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lukasbindreiter merged 1 commit into from
May 22, 2026
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Install posthog integration in docs #113

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5 changes: 5 additions & 0 deletions docs.json
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,11 @@
"interaction": {
"drilldown": false
},
"integrations": {
"posthog": {
"apiKey": "phc_neTVVD8S3p76S25BXYXYf7TadgWK6ri4pg8sLqb4TVhJ"
}
},
"navigation": {
"tabs": [
{
Expand Down
13 changes: 9 additions & 4 deletions guides/workflows/multi-language.mdx
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Expand Up @@ -39,7 +39,12 @@ class ScheduleImageCapture(Task):

def execute(self, context: ExecutionContext) -> None:
# Here you can implement your task logic, submit subtasks, etc.
print(f"Image captured for {self.location} with {self.resolution_m}m resolution and bands {self.spectral_bands}")
context.logger.info(
"Image captured",
location=self.location,
resolution_m=self.resolution_m,
spectral_bands=self.spectral_bands,
)

@staticmethod
def identifier() -> tuple[str, str]:
Expand Down Expand Up @@ -197,10 +202,10 @@ Submit a job to the Go server.
curl http://localhost:8080/submit?lat=40.75&lon=-73.98&resolution=30&bands[]=489.0,560.6,666.5
```

Check the Python runner output, it should print the following line:
Check the Python runner logs for the following entry:

```plaintext Output
Image captured for [40.75, -73.98] with 30m resolution and bands [489, 560.6, 666.5]
```plaintext Logs
Image captured location=[40.75, -73.98] resolution_m=30 spectral_bands=[489, 560.6, 666.5]
```

## Next Steps
Expand Down
14 changes: 7 additions & 7 deletions workflows/caches.mdx
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Expand Up @@ -162,13 +162,13 @@ The following snippet illustrates storing and retrieving data from the cache.
class ConsumerTask(Task):
def execute(self, context: ExecutionContext) -> None:
data = context.job_cache["data"]
print(f"Read {data} from cache")
context.logger.info("Read data from cache", data=data.decode())
```
</CodeGroup>

In this example, data stored under the key `"data"` can be any size that fits the cache backend constraints. Ensure the key remains unique within the job's scope to avoid conflicts.

To test the workflow, you can start a local task runner using the `InMemoryCache` backend. Then, submit a job to execute the `ProducerTask` and observe the output of the `ConsumerTask`.
To test the workflow, you can start a local task runner using the `InMemoryCache` backend. Then, submit a job to execute the `ProducerTask` and inspect the logs emitted by the `ConsumerTask`.

<CodeGroup>
```python Python
Expand All @@ -185,8 +185,8 @@ To test the workflow, you can start a local task runner using the `InMemoryCache
```
</CodeGroup>

```plaintext Output
Read b'my_binary_data_to_store' from cache
```plaintext Logs
Read data from cache data=my_binary_data_to_store
```

## Groups and Hierarchical Keys
Expand Down Expand Up @@ -244,7 +244,7 @@ class PrintSum(Task):
number = group[key] # read data from cache
numbers.append(int(number.decode())) # convert bytes back to int

print(f"Sum of all numbers: {sum(numbers)}")
context.logger.info("Computed sum of all numbers", total=sum(numbers))
```
</CodeGroup>

Expand All @@ -265,6 +265,6 @@ Submitting a job of the `CacheGroupDemo` and running it with a task runner can b
```
</CodeGroup>

```plaintext Output
Sum of all numbers: 284
```plaintext Logs
Computed sum of all numbers total=284
```
40 changes: 26 additions & 14 deletions workflows/concepts/jobs.mdx
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Expand Up @@ -414,10 +414,16 @@ class PrintMovieStats(Task):
def execute(self, context: ExecutionContext) -> None:
params = {"t": self.title, "apikey": "<OMDB API Key>"}
url = "http://www.omdbapi.com/?" + urlencode(params)
response = httpx.get(url).json()
with context.tracer.span("fetch-movie-stats") as span:
span.set_attribute("movie.title", self.title)
response = httpx.get(url).json()
# set the display name of the task to the title of the movie:
context.current_task.display = response["Title"]
print(f"{response['Title']} was released on {response['Released']}")
context.logger.info(
"Movie release date fetched",
title=response["Title"],
released=response["Released"],
)
```
```go Go
package movie
Expand Down Expand Up @@ -521,11 +527,11 @@ job, err := client.Jobs.Submit(ctx, "movies-stats",

One of the `PrintMovieStats` tasks fails with a `KeyError`. This error occurs when a movie title is not found by the [OMDb API](http://www.omdbapi.com/), leading to a response without the `Title` and `Released` fields.

Console output from the task runners confirms this:
Task logs from the runners confirm this:

```plaintext Output
The Matrix was released on 31 Mar 1999
Shrek 2 was released on 19 May 2004
```plaintext Logs
Movie release date fetched title="The Matrix" released="31 Mar 1999"
Movie release date fetched title="Shrek 2" released="19 May 2004"
ERROR: Task PrintMovieStats failed with exception: KeyError('Title')
```

Expand All @@ -539,13 +545,19 @@ class PrintMovieStats(Task):
def execute(self, context: ExecutionContext) -> None:
params = {"t": self.title, "apikey": "<OMDB API Key>"}
url = "http://www.omdbapi.com/?" + urlencode(params)
response = httpx.get(url).json()
with context.tracer.span("fetch-movie-stats") as span:
span.set_attribute("movie.title", self.title)
response = httpx.get(url).json()
if "Title" in response and "Released" in response:
context.current_task.display = response["Title"]
print(f"{response['Title']} was released on {response['Released']}")
context.logger.info(
"Movie release date fetched",
title=response["Title"],
released=response["Released"],
)
else:
context.current_task.display = f"NotFound: {self.title}"
print(f"Could not find the release date for {self.title}")
context.logger.info("Movie release date not found", title=self.title)
```
```go Go
type PrintMovieStats struct {
Expand Down Expand Up @@ -607,15 +619,15 @@ _, err := client.Jobs.Retry(ctx, job.ID)
<img src="/assets/workflows/diagrams/svg/movies-retried.dark.svg" alt="Job retried successfully" className="hidden dark:block" />
</Frame>

Now the console output shows:
Now the task logs show:

```plaintext Output
Could not find the release date for Tilebox - The Movie
The Avengers was released on 04 May 2012
```plaintext Logs
Movie release date not found title="Tilebox - The Movie"
Movie release date fetched title="The Avengers" released="04 May 2012"
```

<Note>
The output confirms that only two tasks were executed, resuming from the point of failure instead of re-executing all tasks.
The logs confirm that only two tasks were executed, resuming from the point of failure instead of re-executing all tasks.
</Note>

The job was retried and succeeded. The two tasks that completed before the failure were not re-executed.
74 changes: 43 additions & 31 deletions workflows/concepts/tasks.mdx
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Expand Up @@ -42,7 +42,7 @@ For python, the key components of this task are:
The `execute` method is the entry point for executing the task. This is where the task's logic is defined. It's invoked by a [task runner](/workflows/concepts/task-runners) when the task runs and performs the task's operation.
</Accordion>
<Accordion title="context: ExecutionContext">
The `context` argument is an `ExecutionContext` instance that provides access to an [API for submitting new tasks](/api-reference/python/tilebox.workflows/ExecutionContext.submit_subtask) as part of the same job and features like [shared caching](/api-reference/python/tilebox.workflows/ExecutionContext.job_cache).
The `context` argument is an `ExecutionContext` instance that provides access to an [API for submitting new tasks](/api-reference/python/tilebox.workflows/ExecutionContext.submit_subtask) as part of the same job, [task logging](/api-reference/python/tilebox.workflows/ExecutionContext.logger), [custom tracing](/api-reference/python/tilebox.workflows/ExecutionContext.tracer), and features like [shared caching](/api-reference/python/tilebox.workflows/ExecutionContext.job_cache).
</Accordion>
</AccordionGroup>

Expand Down Expand Up @@ -129,7 +129,7 @@ class ChildTask(Task):
index: int

def execute(self, context: ExecutionContext) -> None:
print(f"Executing ChildTask {self.index}")
context.logger.info("Executing child task", index=self.index)

# after submitting this task, a task runner may pick it up and execute it
# which will result in 5 ChildTasks being submitted and executed as well
Expand Down Expand Up @@ -425,7 +425,7 @@ class Sum(Task): # The reduce step
for key in squares:
result += int(squares[key].decode())

print("Sum of squares is:", result)
context.logger.info("Computed sum of squares", result=result)
```
</CodeGroup>

Expand All @@ -449,8 +449,8 @@ jobs.display(job)
```
</CodeGroup>

```plaintext Output
Sum of squares is: 336448
```plaintext Logs
Computed sum of squares result=336448
```

<Frame>
Expand Down Expand Up @@ -479,7 +479,7 @@ For example, the `RecursiveTask` below is a valid task that submits smaller inst
num: int

def execute(self, context: ExecutionContext) -> None:
print(f"Executing RecursiveTask with num={self.num}")
context.logger.info("Executing recursive task", num=self.num)
# if num < 2, we reached the base case and stop recursion
if self.num >= 2:
context.submit_subtask(RecursiveTask(self.num // 2))
Expand Down Expand Up @@ -613,7 +613,7 @@ class RootTask(Task):

class FlakyTask(Task):
def execute(self, context: ExecutionContext) -> None:
print(f"Executing FlakyTask")
context.logger.info("Executing flaky task")

if random.random() < 0.1:
raise Exception("FlakyTask failed randomly")
Expand Down Expand Up @@ -683,7 +683,7 @@ class PrintTask(Task):
message: str

def execute(self, context: ExecutionContext) -> None:
print(self.message)
context.logger.info("Print task executed", message=self.message)
```
```go Go
type RootTask struct{}
Expand Down Expand Up @@ -761,23 +761,35 @@ A practical example is a workflow that fetches news articles from an API and pro

def execute(self, context: ExecutionContext) -> None:
url = f"https://newsapi.org/v2/top-headlines?category={self.category}&pageSize={self.max_articles}&country=us&apiKey=API_KEY"
news = httpx.get(url).json()
with context.tracer.span("fetch-news") as span:
span.set_attribute("category", self.category)
span.set_attribute("max_articles", self.max_articles)
news = httpx.get(url).json()
# check out our documentation page on caches to learn
# about a better way of passing data between tasks
Path("news.json").write_text(json.dumps(news))
context.logger.info(
"Fetched news articles",
category=self.category,
article_count=len(news["articles"]),
)

class PrintHeadlines(Task):
def execute(self, context: ExecutionContext) -> None:
news = json.loads(Path("news.json").read_text())
for article in news["articles"]:
print(f"{article['publishedAt'][:10]}: {article['title']}")
context.logger.info(
"News headline",
published_at=article["publishedAt"][:10],
title=article["title"],
)

class MostFrequentAuthors(Task):
def execute(self, context: ExecutionContext) -> None:
news = json.loads(Path("news.json").read_text())
authors = [article["author"] for article in news["articles"]]
for author, count in Counter(authors).most_common():
print(f"Author {author} has written {count} articles")
context.logger.info("Author article count", author=author, count=count)

# now submit a job, and then visualize it
job = job_client.submit("process-news",
Expand Down Expand Up @@ -935,17 +947,17 @@ job, err := client.Jobs.Submit(ctx, "process-news",
```
</CodeGroup>

```plaintext Output
2024-02-15: NASA selects ultraviolet astronomy mission but delays its launch two years - SpaceNews
2024-02-15: SpaceX launches Space Force mission from Cape Canaveral - Orlando Sentinel
2024-02-14: Saturn's largest moon most likely uninhabitable - Phys.org
2024-02-14: AI Unveils Mysteries of Unknown Proteins' Functions - Neuroscience News
2024-02-14: Anthropologists' research unveils early stone plaza in the Andes - Phys.org
Author Jeff Foust has written 1 articles
Author Richard Tribou has written 1 articles
Author Jeff Renaud has written 1 articles
Author Neuroscience News has written 1 articles
Author Science X has written 1 articles
```plaintext Logs
News headline published_at=2024-02-15 title="NASA selects ultraviolet astronomy mission but delays its launch two years - SpaceNews"
News headline published_at=2024-02-15 title="SpaceX launches Space Force mission from Cape Canaveral - Orlando Sentinel"
News headline published_at=2024-02-14 title="Saturn's largest moon most likely uninhabitable - Phys.org"
News headline published_at=2024-02-14 title="AI Unveils Mysteries of Unknown Proteins' Functions - Neuroscience News"
News headline published_at=2024-02-14 title="Anthropologists' research unveils early stone plaza in the Andes - Phys.org"
Author article count author="Jeff Foust" count=1
Author article count author="Richard Tribou" count=1
Author article count author="Jeff Renaud" count=1
Author article count author="Neuroscience News" count=1
Author article count author="Science X" count=1
```

<Frame>
Expand All @@ -963,8 +975,8 @@ This workflow consists of four tasks:
| ------------------- | ------------ | -------------------------------------------------------------------------------------------------------------------------- |
| NewsWorkflow | - | The root task of the workflow. It spawns the other tasks and sets up the dependencies between them. |
| FetchNews | - | A task that fetches news articles from the API and writes the results to a file, which is then read by dependent tasks. |
| PrintHeadlines | FetchNews | A task that prints the headlines of the news articles to the console. |
| MostFrequentAuthors | FetchNews | A task that counts the number of articles each author has written and prints the result to the console. |
| PrintHeadlines | FetchNews | A task that logs the headlines of the news articles. |
| MostFrequentAuthors | FetchNews | A task that counts the number of articles each author has written and logs the result. |

An important aspect is that there is no dependency between the `PrintHeadlines` and `MostFrequentAuthors` tasks. This means they can execute in parallel, which the Tilebox Workflow Orchestrator will do, provided multiple task runners are available.

Expand Down Expand Up @@ -1017,17 +1029,17 @@ class RootTask(Task):
class RequiredTask(Task):
def execute(self, context: ExecutionContext) -> None:
# this task may fail, but the job will continue regardless
print("This task is required to succeed, otherwise the job would stop")
context.logger.info("Required task completed")

class FlakyTask(Task):
def execute(self, context: ExecutionContext) -> None:
# this task may fail, but the job will continue regardless
print("Attempting flaky operation...")
context.logger.info("Attempting flaky operation")

class FinalTask(Task):
def execute(self, context: ExecutionContext) -> None:
# this task runs even if FlakyTask failed
print("Running final step")
context.logger.info("Running final step")
```
```go Go
type RootTask struct{}
Expand Down Expand Up @@ -1111,23 +1123,23 @@ class Step1(Task):

class Step1A(Task):
def execute(self, context: ExecutionContext) -> None:
print("Step1A executed successfully")
context.logger.info("Step1A executed successfully")

class Step1B(Task):
def execute(self, context: ExecutionContext) -> None:
raise ValueError("something went wrong")

class Step1C(Task):
def execute(self, context: ExecutionContext) -> None:
print("This will be skipped because Step1B failed")
context.logger.info("This will be skipped because Step1B failed")

class Step2(Task):
def execute(self, context: ExecutionContext) -> None:
print("This will be skipped because Step1B failed")
context.logger.info("This will be skipped because Step1B failed")

class AlwaysRuns(Task):
def execute(self, context: ExecutionContext) -> None:
print("This runs regardless")
context.logger.info("This runs regardless")
```
```go Go
type Pipeline struct{}
Expand Down
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