# Importing Business Data

## Importing Bills and Invoices

### General

This functionality creates invoices or bills from a csv import file containing rows of invoice entry data. The import file may contain rows for new and/or existing invoices. If an invoice already exists, &app; adds the imported entries to the invoice (unless the invoice is already posted). If the import file contains posting data for an invoice, then &app; will also attempt to post the invoice. If any row of an invoice contains an error, &app; will ignore all rows of the same invoice.

The field separator in the csv file must be either a comma or a semicolon; field values may be enclosed in double quotes.

For the sake of readability, in this chapter the term invoice by itself is used to refer to both customer invoices and vendor bills.

### The format of the import file

The import file should contain rows of invoice entry data. Any row contains both header and entry fields, but &app; takes the invoice header data from the first row of an invoice ID. For informational purposes, the header data may be repeated for each subsequent row of the same invoice.

There is no information in the file to indicate whether it concerns customer invoice or vendor bill data. Instead, a user option in the import dialog makes that distinction.

Each row should contain the fields listed below, in the same sequence, separated by a comma or a semicolon. The fields are listed here by their technical name, which &app; uses in the preview of the import data.

- id - The invoice ID. If the invoice ID is blank, &app; replaces it with the invoice ID from the previous row. If the invoice ID already exists, &app; will add the entries to the existing invoice (unless it is already posted).

- date_opened - Use the same date format as defined in Preferences. Defaulted to today's date if left blank, or if the date provided is not valid.

- owner_id - Customer or vendor number. Mandatory in the first data row of an invoice. If not provided, all rows of the same invoice will be ignored.

- billingid - Billing ID. Optional

- notes - Invoice notes. Optional.

- date - The date of the entry. Defaulted to date opened if left blank, or if the date provided is not valid.

- desc - Description. Optional

- action - Action. Optional

- account - Account for the entry. Mandatory in each row. If not provided or invalid, all rows of the same invoice will be ignored.

- quantity - Quantity. Defaulted to 1 if left blank.

- price - Price. Mandatory for each row. If not provided, all rows of the same invoice will be ignored.

- disc_type - Type of discount. Optional. Only relevant for invoices, not for bills. Use % or blank for percentage value, anything else for monetary value.

- disc_how - Discount how. Optional. Only relevant for invoices, not for bills. Use > for discount applied after tax, = for discount and tax applied before tax, and <, blank or anything else for discount applied before tax.

- discount - Amount or percentage of discount. Optional. Only relevant for invoices, not for bills

- taxable - Is this entry taxable? Optional. Use Y or X for yes, N or blank for no.

- taxincluded - Is tax included in the item price? Optional. Use Y or X for yes, N or blank for no.

- tax_table - Tax table. Optional. If the tax table provided does not exist, it will be blank in the invoice.

- date_posted - Date posted. Optional. Use the same date format as defined in Preferences. If you provide a date posted for the first row of an invoice, &app; will attempt to also post the invoice (as opposed to only saving or updating it).

- due_date - Due date. Optional. Use the same date format as defined in Preferences. Defaulted to date posted, if left blank. Only relevant in the first row of an invoice, if the invoice is posted.

- account_posted - Post to account, for vendor or customer posting. Only mandatory in the first row of an invoice, if the invoice is posted.

- memo_posted - Memo. Optional. Only relevant in the first row of an invoice, if the invoice is posted.

- accu_splits - Accumulate splits? Optional. Use Y or X for yes, N or blank for no. Only relevant in the first row of an invoice, if the invoice is posted. If you use a spreadsheet program to create the import file, it is advised not to use blank for no, because a final column with only blanks may not be recognized as relevant data when the spreadsheet program creates the csv file.

Note on double quotes

If you use the field separator character within a field, the field value should be enclosed in double quotes. Only for the fields description (desc) and notes, can you also include a double quote within a quoted field value, by doubling the double quote. E.g. `"This field value uses the separator, and a ""quoted"" word"`, would be imported as `This field value uses the separator, and a "quoted" word`.

Example content for two bills; one of 2 entries, and one of 3 entries. The first is saved and posted, the second only saved. Using comma field separator, decimal point and dd/mm/yyyy date format.

    1204;15/12/2018;2001;PO 210220;Special delivery;16/12/2018;Pride and Prejudice;pc;Expenses:Books;1;30.00;;;;X;;A1;17/12/2018;17/1/2019;Liabilities:Accounts Payable;;X
    1204;15/12/2018;2001;PO 210220;Special delivery;16/12/2018;Electronic principles;pc;Expenses:Books;1;50.00;;;;X;;A1;17/12/2018;17/1/2019;Liabilities:Accounts Payable;;X
    1205;15/12/2018;2044;PO 21099;;16/12/2018;Ultimate Guide;pc;Expenses:Books;1;10.01;;;;;;;;;;;
    1205;15/12/2018;2044;PO 21099;;16/12/2018;Dinner & drinks;pc;Expenses:Dining;1;10.01;;;;;;;;;;;
    1205;15/12/2018;2044;PO 21099;;16/12/2018;UG course;pc;Expenses:Education;1;10.01;;;;;;;;;;;

Example content for one customer invoice, with one entry, including tax and discount. Using comma field separator, decimal point and dd/mm/yyyy date format. The the value of the description field contains the separator character.

    20221;16/12/2018;1001;Order 3378;Discount as agreed;4/12/2018;"Accounting part 1, 2";ea;Income:Other Income;1;769.95;%;=;10;X;N;A1;16/12/2018;16/01/2019;Assets:Accounts Receivable;Posted by import;X

### Import your data

To import your invoice data, navigate to File Import Import Bills & Invoices… to open a new import dialog, and provide the necessary information.

- 1. Choose the file to import - Select your import file, or manually type the path and file name.

- 2. Select import type - Select the import type, either Bill or Invoice.

- 3. Select import options - Select your csv format. Use the with quotes options if your file contains fields enclosed in double quotes. These options also match fields not enclosed in quotes; except for the fields for description and notes, fields should not contain the quote character itself. See above. Use one of the other options if your file does not have fields enclosed in quotes; any quote characters in the file will be imported as is.

- 4. Preview - Once you have selected your import file and csv format, &app; shows you a preview of the data. You can verify if your data is listed in the correct columns. If you do not see any rows in the preview, then &app; was not able to match your import data rows to the selected csv format. See below.

- 5. Afterwards - You can choose if &app; should open tabs for the invoices after the import. Either for all invoices, or for the invoices that are saved but not posted, or for none of the invoices. Opening tabs slows down the import process considerably.

- Start the import - If you are satisfied with your selections, hit the OK button to start the import.

If your data file contains invoice IDs that already exist, then &app; will ask you (once per import session) to confirm that you want to update existing invoices. If not confirmed, all rows for existing invoices will be ignored.

Internally, &app; uses so called regular expressions to match the import rows to the data fields. The import option Custom regular expression offers the option to use your own regular expression for this matching process. Obviously, this option requires that you are well versed in regular expressions. When you choose the option Custom regular expression, &app; opens a window in which you can edit the &app; regular expression, or replace it with your own. Your regular expression should contain a named subpattern for each of the fields of the csv file (using the technical names). A custom regular expression could be useful if the rows of your source data file contain all required fields, but in a different order or format. E.g. if the format of your source data file starts with customer number, followed by invoice ID, followed by the due date, and uses | as separator, your regular expression would start with something like this:

    	^(?<owner_id>[^|]*)\|(?<id>[^|]*)\|(?<due_date>[^|]*)

With a custom regular expression, &app; could import your source data files, without the need to convert them to the &app; import format.

### Feedback and statistics

&app; executes the import process in three steps:

- Import - Imports the data file and attempts to match each row to the data fields.

- Validation and adjustment - Validates the data fields and replaces data with defaults if applicable.

- Processing - Handles the currency related validations, and creates, updates and posts the invoices.

After all steps have finished, &app; issues information about the result of the process. The initial dialog shows the informational or error messages from the validation and processing steps. The second dialog shows the statistics of the process:

- Import - rows ignored: the number of rows that could not be matched to the data fields.

- Import - rows imported: the number of rows that were successfully matched to the data fields.

- Processing and validation - rows fixed: the number of rows for which a default value was used for a field.

- Processing and validation - rows ignored: the number of rows for that were not processed because of a validation error.

- Processing and validation - invoices created: the number of invoices created.

- Processing and validation - invoices updated: the number of invoices that were updated.

If there were unmatched rows in the import step, a final dialog shows the actual rows that could not be matched.

### What could go wrong?

#### Errors in the import step

If the statistics show unmatched rows under Import - rows ignored, then there is some issue with the format of your import file. Verify that you use and select the correct separator. Verify that your data rows have exactly 21 separator characters (1 for each field, except for the last). Verify whether you use the separator character within a data field; if so, enclose the field in double quotes.

If you use one of the with quotes import options, verify if you use the double quote character in any of the data field values; if within the description or notes fields, make sure that the field value is quoted, and precede each double quote within the field with an extra double quote; if within any other field, remove the double quote character.

#### Errors in the validation step

The following errors can occur in the validation step. Any error in a data row will cause all rows of the same invoice to be ignored.

In versions 3.4 and earlier, an error in a data row would cause just that row to be ignored, as opposed all rows of the same invoice.

- The field ID is blank. &app; replaces a blank invoice ID with the invoice ID from the previous row. But the first row of the import file should always have an invoice ID.

- The field owner_id is blank. Every first row of an invoice should have an owner_id.

- The customer or vendor number in field owner_id does not exist. The owner_id in the first row of an invoice should be an existing customer (for invoices) or vendor (for bills).

- The date in field date_posted is not a valid date. If you provide a value for date_posted in the first row of an invoice, it should be a valid date. Did you use the date format as set in Preferences?

- The account in the field account_posted does not exist. If you provide a value for the field date_posted in the first row of an invoice, the field account_posted should be an existing account.

- The account in the field account_posted is not of type Accounts Receivable (for invoices) or Accounts Payable (for bills). If you provide a value for the field date_posted in the first row of an invoice, the field account_posted should be an account of the correct type.

- The field price is blank. Every row should have a value for the field price.

- The account in the field account does not exist. Every row should have an existing account in the field account.

Any error in the validation step is listed after the overall import process completes. Correct your data file accordingly.

#### Errors in the processing step

The following errors can occur in the processing step.

- The invoice cannot be updated because it is already posted. All rows of the same invoice will be ignored. If you want to update the existing invoice, unpost it first in &app;.

- The currency of the invoice differs from the currency of the account posted (Invoice x NOT posted because currencies don't match). &app; determines the currency of the invoice either from the customer or vendor master data (for a new invoice) or from the invoice itself (for an existing invoice). The currency of the invoice must agree with the currency of the post to account in the field account_posted. &app; creates the invoice but cannot post it. Manually correct the invoice in &app;.

- The invoice requires currency conversion. (Invoice x NOT posted because it requires currency conversion). The invoice contains entries on accounts with different currencies, or the currency of the entries differs from the currency of the post to account. For such an invoice, &app; needs exchange rates to translate the currency amounts. &app; creates the invoice but cannot post it. Post the invoice manually in &app;, and provide the requested exchange rates.

### Not supported invoice functionality

Currently the invoice import function does not support (at least) the following:

- Import of billing terms and job.

- Import of customer and job in default chargeback project for bills.

- Application of billing terms from customer or vendor master data.

- Automatic numbering of invoices.

- Credit notes.

## Importing Customers and Vendors

### General

This functionality creates and updates customers and vendors from a csv import file containing rows of vendor/customer master data. The import file may contain rows for new and/or existing customers/vendors. If a customer/vendor already exists, &app; updates the existing customer/vendor.

### The format of the import file

The import file should contain rows of customer/vendor data, one row for each customer/vendor. The customer/vendor is identified by the customer/vendor number in the field id of the data rows. If the field is blank, &app; will use the next number from the relevant counter (set in the Counters tab under File Properties ).

There is no data in the file to indicate whether it concerns customer or vendor master data. Instead, a user option in the import dialog makes that distinction.

Each row should contain the fields listed below, in the same sequence, separated by a comma or a semicolon. The fields are listed here by their technical name, which &app; uses in the preview of the import data.

- id - The customer/vendor number. If it is for an existing customer/vendor, &app; will update the customer/vendor. Note that in &app; e.g. '000010' is a different customer number than '10'. If the id field is empty, &app; will use the next number from the relevant counter.

- company - The company name. If it is left blank, it is defaulted to the value of field name. If that is also blank, then the row is ignored.

- name - Billing address - Name. Optional.

- addr1 - Billing address - Address line 1. At least one of the four address lines of the billing address must be filled. If not, then the row is ignored.

- addr2 - Billing address - Address line 2.

- addr3 - Billing address - Address line 3.

- addr4 - Billing address - Address line 4.

- phone - Billing address - Phone. Optional

- fax - Billing address - Fax. Optional

- email - Billing address - Email. Optional

- notes - Notes. Optional

- shipname - Shipping information - Name. Optional. Not relevant for vendors.

- shipaddr1 - Shipping information - Address line 1. Optional. Not relevant for vendors.

- shipaddr2 - Shipping information - Address line 2. Optional. Not relevant for vendors.

- shipaddr3 - Shipping information - Address line 3. Optional. Not relevant for vendors.

- shipaddr4 - Shipping information - Address line 4. Optional. Not relevant for vendors.

- shipphone - Shipping information - Phone. Optional. Not relevant for vendors.

- shipfax - Shipping information - Fax. Optional. Not relevant for vendors.

- shipmail - Shipping information - Email. Optional. Not relevant for vendors.

Example content for a customer with a separate shipping address. Using a semicolon for separator.

`2201;All Star Company;All Star Company;Union Avenue 776;San Juan;CA;;0482938838;;contact@allstar.com;Last contacted on 4/4/2018.;All Star Company; John Alderman, Office 456;Union Avenue 777;San Juan;CA;78998766;;alderman@allstar.com`

Example content for a vendor; no ID given, so &app; will take the next number from the counter. Using a comma for separator.

`,Johnson Supplies,Johnson Supplies,Electric Park 56,Plains,VA,,0482986538,,jack@johnson.com,Discount negotiated,,,,,,,,`

All fields by technical name in the required sequence.

`id, company, name, addr1, addr2, addr3, addr4, phone, fax, email, notes, shipname, shipaddr1, shipaddr2, shipaddr3, shipaddr4, shiphone, shipfax, shipmail`

### Import your data

To import your customer or vendor data, navigate to File Import Import Customes & Vendors… to open a new import dialog, and provide the necessary information.

- 1. Choose the file to import - Select your import file, or manually type the path and file name.

- 2. Select import type - Select the import type, either Customer or Vendor.

- 3. Select import options - Select your csv format. Use the with quotes options if your file contains fields enclosed in double quotes. These options also match fields not enclosed in double quotes, but fields should not contain the double quote character itself. Use one of the other options if your file does not have fields enclosed in quotes; any double quote characters in the file will then be imported as is.

- 4. Preview - Once you have selected your import file and csv format, &app; shows you a preview of the data. You can verify if your data is listed in the correct columns. If you do not see any rows in the preview, then &app; was not able to match your import data rows to the selected csv format. See below.

- Start the import - If you are satisfied with your selections, hit the OK button to start the import.

Internally, &app; uses so called regular expressions to match the import rows to the data fields. The import option Custom regular expression offers the option to use your own regular expression for this matching process. Obviously, this option requires that you are well versed in regular expressions. When you choose the option Custom regular expression, &app; opens a window in which you can edit the &app; regular expression, or replace it with your own. Your regular expression should contain a named subpattern for each of the fields of the csv file (using the technical names). A custom regular expression could be useful if the rows of your source data file contain all necessary fields, but in a different order or format. E.g. if the format of your source data file starts with customer number, followed by company name, name, and one address field, and that is all you want to import, then your custom regular expression would be something like this (using comma as a separator):

    ^(?<company>[^,]*),(?<id>[^,]*),(?<name>[^,]*),(?<addr1>[^,]*),(?<addr2>[^,]*),(?<addr3>[^,]*)$

With a custom regular expression, &app; could import your source data files, without the need to convert them to the &app; import format.

### Feedback and statistics

&app; executes the import process in three steps:

- Import - Imports the data file and attempts to match each row to the data fields.

- Validation and adjustment - Validates the data fields and replaces data with defaults if applicable.

- Processing - Creates or updates the vendor or customer master data.

After all steps have finished, &app; issues information about the result of the process. The initial dialog shows the statistics of the process:

- Import results - lines ignored: the number of rows that could not be matched to the data fields.

- Import results - lines imported: the number of rows that were successfully matched to the data fields.

- Import results - customers/vendors fixed: the number of rows for which a default value was used for a field.

- Import results - customers/vendors ignored: the number of rows for that were not processed because of a validation error.

- Import results - customers/vendors created: the number of customers/vendors created.

- Import results - customers/vendors updated: the number of customers/vendors that were updated.

If there were unmatched rows in the import step, a final dialog shows the actual rows that could not be matched.

### What could go wrong?

#### Errors in the import step

If the statistics show unmatched rows under Import results - lines ignored, then there is some issue with the format of your import file. Verify that you use and select the correct separator. Verify that your data rows have exactly 18 separator characters (1 for each field, except for the last). Verify whether you use the separator character within a data field; if so, enclose the field in double quotes.

If you use one of the with quotes import options, verify if you use the double quote character in any of the data field values. If so, remove them; importing double quotes as is, is not supported when using the with quotes import options.

#### Errors in the validation step

If the statistics show rows under Import results - customers/vendors ignored, then data rows were ignored because of one of the errors below:

- The field company and the field name are both blank. The field company is mandatory; if it is blank, then it is defaulted to the value of the field name, but if both are blank, then the data row cannot be processed.

- The fields addr1, addr2, addr3 and addr4 are all blank. At least one of these fields must have a value, otherwise the data row cannot be processed.

### Not supported customer/vendor functionality

Currently the customer/vendor import function does not support (at least) the following:

- Import of any of the fields in the customer tab for billing information: currency, terms, discount, credit limit, tax included and tax table.

- Import of any of the fields in the vendor tab for payment information: currency, terms, tax included and tax table.