This is roughly the same test run in both casper and nightwatch.
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| /* | |
| A script to generate a Google BigQuery-complient JSON-schema from a JSON object. | |
| Make sure the JSON object is complete before generating, null values will be skipped. | |
| References: | |
| https://cloud.google.com/bigquery/docs/data | |
| https://cloud.google.com/bigquery/docs/personsDataSchema.json | |
| https://gist.github.com/igrigorik/83334277835625916cd6 | |
| ... and a couple of visits to StackOverflow |
For a small number of variables ('tokens'), I use a simple shell script along with a templated version of my YAML file. Here's an actual example:
files:
docker-compose-template.yml
docker-compose.yml
compose_replace.sh
run:
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| '''This script goes along the blog post | |
| "Building powerful image classification models using very little data" | |
| from blog.keras.io. | |
| It uses data that can be downloaded at: | |
| https://www.kaggle.com/c/dogs-vs-cats/data | |
| In our setup, we: | |
| - created a data/ folder | |
| - created train/ and validation/ subfolders inside data/ | |
| - created cats/ and dogs/ subfolders inside train/ and validation/ | |
| - put the cat pictures index 0-999 in data/train/cats |
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| --log_gc (Log heap samples on garbage collection for the hp2ps tool.) | |
| type: bool default: false | |
| --expose_gc (expose gc extension) | |
| type: bool default: false | |
| --max_new_space_size (max size of the new generation (in kBytes)) | |
| type: int default: 0 | |
| --max_old_space_size (max size of the old generation (in Mbytes)) | |
| type: int default: 0 | |
| --max_executable_size (max size of executable memory (in Mbytes)) | |
| type: int default: 0 |
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| import json | |
| import requests | |
| # Authentication for user filing issue (must have read/write access to | |
| # repository to add issue to) | |
| USERNAME = 'CHANGEME' | |
| PASSWORD = 'CHANGEME' | |
| # The repository to add this issue to | |
| REPO_OWNER = 'CHANGEME' |
Using Python's built-in defaultdict we can easily define a tree data structure:
def tree(): return defaultdict(tree)That's it!
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| { | |
| "AL": "Alabama", | |
| "AK": "Alaska", | |
| "AS": "American Samoa", | |
| "AZ": "Arizona", | |
| "AR": "Arkansas", | |
| "CA": "California", | |
| "CO": "Colorado", | |
| "CT": "Connecticut", | |
| "DE": "Delaware", |
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