using cookiecutter template

This commit is contained in:
Andrea Mannocci 2023-06-23 17:02:01 +02:00
parent d70036c5fe
commit f2c5e26266
7 changed files with 268 additions and 28 deletions

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@ -2,7 +2,15 @@ FROM jupyter/pyspark-notebook:latest
RUN pip install papermill RUN pip install papermill
USER jovyan USER jovyan
RUN mkdir /home/jovyan/openaire RUN mkdir /home/jovyan/openaire
RUN mkdir /home/jovyan/openaire/data RUN mkdir /home/jovyan/openaire/data
RUN mkdir /home/jovyan/openaire/data/raw
ADD notebooks /home/jovyan/openaire/notebooks
ADD src /home/jovyan/openaire/src
ADD test_environment.py /home/jovyan/openaire/
ADD setup.py /home/jovyan/openaire/
ADD Makefile /home/jovyan/openaire
ADD requirements.txt /home/jovyan/openaire/
ADD notebooks/beginners_kit.ipynb /home/jovyan/openaire/

144
Makefile Normal file
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@ -0,0 +1,144 @@
.PHONY: clean data lint requirements sync_data_to_s3 sync_data_from_s3
#################################################################################
# GLOBALS #
#################################################################################
PROJECT_DIR := $(shell dirname $(realpath $(lastword $(MAKEFILE_LIST))))
BUCKET = [OPTIONAL] your-bucket-for-syncing-data (do not include 's3://')
PROFILE = default
PROJECT_NAME = project_name
PYTHON_INTERPRETER = python3
ifeq (,$(shell which conda))
HAS_CONDA=False
else
HAS_CONDA=True
endif
#################################################################################
# COMMANDS #
#################################################################################
## Install Python Dependencies
requirements: test_environment
$(PYTHON_INTERPRETER) -m pip install -U pip setuptools wheel
$(PYTHON_INTERPRETER) -m pip install -r requirements.txt
## Make Dataset
data: requirements
$(PYTHON_INTERPRETER) src/data/make_dataset.py data/raw
## Delete all compiled Python files
clean:
find . -type f -name "*.py[co]" -delete
find . -type d -name "__pycache__" -delete
## Lint using flake8
lint:
flake8 src
## Upload Data to S3
sync_data_to_s3:
ifeq (default,$(PROFILE))
aws s3 sync data/ s3://$(BUCKET)/data/
else
aws s3 sync data/ s3://$(BUCKET)/data/ --profile $(PROFILE)
endif
## Download Data from S3
sync_data_from_s3:
ifeq (default,$(PROFILE))
aws s3 sync s3://$(BUCKET)/data/ data/
else
aws s3 sync s3://$(BUCKET)/data/ data/ --profile $(PROFILE)
endif
## Set up python interpreter environment
create_environment:
ifeq (True,$(HAS_CONDA))
@echo ">>> Detected conda, creating conda environment."
ifeq (3,$(findstring 3,$(PYTHON_INTERPRETER)))
conda create --name $(PROJECT_NAME) python=3
else
conda create --name $(PROJECT_NAME) python=2.7
endif
@echo ">>> New conda env created. Activate with:\nsource activate $(PROJECT_NAME)"
else
$(PYTHON_INTERPRETER) -m pip install -q virtualenv virtualenvwrapper
@echo ">>> Installing virtualenvwrapper if not already installed.\nMake sure the following lines are in shell startup file\n\
export WORKON_HOME=$$HOME/.virtualenvs\nexport PROJECT_HOME=$$HOME/Devel\nsource /usr/local/bin/virtualenvwrapper.sh\n"
@bash -c "source `which virtualenvwrapper.sh`;mkvirtualenv $(PROJECT_NAME) --python=$(PYTHON_INTERPRETER)"
@echo ">>> New virtualenv created. Activate with:\nworkon $(PROJECT_NAME)"
endif
## Test python environment is setup correctly
test_environment:
$(PYTHON_INTERPRETER) test_environment.py
#################################################################################
# PROJECT RULES #
#################################################################################
#################################################################################
# Self Documenting Commands #
#################################################################################
.DEFAULT_GOAL := help
# Inspired by <http://marmelab.com/blog/2016/02/29/auto-documented-makefile.html>
# sed script explained:
# /^##/:
# * save line in hold space
# * purge line
# * Loop:
# * append newline + line to hold space
# * go to next line
# * if line starts with doc comment, strip comment character off and loop
# * remove target prerequisites
# * append hold space (+ newline) to line
# * replace newline plus comments by `---`
# * print line
# Separate expressions are necessary because labels cannot be delimited by
# semicolon; see <http://stackoverflow.com/a/11799865/1968>
.PHONY: help
help:
@echo "$$(tput bold)Available rules:$$(tput sgr0)"
@echo
@sed -n -e "/^## / { \
h; \
s/.*//; \
:doc" \
-e "H; \
n; \
s/^## //; \
t doc" \
-e "s/:.*//; \
G; \
s/\\n## /---/; \
s/\\n/ /g; \
p; \
}" ${MAKEFILE_LIST} \
| LC_ALL='C' sort --ignore-case \
| awk -F '---' \
-v ncol=$$(tput cols) \
-v indent=19 \
-v col_on="$$(tput setaf 6)" \
-v col_off="$$(tput sgr0)" \
'{ \
printf "%s%*s%s ", col_on, -indent, $$1, col_off; \
n = split($$2, words, " "); \
line_length = ncol - indent; \
for (i = 1; i <= n; i++) { \
line_length -= length(words[i]) + 1; \
if (line_length <= 0) { \
line_length = ncol - indent - length(words[i]) - 1; \
printf "\n%*s ", -indent, " "; \
} \
printf "%s ", words[i]; \
} \
printf "\n"; \
}' \
| more $(shell test $(shell uname) = Darwin && echo '--no-init --raw-control-chars')

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@ -29,31 +29,11 @@
"source": [ "source": [
"This step can take some time depending on your network speed.\n", "This step can take some time depending on your network speed.\n",
"\n", "\n",
"Uncomment and run only if you need to download the data the first time: these lines just download the datasets from the deposition on Zenodo containing data for this kit (https://zenodo.org/record/7490192), untar the content and clean up. All the data needed will sit under the `data` folder." "This project follows the guidelines detailed in https://drivendata.github.io/cookiecutter-data-science/ and uses `make` to perform actions.\n",
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"slideshow": {
"slide_type": "notes"
},
"tags": []
},
"outputs": [],
"source": [
"# import os\n",
"# base_url = \"https://zenodo.org/record/7490192/files/\"\n",
"\n", "\n",
"If you need to download the data the first time, open a terminal and run `make data` from the `openaire` folder; `make` will take care of all the steps (i.e., downloading the relevant datasets from Zenodo, https://zenodo.org/record/7490192, untar the content and clean up). \n",
"\n", "\n",
"# items =[\"communities_infrastructures.tar\",\"dataset.tar\",\"datasource.tar\",\"organization.tar\",\"otherresearchproduct.tar\",\"project.tar\",\"publication.tar\",\"relation.tar\", \"software.tar\"]\n", "At the end, the data we need will sit under the `data/raw` folder. Data in here should be immutable; let's keep it that way."
"\n",
"# for item in items: \n",
"# print(f\"Downloading {item}\")\n",
"# os.system(f'wget {base_url}{item}?download=1 -O data/{item}')\n",
"# print(f\"Extracting {item}\")\n",
"# os.system(f'tar -xf data/{item} -C data/; rm data/{item}')"
] ]
}, },
{ {
@ -108,7 +88,7 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"df = pd.read_json('./data/publication/part-00000.txt.gz', compression='gzip', lines=True)\n", "df = pd.read_json('../data/raw/publication/part-00000.txt.gz', compression='gzip', lines=True)\n",
"df.head(2)" "df.head(2)"
] ]
}, },
@ -128,7 +108,7 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"# files = sorted(glob.glob('./data/publication/part-*.txt.gz'))\n", "# files = sorted(glob.glob('../data/raw/publication/part-*.txt.gz'))\n",
"# publications_df = pd.concat(pd.read_json(f, compression='gzip', lines=True) for f in files)" "# publications_df = pd.concat(pd.read_json(f, compression='gzip', lines=True) for f in files)"
] ]
}, },
@ -194,7 +174,7 @@
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"inputPath = 'data/'\n", "inputPath = '../data/raw/'\n",
" \n", " \n",
"publications = spark.read.schema(StructType.fromJson(json.loads(publicationSchema))).json(inputPath + 'publication')\n", "publications = spark.read.schema(StructType.fromJson(json.loads(publicationSchema))).json(inputPath + 'publication')\n",
"datasets = spark.read.schema(StructType.fromJson(json.loads(datasetSchema))).json(inputPath + 'dataset')\n", "datasets = spark.read.schema(StructType.fromJson(json.loads(datasetSchema))).json(inputPath + 'dataset')\n",
@ -222,7 +202,6 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"\n",
"publications.createOrReplaceTempView(\"publications\")\n", "publications.createOrReplaceTempView(\"publications\")\n",
"datasets.createOrReplaceTempView(\"datasets\")\n", "datasets.createOrReplaceTempView(\"datasets\")\n",
"softwares.createOrReplaceTempView(\"software\")\n", "softwares.createOrReplaceTempView(\"software\")\n",

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requirements.txt Normal file
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@ -0,0 +1,12 @@
# local package
-e .
# external requirements
click
coverage
flake8
python-dotenv>=0.5.1
pandas
igraph
matplotlib
plotly

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setup.py Normal file
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@ -0,0 +1,10 @@
from setuptools import find_packages, setup
setup(
name='src',
packages=find_packages(),
version='0.1.0',
description="OpenAIRE Beginner's Kit.",
author='Andrea Mannocc, Miriam Baglioni, Sandro La Bruzzo',
license='MIT',
)

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src/data/make_dataset.py Normal file
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# -*- coding: utf-8 -*-
import os
from urllib.request import urlretrieve
from urllib.parse import urlsplit
import tarfile
import click
import logging
from pathlib import Path
from dotenv import find_dotenv, load_dotenv
logger = logging.getLogger(__name__)
openaire_files = ["https://zenodo.org/record/7490192/files/communities_infrastructures.tar",
"https://zenodo.org/record/7490192/files/dataset.tar",
"https://zenodo.org/record/7490192/files/datasource.tar",
"https://zenodo.org/record/7490192/files/organization.tar",
"https://zenodo.org/record/7490192/files/otherresearchproduct.tar",
"https://zenodo.org/record/7490192/files/project.tar",
"https://zenodo.org/record/7490192/files/publication.tar",
"https://zenodo.org/record/7490192/files/relation.tar",
"https://zenodo.org/record/7490192/files/software.tar"]
def download_tar(url, path):
tar_name = urlsplit(url).path.split('/')[-1] # publication.tar
tar_path = os.path.join(path, tar_name) # data/raw/publication.tar
untarred_folder = tar_name.split('.')[0] # publication
untarred_path = os.path.join(path, untarred_folder) # data/raw/publication
if not os.path.exists(untarred_path):
if not os.path.exists(tar_path):
logger.info('downloading %s' % url)
urlretrieve(url, tar_path)
logger.info('untar %s' % tar_name)
with tarfile.open(tar_path, "r") as tar:
tar.extractall(path)
logger.info('cleaning')
os.remove(tar_path)
@click.command()
@click.argument('output_filepath', type=click.Path(exists=True))
def main(output_filepath):
""" Downloads data into /data/raw
"""
for tar in openaire_files:
download_tar(tar, output_filepath)
if __name__ == '__main__':
log_fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
logging.basicConfig(level=logging.INFO, format=log_fmt)
# not used in this stub but often useful for finding various files
project_dir = Path(__file__).resolve().parents[2]
# find .env automagically by walking up directories until it's found, then
# load up the .env entries as environment variables
load_dotenv(find_dotenv())
main()

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test_environment.py Normal file
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import sys
REQUIRED_PYTHON = "python3"
def main():
system_major = sys.version_info.major
if REQUIRED_PYTHON == "python":
required_major = 2
elif REQUIRED_PYTHON == "python3":
required_major = 3
else:
raise ValueError("Unrecognized python interpreter: {}".format(
REQUIRED_PYTHON))
if system_major != required_major:
raise TypeError(
"This project requires Python {}. Found: Python {}".format(
required_major, sys.version))
else:
print(">>> Development environment passes all tests!")
if __name__ == '__main__':
main()