Empfehlung: Back up before editing. Delete only with your IDs, using the command-line and user-specified identifiers to avoid errors. Check the initial size of the glossary to understand impact, and prepare a single csv_data file that lists the target glossaries to remove, then execute the deletion into your environment.
To run deletion, use the command-line flow with deeplclientoptions to authenticate and set the scope. For a single glossary, pass the ID or name and run one deletion; for multiple glossaries, reference the csv_data file and process in one batch. The operation should return erfolgreich status for each item.
After the run, verify by querying the API or UI to confirm the glossary is no longer retrievable. Save a timestamp and a local backup file for audit, then remove the temporary csv_data file if you used one.
With DeepL tooling, you control deletions precisely, keep your glossary list clean, and reduce clutter across projects. If you need automation, set up a small script that reads the csv_data and uses the command-line flow to delete glossaries in multiple passes and log outcomes as erfolgreich entries.
Locate the glossary in the DeepL Admin Console
Open the DeepL Admin Console and sign in with your admin credentials. In the left navigation, click Glossaries, then switch to the project context if needed to filter the list. Here you can see the glossary name, doc_id, and status in a searchable table. This view is also available to ihnen.
- Find the glossary: use the search box or filter by name, doc_id, or language pair to isolate the entry; glossaries you don’t need stay hidden until opened.
- Open details: click the glossary row to view entries, variables, and the history. The view shows replacement_entries and the last update date.
- Edit entries: optionally modify entries manually; add new replacements, adjust pairs, and save changes. The method field indicates how the glossary applies during workflows, including translate_document_upload.
- Validate with tests: run tests to confirm translations align with the glossary in mundo and other languages; after changes, compare results to expected outputs.
- Propagate changes: send updates to the client via the streaming option or direct API calls; clientrephrasetextasynca can stream updates while a document is processed.
- Issue handling: if an issue occurs, re-check doc_id and variable mappings, then rerun tests; if needed, create a replacement pair manually and re-upload using translate_document_upload.
- Tips for maintenance: whether you manage a single glossary or a fleet, keep a clean history and concise replacement_entries to reduce noise and improve lookup times.
Back up glossary data before deletion
Export glossary data to a local archive before deleting any entries. Confirm the backup contains all glossaries, glossary_languages mappings, and the associated license metadata.
Back up both source data and the operational context: the glossary entries, the language pairs, and any accounts used to create or modify glossaries. Store a copy of the original data bundle in a separate location to ease retrieval if needed.
Use python3 and a small tool to serialize glossaries to a portable format. Create a package of files including glossary.json, glossary_languages.json, and license.json. Place the backup in a protected directory and ensure the binary path is accessible via usrlocalbin by adding a symlink if required.
For systems with restricted permissions, run the export with sudo only when necessary to access restricted directories. Then adjust permissions to allow your user to read the files. If you operate behind a proxy, export proxy settings to the environment: export http_proxy and https_proxy, and provide credentials as needed.
Validate the backup by computing a checksum (SHA256) and listing files. Open the archive and verify that each glossary_id appears with its language entries. Keep a record of returns of the export script and the file sizes to confirm completeness.
Recovery plan: keep a record of where the backup is stored, the license terms, and the exact source of the data. In case of deletion, re-import via the same tool or API by pointing to the backup package. Rephrase the data to restore formats and mappings as needed, ensuring glossaries and glossary_languages align with the original source.
| Step | Action | Notes / Example |
|---|---|---|
| 1 | Inventory | List glossaries and glossary_languages; capture IDs and language pairs, e.g., "en-de" and "de-en". |
| 2 | Export | Run a Python3-based package to export: example tool export_glossaries --output /backup/glossaries-backup.json --glossaries all; ensure /backup is writable. |
| 3 | Integrity | Compute SHA256 for the archive; compare against a known good value if available. |
| 4 | Schutz | Move to a secured location; set permissions and, if needed, use sudo to adjust ownership. |
| 5 | Documentation | Record the exact source, including license terms and glossary_languages mappings; note proxy usage and account references. |
Delete the glossary from the Admin Console: step-by-step
Delete the glossary directly from the Admin Console by selecting the glossary and clicking Delete, then confirm in the prompt. This action is supported in all plans and would improve data hygiene for glossaries. Ensure you have your deeplclientauthkey ready and the correct project selected; starting from the Admin Console home, switch into the Glossaries view and locate the exact glossary by name. This change would affect only the chosen glossary and keep other glossaries intact.
In the Glossaries view, reach the specific glossary and open its details. Check its source-target mappings (source-target) and confirm you are deleting the intended object. If the glossary includes phrases like hello, cómo, or お元気ですか, consider exporting or reviewing them before deletion. From here, click Delete and confirm in the dialog. The operation targets the specific glossary and would not impact other glossaries.
After deletion, verify the glossary no longer appears in the glossaries list, and review related objects and view configurations to ensure no orphaned references remain. If you manage multi-platform environments such as xamarinwatchos, confirm the change is reflected across all connected devices. Basic validation: ensure the default behavior of the translation workflow is preserved and that providing a clear note about the removal helps traceability.
To minimize impact on formalitymore and functionality, avoid deleting glossaries that are still in use by translations. Providing a short summary in admin notes helps teams stay aligned. As a best practice, perform a test deletion in a staging environment first to verify results and ensure starting governance aligns with your policy.
Finally, run a final check: search for the glossary name again in the view, and ensure it is gone. If any references persist, remove them from related objects via the API or console. The process is straightforward and keeps the Admin Console well organized, ready for future glossary updates; this approach would be reproducible and reliable.
Delete via API: authentication, endpoint, and payload
Authenticate first, then delete the glossary via the API. Use your API key in the Authorization header as Bearer and avoid exposing credentials without this header. Assign a clear client identity such as deepldeeplclient in User-Agent; for cross-platform apps (xamarintvos, monotouch), ensure HttpClient passes headers correctly. If you manage multilingual glossaries, you can initialize deepl_clientcreate_multilingual_glossary during setup to prepare contexts, but deletion relies only on the glossary_id. Log the outcome to an output_path to simplify debugging here and keep variables for status tracking. The key must be awarded to your account to perform deletion; responses include 200 on success, 404 when the glossary_id is unknown, or 429 for rate limiting. The delete call uses the endpoint below; no payload body is required, and the operation should be attempted through a secure channel. If your client requires a minimal body, send an empty JSON object or a payload that carries glossary_id in the path, not in the body.
Authentifizierung
Use the API key from your DeepL Pro account. Example header: Authorization: Bearer . Include Content-Type: application/json if your library requires it; otherwise, omit. In code, store the key securely and never log it. For computer or mobile builds, keep credentials out of source control and propagate errors clearly. The deepldeeplclient name helps tracing in logs and aligns with british spelling when localizing messages. If you need a more diplomatic tone for user-facing messages, surface clear status without exposing details that could aid misuse.
Endpoint and payload
Endpoint: DELETE https://api-free.deepl.com/v2/glossaries/{glossary_id} (use the region matching your plan). There is no body required for a standard delete; if your library enforces a body, keep it empty or include only glossary_id in the path. Parse the JSON response to confirm removal and update your UI or workflow accordingly. Respond to success by updating the user and writing the final state to output_path; on failure, capture the error code and message, then retry with a backoff strategy. Use variables to manage retry counts and timeouts, and ensure the next step in your pipeline runs through the intended path.
Verify deletion across UI and integrations
Delete the glossary entry by ID via the API, then verify the response flag signals success and the item is removed from the source store (deletes).
In the UI, search using the given languagecode and the named term; confirm the result is empty and the entry no longer appears in the list or detail views.
Across integrations, query downstream services that consume glossary data. Compare the referenced IDs with a comma-separated list; confirm no references remain and the affected field uses the updated value.
Generate an export to validate data flow: use csvstream to pull the current glossary state, write to output_path, and include columns for directory, named, and languagecode. If you export with encodingutf-8-sig, the header encodes correctly; otherwise encodingutf-8 works too. The option to use output_path helps track provenance.
For local tests in a homebrew setup, run the CLI from your homebrew-installed tools and verify via the UI and API; times between runs should be minimal, and you can re-run to confirm propagation across projects.
Optionally capture a final verification report: generate a small JSON or CSV file, with fields named, languagecode, number, status (deleted/exists), and empty if none remain; store under the directory named verification_reports.
For xamarintvos builds, kick off a smoke test after deletion to confirm the change surfaces in the mobile UI and any connected services; if not, re-sync with a background job and re-check after a few times.
Troubleshooting: resolve common deletion errors
Identify the exact error code returned by the deletion attempt and inspect the related operation log. This quick identify step centers on contents and the glossary entries you aim to remove, so you can target the root cause without guesswork.
Verify the glossary configuration: review the configured sources, confirm the list of files, and check that my_csv_glossary uses the expected columns. If contents differ from the schema, deletion can fail.
Enter the deletion request with precise keys: copy the entry id, paste it into the console, and press enter. Verify the target glossary id and ensure you remove the right contents.
Disable conflicting plugins or run in a clean mode to avoid side effects. If you use a plugin to handle deletions, temporarily disable it, then re-run and inspect printentries_responsedictionaries0 for the current state.
Rephrase the request if the server rejects the original syntax: use a safe rephrase of the command, then send the response again and compare the response to the expected outcome. The desired result is a successful delete without errors.
For xamarintvos deployments, verify encoding and request headers. The clientrephrasetextasynca function must handle async calls correctly; test with a small batch to ensure the response matches the expected behavior.
About test data, create a minimal subset in files to validate deletion steps. Use cómo you would remove from my_csv_glossary; start with a small sample, then extend to the full glossary.
Continue the inspection by printing the current entries with printentries_responsedictionaries0, then continue to the actual delete once the result aligns with the desired state.
Document the glossary and response after each attempt, so future troubleshooting can re-use the exact steps.
If issues persist, contact support with a concise report that includes the error code, the glossary id, the number of removed entries, and the sample contents.
