#!/usr/bin/env python
# coding: utf-8
---
sidebar_label: "Prolog Script"
sidebar_position: 4
---
# # Running a Prolog Script
# 
# 
# [![stars - badge-generator](https://img.shields.io/github/stars/bacalhau-project/bacalhau?style=social)](https://github.com/bacalhau-project/bacalhau)

# ## Introduction
# Prolog is intended primarily as a declarative programming language: the program logic is expressed in terms of relations, represented as facts and rules. A computation is initiated by running a query over these relations.
# Prolog is well-suited for specific tasks that benefit from rule-based logical queries such as searching databases, voice control systems, and filling templates.
# 
# 
# ## TD;LR
# A quick guide on how to run a hello world script on Bacalhau
# 
# ## Prerequisites
# 
# To get started, you need to install the Bacalhau client, see more information [here](https://docs.bacalhau.org/getting-started/installation)
# 

# ## Running Locally​
# 

# To get started, install swipl 
# 

# In[ ]:


get_ipython().run_cell_magic('bash', '', 'sudo add-apt-repository ppa:swi-prolog/stable\nsudo apt-get update\nsudo apt-get install swi-prolog\n')


# Create a file called `helloworld.pl`. The following script prints ‘Hello World’ to the stdout
# 

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get_ipython().run_cell_magic('writefile', 'helloworld.pl', "hello_world :- write('Hello World'), nl, \n               halt.\n")


# Running the script to print out the output
# 

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get_ipython().run_cell_magic('bash', '', 'swipl -q -s helloworld.pl -g hello_world\n')


# After the script has run successfully locally we can now run it on Bacalhau.  
# 
# Before running it on Bacalhau we need to upload it to IPFS.
# 
# Using the `IPFS cli`
# 

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get_ipython().system('wget https://dist.ipfs.io/go-ipfs/v0.4.2/go-ipfs_v0.4.2_linux-amd64.tar.gz')
get_ipython().system('tar xvfz go-ipfs_v0.4.2_linux-amd64.tar.gz')
get_ipython().system('mv go-ipfs/ipfs /usr/local/bin/ipfs')
get_ipython().system('ipfs init')
get_ipython().system('ipfs cat /ipfs/QmYwAPJzv5CZsnA625s3Xf2nemtYgPpHdWEz79ojWnPbdG/readme')
get_ipython().system('ipfs config Addresses.Gateway /ip4/127.0.0.1/tcp/8082')
get_ipython().system('ipfs config Addresses.API /ip4/127.0.0.1/tcp/5002')
get_ipython().system('nohup ipfs daemon > startup.log &')


# Run the command below to check if our script has been uploaded. This commmand outputs the CID.

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get_ipython().system('ipfs add helloworld.pl')


# Copy the CID of the file which in this case is `QmYq9ipYf3vsj7iLv5C67BXZcpLHxZbvFAJbtj7aKN5qii`

# Since the data uploaded To IPFS isn’t pinned, we will need to do that manually. Check this information on how to pin your [data](https://docs.bacalhau.org/data-ingestion/pin) We recommend using [NFT.Storage](https://nft.storage/).
# 
# 

# ## Running a Bacalhau Job 
# 
# 
# To submit a job, run the following Bacalhau command:

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get_ipython().run_cell_magic('bash', '--out job_id', 'bacalhau docker run \\\n-i ipfs://QmYq9ipYf3vsj7iLv5C67BXZcpLHxZbvFAJbtj7aKN5qii:/helloworld.pl \\\n--wait \\\n--id-only \\\nswipl \\\n -- swipl -q -s helloworld.pl -g hello_world\n')


# ### Structure of the Command
# 
# 
# `-i: ipfs://< CID >:/< name-of-the-script >`: we will mount the script to the container using the -v flag
# 
# `Swipl`: flag
# 
# `-q`: running in quiet mode
# 
# `-s`: load file as a script in this case we want to run the script helloworld.pl
# 
# `-g`: is the name of the function you want to execute in this case its hello_world
# 
# When a job is submitted, Bacalhau prints out the related `job_id`. We store that in an environment variable so that we can reuse it later on.

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get_ipython().run_line_magic('env', 'JOB_ID={job_id}')


# ## Checking the State of your Jobs
# 
# - **Job status**: You can check the status of the job using `bacalhau list`. 

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get_ipython().run_cell_magic('bash', '', 'bacalhau list --id-filter ${JOB_ID} --wide\n')


# When it says `Published` or `Completed`, that means the job is done, and we can get the results.
# 
# - **Job information**: You can find out more information about your job by using `bacalhau describe`.

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get_ipython().run_cell_magic('bash', '', 'bacalhau describe ${JOB_ID}\n')


# - **Job download**: You can download your job results directly by using `bacalhau get`. Alternatively, you can choose to create a directory to store your results. In the command below, we created a directory and downloaded our job output to be stored in that directory.

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get_ipython().run_cell_magic('bash', '', 'rm -rf results && mkdir -p results\nbacalhau get $JOB_ID --output-dir results\n')


# ## Viewing your Job Output
# 
# To view the file, run the following command:

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get_ipython().run_cell_magic('bash', '', 'cat results/stdout\n')