# Custom Logger Function in spaCy v3.8.14

**URL:** <https://support.prodi.gy/t/custom-logger-function-in-spacy-v3-8-14/7664>\
**Category:** Uncategorized\
**Tags:** usage, ner, spacy\
**Created:** [April 30, 2026, 7:07pm UTC](https://support.prodi.gy/t/custom-logger-function-in-spacy-v3-8-14/7664 "2026-04-30T19:07:27Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![dave-espinosa](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/dave-espinosa/32/2628_2.png) [@dave-espinosa](https://support.prodi.gy/u/dave-espinosa)\
**Post date:** [April 30, 2026, 7:07pm UTC](https://support.prodi.gy/t/custom-logger-function-in-spacy-v3-8-14/7664/1 "2026-04-30T19:07:27Z")

</div>

Hello,

I am updating a custom NER model, from v3.6.1 to v3.8.14 (current one at present day). I am reusing some samples originally labeled with Prodigy.

To do so, I am using a previously built GCP Pipeline (former Vertex AI Pipeline), which at some point, requires me to create a custom logger. My current version looks like:

```python
@spacy.registry.loggers("spacy_history_logger.v1")
def custom_logger(log_path):
    def setup_logger(
        nlp: Language,
        stdout: IO=sys.stdout,
        stderr: IO=sys.stderr
    ) -> Tuple[Callable, Callable]:
        stdout.write(f"Logging to {log_path}\n")
        log_file = Path(log_path).open("w", encoding="utf8")
        
        def log_step(info: Optional[Dict[str, Any]]):
            if info:

                to_write = {
                    'epoch': info['epoch'],
                    'step': info['step'],
                    'score': info['score'],
                    'loss_ner': info['losses']['ner'],
                    'f1_score': info['other_scores']['ents_f']
                }
                
                log_file.write(json.dumps(to_write))
                log_file.write("\n")

        def finalize():
            log_file.close()

        return log_step, finalize

    return setup_logger

```

Now, the last time I used this (about 2 years ago) this pipeline worked fine, but nowadays, it is giving me an error at the 'to\_write' values:

```plain_text
TypeError: Object of type float32 is not JSON serializable
File "/logger.py", line 30, in log_step
    log_file.write(json.dumps(to_write))

```

Hence, I have a really simple, but determining question: why this pipeline works fine with spacy v3.6.1 but fails with v3.8.14? What changed regarding loggers?

Thank you

---

<div class="post-metadata">

**Author:** ![magdaaniol](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/magdaaniol/32/2787_2.png) [@magdaaniol](https://support.prodi.gy/u/magdaaniol)\
**Post date:** [May 5, 2026, 12:04pm UTC](https://support.prodi.gy/t/custom-logger-function-in-spacy-v3-8-14/7664/2 "2026-05-05T12:04:44Z")

</div>

Hi @dave-espinosa,

apologies for the delay!  
Nothing about the logger registry/contract changed — what changed is the type of the values you're reading out of the info dict.

In your dict:

- `info["losses"]["ner"]` — comes from the trainable pipe's `update()`, which assigns from `numpy`/`Thinc` ops (e.g. `losses[self.name] += loss` in [spacy/pipeline/transition\_parser.pyx:524](https://github.com/explosion/spaCy/blob/0069cf99b60023363ba5f47404819f59c8a39b3e/spacy/pipeline/transition_parser.pyx#L524)). Across v3.7→v3.8 (Thinc / Cython 3.0 migration in support of Python3.13), these values are now propagated as `numpy.float32` rather than being implicitly unwrapped to Python float.
- `info["other_scores"]["ents_f"]` — comes from `Scorer.score_spans` and is now likewise a `numpy` scalar.

In v3.6.1 you usually got native Python floats back (Cython 0.29 / older Thinc), so `json.dumps` just worked. In v3.8.x they're `np.float32`, and the stdlib json encoder doesn't know how to serialize `numpy` scalars, hence `TypeError: Object of type float32 is not JSON serializable`.

If you look at the built-in `console_logger_v3` at [spacy/training/loggers.py:116-161](https://github.com/explosion/spaCy/blob/0069cf99b60023363ba5f47404819f59c8a39b3e/spacy/training/loggers.py#L116-L161), it explicitly casts every value: `float(info["losses"][pipe_name])`, `float(score)`, `float(info["score"])`.

A minimal patch to your logger would be then:

```python
  def log_step(info):
      if info:
          to_write = {
              "epoch": info["epoch"],
              "step": info["step"],
              "score": float(info["score"]),
              "loss_ner": float(info["losses"]["ner"]),
              "f1_score": float(info["other_scores"]["ents_f"]),
          }
          log_file.write(json.dumps(to_write))
          log_file.write("\n")

```

It will keep working regardless of whether spaCy hands you Python floats or numpy scalars in future versions.

---

<div class="post-metadata">

**Author:** ![dave-espinosa](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/dave-espinosa/32/2628_2.png) [@dave-espinosa](https://support.prodi.gy/u/dave-espinosa)\
**Post date:** [May 7, 2026, 9:38pm UTC](https://support.prodi.gy/t/custom-logger-function-in-spacy-v3-8-14/7664/3 "2026-05-07T21:38:00Z")

</div>

Hello @magdaaniol ,

I got to the same conclusion, thank you for confirming it. That worked. Before receiving your reply, I also added:

```python
"epoch": int(info["epoch"]),
"step": int(info["step"]),

```

As additional safety measure.

BR,

Dave