### Summary
This PR introduces several integration tests, a mix of manually written
tests and those generated using the `generate-integration-tests` Python
script located in the `scripts` folder.
### Tests Added:
- **Authentication tests**: Validating login, registration, and token
handling.
- **FindMany queries**: Fetching multiple records for all existing
entities that do not require input arguments.
### How the Integration Tests Work:
- A `setupTest` function is called during the Jest test run. This
function initializes a test instance of the application and exposes it
on a dedicated port.
- Since tests are executed in isolated workers, they do not have direct
access to the in-memory app instance. Instead, the tests query the
application through the exposed port.
- A static accessToken is used, this one as a big expiration time so it
will never expire (365 years)
- The queries are executed, and the results are validated against
expected outcomes.
### Current State and Next Steps:
- These tests currently run using the existing development seed data. We
plan to introduce more comprehensive test data using `faker` to improve
coverage.
- At the moment, the only mutation tests implemented are for
authentication. Future updates should include broader mutation testing
for other entities.
---------
Co-authored-by: Charles Bochet <charles@twenty.com>
## Context
We recently enabled the option to bypass SSL certificate authority
validation when establishing a connection to PostgreSQL. Previously, if
this validation failed, the server would revert to unencrypted traffic.
Now, it maintains encryption even if the SSL certificate check fails. In
the process, we overlooked a few DataSource setups, prompting a review
of DataSource creation within our code.
## Current State
Our DataSource initialization is distributed as follows:
- **Database folder**: Contains 'core', 'metadata', and 'raw'
DataSources. The 'core' and 'metadata' DataSources manage migrations and
static resolver calls to the database. The 'raw' DataSource is utilized
in scripts and commands that require handling both aspects.
- **typeorm.service.ts script**: These DataSources facilitate
multi-schema connections.
## Vision for Discussion
- **SystemSchema (formerly core) DataSource**: Manages system schema
migrations and system resolvers/repos. The 'core' schema will be renamed
to 'system' as the Core API will include parts of the system and
workspace schemas.
- **MetadataSchema DataSource**: Handles metadata schema migrations and
metadata API resolvers/repos.
- **(Dynamic) WorkspaceSchema DataSource**: Will be used in the Twenty
ORM to access a specific workspace schema.
We currently do not support cross-schema joins, so maintaining these
DataSources separately should be feasible. Core API resolvers will
select the appropriate DataSource based on the field context.
- **To be discussed**: The potential need for an AdminDataSource (akin
to 'Raw'), which would be used in commands, setup scripts, and the admin
panel to connect to any database schema without loading any model. This
DataSource should be reserved for cases where utilizing metadata,
system, or workspace entities is impractical.
## In This PR
- Ensuring all existing DataSources are compliant with the SSL update.
- Introducing RawDataSource to eliminate the need for declaring new
DataSource() instances in commands.
* fix: memory issue with truncate command
* fix: LINK doesn't have any default value
* fix: Cannot convert LINK to column type.
* fix: handle old column type and add a warn to fix them manually
