateKey="C:\PrivateKeyFile.pem:passphrase" set WorkspaceId="Enter WS ID Here" set ModelId="Enter Model ID here" set Operation=-service "https://api.anaplan.com" -auth "https://auth.anaplan.com" -workspace %WorkspaceId% -model %ModelId% -F set Credentials=-certificate %CertPath% -privatekey %PrivateKey% rem *** End of settings - Do not edit below this line *** setlocal enableextensions enabledelayedexpansion || exit /b 1 cd %~dp0 set Command=.\AnaplanClient.bat %Credentials% %Operation% @echo %Command% cmd /c %Command% pause Anaplan Connect Shell Script Example (with Direct Use of the Private Key) #!/bin/sh # This example lists files in a model set CertPath="/path/CertFile.pem" set PrivateKey="/path/PrivateKeyFile.pem:passphrase" WorkspaceId="Enter WS ID Here" ModelId="Enter Model Id Here" Operation="-service 'https://api.anaplan.com' -auth 'https://auth.anaplan.com' -workspace ${WorkspaceId} -model ${ModelId} -F" #________________ Do not edit below this line __________________ if [ "${PrivateKey}" ]; then     Credentials="-certificate ${CertPath} -privatekey ${PrivateKey}" fi echo cd "`dirname "$0"`" cd "`dirname "$0"`" if [ ! -f AnaplanClient.sh ]; then     echo "Please ensure this script is in the same directory as AnaplanClient.sh." >&2     exit 1 elif [ ! -x AnaplanClient.sh ]; then     echo "Please ensure you have executable permissions on AnaplanClient.sh." >&2     exit 1 fi Command="./AnaplanClient.sh ${Credentials} ${Operation}" /bin/echo "${Command}" exec /bin/sh -c "${Command}"  Using a Java Keystore (JKS) Anaplan Connect Windows BAT Script Example (Using a Java Keystore) @echo off rem This example lists files in a model set Keystore="C:\YourKeyStore.jks" set KeystoreAlias="alias1" set KeystorePassword="mypassword" set WorkspaceId="Enter WS ID Here" set ModelId="Enter Model ID here" set Operation=-service "https://api.anaplan.com" -auth "https://auth.anaplan.com" -workspace %WorkspaceId% -model %ModelId% -F set Credentials=-k %Keystore% -ka %KeystoreAlias% -kp %KeystorePassword% rem *** End of settings - Do not edit below this line *** setlocal enableextensions enabledelayedexpansion || exit /b 1 cd %~dp0 set Command=.\AnaplanClient.bat %Credentials% %Operation% @echo %Command% cmd /c %Command% pause Anaplan Connect Shell Script Example (Using a Java Keystore) #!/bin/sh #This example lists files in a model KeyStorePath="/path/YourKeyStore.jks" KeyStoreAlias="alias1" KeyStorePass="mypassword" WorkspaceId="Enter WS ID Here" ModelId="Enter Model Id Here" Operation="-service 'https://api.anaplan.com' -auth 'https://auth.anaplan.com' -workspace ${WorkspaceId} -model ${ModelId} -F" #________________ Do not edit below this line __________________ if [ "${KeyStorePath}" ]; then     Credentials="-keystore ${KeyStorePath} -keystorepass ${KeyStorePass} -keystorealias ${KeyStoreAlias}" fi echo cd "`dirname "$0"`" cd "`dirname "$0"`" if [ ! -f AnaplanClient.sh ]; then     echo "Please ensure this script is in the same directory as AnaplanClient.sh." >&2     exit 1 elif [ ! -x AnaplanClient.sh ]; then     echo "Please ensure you have executable permissions on AnaplanClient.sh." >&2     exit 1 fi Command="./AnaplanClient.sh ${Credentials} ${Operation}" /bin/echo "${Command}" exec /bin/sh -c "${Command}"   
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Note: While all of these scripts have been tested and found to be fully functional, due to the vast amount of potential use cases, Anaplan does not explicitly support custom scripts built by our customers. This article is for information only and does not suggest any future product direction. Getting Started Python 3 offers many options for interacting with an API. This article will explain how you can use Python 3 to automate many of the requests that are available in our apiary, which can be found at   https://anaplan.docs.apiary.io/#. This article assumes you have the requests (version 2.18.4), base64, and JSON modules installed, as well as the Python 3 version 3.6.4. Please make sure you are installing these modules with Python 3, and not for an older version of Python. For more information on these modules, please see their respective websites: Python   (If you are using a Python version older or newer than 3.6.4, or requests version older or newer than 2.18.4, we cannot guarantee the validity of the article.)   Requests   Base Converter   JSON   (Note: Install instructions are not at this site but will be the same as any other Python module.) Note:   Please read the comments at the top of every script before use, as they more thoroughly detail the assumptions that each script makes. Authentication To start, let's talk about Authentication. Every script run that connects to our API will be required to supply valid authentication. There are two ways to authenticate a Python script that I will be covering. Certificate Authentication Basic Encoded Authentication Certificate authentication will require that you have a valid Anaplan certificate, which you can read more about   here. Once you have your certificate saved locally, to properly convert your Anaplan certificate to be usable with the API, first you will need   OpenSSL. Once you have that, you will need to convert the certificate to PEM format by running the following code in your terminal: openssl x509 -inform der -in certificate-(certnumber).cer -out certtest.pem If you are using Certificate Authorization, the scripts we use in this article will assume you know the Anaplan account email associated with the certificate. If you do not know it, you can extract the common name (CN) from the PEM file by running the following code in your terminal: openssl x509 -text -in certtest.pem To be used with the API, the PEM certificate string will need to be converted to base64, but the scripts we will be covering will take care of that for you, so I won't cover that in this section. To use basic authentication, you will need to know the Anaplan account email that is being used, as well as the password. All scripts in this article will have the following code near the top: # Insert the Anaplan account email being used username = '' ----------------- # If using cert auth, replace cert.pem with your pem converted certificate # filename. Otherwise, remove this line. cert = open('cert.pem').read() # If using basic auth, insert your password. Otherwise, remove this line. password = '' # Uncomment your authentication method (cert or basic). Remove the other. user = 'AnaplanCertificate ' + str(base64.b64encode(( f'{username}:{cert}').encode('utf-8')).decode('utf-8')) # user = 'Basic ' + str(base64.b64encode((f'{username}:{password}' # ).encode('utf-8')).decode('utf-8') Regardless of the authentication method, you will need to set the username variable to the Anaplan account email being used. If you are using a certificate to authenticate, you will need to have your PEM converted certificate in the same folder or a child folder of the one you are running the scripts from. If your certificate is in a child folder, please remember to include the file path when replacing cert.pem (e.g. cert/cert.pem). You can remove the password line and its comments, and its respective user variable. If you are using basic authentication, you will need to set the password variable to your Anaplan account password, and you can remove the cert line, its comments, and its respective user variable. Getting the Information Needed for Each Script Most of the scripts covered in this article will require you to know an ID or metadata for the file, action, etc., that you are trying to process. Each script that gets this information for their respective fields is titled get_____.py. For example, if you want to get your file's metadata, you'll run getFiles.py, which will write the file metadata for each file in the selected model, in the selected workspace, in an array to a JSON file titled files.json. You can then open the JSON file, find the file you need to reference, and use the metadata from that entry in your other scripts. TIP:   If you open the raw data tab of the JSON file it makes it much easier to copy the whole set of metadata. The following are the links to download each get____.py script. Each get script uses the requests.get method to send a get request to the proper API endpoint. getWorkspaces.py: Writes an array to workspaces.json of all the workspaces the user has access to. getModels.py: Writes an array to models.json of either all the models a user has access to if wGuid is left blank or all of the models the user has access to in a selected workspace if a workspace ID was inserted. getModelInfo.py: Writes an array to modelInfo.json of all metadata associated with the selected model. getFiles.py: Writes an array to files.json of all metadata for each file the user has access to in the selected model and workspace. (Please refer to   the Apiary   for more information on private vs default files. Generally, it is recommended that all scripts be run via the same user account.) getChunkData.py: Writes an array to chunkData.json of all metadata for each chunk of the selected file in the selected model and workspace. getImports.py: Writes an array to imports.json of all metadata for each import in the selected model and workspace. getExports.py: Writes an array to exports.json of all metadata for each export in the selected model and workspace. getActions.py: Writes an array to actions.json of all metadata for all actions in the selected model and workspace. getProcesses.py: Writes an array to processes.json of all metadata for all processes in the selected model and workspace. Uploads A file can be uploaded to the Anaplan API endpoint either in chunks or as a single chunk. Per our apiary: We recommend that you upload files in several chunks. This enables you to resume an upload that fails before the final chunk is uploaded. In addition, you can compress files on the upload action. We recommend compressing single chunks that are larger than 50MB. This creates a Private File. Note: To upload a file using the API that file must exist in Anaplan. If the file has not been previously uploaded, you must upload it initially using the Anaplan user interface. You can then carry out subsequent uploads of that file using the API. Multiple Chunk Uploads The script we have for reference is built so that if the script is interrupted for any reason, or if any particular chunk of a file fails to upload, simply rerunning the script will start uploading the file again, starting at the last successful chunk. For this to work, the file must be initially split using a standard naming convention, using the terminal script below. split -b [numberofBytes] [path and filename] [prefix for output files] You can store the file in any location as long as you the proper file path when setting the chunkFilePrefix (e.g. chunkFilePrefix = ''upload_chunks/chunk-" This will look for file chunks named chunk-aa, chunk-ab, chunk-ac etc., up to chunk-zz in the folder script_origin/upload_chunks/. It is very unlikely that you will ever exceed chunk-zz). This will let the script know where to look for the chunks of the file to upload. You can download the script for running a multiple chunk upload from this link: chunkUpload.py. Note:   The assumed naming conventions will only be standard if using Terminal, and they do not necessarily work if the file was split using another method in Windows. If you are using Windows you will need to either create a way to standardize the naming of the chunks alphabetically {chunkFilePrefix}(aa - zz) or run the script as detailed in the   Apiary. Note:   The chunkUpload.py script keeps track of the last successful chunk by writing the name of the last successful chunk to a .txt file chunkStop.txt. This file is deleted once the import completes successfully. If the file is modified in between runs of the script, the script may not function correctly. Best practice is to leave the file alone and delete it if you want to start the upload from the first chunk. Single Chunk Upload The single chunk upload should only be used if the file is small enough to upload in a reasonable time frame. If the upload fails, it will have to start again from the beginning. If your file has a different name then that of its version of the server, you will need to modify line 31 ("name" : '') to reflect the name of the local file. This script runs a single put request to the API endpoint to upload the file. You can download the script for running a single chunk upload from this link: singleChunkUpload.py Imports The import.py script sends a post request to the API endpoint for the selected import. You will need to set the importData value to the metadata for the import. See Getting the Information Needed for Each Script for more information. You can download the script for running an import from this link: Import.py. Once the import is finished, the script will write the metadata for the import task in an array to postImport.json, which you can use to verify which task you want to view the status of while running the importStatus.py script. The importStatus.py script will return a list of all tasks associated with the selected importID and their respective list index. If you are wanting to check the status of the last run import, make sure you are checking postImport.json to verify you have the correct taskID. Enter the index for the task and the script will write the task status to an array in file importStatus.json. If the task is still in progress, it will print the task status and progress. If the task finished and a failure dump is available, it will write the failure dump in comma delimited format to importDump.csv which can be used to review the cause of the failure. If the task finished with no failures, you will get a message telling you the import has completed with no failures. You can download the script for importStatus.py from this link: importStatus.py Note:   If you check the status of a task with an old taskID for an import that has been run since you last checked it, the dump will no longer exist and importDump.csv will be overwritten with an HTTP error, and the status of the task will be 410 Gone. Exports The export.py script sends a post request to the API endpoint for the selected export. You will need to set the exportData value to the metadata for the export. See Getting the Information Needed for Each Script for more information. You can download the script for running an export from this link: Export.py Once the export is finished, the script will write the metadata for the export task in an array to postExport.json, which you can use to verify which task you want to view the status of while running the exportStatus.py script. The exportStatus.py script will return a list of all tasks associated with the selected exportID and their respective list index. If you are wanting to check the status of the last run import, make sure you are checking postExport.json to verify you have the correct taskID. Enter the index for the task and the script will write the task status to an array in file exportStatus.json. If the task is still in progress, it will print the task status and progress. It is important to note that no failure dump will be generated if the export fails. You can download the script for exportStatus.py from this link: exportStatus.py Actions The action.py script sends a post request to the API endpoint for the selected action (for use with actions other than imports or exports). You will need to set the actionData value to the metadata for the action. See Getting the Information Needed for Each Script for more information. You can download the script for running an action from this link: actionStatus.py. Processes The process.py script sends a post request to the API endpoint for the selected process. You will need to set the processData value to the metadata for the process. See Getting the Information Needed for Each Script for more information. You can download the script for running a process from this link: Process.py. Once the process is finished, the script will write the metadata for the process task in an array to postProcess.json, which you can use to verify which task you want to view the status of while running the processStatus.py script. The processStatus.py script will return a list of all tasks associated with the selected processID and their respective list index. If you are wanting to check the status of the last run import, make sure you are checking postProcess.json to verify you have the correct taskID. Enter the index for the task and the script will write the task status to an array in file processStatus.json. If the task is still in progress, it will print the task status and progress. If the task finished and a failure dump is available, it will write the failure dump in comma delimited format to processDump.csv which can be used to review the cause of the failure. It is important to note that no failure dump will be generated for the process itself, only if one of the imports in the process failed. If the task finished with no failures, you will get a message telling you the process has completed with no failures. You can download the script for processStatus.py from this link: processStatus.py. Downloading a File Downloading a file from the Anaplan API endpoint will download the file in however many chunks it exists in on the endpoint. It is important to note that you should set the variable fileName to the name it has in the file metadata. First, the downloads individual chunk metadata will be written in an array to downloadChunkData.json for reference. The script will then download the file chunk by chunk and write each chunk to a new local file with the same name as the 'name' listed in the file's metadata. You can download the link for this script from this link: downloadFile.py. Note: If a file already exists in the same folder as your script with the same name as the name value in the file's metadata, the local file will be overwritten with the file being downloaded from the server. Deleting a File You can delete the file contents of any file that the user has access to that exists in the Anaplan server. Note: This only removes private content. Default content and the import data source model object will remain. You can download the link for this script from this link: deleteFile.py. Standalone Requests Code and Their Required Headers In this section, I will list the code for each request detailed above, including the API URL and the headers necessary to complete the call. I will be leaving the content right of Authorization: headers blank. Authorization header values can be either Basic encoded_username: password or AnaplanCertificate encoded_CommonName:PEM_Certificate_String (see   Certificate-Authorization-Using-the-Anaplan-API   for more information on encoded certificates) Note: requests.get will only generate a response body from the server, and no data will be locally saved unless written to a local file. Get Workspaces List requests.get('https://api.anaplan.com/1/3/workspaces/', headers='Authorization':) Get Models List requests.get('https://api.anaplan.com/1/3/models/', headers={'Authorization':}) or requests.get('https://api.anaplan.com/1/3/workspaces/{wGuid}/models', headers={'Authorization':}) Get Model Info requests.get(f'https://api.anaplan.com/1/3/models/{mGuid}', headers={'Authorization':}) Get Files/Imports/Exports/Actions/Processes List The get request for files, imports, exports, actions, or processes is largely the same. Change files to imports, exports, actions, or processes to run each. requests.get('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/files', headers={'Authorization':}) Get Chunk Data requests.get('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/files/{fileID}/chunks', headers={'Authorization':}) Post Chunk Count requests.post('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/files/{fileID}/chunks/{chunkNumber}', headers={'Authorization': , 'Content-type': 'application/json'}, json={fileMetaData}) Upload a Chunk of a File requests.put('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/files/{fileID}/chunks/{chunkNumber}', headers={'Authorization': , 'Content-Type': 'application/octet-stream'}, data={raw contents of local chunk file}) Mark an upload complete requests.put('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/files/{fileID}/complete', headers=={'Authorization': , 'Content-Type': 'application/json'}, json={fileMetaData}) Upload a File in a Single Chunk requests.put('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/files/{fileID}', headers={'Authorization': , 'Content-Type': 'application/octet-stream'}, data={raw contents of local file}) Run an Import/Export/Process The post request for imports, exports, and processes are largely the same. Change imports to exports, actions, or processes to run each. requests.post('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/imports/{Id}/tasks', headers={'Authorization': , 'Content-Type': 'application/json'}, data=json.dumps({'localeName': 'en_US'})) Run an Action requests.post('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/imports/{Id}/tasks', data={'localeName': 'en_US'}, headers={'Authorization': , 'Content-Type': 'application/json'}) Get Task list for an Import/Export/Action/Process The get request for import, export, action and process task lists are largely the same. Change imports to exports, actions, or processes to get each task list. requests.get('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/imports/{importID}/tasks', headers={'Authorization':}) Get Status for an Import/Export/Action/Process Task The get request for import, export, action and process task statuses are largely the same. Change imports to exports, actions, or processes to get each task list. Note: Only imports and processes will ever generate a failure dump. requests.get('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/imports/{ID}/tasks/{taskID}' headers={'Authorization':}) Download a File Note:   You will need to get the chunk metadata for each chunk of a file you want to download. requests.get('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/files/{fileID}/chunks/{chunkID}, headers={'Authorization': ,'Accept': 'application/octet-stream'}) Delete a File Note:   This only removes private content. Default content and the import data source model object will remain. requests.delete('https://api.anaplan.com/1/3/workspaces/{wGuid}/models/{mGuid}/files/{fileID}', headers={'Authorization': , 'Content-type': 'application/json'} Note:  SFDC user administration is not covered in this article, but the same concepts from the scripts provided can be applied to SFDC user administration. For more information on SFDC user administration see the apiary entry for  SFDC user administration .
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Creates the Java KeyStore required for Anaplan Connect 1.4
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