# Csv Schema
[](https://hex.pm/packages/csv_schema)
[](https://travis-ci.org/primait/csv_schema)
[](https://opensource.org/licenses/MIT)
Csv schema is a library helping you to build Ecto.Schema-like modules having a csv file as source.
The idea behind this library is give the possibility to create, at compile-time, a self-contained module exposing functions to retrieve data starting from a CSV.
## Installation
If [available in Hex](https://hex.pm/docs/publish), the package can be installed
by adding `csv_schema` to your list of dependencies in `mix.exs`:
```elixir
def deps do
[
{:csv_schema, "~> 0.2.0"}
]
end
```
## Usage
Supposing you have a CSV file looking like this:
id | first_name | last_name | email | gender | ip_address | date_of_birth
:--:|:----------:|:----------:|:-----------------------------:|:------:|:---------------:|:------------:
1 | Ivory | Overstreet | ioverstreet0@businessweek.com | Female | 30.138.91.62 | 10/22/2018
2 | Ulick | Vasnev | uvasnev1@vkontakte.ru | Male | 35.15.164.70 | 01/19/2018
3 | Chloe | Freemantle | cfreemantle2@parallels.com | Female | 133.133.113.255 | 08/13/2018
... | ... | ... | ... | ... | ... | ...
Is possible to create an Ecto.Schema-like repository using `Csv.Schema` macro
```elixir
defmodule Person do
use Csv.Schema
alias Csv.Schema.Parser
schema "path/to/person.csv" do
field :id, "id", key: true
field :first_name, "first_name", filter_by: true
field :last_name, "last_name"
field :email, "email", unique: true
field :gender, "gender", filter_by: true
field :ip_address, "ip_address"
field :date_of_birth, "date_of_birth", parser: &Parser.date!(&1, "{0M}/{0D}/{0YYYY}")
end
end
```
Note that it's not a requirement to map all fields, but every field mapped must
have a column in csv file.
For example the following field configuration will result in a compilation error
```elixir
field :id, "non_existing_id", ....
```
Schema could be configured using a custom separator
```elixir
use Csv.Schema, separator: ?,
```
Moreover it's possible to configure if csv file has or has not an header. Depending
on header param value field config changes
```elixir
# Csv with header
schema "path/to/person.csv" do
field :id, "id", key: true
...
end
# Csv without header. Note that field 1 is binded with the first csv column. Index goes from 1 to N
schema "path/to/person.csv" do
field :id, 1, key: true
...
end
```
Now Person module is a struct, defined like this:
```elixir
defmodule Person do
defstruct id: nil,
first_name: nil,
last_name: nil,
email: nil,
gender: nil,
ip_address: nil,
date_of_birth: nil
end
```
This macro creates for you inside Person module those functions:
```elixir
def by_id(integer_key), do: ...
def filter_by_first_name(string_value), do: ...
def by_email(string_value), do: ...
def filter_by_gender(string_value), do: ...
def get_all, do: ...
```
Where:
- `by_id` returns a `%Person{}` or `nil` if key is not mapped in csv
- `filter_by_first_name` returns a `[%Person{}, %Person{}, ...]` or `[]` if input predicate does not match any person
- `by_email` returns a `%Person{}` or `nil` if no person have provided email in csv
- `filter_by_gender` returns a `[%Person{}, %Person{}, ...]` or `[]` if input predicate does not match any person gender
- `get_all` return all csv rows as a Stream
## Field configuration
Every field should be formed like this:
```
field {struct_field}, {csv_header}, {opts}
```
where:
- `{struct_field}` will be the struct field name. Could be configured as `string` or as `atom`
- `{csv_header}` is the csv column name from where get values. Must be configured using string only
- `{opts}` is a keyword list containing special configurations
opts:
- `:key`: boolean. At most one key could be set. If set to true creates the `by_{name}` function for you.
- `:unique`: boolean. If set to true creates the `by_{name}` function for you. All csv values must be unique or an exception is raised
- `:filter_by`: boolean. If set to true creates the `filter_by_{name}` function
- `:parser`: function. An arity 1 function used to map values from string to a custom type
Note that every configuration is optional
## Keep in mind
Compilation time increase in a linear manner if csv contains lots of lines and you
configure multiple fields candidate for method creation (flags `key`, `unique` and/or `filter_by` set to true)
Because "without data you're just another person with an opinion" here some data
csv rows | key | unique | filter_by | compile time µs
--------:|:---:|:------:|:---------:|----------------:
1_000 | no | 0 | 0 | 419 ms
1_000 | yes | 1 | 1 | 1_980 ms
1_000 | yes | 2 | 2 | 2_542 ms
1_000 | yes | 2 | 4 | 3_565 ms
1_000 | yes | 2 | 0 | 1_758 ms
1_000 | yes | 0 | 4 | 2_090 ms
1_000 | no | 2 | 0 | 1_634 ms
1_000 | no | 0 | 4 | 1_971 ms
5_000 | no | 0 | 0 | 2_410 ms
5_000 | yes | 1 | 1 | 15_282 ms
5_000 | yes | 2 | 2 | 22_478 ms
5_000 | yes | 2 | 4 | 28_060 ms
5_000 | yes | 2 | 0 | 16_254 ms
5_000 | yes | 0 | 4 | 15_043 ms
5_000 | no | 2 | 0 | 14_518 ms
5_000 | no | 0 | 4 | 12_931 ms
10_000 | no | 0 | 0 | 4_962 ms
10_000 | yes | 1 | 1 | 28_995 ms
10_000 | yes | 2 | 2 | 42_817 ms
10_000 | yes | 2 | 4 | 54_759 ms
10_000 | yes | 2 | 0 | 37_166 ms
10_000 | yes | 0 | 4 | 29_913 ms
10_000 | no | 2 | 0 | 33_578 ms
10_000 | no | 0 | 4 | 29_096 ms
5 compilations average time.
Executed on my machine:
Lenovo Thinkpad T480
CPU: Intel(R) Core(TM) i7-8550U CPU @ 1.80GHz
RAM: 32GB
