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markdown

# retreiving my issue activity

retreive my activity with the github graphql api.

# retreiving my issue activity

retreive my activity with the github graphql api.

retreiving my issue activity

retreive my activity with the github graphql api.

In 1

code

    
    %reload_ext pidgy
    import requests, pandas
    from info import header
    __import__("requests_cache").install_cache(allowable_methods=["POST"])

    
    %reload_ext pidgy
    import requests, pandas
    from info import header
    __import__("requests_cache").install_cache(allowable_methods=["POST"])

markdown

## construct the query from parameters

we use `%` string formatting because of the braces in graphql syntaxes.

## construct the query from parameters

we use `%` string formatting because of the braces in graphql syntaxes.


        {'data': {'text/html': 'construct the query from parameters
\nwe use % string formatting because of the braces in graphql syntaxes.\n'}}

construct the query from parameters

we use % string formatting because of the braces in graphql syntaxes.

In 2

code

    def get_stamps(user="tonyfast", repo="iota-school/notebooks-for-all"):
        return \
query { 
  search(type:ISSUE, query: "user:%s repo:%s", first: 100) {
    edges {
      node {
      ... on Issue {
        url
      }
       ... on PullRequest {
        url
      }
      ... on Comment {
        publishedAt
      }
      }
    }
  }
}\
    
            % (user, repo)

    def get_stamps(user="tonyfast", repo="iota-school/notebooks-for-all"):
        return \
query { 
  search(type:ISSUE, query: "user:%s repo:%s", first: 100) {
    edges {
      node {
      ... on Issue {
        url
      }
       ... on PullRequest {
        url
      }
      ... on Comment {
        publishedAt
      }
      }
    }
  }
}\
    
            % (user, repo)

def get_stamps(user="tonyfast", repo="iota-school/notebooks-for-all"):
    return \

query { search(type:ISSUE, query: "user:%s repo:%s", first: 100) { edges { node { ... on Issue { url } ... on PullRequest { url } ... on Comment { publishedAt } } } } }\

        % (user, repo)

In 3

code

<details open="">
    <summary>
a graphql query the find the dates a user made comments on issues or pull requests.
    </summary>


```graphql
{{get_stamps()}}
```

</details>

<details open>
    <summary>
a graphql query the find the dates a user made comments on issues or pull requests.
    </summary>


```graphql
{{get_stamps()}}
```

</details>

a graphql query the find the dates a user made comments on issues or pull requests.

query { 
  search(type:ISSUE, query: "user:tonyfast repo:iota-school/notebooks-for-all", first: 100) {
    edges {
      node {
      ... on Issue {
        url
      }
       ... on PullRequest {
        url
      }
      ... on Comment {
        publishedAt
      }
      }
    }
  }
}

In 4

code

    df = pandas.DataFrame((
        response := requests.post("https://api.github.com/graphql", json=dict(query=get_stamps()), **header)
    ).json()["data"]["search"]["edges"])["node"].apply(pandas.Series)
    df.publishedAt = df.publishedAt.pipe(pandas.to_datetime)

    df = pandas.DataFrame((
        response := requests.post("https://api.github.com/graphql", json=dict(query=get_stamps()), **header)
    ).json()["data"]["search"]["edges"])["node"].apply(pandas.Series)
    df.publishedAt = df.publishedAt.pipe(pandas.to_datetime)

df = pandas.DataFrame((
    response := requests.post("https://api.github.com/graphql", json=dict(query=get_stamps()), **header)
).json()["data"]["search"]["edges"])["node"].apply(pandas.Series)
df.publishedAt = df.publishedAt.pipe(pandas.to_datetime)

In 5

code

    freq = df.groupby(pandas.Grouper(freq="1D", key="publishedAt")).count()

    freq = df.groupby(pandas.Grouper(freq="1D", key="publishedAt")).count()

freq = df.groupby(pandas.Grouper(freq="1D", key="publishedAt")).count()

markdown

what days where these comments made at?

what days where these comments made at?

what days where these comments made at?

In 6

code

    days = freq[freq.astype(bool)].dropna()
    days

    days = freq[freq.astype(bool)].dropna()
    days

	url
publishedAt
2015-08-07 00:00:00+00:00	1.0
2016-01-02 00:00:00+00:00	2.0
2016-01-03 00:00:00+00:00	3.0
2016-01-11 00:00:00+00:00	1.0
2016-01-23 00:00:00+00:00	1.0
...	...
2022-11-08 00:00:00+00:00	2.0
2022-11-16 00:00:00+00:00	1.0
2022-11-21 00:00:00+00:00	1.0
2022-11-22 00:00:00+00:00	1.0
2022-12-14 00:00:00+00:00	1.0

64 rows × 1 columns

days = freq[freq.astype(bool)].dropna()
days

In 7

code

    days

    days

	url
publishedAt
2015-08-07 00:00:00+00:00	1.0
2016-01-02 00:00:00+00:00	2.0
2016-01-03 00:00:00+00:00	3.0
2016-01-11 00:00:00+00:00	1.0
2016-01-23 00:00:00+00:00	1.0
...	...
2022-11-08 00:00:00+00:00	2.0
2022-11-16 00:00:00+00:00	1.0
2022-11-21 00:00:00+00:00	1.0
2022-11-22 00:00:00+00:00	1.0
2022-12-14 00:00:00+00:00	1.0

64 rows × 1 columns

days

In None

code