# fsspec-reference-maker
Functions to make reference descriptions for ReferenceFileSystem
[](https://intake.github.io/fsspec-reference-maker/)
[](https://github.com/intake/fsspec-reference-maker/actions/workflows/tests.yml)
[](https://pypi.python.org/pypi/fsspec-reference-maker/)
[](https://anaconda.org/conda-forge/fsspec-reference-maker)
### Version 0
Prototype spec for the structure required by ReferenceFileSystem:
```json
{
"key0": "data",
"key1": ["protocol://target_url", 10000, 100]
}
```
where:
* `key0` includes data as-is (stored as text)
* `key1` refers to a data file URL, the offset within the file (in bytes), and the length of the data item (in bytes).
For example, Zarr data in this proposed spec might be represented as:
```json
{
".zgroup": "{\n \"zarr_format\": 2\n}",
".zattrs": "{\n \"Conventions\": \"UGRID-0.9.0\n\"}",
"x/.zattrs": "{\n \"_ARRAY_DIMENSIONS\": [\n \"node\"\n ...",
"x/.zarray": "{\n \"chunks\": [\n 9228245\n ],\n \"compressor\": null,\n \"dtype\": \"<f8\",\n ...",
"x/0": ["s3://bucket/path/file.nc", 294094376, 73825960]
}
```
### Version 1
Metadata structure in JSON. We note, for future possible binary storage, that "version", "gen" and "templates" should
be considered attributes, and "refs" as the data that ought to dominate the storage size. The previous definition,
Version 0, is compatible with the "refs" entry, but here we add features. It will also be possible to *expand*
this new enhanced spec into Version 0 format.
```
{
"version": (required, must be equal to) 1,
"templates": (optional, zero or more arbitrary keys) {
"template_name": jinja-str
},
"gen": (optional, zero or more items) [
"key": (required) jinja-str,
"url": (required) jinja-str,
"offset": (optional, required with "length") jinja-str,
"length": (optional, required with "offset") jinja-str,
"dimensions": (required, one or more arbitrary keys) {
"variable_name": (required)
{"start": (optional) int, "stop": (required) int, "step": (optional) int}
OR
[int, ...]
}
],
"refs": (optional, zero or more arbitrary keys) {
"key_name": (required) str OR [url(jinja-str)] OR [url(jinja-str), offset(int), length(int)]
}
}
```
Where:
- `jinja-str` is a string which will be rendered by jinja2 or its non-python equivalent; i.e., it may be
a literal string, or may include "{{..}}" annotations, where
- for the values associated with a template_name, the variables are to be passed in reference URL strings that
use this template
- for the values within a "gen" object, variables come from the "dimensions" and "templates"
- the `str` format of a reference value may be
- a string starting "base64:", which will be decoded to binary
- any other string, interpreted as ascii data
- the str version of ref values indicates data, the one-element array a whole url, and the three-element version
a binary section of a url
Here is an example
```json
{
"version": 1,
"templates": {
"u": "server.domain/path",
"f": "{{c}}"
},
"gen": [
{
"key": "gen_key{{i}}",
"url": "http://{{u}}_{{i}}",
"offset": "{{(i + 1) * 1000}}",
"length": "1000",
"dimensions":
{
"i": {"stop": 5}
}
}
],
"refs": {
"key0": "data",
"key1": ["http://target_url", 10000, 100],
"key2": ["http://{{u}}", 10000, 100],
"key3": ["http://{{f(c='text')}}", 10000, 100]
}
}
```
Here the variable `i` takes the values `[0, 1, 2, 3, 4]`, which could have been provided in array form. Where there
is more than one variable, a cartesian product is formed.
This example evaluates to the Version 0 equivalent
```json
{
"key0": "data",
"key1": ["http://target_url", 10000, 100],
"key2": ["http://server.domain/path", 10000, 100],
"key3": ["http://text", 10000, 100],
"gen_key0": ["http://server.domain/path_0", 1000, 1000],
"gen_key1": ["http://server.domain/path_1", 2000, 1000],
"gen_key2": ["http://server.domain/path_2", 3000, 1000],
"gen_key3": ["http://server.domain/path_3", 4000, 1000],
"gen_key4": ["http://server.domain/path_4", 5000, 1000]
}
```
such that accessing, for instance, "key0" returns `b"data"` and accessing "gen_key0" returns 1000 bytes
from the given URL, at an offset of 1000.
## Examples
Run a notebook example comparing reading HDF5 using this approach vs. native Zarr format: <br>
[](https://aws-uswest2-binder.pangeo.io/v2/gh/intake/fsspec-reference-maker/main?urlpath=lab%2Ftree%2Fexamples%2Fike_intake.ipynb)