https://github.com/datalpia/laketower
Oversee your lakehouse
https://github.com/datalpia/laketower
apache-iceberg arrow data deltalake duckdb lakehouse sql
Last synced: about 4 hours ago
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Oversee your lakehouse
- Host: GitHub
- URL: https://github.com/datalpia/laketower
- Owner: datalpia
- License: apache-2.0
- Created: 2025-02-04T21:56:23.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2026-06-13T17:10:16.000Z (7 days ago)
- Last Synced: 2026-06-13T17:27:41.814Z (7 days ago)
- Topics: apache-iceberg, arrow, data, deltalake, duckdb, lakehouse, sql
- Language: JavaScript
- Homepage:
- Size: 12.6 MB
- Stars: 12
- Watchers: 1
- Forks: 0
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# 🗼 Laketower
> Oversee your lakehouse
[](https://pypi.org/project/laketower/)
[](https://pypi.org/project/laketower/)
[](https://github.com/datalpia/laketower/actions/workflows/ci-cd.yml)
[](https://github.com/datalpia/laketower/blob/main/LICENSE)
Utility application to explore and manage tables in your data lakehouse, especially tailored for data pipelines local development.
## Features
- Delta Lake table format support
- Remote tables support (S3, ADLS)
- Inspect table metadata
- Inspect table schema
- Inspect table history
- Get table statistics
- Import data into a table from CSV files
- View table content with a simple query builder
- Query all registered tables with DuckDB SQL dialect
- Execute saved queries
- Export query results to CSV files
- Static and versionable YAML configuration
- Web application
- CLI application
## Installation
Using `pip` (or any other Python package manager):
```bash
pip install laketower
```
Using `uvx`:
```bash
uvx laketower
```
## Usage
### Configuration
Laketower configuration is based on a static YAML configuration file allowing to:
- List all tables to be registered
Format:
```yaml
settings:
max_query_rows: 1000
web:
hide_tables: false
storage_credentials:
:
s3: # mutually exclusive with adls
access_key_id:
secret_access_key:
region:
endpoint_url:
allow_http: false
adls: # mutually exclusive with s3
account_name:
access_key:
sas_key:
tenant_id:
client_id:
client_secret:
msi_endpoint:
use_azure_cli: false
tables:
- name:
uri:
format: {delta}
storage_credential: # optional, references storage_credentials
queries:
- name:
title:
description:
totals_row: true
parameters:
:
default:
sql:
```
Current limitations:
- `tables.uri`:
- Local paths are supported (`./path/to/table`, `/abs/path/to/table`, `file:///abs/path/to/table`)
- Remote paths to S3 (`s3:///`) and ADLS (`abfss:///`)
- `tables.format`: only `delta` is allowed
Example from the provided demo:
```yaml
tables:
- name: sample_table
uri: demo/sample_table
format: delta
- name: weather
uri: demo/weather
format: delta
queries:
- name: all_data
title: All data
sql: |
select
sample_table.*,
weather.*
from
sample_table,
weather
limit 10
- name: daily_avg_temperature
title: Daily average temperature
sql: |
select
date_trunc('day', time) as day,
round(avg(temperature_2m)) as avg_temperature
from
weather
group by
day
order by
day asc
```
Support for environment variables substitution is also supported within the YAML
configuration using a object containing a single key `env` with the name of the
environment variable to be injected. The value of the variable can contain JSON
and will be decoded in a best effort manner (default to string value). For instance:
```yaml
# export TABLE_URI=path/to/table
tables:
- name: sample_table
uri:
env: TABLE_URI
format: delta
```
For string values that only need partial substitution, use the `${VAR_NAME}`
inline syntax instead. Multiple variables in a single value are supported:
```yaml
# export BUCKET=my-bucket
# export PREFIX=my-prefix
tables:
- name: sample_table
uri: s3://${BUCKET}/${PREFIX}/sample_table
format: delta
```
The two syntaxes are independent: `{env: VAR}` replaces the entire value (any
type), while `${VAR}` interpolates within a string.
#### Config Includes
Large or multi-environment setups can split the configuration across multiple
YAML files using the `include` directive. Included files are deep-merged before
the main file, so the main file always wins on conflict.
```yaml
# queries.yml (shared across environments)
queries:
- name: all_data
title: All data
sql: "select * from my_table"
```
```yaml
# laketower.production.yml
include:
- queries.yml
storage_credentials:
s3_creds:
s3:
access_key_id: ${AWS_ACCESS_KEY_ID}
secret_access_key: ${AWS_SECRET_ACCESS_KEY}
tables:
- name: my_table
uri: s3://production-bucket/tables/my_table
format: delta
storage_credential: s3_creds
```
Merge semantics:
- **Lists** (`tables`, `queries`, ...): included file items come first, main file items appended
- **Dicts** (`settings`, `storage_credentials`, ...): recursively deep-merged, main file values win on conflict
- **Scalars**: main file wins
Rules:
- `include` paths are relative to the directory of the file declaring them
- Multiple files are merged in order (first listed = lowest priority)
- Environment variable substitution works in included files
- Included files themselves do not support `include` (no recursive includes)
#### Storage Credentials
Storage credentials are defined once under the top-level `storage_credentials`
key as a named registry, then referenced by name from each table via the
`storage_credential` field. This avoids repeating the same credentials across
multiple tables.
##### Remote S3 Tables
Configuring S3 tables (AWS, MinIO, Cloudflare R2, Scaleway Object Storage, …):
```yaml
storage_credentials:
my_s3:
s3:
access_key_id: access-key-id
secret_access_key: secret-access-key
region: s3-region
endpoint_url: http://s3.domain.com
allow_http: false
tables:
- name: delta_table_s3
uri: s3:///path/to/table
format: delta
storage_credential: my_s3
```
Depending on your object storage location and configuration, one might have to
set part or all the available `s3` parameters. The only required ones
are `access_key_id` and `secret_access_key`.
As a security best practice, avoid writing secrets directly in static
configuration files. Use environment variable substitution instead:
```yaml
storage_credentials:
my_s3:
s3:
access_key_id: access-key-id
secret_access_key:
env: S3_SECRET_ACCESS_KEY
region: s3-region
endpoint_url: http://s3.domain.com
allow_http: false
tables:
- name: delta_table_s3
uri: s3:///path/to/table
format: delta
storage_credential: my_s3
```
##### Remote ADLS Tables
Configuring Azure ADLS tables:
```yaml
storage_credentials:
my_adls:
adls:
account_name: adls-account-name
access_key: adls-access-key
sas_key: adls-sas-key
tenant_id: adls-tenant-id
client_id: adls-client-id
client_secret: adls-client-secret
msi_endpoint: https://msi.azure.com
use_azure_cli: false
tables:
- name: delta_table_adls
uri: abfss:///path/to/table
format: delta
storage_credential: my_adls
```
Depending on your object storage location and configuration, one might have to
set part or all the available `adls` parameters. The only required one
is `account_name`.
As a security best practice, avoid writing secrets directly in static
configuration files. Use environment variable substitution instead:
```yaml
storage_credentials:
my_adls:
adls:
account_name: adls-account-name
access_key:
env: ADLS_ACCESS_KEY
tables:
- name: delta_table_adls
uri: abfss:///path/to/table
format: delta
storage_credential: my_adls
```
#### Predefined Query Parameters
Predefined queries allows for specifying named parameters that can then be used
with an SQL statement using the `$param_name` syntax.
When a query parameter is left blank by the user, it is treated as `NULL` by the
SQL engine. Use `COALESCE` to provide a fallback so the filter becomes a no-op
instead of returning an error or empty results:
```yaml
queries:
- name: daily_avg_temperature_params
title: Daily average temperature with parameters
parameters:
start_date:
default: "2025-01-01"
end_date:
default: "2025-01-31"
sql: |
select
date_trunc('day', time) as day,
round(avg(temperature_2m)) as avg_temperature
from
weather
where
day between coalesce($start_date::timestamp, timestamp '-infinity')
and coalesce($end_date::timestamp, timestamp 'infinity')
group by
day
order by
day asc
```
In this example:
- Blank `start_date` leads to `timestamp '-infinity'` (no lower bound)
- Blank `end_date` leads to `timestamp 'infinity'` (no upper bound)
- If both parameters are blank, all rows are returned
### Web Application
The easiest way to get started is to launch the Laketower web application:
```bash
$ laketower -c demo/laketower.yml web
```
By default, the web application will run on host `127.0.0.1` and port `8000`.
If some custom setup is required (especially for cloud deployment), this configuration
can be customized at runtime:
```bash
$ laketower -c demo/laketower.yml web --host 0.0.0.0 --port 5000
```
#### Screenshots
### CLI
Laketower provides a CLI interface:
```bash
$ laketower --help
usage: laketower [-h] [--version] [--config CONFIG] {web,config,tables,queries} ...
options:
-h, --help show this help message and exit
--version show program's version number and exit
--config, -c CONFIG Path to the Laketower YAML configuration file (default: laketower.yml)
commands:
{web,config,tables,queries}
web Launch the web application
config Work with configuration
tables Work with tables
queries Work with queries
```
By default, a YAML configuration file named `laketower.yml` will be looked for.
A custom path can be specified with the `-c` / `--config` argument.
#### Show resolved YAML configuration
Print the fully resolved configuration after include merging, useful for debugging composed setups.
```bash
$ laketower -c demo/laketower.yml config show
```
Pass `--with-env-vars-substitution` to also resolve environment variable references:
```bash
$ laketower -c demo/laketower.yml config show --with-env-vars-substitution
```
#### Validate YAML configuration
```bash
$ laketower -c demo/laketower.yml config validate
╭────────────────────────╮
│ Configuration is valid │
╰────────────────────────╯
Config(
tables=[
ConfigTable(name='sample_table', uri='demo/sample_table', table_format=),
ConfigTable(name='weather', uri='demo/weather', table_format=)
]
)
```
#### List all registered tables
```bash
$ laketower -c demo/laketower.yml tables list
tables
├── sample_table
│ ├── format: delta
│ └── uri: demo/sample_table
└── weather
├── format: delta
└── uri: demo/weather
```
#### Display a given table metadata
```bash
$ laketower -c demo/laketower.yml tables metadata sample_table
sample_table
├── name: Demo table
├── description: A sample demo Delta table
├── format: delta
├── uri: /Users/romain/Documents/dev/datalpia/laketower/demo/sample_table/
├── id: c1cb1cf0-1f3f-47b5-a660-3cc800edd341
├── version: 3
├── created at: 2025-02-05 22:27:39.579000+00:00
├── partitions:
└── configuration: {}
```
#### Display a given table schema
```bash
$ laketower -c demo/laketower.yml tables schema weather
weather
├── time: timestamp[us, tz=UTC]
├── city: string
├── temperature_2m: float
├── relative_humidity_2m: float
└── wind_speed_10m: float
```
#### Display a given table history
```bash
$ uv run laketower -c demo/laketower.yml tables history weather
weather
├── version: 2
│ ├── timestamp: 2025-02-05 22:27:46.425000+00:00
│ ├── client version: delta-rs.0.23.1
│ ├── operation: WRITE
│ ├── operation parameters
│ │ └── mode: Append
│ └── operation metrics
│ ├── execution_time_ms: 4
│ ├── num_added_files: 1
│ ├── num_added_rows: 168
│ ├── num_partitions: 0
│ └── num_removed_files: 0
├── version: 1
│ ├── timestamp: 2025-02-05 22:27:45.666000+00:00
│ ├── client version: delta-rs.0.23.1
│ ├── operation: WRITE
│ ├── operation parameters
│ │ └── mode: Append
│ └── operation metrics
│ ├── execution_time_ms: 4
│ ├── num_added_files: 1
│ ├── num_added_rows: 408
│ ├── num_partitions: 0
│ └── num_removed_files: 0
└── version: 0
├── timestamp: 2025-02-05 22:27:39.722000+00:00
├── client version: delta-rs.0.23.1
├── operation: CREATE TABLE
├── operation parameters
│ ├── metadata: {"configuration":{},"createdTime":1738794459722,"description":"Historical and forecast weather data from
│ │ open-meteo.com","format":{"options":{},"provider":"parquet"},"id":"a9615fb1-25cc-4546-a0fe-1cb534c514b2","name":"Weather","partitionCol
│ │ umns":[],"schemaString":"{\"type\":\"struct\",\"fields\":[{\"name\":\"time\",\"type\":\"timestamp\",\"nullable\":true,\"metadata\":{}},
│ │ {\"name\":\"city\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"temperature_2m\",\"type\":\"float\",\"nullable\":
│ │ true,\"metadata\":{}},{\"name\":\"relative_humidity_2m\",\"type\":\"float\",\"nullable\":true,\"metadata\":{}},{\"name\":\"wind_speed_1
│ │ 0m\",\"type\":\"float\",\"nullable\":true,\"metadata\":{}}]}"}
│ ├── protocol: {"minReaderVersion":1,"minWriterVersion":2}
│ ├── mode: ErrorIfExists
│ └── location: file:///Users/romain/Documents/dev/datalpia/laketower/demo/weather
└── operation metrics
```
#### Get statistics of a given table
Get basic statistics on all columns of a given table:
```bash
$ laketower -c demo/laketower.yml tables statistics weather
┏━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ column_name ┃ count ┃ avg ┃ std ┃ min ┃ max ┃
┡━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
│ time │ 576 │ None │ None │ 2025-01-26 01:00:00+01 │ 2025-02-12 00:00:00+01 │
│ city │ 576 │ None │ None │ Grenoble │ Grenoble │
│ temperature_2m │ 576 │ 5.2623263956047595 │ 3.326529069892729 │ 0.0 │ 15.1 │
│ relative_humidity_2m │ 576 │ 78.76909722222223 │ 15.701802163559918 │ 29.0 │ 100.0 │
│ wind_speed_10m │ 576 │ 7.535763886032833 │ 10.00898058743763 │ 0.0 │ 42.4 │
└──────────────────────┴───────┴────────────────────┴────────────────────┴────────────────────────┴────────────────────────┘
```
Specifying a table version yields according results:
```bash
$ laketower -c demo/laketower.yml tables statistics --version 0 weather
┏━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━┳━━━━━━┳━━━━━━┳━━━━━━┓
┃ column_name ┃ count ┃ avg ┃ std ┃ min ┃ max ┃
┡━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━╇━━━━━━╇━━━━━━╇━━━━━━┩
│ time │ 0 │ None │ None │ None │ None │
│ city │ 0 │ None │ None │ None │ None │
│ temperature_2m │ 0 │ None │ None │ None │ None │
│ relative_humidity_2m │ 0 │ None │ None │ None │ None │
│ wind_speed_10m │ 0 │ None │ None │ None │ None │
└──────────────────────┴───────┴──────┴──────┴──────┴──────┘
```
#### Import data into a given table
Import a CSV dataset into a table in append mode:
```bash
$ laketower -c demo/laketower.yml tables import weather --file data.csv --mode append --format csv --delimiter ',' --encoding 'utf-8'
```
`--mode` argument can be one of:
- `append`: append rows to the table (default)
- `overwrite`: replace all rows with the ones from the input file
`--format` argument can be one of:
- `csv`: CSV file format (default)
- `xlsx`: Excel file format (requires `laketower[excel]`, imports the first sheet)
`--delimiter` argument can be:
- Any single character (only valid for CSV file format)
- Default is _comma_ (`','`)
`--encoding` argument can be:
- Any [standard Python encoding](https://docs.python.org/3/library/codecs.html#standard-encodings),
- Default is `'utf-8'`
- Only applies to CSV file format
#### View a given table
Using a simple query builder, the content of a table can be displayed.
Optional arguments:
- `--cols `: select which columns to display
- `--sort-asc `: sort by a column name in ascending order
- `--sort-desc `: sort by a column name in descending order
- `--limit ` (default 10): limit the number of rows
- `--version`: time-travel to table revision number
```bash
$ laketower -c demo/laketower.yml tables view weather
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓
┃ time ┃ city ┃ temperature_2m ┃ relative_humidity_2m ┃ wind_speed_10m ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩
│ 2025-02-05 01:00:00+01:00 │ Grenoble │ 2.0 │ 84.0 │ 4.0 │
│ 2025-02-05 02:00:00+01:00 │ Grenoble │ 2.0999999046325684 │ 83.0 │ 1.5 │
│ 2025-02-05 03:00:00+01:00 │ Grenoble │ 1.600000023841858 │ 86.0 │ 1.100000023841858 │
│ 2025-02-05 04:00:00+01:00 │ Grenoble │ 1.899999976158142 │ 80.0 │ 4.199999809265137 │
│ 2025-02-05 05:00:00+01:00 │ Grenoble │ 1.899999976158142 │ 81.0 │ 3.299999952316284 │
│ 2025-02-05 06:00:00+01:00 │ Grenoble │ 1.399999976158142 │ 88.0 │ 4.300000190734863 │
│ 2025-02-05 07:00:00+01:00 │ Grenoble │ 1.7000000476837158 │ 87.0 │ 5.5 │
│ 2025-02-05 08:00:00+01:00 │ Grenoble │ 1.5 │ 82.0 │ 4.699999809265137 │
│ 2025-02-05 09:00:00+01:00 │ Grenoble │ 1.899999976158142 │ 80.0 │ 2.200000047683716 │
│ 2025-02-05 10:00:00+01:00 │ Grenoble │ 2.9000000953674316 │ 80.0 │ 0.800000011920929 │
└───────────────────────────┴──────────┴────────────────────┴──────────────────────┴───────────────────┘
```
```bash
$ laketower -c demo/laketower.yml tables view weather --cols time city temperature_2m --limit 5 --sort-desc time
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓
┃ time ┃ city ┃ temperature_2m ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩
│ 2025-02-12 00:00:00+01:00 │ Grenoble │ 5.099999904632568 │
│ 2025-02-12 00:00:00+01:00 │ Grenoble │ 5.099999904632568 │
│ 2025-02-11 23:00:00+01:00 │ Grenoble │ 4.900000095367432 │
│ 2025-02-11 23:00:00+01:00 │ Grenoble │ 4.900000095367432 │
│ 2025-02-11 22:00:00+01:00 │ Grenoble │ 4.900000095367432 │
└───────────────────────────┴──────────┴───────────────────┘
```
```bash
$ laketower -c demo/laketower.yml tables view weather --version 1
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓
┃ time ┃ city ┃ temperature_2m ┃ relative_humidity_2m ┃ wind_speed_10m ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
│ 2025-01-26 01:00:00+01:00 │ Grenoble │ 7.0 │ 87.0 │ 8.899999618530273 │
│ 2025-01-26 02:00:00+01:00 │ Grenoble │ 6.099999904632568 │ 87.0 │ 6.199999809265137 │
│ 2025-01-26 03:00:00+01:00 │ Grenoble │ 6.0 │ 86.0 │ 2.700000047683716 │
│ 2025-01-26 04:00:00+01:00 │ Grenoble │ 6.099999904632568 │ 82.0 │ 3.0999999046325684 │
│ 2025-01-26 05:00:00+01:00 │ Grenoble │ 5.5 │ 87.0 │ 3.299999952316284 │
│ 2025-01-26 06:00:00+01:00 │ Grenoble │ 5.199999809265137 │ 91.0 │ 2.200000047683716 │
│ 2025-01-26 07:00:00+01:00 │ Grenoble │ 4.800000190734863 │ 86.0 │ 3.0 │
│ 2025-01-26 08:00:00+01:00 │ Grenoble │ 4.900000095367432 │ 83.0 │ 1.100000023841858 │
│ 2025-01-26 09:00:00+01:00 │ Grenoble │ 4.0 │ 92.0 │ 3.0999999046325684 │
│ 2025-01-26 10:00:00+01:00 │ Grenoble │ 5.0 │ 86.0 │ 6.400000095367432 │
└───────────────────────────┴──────────┴───────────────────┴──────────────────────┴────────────────────┘
```
#### Query all registered tables
Query any registered tables using DuckDB SQL dialect!
```bash
$ laketower -c demo/laketower.yml tables query "select date_trunc('day', time) as day, avg(temperature_2m) as mean_temperature from weather group by day order by day desc limit 3"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓
┃ day ┃ mean_temperature ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
│ 2025-02-12 00:00:00+01:00 │ 5.099999904632568 │
│ 2025-02-11 00:00:00+01:00 │ 4.833333373069763 │
│ 2025-02-10 00:00:00+01:00 │ 2.1083333243926368 │
└───────────────────────────┴────────────────────┘
3 rows returned
Execution time: 33.72ms
```
Use named parameters within a giving query (note: escape `$` prefixes properly!):
```bash
$ laketower -c demo/laketower.yml tables query "select date_trunc('day', time) as day, avg(temperature_2m) as mean_temperature from weather where day between \$start_date and \$end_date group by day order by day desc" -p start_date 2025-01-29 -p end_date 2025-01-31
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓
┃ day ┃ mean_temperature ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
│ 2025-01-31 00:00:00+01:00 │ 5.683333257834117 │
│ 2025-01-30 00:00:00+01:00 │ 8.900000015894571 │
│ 2025-01-29 00:00:00+01:00 │ 7.770833313465118 │
└───────────────────────────┴────────────────────┘
4 rows returned
Execution time: 30.59ms
```
Export query results to CSV:
```bash
$ laketower -c demo/laketower.yml tables query --output results.csv "select date_trunc('day', time) as day, avg(temperature_2m) as mean_temperature from weather group by day order by day desc limit 3"
Query results written to: results.csv
```
#### List saved queries
```bash
$ laketower -c demo/laketower.yml queries list
queries
├── all_data
└── daily_avg_temperature
```
#### Execute saved queries
```bash
$ laketower -c demo/laketower.yml queries view daily_avg_temperature
┏━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ # ┃ day ┃ avg_temperature ┃
┡━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ 1 │ 2025-01-26 00:00:00+01:00 │ 8.0 │
│ 2 │ 2025-01-27 00:00:00+01:00 │ 13.0 │
│ 3 │ 2025-01-28 00:00:00+01:00 │ 7.0 │
│ 4 │ 2025-01-29 00:00:00+01:00 │ 8.0 │
│ 5 │ 2025-01-30 00:00:00+01:00 │ 9.0 │
│ 6 │ 2025-01-31 00:00:00+01:00 │ 6.0 │
│ 7 │ 2025-02-01 00:00:00+01:00 │ 4.0 │
│ 8 │ 2025-02-02 00:00:00+01:00 │ 4.0 │
│ 9 │ 2025-02-03 00:00:00+01:00 │ 4.0 │
│ 10 │ 2025-02-04 00:00:00+01:00 │ 3.0 │
│ 11 │ 2025-02-05 00:00:00+01:00 │ 3.0 │
│ 12 │ 2025-02-06 00:00:00+01:00 │ 2.0 │
│ 13 │ 2025-02-07 00:00:00+01:00 │ 6.0 │
│ 14 │ 2025-02-08 00:00:00+01:00 │ 7.0 │
│ 15 │ 2025-02-09 00:00:00+01:00 │ 5.0 │
│ 16 │ 2025-02-10 00:00:00+01:00 │ 2.0 │
│ 17 │ 2025-02-11 00:00:00+01:00 │ 5.0 │
│ 18 │ 2025-02-12 00:00:00+01:00 │ 5.0 │
├───────┼───────────────────────────┼─────────────────┤
│ Total │ - │ 101.0 │
└───────┴───────────────────────────┴─────────────────┘
18 rows returned
Execution time: 27.02ms
```
Executing a predefined query with parameters (here `start_date` and `end_date`):
```bash
$ laketower -c demo/laketower.yml queries view daily_avg_temperature_params -p start_date 2025-02-01 -p end_date 2025-02-05
┏━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ # ┃ day ┃ avg_temperature ┃
┡━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ 1 │ 2025-02-01 00:00:00+01:00 │ 4.0 │
│ 2 │ 2025-02-02 00:00:00+01:00 │ 4.0 │
│ 3 │ 2025-02-03 00:00:00+01:00 │ 4.0 │
│ 4 │ 2025-02-04 00:00:00+01:00 │ 3.0 │
│ 5 │ 2025-02-05 00:00:00+01:00 │ 3.0 │
│ 6 │ 2025-02-06 00:00:00+01:00 │ 2.0 │
└───┴───────────────────────────┴─────────────────┘
6 rows returned
Execution time: 29.70ms
```
## License
Licensed under [Apache License 2.0](LICENSE)
Copyright (c) 2025 - present Romain Clement / Datalpia