Bulk importing is the fastest way to get your organization up and running in Prospero, so everyone can start working from a complete, familiar schedule right away. It's also a great way to quickly upload complex patterns of events that occur regularly within your production schedule.

Supported Formats

To ensure a successful import, your event data must be correctly formatted. Bulk import currently supports one file format:

CSV (comma-separated values)

CSVs are easy to generate with most spreadsheet programs:

Google Sheets - File > Download > Comma Separated Values (.csv)
Excel - File > Save As > Save as type > CSV (Comma delimited)
Numbers - File > Export To > CSV…

Supported Data Types

People
Events
Items

Other data types (like Projects, Locations, and Consumables) must currently be manually entered in-app. If you need support for another data type, let us know at support@prosperoapp.com.

❗️Only Events can be bulk imported by users. Bulk people and items data imports are currently handled directly by the Prospero team. Only data that has been properly formatted can be imported. Please reach out to us at support@prosperoapp.com with your request or questions about formatting. We are working on bringing this functionality into the app for all resources.

Schemas

Your data must conform to Prospero’s schema to be properly processed. Schemas for supported data types are described below, along with an example CSV file that you can open in your preferred spreadsheet program.

✅ Required fields must be present in a row for that row to be imported. Optional fields may be left blank.

Import Events

To ensure a successful import, your event data must be correctly formatted. Any event-linked resources (locations, people, items, projects, etc.) must already exist in Prospero in order for the data to be imported. Names do not need to match exactly, but they must be close enough for Prospero to recognize and suggest the correct resource. If a resource cannot be matched, it will appear as “not found” during the import process and must be fixed before importing.

The Event schema contains the following fields:

	Required fields	Usage
title	✅
start_date	✅	`year-month-day` i.e., 2025-06-14
start_time	⚠️	`hour:minute` i.e., 7:30 or 14:00 NOTE: If `start_time` and `end_time` are blank, this will be an all-day Event. `start_time` and `end_time` must be either both populated or both blank.
end_date	⚠️	`year-month-day` i.e., 2025-06-14 NOTE: If `end_date` is blank, the `end_date` will be the `start_date`
end_time	⚠️	`hour:minute` i.e., 7:30 or 14:00 NOTE: If `end_time` and `start_time` are blank, this will be an all-day event. `end_time` and `start_time` must be either both populated or both blank.
status	✅	One of: -Tentative -Confirmed -Canceled
flag		Leave this field blank to keep `flag` off. Use the number 1 to add a flag to this Event
draft		Leave this field blank to keep `draft` off. Use the number 1 to mark this Event as a draft
projects		Project names separated by semicolons i.e., Footloose;The Tempest
role_groups		Role Group names separated by semicolons i.e., Creative Team;Cast NOTE: Including a Role Group name will automatically add all Roles in that Role Group to the Event, as well as the People associated with those Roles
roles		Role names separated by semicolons i.e., Director;Music Director NOTE: Including a Role name will automatically add the Person associated with that Role to the Event, if there is an associated Person
locations		Location names separated by semicolons i.e., Studio A;Mainstage
groups		Group names separated by semicolons i.e., Admin;Cast NOTE: Including a Group name will automatically add all People in that Group to the Event
people		Person first and last names or emails separated by semicolons i.e., seymour@prosperotheatre.com;ellie@prosperotheatre.com
collections		Collection names separated by semicolons i.e., Rehearsal Set;Footloose Props NOTE: Including a Collection name will automatically add all Items in that Collection to the Event
items		name:quantity separated by semicolons (quantity is optional) i.e., Rehearsal Blocks:4;Band Uniform NOTE: If quantity is not included, all Items in that set will be added to the Event
consumables		name:quantity separated by semicolons (quantity is required) i.e., Coffee:5;Sandwiches:5
tags		Tag names separated by semicolons i.e., Press;Rehearsal
details

Events Import Example CSV

💡 AI tools like Claude (claude.ai) or ChatGPT (chatgpt.com) can dramatically speed up the formatting process. Simply paste or upload your data in the form of a rough table, a copied spreadsheet, or even plain text, along with Prospero's schema requirements, and ask the AI to reformat it into a properly structured CSV. Always review the AI's output before uploading, but for large or complex schedules, it can save significant time compared to manual reformatting.

💡 Here is an example of a prompt you can use with your preferred AI model:

I need to format event data for import into a scheduling app called Prospero. Please reformat my data as a CSV that matches the following schema exactly:

Required fields:

title — event name
start_date — formatted as YYYY-MM-DD (e.g. 2025-06-14)
status — must be exactly one of: Tentative, Confirmed, or Canceled

Optional fields:

start_time — formatted as H:MM or HH:MM (e.g. 7:30 or 14:00). If blank, event will be treated as all-day. Must be populated if end_time is populated.
end_date — formatted as YYYY-MM-DD. If blank, defaults to start_date.
end_time — formatted as H:MM or HH:MM. Must be populated if start_time is populated.
flag — leave blank or use 1
draft — leave blank or use 1
projects — project names separated by semicolons (e.g. Footloose;The Tempest)
role_groups — role group names separated by semicolons
roles — role names separated by semicolons
locations — location names separated by semicolons
groups — group names separated by semicolons
people — email addresses separated by semicolons
collections — collection names separated by semicolons
items — name:quantity separated by semicolons (e.g. Rehearsal Blocks:4). Quantity is optional.
consumables — name:quantity separated by semicolons (quantity is required)
tags — tag names separated by semicolons
details — any additional notes

Rules:

Every row must have a title, start_date, and status
start_time and end_time must either both be filled in or both be left blank
Do not invent or assume data that isn't present — leave the field blank if unsure
Output only the CSV with no explanation or additional text
Every row must have exactly 19 comma-separated values. Even if a field is empty, its comma placeholder must be present. Count the commas in each row before outputting — there must always be exactly 18 commas per row.

Here is my data: [PASTE YOUR DATA HERE]

Upload your CSV

Once your spreadsheet is ready, navigate to the Bulk Import from the three-dots menu next to Filters. Select the timezone you would like applied to your events, select the CSV file to upload, and click Next.

After uploading, you’ll see a table containing all imported rows, showing which values have been accepted and which need attention. If a field cannot be matched to an existing entity, it will be marked as “not found.” Prospero may suggest a close match based on the name provided, but if it

You can select the correct entity where applicable, or choose to delete the row if the data is not valid. All rows must have accepted values before you can move forward.

Review Imported Events

Once all values are accepted, you can enter Review Mode.

In Review Mode, you can see your imported events as they would appear on the calendar, giving you a clear sense of how the schedule will look once finalized. You can click into individual events and make edits just as you would with any event in Prospero. However, if you find that multiple events need the same change, it’s best to return to your CSV file, make the updates there, and re-upload to avoid repetitive manual edits.

When you’re satisfied with how everything appears in Review Mode, you can proceed with the import. All imported events will be added to your calendar as Draft events, allowing for one final layer of review before they are made visible to others by setting them to public. After importing, you can use bulk editing tools to change multiple events from Draft to Public at once.

People

The People schema contains the following fields:

	Required fields
legal_first_name	✅
legal_last_name	✅
stage_name
nickname
title
email
phone
notes

Once your personnel data is formatted correctly, you can send it to the Prospero team for import.

Note that not all People fields are supported. The following fields can only be edited in-app:

Pronouns
Headshot

We suggest updating these fields in-app after importing your data.

People Import Example CSV

💡 Here is an example of a prompt you can use with your preferred AI model:

I need to format personnel data for import into a scheduling app called Prospero. Please reformat my data as a CSV that matches the following schema exactly:

Required fields:

legal_first_name
legal_last_name

Optional fields:

stage_name
nickname
title — job title or role
email
phone
notes

Rules:

Every row must have a legal_first_name and legal_last_name
Do not invent or assume data that isn't present — leave the field blank if unsure
Do not include fields for pronouns or headshots — these are not supported and must be added in-app later
Output only the CSV with no explanation or additional text
Output the CSV in two steps. First, output the data as a markdown table so the column alignment can be visually verified. Then, immediately below it, output the final CSV. Before writing the CSV, double-check every row against the markdown table to confirm each value appears under the correct column header. There must be exactly 7 commas per data row — no more, no fewer. Do not add trailing commas after the last field.

Here is my data: [PASTE YOUR DATA HERE]

Items

📦 Items vs. Item Sets - In Prospero, items belong to item sets. When importing items via CSV, these fields correspond to item sets:

name
color
details
tags

The quantity field determines the number of child items that are created within the item set. These fields correspond to the child items:

default_location
condition
lifecycle_status

Note that all child items will share the same values for these fields. If you would like to alter a specific item's values, you will need to do so in-app after importing.

The Item schema contains the following fields:

	Required fields	Item Set or Item field	Usage
name	✅	Item Set
color		Item Set	A color hex code without the leading #. Leaving this field blank will result in 000000 (black).
details		Item Set
tags		Item Set	Tag names separated by semicolons i.e., Microphone;Handheld
quantity	✅		Minimum 1
default_location		Item	Location name i.e., Props Closet
condition	✅	Item	One of: -Functional -Needs Repair -Under Repair
lifecycle_status	✅	Item	One of: -In Transit -Owned -Discarded

Once your item data is formatted correctly, you can send it to the Prospero team for import.

Note that not all Item fields are supported. The following fields can only be edited in-app:

Custom ID

We suggest updating these fields in-app after importing your data.

Items Import Example CSV

💡 AI tools like Claude (claude.ai) or ChatGPT (chatgpt.com) can dramatically speed up the formatting process. Simply paste or upload your data in the form of a rough table, a copied spreadsheet, or even plain text, along with Prospero's schema requirements, and ask the AI to reformat it into a properly structured CSV. Always review the AI's output before uploading, but for large or complex schedules, it can save significant time compared to manual reformatting.

💡 Here is an example of a prompt you can use with your preferred AI model:

I need to format inventory data for import into a scheduling app called Prospero. Please reformat my data as a CSV that matches the following schema exactly.

Important context: In Prospero, items are organized into item sets. Each row in the CSV represents one item set. The quantity field determines how many individual items are created within that set. All items in a set will share the same default_location, condition, and lifecycle_status values.

Required fields:

name — the name of the item set
quantity — number of individual items in the set, minimum 1
condition — must be exactly one of: Functional, Needs Repair, or Under Repair
lifecycle_status — must be exactly one of: In Transit, Owned, or Discarded

Optional fields:

color — a hex color code without the leading # (e.g. ff0000 for red). If blank, defaults to black (000000)
details — any additional notes about the item set
tags — tag names separated by semicolons (e.g. Microphone;Handheld)
default_location — location name where items are stored (e.g. Props Closet)

Rules:

Every row must have a name, quantity, condition, and lifecycle_status
Do not include a # before hex color codes
Do not invent or assume data that isn't present — leave the field blank if unsure
Do not include a field for Custom ID — this is not supported and must be added in-app later
Output only the CSV with no explanation or additional text
Output the CSV in two steps. First, output the data as a markdown table so the column alignment can be visually verified. Then, immediately below it, output the final CSV. Before writing the CSV, double-check every row against the markdown table to confirm each value appears under the correct column header. There must be exactly 7 commas per data row — no more, no fewer. Do not add trailing commas after the last field.