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@ -20,38 +20,57 @@ library(shroomDK)
Documentation can be viewed within RStudio with ```?create_query_token``` for new packages you may need to restart R to get to the documentation. It is summarized here:
Description
Uses Flipside ShroomDK to create a Query Token to access Flipside Crypto data. The query token is cached up to ttl minutes allowing for pagination and multiple requests before expending more daily request uses.
| Item | Definition |
| ----------- | ----------- |
| Description | Uses Flipside ShroomDK to create a Query Token to access Flipside Crypto data. The query token is cached up to ttl minutes allowing for pagination and multiple requests before expending more daily request uses.|
| Usage | create_query_token(query, api_key, ttl = 10, cache = TRUE)|
| query | Flipside Crypto Snowflake SQL compatible query as a string. |
| api_key | Flipside Crypto ShroomDK API Key |
| ttl | time (in minutes) to keep query in cache. |
| cache | Use cached results; set as FALSE to re-execute. |
| Value | list of `token` and `cached` use `token` in `get_query_from_token()`|
Usage
create_query_token(query, api_key, ttl = 10, cache = TRUE)
Arguments
query
Flipside Crypto Snowflake SQL compatible query as a string.
api_key
Flipside Crypto ShroomDK API Key
ttl
time (in minutes) to keep query in cache.
cache
Use cached results; set as FALSE to re-execute.
Value
list of'token' and 'cached' use 'token' in 'get_query_from_token()'
Examples
Run examples
## Not run:
```
# example
create_query_token(
query = "SELECT * FROM ethereum.core.fact_transactions LIMIT 1",
api_key = readLines("api_key.txt"),
api_key = readLines("api_key.txt"), # gitignore your api_key! don't share!
ttl = 15,
cache = TRUE)
```
### get_query_from_token()
Documentation can be viewed within RStudio with ```?get_query_from_token``` for new packages you may need to restart R to get to the documentation. It is summarized here:
| Item | Definition |
| ----------- | ----------- |
| Description | Uses Flipside ShroomDK to access a Query Token. Query tokens are cached up to 'ttl' minutes for each 'query'. This function is for pagination and multiple requests while reducing your use of your daily rate limit. Note: To reduce payload it returns a list of outputs (separating column names from rows).|
| Usage | get_query_from_token(query_token, api_key, page_number = 1, page_size = 1e+05)|
| query_token | token from 'create_query_token()' |
| api_key | Flipside Crypto ShroomDK API Key |
| page_number |Query tokens are cached and 100k rows max. Get up to 1M rows by going through pages. |
| page_size | Default 100,000. Paginate via page_number. |
| Value | returns a request of length 8: `results`, `columnLabels`, `columnTypes`, `startedAt`, `endedAt`, `pageNumber`, `pageSize`, `status` |
```
# example
query = create_query_token("SELECT * FROM ETHEREUM.CORE.FACT_TRANSACTIONS LIMIT 10000", api_key) #gitignore your API key!
get_query_from_token(query$token, api_key, 1, 10000)
```
### clean_query()
Documentation can be viewed within RStudio with ```?clean_query``` for new packages you may need to restart R to get to the documentation. It is summarized here:
| Item | Definition |
| ----------- | ----------- |
| Description | Cleans Query to be in Data Frame format |
| Usage | clean_query(request, try_simplify = TRUE)|
| `request` | The request output from `get_query_from_token()` |
|try_simplify | because requests can return JSON and/or may not have the same length across values, they may not be data frame compliant (all columns having the same number of rows). A key example would be TX_JSON in EVM FACT_TRANSACTION tables which include 50+ extra details from transaction logs. But other examples like NULLs TO_ADDRESS can have similar issues. Default TRUE. |
| Value | Always returns a data frame. If 'try_simplify' is `FALSE` OR if 'try_simplify' `TRUE` fails (columns having different rows) then the data frame is comprised of lists, where each column must be coerced to a desired class (e.g., with `as.numeric()`) to ensure each column has the same number of rows.|
Note: The vast majority (95%+) of queries will return a simple data frame with the classes coerced intelligently (e.g., Block_Number being numeric). But check the warnings and check your column classes, if the class is a list then try_simplify failed (i.e., not all columns have the same number of rows when coerced).