- figure-1a__number__auto-loans
- figure-1a__volume__auto-loans
- figure-1c__map__auto-loans
- figure-1b__yoy-number__auto-loans
- figure-1b__yoy-volume__auto-loans
- figure-2a__deep-subprime__auto-loans
- figure-2a__subprime__auto-loans
- figure-2a__near-prime__auto-loans
- figure-2a__prime__auto-loans
- figure-2a__superprime__auto-loans
- figure-2b__deep-subprime__auto-loans
- figure-2b__subprime__auto-loans
- figure-2b__near-prime__auto-loans
- figure-2b__prime__auto-loans
- figure-2b__superprime__auto-loans
- figure-3a__low__auto-loans
- figure-3a__moderate__auto-loans
- figure-3a__middle__auto-loans
- figure-3a__high__auto-loans
- figure-3b__low__auto-loans
- figure-3b__moderate__auto-loans
- figure-3b__middle__auto-loans
- figure-3b__high__auto-loans
- figure-4a__younger-than-30__auto-loans
- figure-4a__30-to-44__auto-loans
- figure-4a__45-to-64__auto-loans
- figure-4a__65-and-older__auto-loans
- figure-4b__younger-than-30__auto-loans
- figure-4b__30-to-44__auto-loans
- figure-4b__45-to-64__auto-loans
- figure-4b__65-and-older__auto-loans
- figure-1a__number__credit-cards
- figure-1a__volume__credit-cards
- figure-1c__map__credit-cards
- figure-1b__yoy-number__credit-cards
- figure-1b__yoy-volume__credit-cards
- figure-2a__deep-subprime__credit-cards
- figure-2a__subprime__credit-cards
- figure-2a__near-prime__credit-cards
- figure-2a__prime__credit-cards
- figure-2a__superprime__credit-cards
- figure-2b__deep-subprime__credit-cards
- figure-2b__subprime__credit-cards
- figure-2b__near-prime__credit-cards
- figure-2b__prime__credit-cards
- figure-2b__superprime__credit-cards
- figure-3a__low__credit-cards
- figure-3a__moderate__credit-cards
- figure-3a__middle__credit-cards
- figure-3a__high__credit-cards
- figure-3b__low__credit-cards
- figure-3b__moderate__credit-cards
- figure-3b__middle__credit-cards
- figure-3b__high__credit-cards
- figure-4a__younger-than-30__credit-cards
- figure-4a__30-to-44__credit-cards
- figure-4a__45-to-64__credit-cards
- figure-4a__65-and-older__credit-cards
- figure-4b__younger-than-30__credit-cards
- figure-4b__30-to-44__credit-cards
- figure-4b__45-to-64__credit-cards
- figure-4b__65-and-older__credit-cards
- figure-1a__number__mortgages
- figure-1a__volume__mortgages
- figure-1c__map__mortgages
- figure-1b__yoy-number__mortgages
- figure-1b__yoy-volume__mortgages
- figure-2a__deep-subprime__mortgages
- figure-2a__subprime__mortgages
- figure-2a__near-prime__mortgages
- figure-2a__prime__mortgages
- figure-2a__superprime__mortgages
- figure-2b__deep-subprime__mortgages
- figure-2b__subprime__mortgages
- figure-2b__near-prime__mortgages
- figure-2b__prime__mortgages
- figure-2b__superprime__mortgages
- figure-3a__low__mortgages
- figure-3a__moderate__mortgages
- figure-3a__middle__mortgages
- figure-3a__high__mortgages
- figure-3b__low__mortgages
- figure-3b__moderate__mortgages
- figure-3b__middle__mortgages
- figure-3b__high__mortgages
- figure-4a__younger-than-30__mortgages
- figure-4a__30-to-44__mortgages
- figure-4a__45-to-64__mortgages
- figure-4a__65-and-older__mortgages
- figure-4b__younger-than-30__mortgages
- figure-4b__30-to-44__mortgages
- figure-4b__45-to-64__mortgages
- figure-4b__65-and-older__mortgages
- figure-1a__number__student-loans
- figure-1a__volume__student-loans
- figure-1c__map__student-loans
- figure-1b__yoy-number__student-loans
- figure-1b__yoy-volume__student-loans
- figure-2a__deep-subprime__student-loans
- figure-2a__subprime__student-loans
- figure-2a__near-prime__student-loans
- figure-2a__prime__student-loans
- figure-2a__superprime__student-loans
- figure-2b__deep-subprime__student-loans
- figure-2b__subprime__student-loans
- figure-2b__near-prime__student-loans
- figure-2b__prime__student-loans
- figure-2b__superprime__student-loans
- figure-3a__low__student-loans
- figure-3a__moderate__student-loans
- figure-3a__middle__student-loans
- figure-3a__high__student-loans
- figure-3b__low__student-loans
- figure-3b__moderate__student-loans
- figure-3b__middle__student-loans
- figure-3b__high__student-loans
- figure-4a__younger-than-30__student-loans
- figure-4a__30-to-44__student-loans
- figure-4a__45-to-64__student-loans
- figure-4a__65-and-older__student-loans
- figure-4b__younger-than-30__student-loans
- figure-4b__30-to-44__student-loans
- figure-4b__45-to-64__student-loans
- figure-4b__65-and-older__student-loans
auto-loans, origination-activity, line
figure-1a
Number of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, origination-activity, line
figure-1a
Volume of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, origination-activity, map
figure-1c
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, origination-activity, bar
figure-1b
Number of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, origination-activity, bar
figure-1b
Volume of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, line
figure-2a
Deep subprime (credit scores below 580)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, line
figure-2a
Subprime (credit scores 580 - 619)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, line
figure-2a
Near prime (credit scores 620 - 679)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, line
figure-2a
Prime (credit scores 680 - 719)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, line
figure-2a
Superprime (credit scores 720 and above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, bar
figure-2b
Deep subprime (credit scores below 580)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, bar
figure-2b
Subprime (credit scores 580 - 619)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, bar
figure-2b
Near prime (credit scores 620 - 679)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, bar
figure-2b
Prime (credit scores 680 - 719)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-risk-profiles, bar
figure-2b
Superprime (credit scores 720 and above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, income-level, line
figure-3a
Low income (relative income less than 50%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, income-level, line
figure-3a
Moderate income (relative income 50 to 79%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, income-level, line
figure-3a
Middle income (relative income 80 to 119%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, income-level, line
figure-3a
High income (relative income 120% or above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, income-level, bar
figure-3b
Low income (relative income less than 50%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, income-level, bar
figure-3b
Moderate income (relative income 50 to 79%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, income-level, bar
figure-3b
Middle income (relative income 80 to 119%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, income-level, bar
figure-3b
High income (relative income 120% or above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-age, line
figure-4a
Younger than 30
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-age, line
figure-4a
Age 30 to 44
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-age, line
figure-4a
Age 45 to 64
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-age, line
figure-4a
Age 65 and older
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-age, bar
figure-4b
Younger than 30
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-age, bar
figure-4b
Age 30 to 44
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-age, bar
figure-4b
Age 45 to 64
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
auto-loans, borrower-age, bar
figure-4b
Age 65 and older
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, origination-activity, line
figure-1a
Number of credit cards originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, origination-activity, line
figure-1a
Volume of credit cards originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, origination-activity, map
figure-1c
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, origination-activity, bar
figure-1b
Number of credit cards originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, origination-activity, bar
figure-1b
Volume of credit cards originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, line
figure-2a
Deep subprime (credit scores below 580)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, line
figure-2a
Subprime (credit scores 580 - 619)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, line
figure-2a
Near prime (credit scores 620 - 679)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, line
figure-2a
Prime (credit scores 680 - 719)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, line
figure-2a
Superprime (credit scores 720 and above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, bar
figure-2b
Deep subprime (credit scores below 580)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, bar
figure-2b
Subprime (credit scores 580 - 619)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, bar
figure-2b
Near prime (credit scores 620 - 679)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, bar
figure-2b
Prime (credit scores 680 - 719)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-risk-profiles, bar
figure-2b
Superprime (credit scores 720 and above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, income-level, line
figure-3a
Low income (relative income less than 50%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, income-level, line
figure-3a
Moderate income (relative income 50 to 79%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, income-level, line
figure-3a
Middle income (relative income 80 to 119%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, income-level, line
figure-3a
High income (relative income 120% or above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, income-level, bar
figure-3b
Low income (relative income less than 50%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, income-level, bar
figure-3b
Moderate income (relative income 50 to 79%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, income-level, bar
figure-3b
Middle income (relative income 80 to 119%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, income-level, bar
figure-3b
High income (relative income 120% or above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-age, line
figure-4a
Younger than 30
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-age, line
figure-4a
Age 30 to 44
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-age, line
figure-4a
Age 45 to 64
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-age, line
figure-4a
Age 65 and older
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-age, bar
figure-4b
Younger than 30
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-age, bar
figure-4b
Age 30 to 44
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-age, bar
figure-4b
Age 45 to 64
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
credit-cards, borrower-age, bar
figure-4b
Age 65 and older
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, origination-activity, line
figure-1a
Number of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, origination-activity, line
figure-1a
Volume of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, origination-activity, map
figure-1c
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, origination-activity, bar
figure-1b
Number of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, origination-activity, bar
figure-1b
Volume of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, line
figure-2a
Deep subprime (credit scores below 580)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, line
figure-2a
Subprime (credit scores 580 - 619)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, line
figure-2a
Near prime (credit scores 620 - 679)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, line
figure-2a
Prime (credit scores 680 - 719)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, line
figure-2a
Superprime (credit scores 720 and above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, bar
figure-2b
Deep subprime (credit scores below 580)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, bar
figure-2b
Subprime (credit scores 580 - 619)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, bar
figure-2b
Near prime (credit scores 620 - 679)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, bar
figure-2b
Prime (credit scores 680 - 719)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-risk-profiles, bar
figure-2b
Superprime (credit scores 720 and above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, income-level, line
figure-3a
Low income (relative income less than 50%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, income-level, line
figure-3a
Moderate income (relative income 50 to 79%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, income-level, line
figure-3a
Middle income (relative income 80 to 119%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, income-level, line
figure-3a
High income (relative income 120% or above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, income-level, bar
figure-3b
Low income (relative income less than 50%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, income-level, bar
figure-3b
Moderate income (relative income 50 to 79%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, income-level, bar
figure-3b
Middle income (relative income 80 to 119%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, income-level, bar
figure-3b
High income (relative income 120% or above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-age, line
figure-4a
Younger than 30
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-age, line
figure-4a
Age 30 to 44
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-age, line
figure-4a
Age 45 to 64
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-age, line
figure-4a
Age 65 and older
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-age, bar
figure-4b
Younger than 30
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-age, bar
figure-4b
Age 30 to 44
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-age, bar
figure-4b
Age 45 to 64
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
mortgages, borrower-age, bar
figure-4b
Age 65 and older
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, origination-activity, line
figure-1a
Number of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, origination-activity, line
figure-1a
Volume of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, origination-activity, map
figure-1c
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, origination-activity, bar
figure-1b
Number of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, origination-activity, bar
figure-1b
Volume of loans originated
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, line
figure-2a
Deep subprime (credit scores below 580)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, line
figure-2a
Subprime (credit scores 580 - 619)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, line
figure-2a
Near prime (credit scores 620 - 679)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, line
figure-2a
Prime (credit scores 680 - 719)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, line
figure-2a
Superprime (credit scores 720 and above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, bar
figure-2b
Deep subprime (credit scores below 580)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, bar
figure-2b
Subprime (credit scores 580 - 619)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, bar
figure-2b
Near prime (credit scores 620 - 679)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, bar
figure-2b
Prime (credit scores 680 - 719)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-risk-profiles, bar
figure-2b
Superprime (credit scores 720 and above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, income-level, line
figure-3a
Low income (relative income less than 50%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, income-level, line
figure-3a
Moderate income (relative income 50 to 79%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, income-level, line
figure-3a
Middle income (relative income 80 to 119%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, income-level, line
figure-3a
High income (relative income 120% or above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, income-level, bar
figure-3b
Low income (relative income less than 50%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, income-level, bar
figure-3b
Moderate income (relative income 50 to 79%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, income-level, bar
figure-3b
Middle income (relative income 80 to 119%)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, income-level, bar
figure-3b
High income (relative income 120% or above)
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-age, line
figure-4a
Younger than 30
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-age, line
figure-4a
Age 30 to 44
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-age, line
figure-4a
Age 45 to 64
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-age, line
figure-4a
Age 65 and older
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-age, bar
figure-4b
Younger than 30
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-age, bar
figure-4b
Age 30 to 44
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-age, bar
figure-4b
Age 45 to 64
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.
student-loans, borrower-age, bar
figure-4b
Age 65 and older
Source: Download CSV file
Date published: December 2016
Note: Data from the last six months are not final.


RSMoneyMaker
Usage
To run the example project, clone the repo, and run pod install
from the Example directory first.
Requirements
Installation
RSMoneyMaker is available through CocoaPods. To install it, simply add the following line to your Podfile:
pod "RSMoneyMaker"
Author
Venkat S. Rao<EMAIL_ADDRESS>License
RSStoreKit is available under the MIT license. See the LICENSE file for more info.


--- layout: post esbma_id: 3068 title: Unicode date: 2014-04-18 12:00:00 keywords: mssql_to_sqlite teaser: SQLite has no distinction between CHAR and NCHAR. Everything is Unicode. ---
(This entry is part of a series. The audience: SQL Server developers. The topic: SQLite on mobile devices.)
First, go read this blog entry by Miguel de Icaza. Right now. I'll wait.
Welcome back. Now let me apologize.  But the topic here is Unicode, so there really is no other way.
The relevant difference with SQLite is easy to describe:
In the world of Windows and SQL Server, you have all kinds of possible code pages.
In SQLite, everything is Unicode.
But if you don't have much context on these issues, I haven't really told you much. Let's go further.
I don't want to rewrite articles that have already been written quite well. So you should probably also go read this blog entry by Joel Spolsky. I'll be here when you get back.
SQL Server has two basic ways you store text:
You can use the char/varchar types, which can be used with one of several collations, each of which implies a specific code page, which implies a specific character encoding.
Or you can use the nchar/nvarchar types (note the extra 'n'), which are Unicode.
SQLite has no such distinction. All text in SQLite is Unicode.
It's a character set: a collection of characters, each with a number that can be used to refer to it.
More specifically, it's the only character set which is [trying to be] complete. If you choose any character set or encoding which is not Unicode, there will be characters you cannot use.
Saying that SQLite uses Unicode doesn't tell you how the text is actually represented. Unicode is not an encoding. It is more abstract than that. There are lots of different ways of representing Unicode as bytes.
In the Windows and SQL Server world, there is a long history of encoding Unicode in 16-bit-ish ways. Originally, this was UCS-2, a simple encoding which represents each character as a 16-bit number. But then the Unicode consortium realized that 16 bits are not enough, so they expanded the space to 32 bits. This left Microsoft in an awkward spot. UCS-2 is a fundamentally defective encoding of Unicode, since there are many characters in Unicode that simply cannot be represented.
If the goal of Unicode is to be complete, it is reasonable to say that, well actually, UCS-2 is not Unicode.
The conceptual replacement for UCS-2 is to use 32 bits for every character. This encoding is called UCS-4 or UTF-32. But now the wasted space for storing a simple English string is getting out of hand. Switching the complete works of Arthur Conan Doyle from ASCII (which is also an encoding) to UCS-4 would take four times as much space.
Gradually, the world seems to be adopting UTF-8 as the most popular Unicode encoding. This is a variable width encoding. Sometimes a single character is represented with just one byte. Sometimes it needs more. That's very unfortunate, but the only fixed width alternative is UCS-4, which is also very unfortunate. Choose which problem you prefer, but keep in mind that almost everybody has chosen to accept the problems of UTF-8.
But Microsoft has so much history with UCS-2 that transitioning everything to UTF-8 would be really hard. So they have been moving from UCS-2 to UTF-16, which is basically a variable width encoding built around a 16-bit unit instead of an 8-bit unit. UTF-16 is approximately the worst correct way of representing Unicode, unless you have invested billions of dollars in the fundamentally broken UCS-2, in which case UTF-16 is a pretty awesome way out of the mess you ended up in.
Just remember that if you're going out tonight to a club for pedantic nerds and you want to impress someone, you've got to keep the terminology straight:
Unicode is an abstraction, not an encoding, not a code page, not a data format, and not a font.
Saying your text is Unicode says nothing about how it is represented. It might be UTF-8. It might UTF-16. It might be code point numbers handwritten on Post-It notes stuck on the wall. All of these are valid representations of Unicode.
If you ever say anything to suggest that you think Unicode is 16 bits per character, you will be identified as clueless.
If you say that your text is stored in Unicode, you are not entirely incorrect, but people will wonder about whether you really know the difference between Unicode and the encodings of same.
SQLite always uses Unicode to represent text.
(Hopefully you are now screaming at me saying, "Yeah, but which encoding?!?")
The best answer to this question is: SQLite uses UTF-8. Forget about everything else.
A more correct answer to this question is: SQLite uses UTF-8 but also supports UTF-16.
Either way, there is no distinction between char and nchar. There is no way to save storage space in a column by realizing that you only use lower case english characters so it's safe to use char instead of nchar. There are no code pages. There is no way to move your Shift JIS data into SQLite without converting it to Unicode (or storing it as blobs, I suppose).
Microsoft has done a lot of things right, but its history with Unicode is very unfortunate. And it's not entirely their fault. They adopted Unicode early and it changed underneath them.
With respect to its emphasis on UTF-8, SQLite is far more typical of most non-Microsoft software today.


Hello! I currently reside in Florida. I am learning how to develop coherent web maps with the help of the University of Kentucky's New Maps Plus program.
When I am not at work or slumped over a keyboard I enjoy hiking, kayaking, and cycling around Florida's unique landscapes.


BEST SELLING ALBUMS
A list of best-selling albums by year and by country
Please select a year:
Please select a country of origin:
All
United States
United Kingdom
Do you want a SURPRISE?
Please choose
Yes
No
Go
Year
Artist
Nationality
Album


micro-mvc
This package exposes two very basic classes that can be used create reactive MVC interfaces.
Models are created from basic objects. Simply create an object with the desired properties, and instantiate the Model class with the object as the argument in the constructor:
JavaScript
let Model = mvc.Model;
let application = {
name: 'My Application',
version: '1.0.0'
};
let applicationModel = new Model(application);
The applicationModel
above will encapsulate the raw object and provide getters and setters for its properites. Setters for the properties will trigger events for which a View listens.
Views are established from a DOM object and existing models. It is assumed that the DOM is left unfilled, and upon construction, the View with force the model to emit an event that fills in all the data:
HTML

JavaScript
let View = mvc.View;
let applicationContainer = document.querySelector('.application-container');
let applicationView = new View(applicationContainer, applicationModel);


Long the intergalactic bottom, stop at 0, target the moon = Lambo.
Retweets
105
Likes
746
ITS SO EASY YOU GUYS
CANT YOU SEE THE HIGHER LOWS
But nonetheless the dumping is getting less and less each time
close to - or at the bottom I think
You feel/see it everywhere
twitter/general news etc
even discord is more quiet
@Hollowman9000 only stopping by now and then
CryptoNinjaa21-Jan-19 10:57 AM
Tbh when we hit around $3100-3200 a couple of weeks ago i thought we are close.
Cryptoon21-Jan-19 10:59 AM
double bottom at 3100?
Anyway, kmd discord still one of the - if not the most active one I am in
so that's also saying a lot tbh
jorian21-Jan-19 11:03 AM
still, 2019 could be a year long bottom
going sideways most of the year
4
CryptoNinjaa21-Jan-19 11:09 AM
Would agree that the lack of hollowman9000 would suggest we are in the "ive forgot all about crypto now" stage.
January 21, 2019: Anthony Day posted images on LinkedIn
Interesting
blackjok3r21-Jan-19 12:56 PM
Public sector and agricultural benift the most
Public sector is definatly going to be one of the last to adopt I think... All those ppl who are employed to litterally do nothing are not going away easily.

ComputerGenie 👴👴👴21-Jan-19 01:10 PM
That "gay horse" has a spire emanating form its forehead that can stab you in the feken eye
4
Caglio21-Jan-19 01:10 PM
I have an eye patch
ComputerGenie 👴👴👴21-Jan-19 01:10 PM
do you have 2?

Caglio21-Jan-19 01:12 PM
awww, butthurt much ?
 Tradeview chat is dying. Also agree it could take a really long time to see anything positive despite this.
however, longs and shorts data on bfx still show longs are a massive target, they need to be continually destroyed until they give up before we can actually go up properly.... I personally gave up and am just watching BTC, waiting for optimal entry zones and watching price action. Other traders are probably buying every level, getting stopped out, and trying again. Revenge traders who do not want to miss the next great bull run... when they all go short we can go up
sadly this could be below 3k, I hope not though, hopefully a good shakedown soon and some spikes in long and short data would be enough for a new upswing.
$KMD 3D Chart:
Support is at 1845 sats, we will see a bounce to the resistance line at 2579 sats.
Accumulation has been growing upon finding the local bottom. The 2.6K Sat to 3.4K sat line has a lot of volume gaps - realistically we will see move above this area to 3.4K ...
0x0321-Jan-19 03:29 PM
i'd just like to say that crex24 wasnt able to answer my question despite asking once a day for now 4 days in a row. maybe not the best of exchanges with this kind of 'support'(edited)
and it's definitely not that i was asking for plans for la bomba or something
bishop21-Jan-19 03:42 PM
Am I the only one bothered when TA commentary speaks in absolutes?
Cryptoon21-Jan-19 03:43 PM
I have been seeing the same types of messages that KMD is definitely hitting 30k+ within xx time etc for the past few months
1
Still waiting
bishop21-Jan-19 03:44 PM
Exactly... the evidence can provide an idea of what COULD happen, not what WILL happen
dokrates21-Jan-19 04:07 PM
Next resistance 26k
Cryptoon21-Jan-19 04:34 PM
I'll take it
ver_User21-Jan-19 04:47 PM
In particular when it's based off one trendline and basic of basic support/resistance. Even gorillas can spot that stuff.
The other day I saw someone post "IN 36 HOURS EURUSD WILL BE AT 1.15XX" so I said to him, probable, maybe, not WILL. He said, "SEE MY PAST ANALYSIS".
36 hours later, euro was at 1.143...
upside seems likely, but time is the hardest factor in charting IMO, especially when making long term lows/highs or corrections.
Marketing Reality in Blockchain. Following my post on Blockchain Marketing, I've classified some projects in 3 buckets: Right, Under & Over Marketed. It is based on their own or community-driven activity. I understand some will push back, but this is how I view the market ...
@wmougayar $KMD so under marketed it fell off the page...@KomodoPlatform
Thx for the inspiration @tolken
Hahaha
LocoMB21-Jan-19 09:00 PM
why @ComputerGenie 👴👴👴 now a pink unicorn? to provide s.t. to rant about for hollowman? (edited)
Cryptoon21-Jan-19 09:19 PM
@Caglio said it best
I just always found you like a masculine tough guy, not a gay horse
ComputerGenie 👴👴👴21-Jan-19 09:23 PM
is still waiting for an explanation as to how his unicorn isn't masculine....
Cryptoon21-Jan-19 09:49 PM
I guess because it's pink and the general consensus is that pink is for girls
if it were a black unicorn with rainbow manes
now THAT would the the epitome of masculinity
bishop21-Jan-19 10:00 PM
I could use a long, firm, unicorn in my life
1
1
ComputerGenie 👴👴👴21-Jan-19 10:27 PM
and the general consensus is that pink is for girls
and that slavery is still a public good because it's still 1804?
Lieutenant21-Jan-19 10:32 PM
btc again dump. soon kmd 16k sat
tolken21-Jan-19 10:57 PM
What time will dump happen?
1
meatspoon21-Jan-19 11:01 PM
Lieutenant’s comments kind of read like he is actually yelling them into an old radio over the din of incoming mortar and MG42 fire. No time for superfluous words.


In this tutorial, we will:
Explore the Boston Housing Dataset like what it looks like, what are the features available and what we need to predict.
Implement a Simple Linear Regressor using Tensorflow and see how well the regressor performs on this data using the decrease in the Cost/Loss Function depicted using a plot w.r.t Epochs and other metrics.
Implement a LinearRegressor and a DNNRegressor using Tensorflow Estimator API and see how easy it is to implement a regressor using Tensorflow Estimator API.
Requirements
- OS: Ubuntu/AWS Cloud/Google Cloud/Windows
- Python 3+
- Tensorflow
- Numpy [+ mkl for Windows]
Just show me the Code !!
The code for this tutorial is available as a iPython notebook here.
So, let's get started.
Exploring Boston Housing Price Dataset
Load Data and Feature Intuition
The first step is to load the dataset and do any preprocessing if necessary. To load the dataset, I'll be using scikit-learn as it contains this dataset which contains the description [DESCR] of each feature, data i.e. the feature values and finally the target i.e. the labels.
NOTE: If you want to download a dataset from any website, then you might required to do some preprocessing, but I am not covering that step here.
Once we have downloaded the dataset, let's use pandas library and get some insight about the dataset like how well the features correlate with the output i.e. the prices, how much the features correlate with each other and whether a change in the features has a positive or a negative impact on the output. Also, an important thing to notice would be that if the dataset is balanced or not.
The above code gives us a lot of useful information about the dataset. It tells us the important features that we must look at while implementing the algorithms for training on this dataset.
Data Preprocessing and Train-Test Split
Since, now we know that all the features that are important and how they correlate with each other, we can just go on and implement the algorithm to train it, can't we !! Well......not just yet.
Before sending the data to the model, an important step is data preprocessing and then cross-validation. Since, we have the dataset that has values for each feature which lie in different ranges i.e. some of those are in hundreds and some of them are in decimal points etc. So, we need to normalize them so that they all lie on the same scale. This way we make sure that the small values are not entirely neglected and the larger values get more importance.
Also, we cannot send the whole data as it is to train the model as this can lead to Overfitting i.e. since the dataset is small, the model can try to learn the dataset and fit to that. This leads to a very good performance on the training data but when we try it on an external data, the model performs pretty bad.
One more thing to consider is that the preprocessing will be applied to the training and test features only and not the labels as we need the output in the range of the labels.
So, let's get started.
Now that we are done with the hard part, it's time to define our Regressor models and see that how well they perform for predicting the house prices.
Linear Regression using Tensorflow
In this part, we will implement the Linear Regression model using pure tensorflow and no other wrappers around it. We will define our placeholders, variables and train the model to reduce the cost function using a Optimizer function.
So, let's get started.
So, we just trained a basic tensorflow model to predict the housing prices.
Tensorflow Linear Regressor using Estimator API
In this part, we'll leverage the same preprocessed dataset but with a different approach. In this, we'll be using a Linear Regressor model from Tensorflow's Estimator API.
So, we just trained a Linear Regressor model using tensorflow's Estimator API to predict the housing prices.
NOTE that the aim of this tutorial is to get you acquainted with the Estimator API and show that how it works. The current loss using this API for this example is a bit high and this model can be tuned further to reduce that error and get better predictions.
Tensorflow DNN Regressor using Estimator API
In this part, we'll leverage the same preprocessed dataset but with a different approach. In this, we'll be using a DNN Regressor model from Tensorflow's Estimator API.
So, we just trained a DNN Regressor model using tensorflow's Estimator API to predict the housing prices.
NOTE that the aim of this tutorial is to get you acquainted with the Estimator API and show that how it works. The current loss using this API for this example is a bit high and this model can be tuned further to reduce that error and get better predictions.
So, we have reached the end of this tutorial. I hope I was able to make you understand that how we can use Tensorflow and the Estimator API for a Regression task.
In the next tutorial, we'll go over on how to use Tensorflow and the Estimator API for Classification Task.
For more projects and code, follow me on Github
Please feel free to leave any comments, suggestions, corrections if any :)
comments powered by Disqus


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I obtained eight fentanyl patches (each one containing 5 mg fentanyl - 50 mcg/hr time released) which I found in the garbage of my grandma who has died of cancer recently.
There are numerous descriptions on how to use the fentanyl from time-released patches. Some sources recommend against cutting it open, saying it is a waste, but I have found a good way. If I make a small hole in the plastic patches, for instance, with a needle, and firmly press on the patch, I can easily push the gel out. I'm careful not to push the needle through the entire patch, just reaching the middle layer with the gel in it. Only need a tiny drop, am careful not too use too much. It is possible to build up the dose slowly: within 30 seconds after inhaling I can feel the effect. Don't want to take too much of this powerful stuff. When I have obtained enough gel out of the patch, I close the hole with a piece of tape, pressing firmly, it must be closed well for storage. This way I can use a bit of the patch many times.
I use a spoon to put the gel on a piece of tinfoil and have to remember where, because the gel is transparent. I fold the tin foil inwards horizontally and vertically and folding outwards again, so I see two folding lines making a cross, and putting the stuff there - I know where to heat and inhale.
Then I need a lighter and a little tube or pipe, or any other small, hollow, cylinder-shaped object. Don't need a very big one. I just make sure to hold it just above the gel when I heat it, otherwise the smoke which is not or barely visible may go somewhere else - this happened to me the first few times. So I hold the tinfoil with one hand, the tube in my mouth just above the gel, and heat it underneath with a lighter (or candle). Inhale. Hold it and exhale. Wait a few seconds to see if I already feel any effect. Repeat the process until I no longer hear the sishing sound from the heated gel, then it's gone.
When I follow these simple steps, I feel warm and nice and forget my problems and worries. If I take more the effect becomes even better. But if I take too much, I'll feel itching all over my body and will be unable to go to the toilet. I've never had vomiting problems with it but it is possible. I have experienced blurry vision many times with fentanyl.
It is very addictive too.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


It seems like everybody is talking about the internet of things (IoT) whether it is good or bad. The IoT is when everyday products like refrigerator, speakers, watches and more are connected to the internet and to one another. The Internet of things are already transforming our homes and workplaces. So, now the question arises what is the future of this Internet of things??
Wave of the future
In the future, there will be so many IP addresses, so many devices, sensors, things that we are wearing, things that we are interacting with that we don't even sense it. It will be a part of our presence all the time. Suppose imagine that we entered into a room that is dynamic and with all our permissions and all of that we can actually interact with the things going on in that room.
Major impact in the industry
IoT is transforming the everyday objects that surrounds us into an ecosystem of information that will enrich our lives. From speakers to parking spaces to our homes IoT is bringing a revolution everywhere. Smart homes and other connected products will not be aimed at home life only they are also going to have a major effect in the industrial growth too.
The new revolution
IoT is changing and transforming everything from business to life. Imaginations are boundless and opportunities are infinite. Everything is being wired up or connected wirelessly- architecture, energy efficient sensing, secure networks, cloud computing, IS based visualization and international activities. It means that the powerful information will be at our fingertips.
The global industrial sector is poised to undergo a fundamental structural change in the upcoming years. Equipment is becoming more and more digitized and connected establishing networks between machines, humans and the internet leading to the creation of higher productivity, better efficiency and more profitability.
Sources / References [If Any] : Internet


My name is Sayef Iqbal, a student programmer and IT network assistant at St. John's University. When I am not playing Cricket or doing BBQ, I like to learn new programming languages and cloud services, especially AWS. Most of the time, I am on my Ubuntu 18.04 machine either building native app pages in React-Native or learning about serverless cloud computation in AWS Lambda. The rest of the time, I am configuring network ACLs, creating SVIs or changing AAA commands in cisco switches and routers for St. John's University's IT-Network Department.
Computer science is a fast evolving profession where there is room and opportunity for anyone to develop new skills every single day. While I strive towrds building new skills in AWS, Networking, React-Native and other topics, I have work experience in designing and coding cli software for restaurant management systems, programming Sentiment analysis project in Java to analyze emotions from tweets, Vector Space modelling for textual similarity with query also using Java, Login Forms and CS Book app using React-Native and much more.
A command line interface for both customers and restaurant owners to be able to reserve seats and review restaurants. This simple peice of software utilizes the observer-observable pattern and is serializable hence both restaurants and customers are able to get notified for any new reviews that drops in.
Close ProjectBooklist is a mobile application built using react-native. It is inspired from stephengriders prokect of album list. But this mobile application lists the top 5 book of the week by calling my own api server hosted in my personal machine. To get the source code for this react-native project visit Booklist repository
Close ProjectThis video could be used to a way around to understand some basic configuration for deplying a lan network in a campus wide. The configuration covers basic concept of networking like Vlan, SVI, Static routes, SSH, Telnet etc.
Close ProjectThis simple program is written in java simply focusing on analyzing different characteristics of a tweet to validate it as postive or negative sentimental statement using machine learning algorithms. The findings are very interesting.To get the source code for this tweet sentiment analysis project visit Tweet Sentiment Analysis repository
Close ProjectThis project was to retrieve and rank the 50-100 most relevant documents from a list of 40,000 documents. Documents in this case is represented as a single sentence comprising of natural language words. I used vector space modelling and cosine similarity to find relevance. The documents were preprocessed and stemmed using Porter Stemmer library. In order to view the source code for VSR Model project visit Textual similarity repository
Close ProjectThis was a research done by me and Associate Professor. Fazel Keshtkat at St. John's University in order to understand how some building features (concrete walls, glass windows, floor size etc.) can contribute towards energy consumption. The main goal of this research was to classify good, bad and excellent energy consumption behavior shown by commercial buildings in the United states using raw data from U.S. Energy Information Adminstration. In order to acces the result sheet, analyzed data or our research paper please email me at<EMAIL_ADDRESS>Close Project


Meek Mill's Limited-Release DreamChaser Hats To Help Raise Funds For REFORM Alliance
by Yohance Kyles (@HUEYmixwitRILEY)The DC label head also worked with Michael Rubin to free a Pennsylvania inmate.
(AllHipHop News) Robert "Meek Mill" Williams continues to take steps to support criminal justice reform. Meek is now helping to raise money for the REFORM Alliance, a nonprofit dedicated to changing the laws, policies, and practices that perpetuate injustice in America.
Beginning November 26, Lids will sell limited-release DreamChasers hats. A percentage of the proceeds from the individual sale of each headpiece will be donated to the REFORM Alliance.
Meek Mill is the co-owner and creative director for Lids. He is also the co-founder of REFORM Alliance alongside Michael Rubin, Shawn “Jay-Z” Carter, Robert Kraft, Robert F. Smith, Clara Wu Tsai, Laura Arnold, Michael Novogratz, and Daniel S. Loeb.
“Having my own line with Lids is special, but I’m especially proud that proceeds from this hat will be used to help fix the broken criminal justice system,” said Mill. “I’m grateful that our team at Lids was committed to making a hat that’s stylish, but will go toward a greater cause.”
Last week, REFORM Alliance Co-Chairs Meek Mill and Michael Rubin helped free Philadelphia native Maurice Hudson from state prison. Hudson was sentenced to 1 ½ to 3 years because he could not afford to pay $1,941 in outstanding court costs.
The Pennsylvania Supreme Court ordered Hudson’s release on Friday morning. Rubin and fellow Philadelphia 76ers partner Josh Harris hosted Hudson as a VIP guest at the Sixers' home game against the Spurs that night.
Meek also provided Hudson and his family with new clothes from fashion designer Milano di Rouge as well as items from PUMA. Plus, the Grammy-nominated emcee is assisting the 29-year-old father with transitioning back to society and finding a job.


Item as wide as the content.
Item with more text in it. Because the contents of it are wider than the maximum width, it is clamped at 300 pixels.
Flexible item


Users
{{numberu}}
Projects
{{numberp}}
Tasks
{{numbert}}
Speciality
4
Last Update
Last Update
Last Update


Thanks for playing!
Do you want to be included in our experiment? All fields are optional, but it would contribute very helpful info to our research.
To find out more about what this experiment was investigating, please visit this page
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partipantid
browser
Name
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Place of birth
Where did you live between 1-14 years of age? (if you lived in more places, please list them below, specifying between what ages you lived in each of them)
Where do you live now?

What other languages do you speak, besides English, and what is your level of proficiency (beginner, intermediate, advanced)?
Have you ever been diagnosed for, or have you ever had hearing/speech problems?
Have you participated in a similar experiment in the past?
What do you think this experiment was for? What did you learn?


By chance, can anyone see what's wrong with this curl command?
curl --user userXX:passXXXX --data-binary '{"jsonrpc": "1.0", "id":"curltest", "method":"z_listunspent", "params": [1 100 false "[\"zs1wqykmk74mv2ezjscpxsgzrn4fasqwh50tgk0ym64m45c5yw5fjtpkps64gle963veqzuj04872z\"]" }' -H 'content-type: text/plain;' http://<IP_ADDRESS>:8923


--- title: Data Model ---
A series is identified by key, and a unique set of tags.
Keys, tag keys, and tag values can contain any valid unicode string, internally they are stored in UTF-8.
A series represents something over time, where something is currently either a set of data points, or events.
Java Class: {% include github-link.html module='heroic-component' name='metric.Point' %}
Each data point stores the timestamp at which they were sampled, and the value which they carry.
The timestamp is stored as a 64-bit number (long), which represents the number of milliseconds since the unix epoch.
The value is stored as a 64-bit floating point number (double).
A data point is then typically represented as a JSON array, with two elements.
[<timestamp>, <value>]
Java Class: {% include github-link.html module='heroic-component' name='metric.Event' %}
Events are currently experimental and not supported by the Cassandra backend.
Each event stores the timestamp at which they were sampled, and a JSON payload (preferrably small).
The timestamp is stored as a 64-bit number (long), which represents the number of milliseconds since the unix epoch.
The payload is a JSON payload stored as an arbitrarily sized binary blob.
An event is typically represented as a JSON array, with two elements.
[<timestamp>, {<payload>}]
We strongly encourage the concept of semantic series.
The idea behind semantic series is to move away from obscure identifiers and introduce metrics that are structured in a way that makes it easier for a human and a computer to reason about.
So a series like the idle cpu utilization for a host could be identified as the following.
{
"key": "system",
"tags": {
"host": "database.example.com",
"site": "lon",
"what": "cpu-idle-percentage",
"system-component": "cpu",
"cpu-type": "idle",
"unit": "%"
}
}
This can also be represented in a more compact, human readable format as below.
system { host=database.example.com, site=lon, what=cpu-idle-percentage, ... }
The need for semantic metrics becomes more apparent when you start to reason about how to model series for certain use cases using a traditional, hierarchical model.
Assume that the above series was stored in a hierarchical time series database like the following.
database.example.com.system.cpu-idle-percentage
By promoting the use of tags, and a convention over which tags should be used how, the problem becomes more manageable.
Instead of a strict hierarchy where discovery and expression is limited, you can have a multi-dimensional system that enables strong correlations and natural groupings.
Conversely, if a given convention is followed, an administrator learning what
a specific tag like what
means will find it easier to
navigate unknown contexts where that tag is used.


Widget module.
MIT. See LICENSE for full details.
Canvas widgets implement structured graphics. A canvas displays any number of items, which may be things like rectangles, circles, lines, and text. Items may be manipulated (e.g. moved or re-colored) and commands may be associated with items in much the same way that the bind command allows commands to be bound to widgets.
auto canvas = new Canvas(Color.white) .setWidth(350) .setHeight(250) .addItem(new CanvasRectangle([10, 10, 200, 100])) .bind("<ButtonPress-1>", delegate(CommandArgs args){ ... }) .pack();
Border
Height
Relief
Width
XScrollCommand
XView
YScrollCommand
YView
<<PrevWindow>>, <Alt-Key>, <Key-F10>, <Key-Tab>,
Construct the widget.
| UiElement parent | The parent of this widget. |
| string backgroundColor | The background color. |
Construct the widget.
| string backgroundColor | The background color. |
Set the background color. Use colors from the preset color list or a web style hex color.
| string color | The background color. |
This widget to aid method chaining.
Specifies a floating-point value indicating how close the mouse cursor must be to an item before it is considered to be 'inside' the item and able to select it. Defaults to 1.0.
| double tolerance | The tolerance of the selection. |
This widget to aid method chaining.
Set the scroll region of the canvas. This region can be scrolled using scrollbars if it's bigger than the canvas widget itself.
| double left | The left hand side of the widget. |
| double top | The top side of the widget. |
| double right | The right hand side of the widget. |
| double bottom | The bottom side of the widget. |
This widget to aid method chaining.
Set the scroll increment i.e. how many pixels are scrolled per each click on a scrollbar.
| int increment | The increment to scroll by. |
This widget to aid method chaining.
Get the horizontal position on the canvas that relates to a particular horizontal position on screen.
| int screenXPos | The horizontal screen position to transpose. |
| int gridSpacing | The grid spacing to round it to. |
The horizontal canvas position.
Get the vertical position on the canvas that relates to a particular vertical position on screen.
| int screenYPos | The vertical screen position to transpose. |
| int gridSpacing | The grid spacing to round it to. |
The vertical canvas position.
Tag an item nearest to coordinates. If more than one item is at the same closest distance (e.g. two items overlap the point), then the top-most of these items (the last one in the display list) is used. If radius is specified, then it must be a non-negative value. Any item closer than halo to the point is considered to overlap it.
| string tag | The tag to add. |
| int xPos | The horizontal position. |
| int yPos | The vertical position. |
| uint radius | The radius around the point. |
This widget to aid method chaining.
Tag items within a selection region.
| string tag | The tag to add. |
| int x1 | The left edge of the selection region. |
| int y1 | The top edge of the selection region. |
| int x2 | The right edge of the selection region. |
| int y2 | The bottom edge of the selection region. |
| bool enclosedFully | Specifies if the items have to be enclosed fully or not. |
This widget to aid method chaining.
Tag items that are already tagged with another tag.
| string tag | The tag to add. |
| string searchTag | The tag to select items to tag. |
This widget to aid method chaining.
Get an item id nearest to coordinates. If more than one item is at the same closest distance (e.g. two items overlap the point), then the top-most of these items (the last one in the display list) is used. If radius is specified, then it must be a non-negative value. Any item closer than halo to the point is considered to overlap it.
| int xPos | The horizontal position. |
| int yPos | The vertical position. |
| uint radius | The radius around the point. |
The item found.
Get items within a selection region.
| int x1 | The left edge of the selection region. |
| int y1 | The top edge of the selection region. |
| int x2 | The right edge of the selection region. |
| int y2 | The bottom edge of the selection region. |
| bool enclosedFully | Specifies if the items have to be enclosed fully or not. |
An array of found items.
Add an item to the canvas.
| CanvasItem item | The item to add. |
This widget to aid method chaining.
Add a tag configuration to the canvas. These can apply options to a tag which can then be applied to any item.
| CanvasTagConfig tagConfig | The configuration to add. |
This widget to aid method chaining.
This command is used to implement scanning on canvases. Records x and y positions and the canvas's current view. This is used in conjunction with later scanDragTo commands.
| double xPos | The marked horizontal starting point of a scan. |
| double yPos | The marked vertical starting point of a scan. |
This widget to aid method chaining.
This command is used to implement scanning on canvases. This command computes the difference between its xPos and yPos arguments (which are typically mouse coordinates) and the xPos and yPos arguments to the last setScanMark command for the widget. It then adjusts the view by gain times the difference in coordinates, where gain defaults to 1. This command is typically associated with mouse motion events in the widget, to produce the effect of dragging the canvas at high speed through its window.
| double xPos | The marked horizontal starting point of a scan. |
| double yPos | The marked vertical starting point of a scan. |
| int gain | The adjustment in the drag amount. |
This widget to aid method chaining.
Set the border width of the widget.
| int width | The desired border width. |
This widget to aid method chaining.
Class representing a tag configuration. Tags can be applied to numerous items on the canvas but keep in mind the tag options set in the configuration must be compatible for all items the tag is assigned to or an error will occur. Tags must be applied to items before they can be configured.
Anchor
ArcSpecific
Bind
FillColor
ImageSpecific
LineSpecific
OutlineColor
OutlineDash
OutlineWidth
State
TextSpecific
Vertex
WidgetSpecific
Constructor.
| string tagName | The name of the tag to configure. |
Get the anchor.
The anchor of the item.
Set the anchor position.
| string anchor | The anchor position of the text. |
This widget to aid method chaining.
Abstract base class of all canvas items.
Get the type of canvas item.
The type of canvas item.
Get the coords of this item.
An array of coords of this item.
Set the coordinates used to draw this item.
| int[] coords | The coords used for this item. |
This item to aid method chaining.
Get the tags associated with this item.
An array of tags associated with this item.
Set tags associated with this item.
| string[] tags | The tags to associated with this item. |
This item to aid method chaining.
Add a specific tag to this item.
| string tag | The tags to add. |
This item to aid method chaining.
Delete a specific tag associated to this item.
| string tag | The tags to delete. |
This item to aid method chaining.
Delete all tags associated to this item.
This item to aid method chaining.
Destroy this item and remove it from the canvas.
Set the keyboard focus to this item in the canvas.
This widget to aid method chaining.
Lower an item in the drawing order.
This widget to aid method chaining.
Raise an item in the drawing order.
This widget to aid method chaining.
Move an item on the canvas by an amount.
| int xAmount | The amount to move the item horizontally. |
| int yAmount | The amount to move the item vertically. |
This widget to aid method chaining.
Move an item on the canvas to a position.
| int xPos | The new horizontal position. |
| int yPos | The new vertical position. |
This widget to aid method chaining.
Scale an item on the canvas. Note that some items have only a single pair of coordinates (e.g., text, images and widgets) and so scaling of them by this command can only move them around.
| double xOrigin | The horizontal origin from which to perform the scale. |
| double yOrigin | The vertical origin from which to perform the scale. |
| double xPercent | The amount to scale horizontally. |
| double yPercent | The amount to scale vertically. |
This widget to aid method chaining.
Bind a callback to a particular event triggered by this item. This command is identical to UiElement's bind method.
If bindings have been created for a canvas widget they are invoked in addition to bindings created for the canvas's items. The bindings for items will be invoked before any of the bindings for the window as a whole.
| string binding | The binding that triggers this event. See below. |
| CommandCallback callback | The delegate callback to execute when the event triggers. |
This item to aid method chaining.
| CommandArgs.element | The item that executed the callback. |
| CommandArgs.uniqueData | The binding that was responded to. |
| CommandArgs.callback | The callback which was executed. |
| CommandArgs.event.button | The number of any button that was pressed. |
| CommandArgs.event.keyCode | The key code of any key pressed. |
| CommandArgs.event.x | The horizontal position of the mouse relative to the widget. |
| CommandArgs.event.y | The vertical position of the mouse relative to the widget. |
| CommandArgs.event.wheel | Mouse wheel delta. |
| CommandArgs.event.key | Key symbol of any key pressed. |
| CommandArgs.event.screenX | The horizontal position of the mouse relative to the screen. |
| CommandArgs.event.screenY | The vertical position of the mouse relative to the screen. |
tkd.element.element.CommandCallback
tkd.element.uielement.UiElement
Unbind a previous event binding.
| string binding | The binding to remove. |
This item to aid method chaining.
A canvas arc item.
ArcSpecific
FillColor
OutlineColor
OutlineDash
OutlineWidth
Create an arc. Use colors from the preset color list or a web style hex color.
| double[] coords | The coordinates of the outer elipse. |
| string style | The style of arc. |
| string fillColor | The fill color. |
| string outlineColor | The outline color. |
| int outlineWidth | The outline width. |
Get the style of the arc.
The style of the arc;
Specifies how to draw the arc. If type is pie (the default) then the arc's region is defined by a section of the oval's perimeter plus two line segments, one between the center of the oval and each end of the perimeter section. If type is chord then the arc's region is defined by a section of the oval's perimeter plus a single line segment connecting the two end points of the perimeter section. If type is arc then the arc's region consists of a section of the perimeter alone. In this last case the fill color is ignored.
| string style | The style of the arc. |
This item to aid method chaining.
Get the extent of the arc.
The extent of the arc;
Specifies the size of the angular range occupied by the arc. The arc's range extends for degrees counter-clockwise from the starting angle. Degrees may be negative. If it is greater than 360 or less than -360, then degrees modulo 360 is used as the extent.
| int extent | The extent of the arc. |
This item to aid method chaining.
Get the start angle of the arc.
The start angle of the arc;
Specifies the beginning of the angular range occupied by the arc. Degrees is given in units of degrees measured counter-clockwise from the 3-o'clock position; it may be either positive or negative.
| A startAngle | The start angle of the arc. |
This item to aid method chaining.
Styles of arcs
An canvas image item.
Create an image.
| double[] coords | The coordinates where to position the image. |
| Image image | The image to draw. |
| string anchor | The anchor position of the image. |
tkd.image.gif
tkd.image.image
tkd.image.png
tkd.widget.anchorposition
Get the anchor.
The anchor of the item.
Set the anchor position.
| string anchor | The anchor position of the text. |
This widget to aid method chaining.
A canvas line item.
FillColor
LineSpecific
OutlineDash
OutlineWidth
Vertex
Create a line from coordinates. Use colors from the preset color list or a web style hex color.
| double[] coords | The coordinates where to draw the line. |
| string fillColor | The color of the line. |
| int outlineWidth | The outline width. |
Get the fill color.
The fill color;
Set the fill color. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
Get the active fill color. An item's active state is triggered when the mouse rolls over the item.
The active fill color;
Set the active fill color. An item's active state is triggered when the mouse rolls over the item. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
Get the disabled fill color.
The disabled fill color;
Set the disabled fill color. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
Arrow positions on a canvas line.
The cap styles of a canvas line.
The join styles of a canvas line.
The join styles of a canvas line.
A canvas rectangle item.
FillColor
OutlineColor
OutlineDash
OutlineWidth
Create a rectangle from four coordinates. Use colors from the preset color list or a web style hex color.
| double[] coords | The coordinates where to draw the rectangle. |
| string fillColor | The fill color. |
| string outlineColor | The outline color. |
| int outlineWidth | The outline width. |
Get the fill color.
The fill color;
Set the fill color. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
Get the active fill color. An item's active state is triggered when the mouse rolls over the item.
The active fill color;
Set the active fill color. An item's active state is triggered when the mouse rolls over the item. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
Get the disabled fill color.
The disabled fill color;
Set the disabled fill color. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
A canvas oval item.
FillColor
OutlineColor
OutlineDash
OutlineWidth
Create an oval from four coordinates. Use colors from the preset color list or a web style hex color.
| double[] coords | The coordinates where to draw the oval. |
| string fillColor | The fill color. |
| string outlineColor | The outline color. |
| int outlineWidth | The outline width. |
Get the fill color.
The fill color;
Set the fill color. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
Get the active fill color. An item's active state is triggered when the mouse rolls over the item.
The active fill color;
Set the active fill color. An item's active state is triggered when the mouse rolls over the item. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
Get the disabled fill color.
The disabled fill color;
Set the disabled fill color. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
A canvas polygon item.
FillColor
OutlineColor
OutlineDash
OutlineWidth
Vertex
Create a polygon from coordinates. Use colors from the preset color list or a web style hex color.
| double[] coords | The coordinates where to draw the polygon. |
| string fillColor | The fill color. |
| string outlineColor | The outline color. |
| int outlineWidth | The outline width. |
Get the fill color.
The fill color;
Set the fill color. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
Get the active fill color. An item's active state is triggered when the mouse rolls over the item.
The active fill color;
Set the active fill color. An item's active state is triggered when the mouse rolls over the item. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
Get the disabled fill color.
The disabled fill color;
Set the disabled fill color. Use colors from the preset color list or a web style hex color.
| string color | The fill color. |
This widget to aid method chaining.
A canvas text item.
Create a text item. Use colors from the preset color list or a web style hex color.
| double[] coords | The coordinates where to draw the polygon. |
| string text | The text. |
| string fillColor | The fill color. |
| string anchor | The anchor position of the image. |
Get the anchor.
The anchor of the item.
Set the anchor position.
| string anchor | The anchor position of the text. |
This widget to aid method chaining.
A canvas widget item.
Create a widget item.
| double[] coords | The coordinates where to draw the polygon. |
| Widget widget | The widget to use. |
| string anchor | The anchor position of the image. |
Get the anchor.
The anchor of the item.
Set the anchor position.
| string anchor | The anchor position of the text. |
This widget to aid method chaining.


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Content Creator
Created in May 2017, the Infinity Labs YouTube channel focuses on reviewing laptops from high performance workstations to thin and light ultrabooks. As computers get faster with lower power consumption, laptops become increasingly popular due to their portability. With premium laptops starting at $2,400 or more, it is important you pick the right laptop to suit your needs and preferences.


§353-69 Parole when. [Repeal and reenactment on July 1, 2018. L 2013, c 67, §2.] Except as provided in section 706-670, no parole shall be granted unless it appears to the Hawaii paroling authority that there is a reasonable probability that the prisoner concerned will live and remain at liberty without violating the law and that the prisoner's release is not incompatible with the welfare and safety of society. [L 1917, c 103, §4; RL 1925, §1563; am L 1931, c 126, §5; RL 1935, §6457; RL 1945, §3962; RL 1955, §83-67; HRS §353-69; am L 1976, c 92, pt of §8; gen ch 1985; am L 2012, c 139, §§11, 14(4)]
Note
Repeal and reenactment of section on July 1, 2018, by L 2013, c 67, §2; L 2016, c 231, §69 deleted by L 2017, c 77, §2.
Case Notes
No due process liberty interest in parole is created under this section. 795 F. Supp. 1020 (1992).


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97 Things Every SRE Should Know-preface
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March 12, 2021
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97 Things Every SRE Should Know-01
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March 18, 2021
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97 Things Every SRE Should Know-02
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March 18, 2021
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服务质量说明
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November 3, 2021
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acme.sh Applies for an SSL certificate
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June 7, 2022
Steven Lee
<EMAIL_ADDRESS>SRE
China


(#) Potential AAPT crash
!!! ERROR: Potential AAPT crash
This is an error, and is also enforced at build time when
supported by the build system. For Android this means it will
run during release builds.
Id
: `AaptCrash`
Summary
: Potential AAPT crash
Severity
: Fatal
Category
: Correctness
Platform
: Android
Vendor
: Android Open Source Project
Feedback
: https://issuetracker.google.com/issues/new?component=192708
Affects
: Resource files
Editing
: This check runs on the fly in the IDE editor
Implementation
: [Source Code](https://cs.android.com/android-studio/platform/tools/base/+/mirror-goog-studio-main:lint/libs/lint-checks/src/main/java/com/android/tools/lint/checks/ResourceCycleDetector.kt)
Tests
: [Source Code](https://cs.android.com/android-studio/platform/tools/base/+/mirror-goog-studio-main:lint/libs/lint-tests/src/test/java/com/android/tools/lint/checks/ResourceCycleDetectorTest.java)
Copyright Year
: 2014
Defining a style which sets `android:id` to a dynamically generated id
can cause many versions of `aapt`, the resource packaging tool, to
crash. To work around this, declare the id explicitly with ` ` instead.
(##) Example
Here is an example of lint warnings produced by this check:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~text
res/values/aaptcrash.xml:5:Error: This construct can potentially crash
aapt during a build. Change @+id/titlebar to @id/titlebar and define the
id explicitly using instead.
[AaptCrash]
<item name="android:id">@+id/titlebar</item>
--------------------------------------------
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Here is the source file referenced above:
`res/values/aaptcrash.xml`:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~xml linenumbers
<?xml version="1.0" encoding="utf-8"?>
<resources xmlns:android="http://schemas.android.com/apk/res/android">
<style name="TitleBar">
<item name="android:orientation">horizontal</item>
<item name="android:id">@+id/titlebar</item>
<item name="android:background">@drawable/bg_titlebar</item>
<item name="android:layout_width">fill_parent</item>
<item name="android:layout_height">@dimen/titlebar_height</item>
</style>
</resources>
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
You can also visit the
[source code](https://cs.android.com/android-studio/platform/tools/base/+/mirror-goog-studio-main:lint/libs/lint-tests/src/test/java/com/android/tools/lint/checks/ResourceCycleDetectorTest.java)
for the unit tests for this check to see additional scenarios.
The above example was automatically extracted from the first unit test
found for this lint check, `ResourceCycleDetector.testAaptCrash`.
To report a problem with this extracted sample, visit
https://issuetracker.google.com/issues/new?component=192708.
(##) Suppressing
You can suppress false positives using one of the following mechanisms:
* Adding the suppression attribute `tools:ignore="AaptCrash"` on the
problematic XML element (or one of its enclosing elements). You may
also need to add the following namespace declaration on the root
element in the XML file if it's not already there:
`xmlns:tools="http://schemas.android.com/tools"`.
```xml
<?xml version="1.0" encoding="UTF-8"?>
<resources xmlns:tools="http://schemas.android.com/tools">
...
<include tools:ignore="AaptCrash" .../>
...
</resources>
```
* Using a special `lint.xml` file in the source tree which turns off
the check in that folder and any sub folder. A simple file might look
like this:
```xml
<?xml version="1.0" encoding="UTF-8"?>
<lint>
<issue id="AaptCrash" severity="ignore" />
</lint>
```
Instead of `ignore` you can also change the severity here, for
example from `error` to `warning`. You can find additional
documentation on how to filter issues by path, regular expression and
so on
[here](https://googlesamples.github.io/android-custom-lint-rules/usage/lintxml.md.html).
* In Gradle projects, using the DSL syntax to configure lint. For
example, you can use something like
```gradle
lintOptions {
disable 'AaptCrash'
}
```
In Android projects this should be nested inside an `android { }`
block.
* For manual invocations of `lint`, using the `--ignore` flag:
```
$ lint --ignore AaptCrash ...`
```
* Last, but not least, using baselines, as discussed
[here](https://googlesamples.github.io/android-custom-lint-rules/usage/baselines.md.html).


Pattern
find
(λ [&Pattern, &String] Int)
finds the index of a pattern in a string.
Returns -1
if it doesn’t find a matching pattern.
find-all
(λ [&Pattern, &String] (Array Int))
finds all indices of a pattern in a string.
Returns []
if it doesn’t find a matching pattern.
from-chars
(λ [(Ref (Array Char))] Pattern)
(from-chars chars)
creates a pattern that matches a group of characters from a list of those characters.
global-match
(λ [&Pattern, &String] (Array (Array String)))
finds all matches of a pattern in a string as a nested array.
Returns []
if it doesn’t find a matching pattern.
match-groups
(λ [&Pattern, &String] (Array String))
finds the match groups of the first match of a pattern in a string.
Returns []
if it doesn’t find a matching pattern.
match-str
(λ [&Pattern, &String] String)
finds the first match of a pattern in a string.
Returns []
if it doesn’t find a matching pattern.
matches?
(λ [&Pattern, &String] Bool)
(matches? pat s)
checks whether a pattern matches a string.
substitute
(λ [&Pattern, &String, &String, Int] String)
finds all matches of a pattern in a string and replaces it by another pattern n
times.
If you want to replace all occurrences of the pattern, use -1
.


Plugin Information |
|---|
View Keychains and Provisioning Profiles Management on the plugin site for more information. |
Description
This plugin integrates a keychains and mobile provisioning profiles management for iOS and OSX projects into Jenkins. Simply upload keychain and provisioning profile files and configure your build job to use them. When the build is executed, than the keychain and provisioning profile files are automatically distributed to the Jenkins node (master or slave). There is no need to manage these files manually on each Jenkins node.
Status: In Progress
Configuration
Main plugin configuration
- Go to the "Manage Jenkins" page.
- Click on "Keychains and Provisioning Profiles Management" and the main plugin configuration page is shown.
Upload keychain and provisioning profile files section
1. Click on "Choose File" and select the keychain or provisioning profile file.
2. Click on "Upload". The keychain or provisioning profile file is automatically uploaded and stored on the jenkins.
Manage keychains section
Filename - The name of the keychain. The name is automatically filled by jenkins.
Password - Give the correct password for the keychain.
Description - Specify a short description for the keychain.
Identities - Lists all added code signing identities.
Delete/ Add Code Signing Identity - You can add more than one "Code Signing Identity" to the same keychain and also remove a code signing identity from the keychain.
Delete Keychain - Will delete your complete keychain after the configuration is saved.
Manage code signing identities section
1. Open the program "Keychain Access“.
2. Select by category "My Certificates“ and select your certificate.
3. At next, click "get info" and copy the line "Common Name". This is the common name of the code signing indentity.
Manage provisioning profiles
1. Only if iOS or OSX projects are to be built on the master, than type in the directory path where provisioning profiles are stored, that is optinal.
Generally:
/Users/<USERNAME>/Library/MobileDevice/Provisioning Profiles
Node configuration
1.Only if iOS or OSX projects are to be built on this node, than type in the directory path where provisioning profiles are stored on the node.
Generally:
/Users/<USERNAME>/Library/MobileDevice/Provisioning Profiles
Build job configuration
Build environment configuration section
There are two pre-build steps added to the job configuration page.
Keychains and Code Signing Identities
Keychain and Code Signing Identities - Mark this checkbox to use keychains and code signing identities.
Overwrite existing keychains - Mark this checkbox to override existing keychains on the node.
Delete copied keychains after build - Mark this checkbox, if copied keychains are to be deleted after the build.
Keychain - Select the keychain.
Variable Prefix - If more than one keychain is to be used, than set a prefix for the variable names to avoid variable name collisions.
Variables - Get the variable names. They can be used in other build steps.
Delete - Delete keychain configuration.
Add Keychain - Add keychain configuration.
Mobile Provisioning Profiles
Mobile Provisioning Profiles - Mark this checkbox to use provisioning profiles.
Overwrite existing provisioning profiles - Mark this checkbox to override existing provisioning profiles on the node.
Delete copied provisioning profiles after build - Mark this checkbox, if copied provisioning profiles are to be deleted after the build.
Provisioning Profile - Select a provisioning profile.
Variable Prefix - If more than one provisioning profile is to be used, than set a prefix for the variable names to avoid variable name collisions.
Variable - Get the variable names. They can be used in other build steps.
Delete - Delete provisioning profile configuration.
Add Provisioning Profile - Add provisioning profile configuration.
Build step integration
Next, the integration of the "Keychains and Provisioning Profiles Plugin" into other build steps is explained on the example of the Jenkins Xcode Plugin.
Custom xcodebuild arguments - Give a reference to the provisioning profile.
PROVISIONING_PROFILE=${PROVISIONING_PROFILE}
Unlock Keychain - Mark the checkbox to unlock the keychain.
Keychain path - Type in the variable name for the keychain path.
Keychain password - Type in the variable name for the keychain password.
Changelog
Release 1.0
- Initial Release
Attachments:
Screen Shot 2013-08-06 at 10.44.18.png (image/png)
codesigning_1.jpg (image/jpeg)
codesigning_1.jpg (image/jpeg)
codesigning_1.tiff (image/tiff)
codesigning_1.jpeg (image/jpeg)
Screen Shot 2013-08-06 at 10.44.46.png (image/png)
codesigning_1.png (image/png)
g.png (image/png)
Screen-Shot-2013-08-05-at-13.26_1.png (image/png)
image_test.png (image/png)
codesigning_Key_1.png (image/png)
codesigning_Key_2.png (image/png)
codesigning_Key_2.png (image/png)
Upload_keychain.png (image/png)
manage_Keychain.png (image/png)
Screen Shot 2013-08-07 at 13.36.24.png (image/png)
Screen Shot 2013-08-07 at 14.17.05.png (image/png)
Screen Shot 2013-08-07 at 15.26.50.png (image/png)
Screen Shot 2013-08-08 at 10.50.56.png (image/png)
Screen Shot 2013-08-08 at 10.51.23.png (image/png)
Screen Shot 2013-08-08 at 12.40.09.png (image/png)
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Screen Shot 2013-08-08 at 14.07.25.png (image/png)
Screen Shot 2013-08-08 at 14.22.42.png (image/png)
Screen Shot 2013-08-08 at 15.27.47.png (image/png)
keyjjjchain.png (image/png)
Screen Shot 2013-08-09 at 10.29.46.png (image/png)
iconde_bold.png (image/png)