invalid type: boolean true, expected i64 at line 1 column 2: what it means and how to fix it
Troubleshoot invalid type: boolean true, expected i64 at line 1 column 2 quickly and validate JSON locally (no upload).
What the error means
invalid type: boolean true, expected i64 at line 1 column 2 usually means the JSON was parsed, but the value at some path does not match the type/schema your code expects (for example: array vs object, number vs string, null vs non-nullable).
Most common real-world causes
- Your code expects a different type (number vs string, bool vs string, object vs array).
- A field is null/missing but your type is non-nullable (or your code assumes it is always present).
- The API response shape changed (or differs by environment / feature flags).
- You are deserializing the wrong endpoint or the response is an error payload with a different schema.
- Date/UUID/IP formats don't match what the deserializer expects.
Fast debugging steps
- Parse into a generic JSON type first (Value/JToken/JsonElement/JsonNode) and inspect the actual shape at the failing path.
- Confirm whether the field is an array vs object and whether scalars are strings vs numbers.
- Add defensive handling for null/missing fields (optional types, defaults, or custom converters).
- Log the raw response (or a redacted sample) and validate it locally to rule out truncation or hidden prefixes.
- Update DTO/types to match the real response shape (or use a more flexible model for unstable fields).
Code example (rust)
use serde_json::Value;
// Parse into Value first to inspect actual types
let v: Value = serde_json::from_str(&text)?;
// Example checks
if let Some(value) = v.get("value") {
println!("{:?}", value);
}
// Then deserialize into a strong type once the schema matches
// let dto: MyDto = serde_json::from_value(v)?;
Fix without uploading data
If the JSON contains sensitive data, validate and fix it locally. No Upload Tools runs 100% in your browser.
- JSON Validator to pinpoint the exact syntax error.
- JSON Repair to remove comments/trailing commas when the source is not strict.
- JSON Formatter to pretty-print and inspect structure.
- JSON String Escape if the issue is inside a string (newlines/tabs/quotes).
Workflow: validate -> fix the first error -> validate again -> export/convert.
FAQ
Does this mean the JSON is invalid? Not necessarily. Many of these errors happen when the JSON is valid, but your code expects a different type/shape.
What is the fastest fix? Parse into a generic JSON type first (Value/JToken/JsonElement/JsonNode), inspect the failing path, then update your DTO/type (or add a converter) to match the real response.