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Copy file name to clipboardExpand all lines: CONTRIBUTING.md
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@@ -6,7 +6,7 @@ Reporting bugs and asking questions
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You can post questions or issues or feedback through the following channels:
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1.[Github Discussions](https://github.com/lithops-cloud/lithops/discussions): For discussions about development, questions about usage, and feature requests.
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1.[GitHub Discussions](https://github.com/lithops-cloud/lithops/discussions): For discussions about development, questions about usage, and feature requests.
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2.[GitHub Issues](https://github.com/lithops-cloud/lithops/issues): For bug reports and feature requests.
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harder to merge in a large change with a lot of disjoint features.
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2. Submit the patch as a GitHub pull request against the master branch.
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3. Make sure that your code passes the tests.
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4. Make sure that your code passes the linter. Install `flake8` with `pip3 install flake8` and run the following command until you don't see any linting error:
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4. Make sure that your code passes the linter. Install `flake8` with `pip3 install flake8` and run the following command until you see no linting errors:
Lithops is a Python multi-cloud distributed computing framework that lets you run unmodified Python code at massive scale across cloud, HPC, and on-premise platforms. It supports major cloud providers and Kubernetes platforms, running your code transparently without requiring you to manage deployment or infrastructure.
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## Installation
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1. Install Lithops from the PyPi repository:
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1. Install Lithops from the PyPI repository:
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```bash
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pip install lithops
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## High-level API
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Lithops is shipped with 2 different high-level Compute APIs, and 2 high-level Storage APIs
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Lithops ships with 2 different high-level Compute APIs, and 2 high-level Storage APIs.
Copy file name to clipboardExpand all lines: config/README.md
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# Lithops configuration
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By default Lithops works on Localhost if no configuration is provided. To run workloads on the Cloud, you must configure both a compute and a storage backend. Failing to configure them properly will prevent Lithops to submit workloads. Lithops configuration can be provided either in a configuration file or in runtime via a Python dictionary.
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By default Lithops works on Localhost if no configuration is provided. To run workloads on the Cloud, you must configure both a compute and a storage backend. Failing to configure them properly will prevent Lithops from submitting workloads. Lithops configuration can be provided either in a configuration file or at runtime via a Python dictionary.
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### Configuration file
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To configure Lithops through a [configuration file](config_template.yaml) you have multiple options:
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1. Create a new file called `config` in the `~/.lithops` folder (i.e:`~/.lithops/config`).
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1. Create a new file called `config` in the `~/.lithops` folder (i.e.,`~/.lithops/config`).
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2. Create a new file called `.lithops_config` in the root directory of your project from where you will execute your Lithops scripts.
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3. Create a new file called `config` in the `/etc/lithops/` folder (i.e:`/etc/lithops/config`). Useful for sharing the config file on multi-user machines.
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3. Create a new file called `config` in the `/etc/lithops/` folder (i.e.,`/etc/lithops/config`). Useful for sharing the config file on multi-user machines.
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4. Create the config file in any other location and configure the `LITHOPS_CONFIG_FILE` system environment variable:
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LITHOPS_CONFIG_FILE=<CONFIG_FILE_LOCATION>
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### Configuration keys in runtime
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An alternative mode of configuration is to use a python dictionary. This option allows to pass all the configuration details as part of the Lithops invocation in runtime. An entire list of sections and keys is [here](config_template.yaml)
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An alternative mode of configuration is to use a Python dictionary. This option allows you to pass all the configuration details as part of the Lithops invocation at runtime. The full list of sections and keys is [here](config_template.yaml)
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## Compute and Storage backends
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Choose your compute and storage engines from the table below
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Choose your compute and storage backends from the table below
Copy file name to clipboardExpand all lines: docs/source/api_stats.rst
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Execution summary plots
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-----------------------
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The :code:`plot()` method from :code:`FunctionExecutor` creates a scatter plot and a histogram plot showing a summary of the tasks executed by a :code:`FunctionExecutor`. By default, lithops creates a :code:`plots/` directory in the working directory path containing both plots in PNG format. For more details refer to the `FunctionExecutor API reference <https://lithops-cloud.github.io/docs/source/api_futures.html>`_.
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The :code:`plot()` method from :code:`FunctionExecutor` creates a scatter plot and a histogram plot showing a summary of the tasks executed by a :code:`FunctionExecutor`. By default, Lithops creates a :code:`plots/` directory in the working directory path containing both plots in PNG format. For more details, refer to the `FunctionExecutor API reference <https://lithops-cloud.github.io/docs/source/api_futures.html>`_.
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To get started, first install Lithops and the plotting dependencies with:
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* - Stat
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- Description
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* - :code:`func_data_size_bytes`
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- Size in bytes of the input data processed by this function. That is, the object size of the input list item processed by this function. Note that if the function processes data obtained from object storage, this value does not include the size of that data, only those that have been serialized and sent from the host process to the function.
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- Size in bytes of the input data processed by this function. That is, the object size of the input list item processed by this function. Note that if the function processes data obtained from object storage, this value does not include the size of that data—only the data serialized and sent from the host process to the function.
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* - :code:`func_module_size_bytes`
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- Size in bytes of the dependencies (function and modules) serialized and uploaded by the host process.
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* - :code:`func_result_size`
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* - :code:`host_job_serialize_time`
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- Total time taken by the host process to serialize the input data and dependencies (functions and modules).
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* - :code:`host_result_done_tstamp`
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- Timestamp of when host received the function result from cloud object storage.
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- Timestamp of when the host received the function result from cloud object storage.
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* - :code:`host_result_query_count`
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- Number of queries to the object storage to get the result object.
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* - :code:`host_status_done_tstamp`
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* - :code:`worker_cold_start`
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- Indicates whether it was a "warm" invocation (the container was already running) or "cold" (the container had to be deployed).
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* - :code:`worker_end_tstamp`
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- Timestamp in which the worker function had finished its execution.
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- Timestamp when the worker function finished its execution.
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* - :code:`worker_exec_time`
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- Total execution time of the worker function (Lithops wrapper + user-defined function execution time).
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